diff --git a/.dockerignore b/.dockerignore index 09f4c9f0c..889a4dfc7 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,9 +1,8 @@ .git .gitignore Dockerfile +Dockerfile.armhf .dockerignore -config.json* -*.sqlite .coveragerc .eggs .github @@ -13,4 +12,13 @@ CONTRIBUTING.md MANIFEST.in README.md freqtrade.service +freqtrade.egg-info + +config.json* +*.sqlite user_data +*.log + +.vscode +.mypy_cache +.ipynb_checkpoints diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 000000000..00abd1d9d --- /dev/null +++ b/.gitattributes @@ -0,0 +1,3 @@ +*.py eol=lf +*.sh eol=lf +*.ps1 eol=crlf diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml new file mode 100644 index 000000000..7591c1fb0 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -0,0 +1,6 @@ +--- +blank_issues_enabled: false +contact_links: + - name: Discord Server + url: https://discord.gg/MA9v74M + about: Ask a question or get community support from our Discord server diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 61ecaa522..5a0837eb2 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -148,6 +148,7 @@ jobs: - name: Installation - macOS run: | + brew update brew install hdf5 c-blosc python -m pip install --upgrade pip export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH @@ -300,7 +301,7 @@ jobs: runs-on: ubuntu-20.04 steps: - name: Cleanup previous runs on this branch - uses: rokroskar/workflow-run-cleanup-action@v0.2.2 + uses: rokroskar/workflow-run-cleanup-action@v0.3.3 if: "!startsWith(github.ref, 'refs/tags/') && github.ref != 'refs/heads/stable' && github.repository == 'freqtrade/freqtrade'" env: GITHUB_TOKEN: "${{ secrets.GITHUB_TOKEN }}" @@ -310,9 +311,18 @@ jobs: needs: [ build_linux, build_macos, build_windows, docs_check ] runs-on: ubuntu-20.04 steps: + + - name: Check user permission + id: check + uses: scherermichael-oss/action-has-permission@1.0.6 + with: + required-permission: write + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + - name: Slack Notification uses: lazy-actions/slatify@v3.0.0 - if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) + if: always() && steps.check.outputs.has-permission && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} job_name: '*Freqtrade CI*' diff --git a/Dockerfile b/Dockerfile index 4b399174b..7d5afac9c 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,14 +1,23 @@ -FROM python:3.9.2-slim-buster as base +FROM python:3.9.5-slim-buster as base # Setup env ENV LANG C.UTF-8 ENV LC_ALL C.UTF-8 ENV PYTHONDONTWRITEBYTECODE 1 ENV PYTHONFAULTHANDLER 1 -ENV PATH=/root/.local/bin:$PATH +ENV PATH=/home/ftuser/.local/bin:$PATH +ENV FT_APP_ENV="docker" # Prepare environment -RUN mkdir /freqtrade +RUN mkdir /freqtrade \ + && apt update \ + && apt install -y sudo \ + && apt-get clean \ + && useradd -u 1000 -G sudo -U -m ftuser \ + && chown ftuser:ftuser /freqtrade \ + # Allow sudoers + && echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers + WORKDIR /freqtrade # Install dependencies @@ -24,7 +33,8 @@ RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib* ENV LD_LIBRARY_PATH /usr/local/lib # Install dependencies -COPY requirements.txt requirements-hyperopt.txt /freqtrade/ +COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/ +USER ftuser RUN pip install --user --no-cache-dir numpy \ && pip install --user --no-cache-dir -r requirements-hyperopt.txt @@ -33,13 +43,13 @@ FROM base as runtime-image COPY --from=python-deps /usr/local/lib /usr/local/lib ENV LD_LIBRARY_PATH /usr/local/lib -COPY --from=python-deps /root/.local /root/.local - - +COPY --from=python-deps --chown=ftuser:ftuser /home/ftuser/.local /home/ftuser/.local +USER ftuser # Install and execute -COPY . /freqtrade/ -RUN pip install -e . --no-cache-dir \ +COPY --chown=ftuser:ftuser . /freqtrade/ + +RUN pip install -e . --user --no-cache-dir \ && mkdir /freqtrade/user_data/ \ && freqtrade install-ui diff --git a/Dockerfile.armhf b/Dockerfile.armhf index eecd9fdc0..2b3bca042 100644 --- a/Dockerfile.armhf +++ b/Dockerfile.armhf @@ -1,19 +1,24 @@ -FROM --platform=linux/arm/v7 python:3.7.9-slim-buster as base +FROM --platform=linux/arm/v7 python:3.7.10-slim-buster as base # Setup env ENV LANG C.UTF-8 ENV LC_ALL C.UTF-8 ENV PYTHONDONTWRITEBYTECODE 1 ENV PYTHONFAULTHANDLER 1 -ENV PATH=/root/.local/bin:$PATH +ENV PATH=/home/ftuser/.local/bin:$PATH +ENV FT_APP_ENV="docker" # Prepare environment -RUN mkdir /freqtrade -WORKDIR /freqtrade +RUN mkdir /freqtrade \ + && apt-get update \ + && apt-get -y install libatlas3-base curl sqlite3 libhdf5-serial-dev sudo \ + && apt-get clean \ + && useradd -u 1000 -G sudo -U -m ftuser \ + && chown ftuser:ftuser /freqtrade \ + # Allow sudoers + && echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers -RUN apt-get update \ - && apt-get -y install libatlas3-base curl sqlite3 \ - && apt-get clean +WORKDIR /freqtrade # Install dependencies FROM base as python-deps @@ -28,7 +33,8 @@ RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib* ENV LD_LIBRARY_PATH /usr/local/lib # Install dependencies -COPY requirements.txt /freqtrade/ +COPY --chown=ftuser:ftuser requirements.txt /freqtrade/ +USER ftuser RUN pip install --user --no-cache-dir numpy \ && pip install --user --no-cache-dir -r requirements.txt @@ -37,13 +43,14 @@ FROM base as runtime-image COPY --from=python-deps /usr/local/lib /usr/local/lib ENV LD_LIBRARY_PATH /usr/local/lib -COPY --from=python-deps /root/.local /root/.local +COPY --from=python-deps --chown=ftuser:ftuser /home/ftuser/.local /home/ftuser/.local +USER ftuser # Install and execute -COPY . /freqtrade/ -RUN apt-get install -y libhdf5-serial-dev \ - && apt-get clean \ - && pip install -e . --no-cache-dir \ +COPY --chown=ftuser:ftuser . /freqtrade/ + +RUN pip install -e . --user --no-cache-dir \ + && mkdir /freqtrade/user_data/ \ && freqtrade install-ui ENTRYPOINT ["freqtrade"] diff --git a/README.md b/README.md index c3a665c47..ab9597a77 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Freqtrade +# ![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade_poweredby.svg) [![Freqtrade CI](https://github.com/freqtrade/freqtrade/workflows/Freqtrade%20CI/badge.svg)](https://github.com/freqtrade/freqtrade/actions/) [![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop) @@ -154,7 +154,7 @@ You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/ If you discover a bug in the bot, please [search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue) first. If it hasn't been reported, please -[create a new issue](https://github.com/freqtrade/freqtrade/issues/new) and +[create a new issue](https://github.com/freqtrade/freqtrade/issues/new/choose) and ensure you follow the template guide so that our team can assist you as quickly as possible. @@ -163,7 +163,7 @@ quickly as possible. Have you a great idea to improve the bot you want to share? Please, first search if this feature was not [already discussed](https://github.com/freqtrade/freqtrade/labels/enhancement). If it hasn't been requested, please -[create a new request](https://github.com/freqtrade/freqtrade/issues/new) +[create a new request](https://github.com/freqtrade/freqtrade/issues/new/choose) and ensure you follow the template guide so that it does not get lost in the bug reports. diff --git a/build_helpers/install_ta-lib.sh b/build_helpers/install_ta-lib.sh index cb86e5f64..dd87cf105 100755 --- a/build_helpers/install_ta-lib.sh +++ b/build_helpers/install_ta-lib.sh @@ -8,10 +8,13 @@ if [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then tar zxvf ta-lib-0.4.0-src.tar.gz cd ta-lib \ && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \ + && curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.guess;hb=HEAD' -o config.guess \ + && curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.sub;hb=HEAD' -o config.sub \ && ./configure --prefix=${INSTALL_LOC}/ \ - && make \ + && make -j$(nproc) \ && which sudo && sudo make install || make install \ && cd .. else echo "TA-lib already installed, skipping installation" fi +# && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \ diff --git a/config_ftx.json.example b/config_ftx.json.example new file mode 100644 index 000000000..facd54b25 --- /dev/null +++ b/config_ftx.json.example @@ -0,0 +1,99 @@ +{ + "max_open_trades": 3, + "stake_currency": "USD", + "stake_amount": 50, + "tradable_balance_ratio": 0.99, + "fiat_display_currency": "USD", + "timeframe": "5m", + "dry_run": true, + "cancel_open_orders_on_exit": false, + "unfilledtimeout": { + "buy": 10, + "sell": 30 + }, + "bid_strategy": { + "ask_last_balance": 0.0, + "use_order_book": false, + "order_book_top": 1, + "check_depth_of_market": { + "enabled": false, + "bids_to_ask_delta": 1 + } + }, + "ask_strategy": { + "use_order_book": false, + "order_book_min": 1, + "order_book_max": 1, + "use_sell_signal": true, + "sell_profit_only": false, + "ignore_roi_if_buy_signal": false + }, + "exchange": { + "name": "ftx", + "key": "your_exchange_key", + "secret": "your_exchange_secret", + "ccxt_config": {"enableRateLimit": true}, + "ccxt_async_config": { + "enableRateLimit": true, + "rateLimit": 50 + }, + "pair_whitelist": [ + "BTC/USD", + "ETH/USD", + "BNB/USD", + "USDT/USD", + "LTC/USD", + "SRM/USD", + "SXP/USD", + "XRP/USD", + "DOGE/USD", + "1INCH/USD", + "CHZ/USD", + "MATIC/USD", + "LINK/USD", + "OXY/USD", + "SUSHI/USD" + ], + "pair_blacklist": [ + "FTT/USD" + ] + }, + "pairlists": [ + {"method": "StaticPairList"} + ], + "edge": { + "enabled": false, + "process_throttle_secs": 3600, + "calculate_since_number_of_days": 7, + "allowed_risk": 0.01, + "stoploss_range_min": -0.01, + "stoploss_range_max": -0.1, + "stoploss_range_step": -0.01, + "minimum_winrate": 0.60, + "minimum_expectancy": 0.20, + "min_trade_number": 10, + "max_trade_duration_minute": 1440, + "remove_pumps": false + }, + "telegram": { + "enabled": false, + "token": "your_telegram_token", + "chat_id": "your_telegram_chat_id" + }, + "api_server": { + "enabled": false, + "listen_ip_address": "127.0.0.1", + "listen_port": 8080, + "verbosity": "error", + "jwt_secret_key": "somethingrandom", + "CORS_origins": [], + "username": "freqtrader", + "password": "SuperSecurePassword" + }, + "bot_name": "freqtrade", + "initial_state": "running", + "forcebuy_enable": false, + "internals": { + "process_throttle_secs": 5 + } +} diff --git a/config_full.json.example b/config_full.json.example index 717797933..24d364fdf 100644 --- a/config_full.json.example +++ b/config_full.json.example @@ -23,7 +23,8 @@ "stoploss": -0.10, "unfilledtimeout": { "buy": 10, - "sell": 30 + "sell": 30, + "unit": "minutes" }, "bid_strategy": { "price_side": "bid", @@ -163,7 +164,9 @@ "warning": "on", "startup": "on", "buy": "on", + "buy_fill": "on", "sell": "on", + "sell_fill": "on", "buy_cancel": "on", "sell_cancel": "on" } diff --git a/docker-compose.yml b/docker-compose.yml index 1f63059f0..80e194ab2 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -9,7 +9,7 @@ services: # Build step - only needed when additional dependencies are needed # build: # context: . - # dockerfile: "./docker/Dockerfile.technical" + # dockerfile: "./docker/Dockerfile.custom" restart: unless-stopped container_name: freqtrade volumes: diff --git a/docker/Dockerfile.aarch64 b/docker/Dockerfile.aarch64 new file mode 100644 index 000000000..71c10d949 --- /dev/null +++ b/docker/Dockerfile.aarch64 @@ -0,0 +1,58 @@ +FROM --platform=linux/arm64/v8 python:3.9.4-slim-buster as base + +# Setup env +ENV LANG C.UTF-8 +ENV LC_ALL C.UTF-8 +ENV PYTHONDONTWRITEBYTECODE 1 +ENV PYTHONFAULTHANDLER 1 +ENV PATH=/home/ftuser/.local/bin:$PATH +ENV FT_APP_ENV="docker" + +# Prepare environment +RUN mkdir /freqtrade \ + && apt-get update \ + && apt-get -y install libatlas3-base curl sqlite3 libhdf5-serial-dev sudo \ + && apt-get clean \ + && useradd -u 1000 -G sudo -U -m ftuser \ + && chown ftuser:ftuser /freqtrade \ + # Allow sudoers + && echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers + +WORKDIR /freqtrade + +# Install dependencies +FROM base as python-deps +RUN apt-get update \ + && apt-get -y install curl build-essential libssl-dev git libffi-dev libgfortran5 pkg-config cmake gcc \ + && apt-get clean \ + && pip install --upgrade pip + +# Install TA-lib +COPY build_helpers/* /tmp/ +RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib* +ENV LD_LIBRARY_PATH /usr/local/lib + +# Install dependencies +COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/ +USER ftuser +RUN pip install --user --no-cache-dir numpy \ + && pip install --user --no-cache-dir -r requirements-hyperopt.txt + +# Copy dependencies to runtime-image +FROM base as runtime-image +COPY --from=python-deps /usr/local/lib /usr/local/lib +ENV LD_LIBRARY_PATH /usr/local/lib + +COPY --from=python-deps --chown=ftuser:ftuser /home/ftuser/.local /home/ftuser/.local + +USER ftuser +# Install and execute +COPY --chown=ftuser:ftuser . /freqtrade/ + +RUN pip install -e . --user --no-cache-dir \ + && mkdir /freqtrade/user_data/ \ + && freqtrade install-ui + +ENTRYPOINT ["freqtrade"] +# Default to trade mode +CMD [ "trade" ] diff --git a/docker/Dockerfile.custom b/docker/Dockerfile.custom new file mode 100644 index 000000000..3b55fcb0e --- /dev/null +++ b/docker/Dockerfile.custom @@ -0,0 +1,10 @@ +FROM freqtradeorg/freqtrade:develop + +# Switch user to root if you must install something from apt +# Don't forget to switch the user back below! +# USER root + +# The below dependency - pyti - serves as an example. Please use whatever you need! +RUN pip install --user pyti + +# USER ftuser diff --git a/docker/Dockerfile.develop b/docker/Dockerfile.develop index cb49984e2..7c580f234 100644 --- a/docker/Dockerfile.develop +++ b/docker/Dockerfile.develop @@ -3,8 +3,8 @@ FROM freqtradeorg/freqtrade:develop # Install dependencies COPY requirements-dev.txt /freqtrade/ -RUN pip install numpy --no-cache-dir \ - && pip install -r requirements-dev.txt --no-cache-dir +RUN pip install numpy --user --no-cache-dir \ + && pip install -r requirements-dev.txt --user --no-cache-dir # Empty the ENTRYPOINT to allow all commands ENTRYPOINT [] diff --git a/docker/Dockerfile.jupyter b/docker/Dockerfile.jupyter index b7499eeef..7d603c667 100644 --- a/docker/Dockerfile.jupyter +++ b/docker/Dockerfile.jupyter @@ -1,7 +1,7 @@ FROM freqtradeorg/freqtrade:develop_plot -RUN pip install jupyterlab --no-cache-dir +RUN pip install jupyterlab --user --no-cache-dir # Empty the ENTRYPOINT to allow all commands ENTRYPOINT [] diff --git a/docker/Dockerfile.plot b/docker/Dockerfile.plot index 40bc72bc5..d2fc3618a 100644 --- a/docker/Dockerfile.plot +++ b/docker/Dockerfile.plot @@ -4,4 +4,4 @@ FROM freqtradeorg/freqtrade:${sourceimage} # Install dependencies COPY requirements-plot.txt /freqtrade/ -RUN pip install -r requirements-plot.txt --no-cache-dir +RUN pip install -r requirements-plot.txt --user --no-cache-dir diff --git a/docker/Dockerfile.technical b/docker/Dockerfile.technical deleted file mode 100644 index 9431e72d0..000000000 --- a/docker/Dockerfile.technical +++ /dev/null @@ -1,6 +0,0 @@ -FROM freqtradeorg/freqtrade:develop - -RUN apt-get update \ - && apt-get -y install git \ - && apt-get clean \ - && pip install git+https://github.com/freqtrade/technical diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md index bdaafb936..c86978b80 100644 --- a/docs/advanced-hyperopt.md +++ b/docs/advanced-hyperopt.md @@ -4,79 +4,6 @@ This page explains some advanced Hyperopt topics that may require higher coding skills and Python knowledge than creation of an ordinal hyperoptimization class. -## Derived hyperopt classes - -Custom hyperopt classes can be derived in the same way [it can be done for strategies](strategy-customization.md#derived-strategies). - -Applying to hyperoptimization, as an example, you may override how dimensions are defined in your optimization hyperspace: - -```python -class MyAwesomeHyperOpt(IHyperOpt): - ... - # Uses default stoploss dimension - -class MyAwesomeHyperOpt2(MyAwesomeHyperOpt): - @staticmethod - def stoploss_space() -> List[Dimension]: - # Override boundaries for stoploss - return [ - Real(-0.33, -0.01, name='stoploss'), - ] -``` - -and then quickly switch between hyperopt classes, running optimization process with hyperopt class you need in each particular case: - -``` -$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ... -or -$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt2 --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ... -``` - -## Sharing methods with your strategy - -Hyperopt classes provide access to the Strategy via the `strategy` class attribute. -This can be a great way to reduce code duplication if used correctly, but will also complicate usage for inexperienced users. - -``` python -from pandas import DataFrame -from freqtrade.strategy.interface import IStrategy -import freqtrade.vendor.qtpylib.indicators as qtpylib - -class MyAwesomeStrategy(IStrategy): - - buy_params = { - 'rsi-value': 30, - 'adx-value': 35, - } - - def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - return self.buy_strategy_generator(self.buy_params, dataframe, metadata) - - @staticmethod - def buy_strategy_generator(params, dataframe: DataFrame, metadata: dict) -> DataFrame: - dataframe.loc[ - ( - qtpylib.crossed_above(dataframe['rsi'], params['rsi-value']) & - dataframe['adx'] > params['adx-value']) & - dataframe['volume'] > 0 - ) - , 'buy'] = 1 - return dataframe - -class MyAwesomeHyperOpt(IHyperOpt): - ... - @staticmethod - def buy_strategy_generator(params: Dict[str, Any]) -> Callable: - """ - Define the buy strategy parameters to be used by Hyperopt. - """ - def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: - # Call strategy's buy strategy generator - return self.StrategyClass.buy_strategy_generator(params, dataframe, metadata) - - return populate_buy_trend -``` - ## Creating and using a custom loss function To use a custom loss function class, make sure that the function `hyperopt_loss_function` is defined in your custom hyperopt loss class. @@ -142,3 +69,315 @@ This function needs to return a floating point number (`float`). Smaller numbers !!! Note Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface later. + +## Overriding pre-defined spaces + +To override a pre-defined space (`roi_space`, `generate_roi_table`, `stoploss_space`, `trailing_space`), define a nested class called Hyperopt and define the required spaces as follows: + +```python +class MyAwesomeStrategy(IStrategy): + class HyperOpt: + # Define a custom stoploss space. + def stoploss_space(self): + return [SKDecimal(-0.05, -0.01, decimals=3, name='stoploss')] +``` + +## Space options + +For the additional spaces, scikit-optimize (in combination with Freqtrade) provides the following space types: + +* `Categorical` - Pick from a list of categories (e.g. `Categorical(['a', 'b', 'c'], name="cat")`) +* `Integer` - Pick from a range of whole numbers (e.g. `Integer(1, 10, name='rsi')`) +* `SKDecimal` - Pick from a range of decimal numbers with limited precision (e.g. `SKDecimal(0.1, 0.5, decimals=3, name='adx')`). *Available only with freqtrade*. +* `Real` - Pick from a range of decimal numbers with full precision (e.g. `Real(0.1, 0.5, name='adx')` + +You can import all of these from `freqtrade.optimize.space`, although `Categorical`, `Integer` and `Real` are only aliases for their corresponding scikit-optimize Spaces. `SKDecimal` is provided by freqtrade for faster optimizations. + +``` python +from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal, Real # noqa +``` + +!!! Hint "SKDecimal vs. Real" + We recommend to use `SKDecimal` instead of the `Real` space in almost all cases. While the Real space provides full accuracy (up to ~16 decimal places) - this precision is rarely needed, and leads to unnecessary long hyperopt times. + + Assuming the definition of a rather small space (`SKDecimal(0.10, 0.15, decimals=2, name='xxx')`) - SKDecimal will have 5 possibilities (`[0.10, 0.11, 0.12, 0.13, 0.14, 0.15]`). + + A corresponding real space `Real(0.10, 0.15 name='xxx')` on the other hand has an almost unlimited number of possibilities (`[0.10, 0.010000000001, 0.010000000002, ... 0.014999999999, 0.01500000000]`). + +--- + +## Legacy Hyperopt + +This Section explains the configuration of an explicit Hyperopt file (separate to the strategy). + +!!! Warning "Deprecated / legacy mode" + Since the 2021.4 release you no longer have to write a separate hyperopt class, but all strategies can be hyperopted. + Please read the [main hyperopt page](hyperopt.md) for more details. + +### Prepare hyperopt file + +Configuring an explicit hyperopt file is similar to writing your own strategy, and many tasks will be similar. + +!!! Tip "About this page" + For this page, we will be using a fictional strategy called `AwesomeStrategy` - which will be optimized using the `AwesomeHyperopt` class. + +#### Create a Custom Hyperopt File + +The simplest way to get started is to use the following command, which will create a new hyperopt file from a template, which will be located under `user_data/hyperopts/AwesomeHyperopt.py`. + +Let assume you want a hyperopt file `AwesomeHyperopt.py`: + +``` bash +freqtrade new-hyperopt --hyperopt AwesomeHyperopt +``` + +#### Legacy Hyperopt checklist + +Checklist on all tasks / possibilities in hyperopt + +Depending on the space you want to optimize, only some of the below are required: + +* fill `buy_strategy_generator` - for buy signal optimization +* fill `indicator_space` - for buy signal optimization +* fill `sell_strategy_generator` - for sell signal optimization +* fill `sell_indicator_space` - for sell signal optimization + +!!! Note + `populate_indicators` needs to create all indicators any of thee spaces may use, otherwise hyperopt will not work. + +Optional in hyperopt - can also be loaded from a strategy (recommended): + +* `populate_indicators` - fallback to create indicators +* `populate_buy_trend` - fallback if not optimizing for buy space. should come from strategy +* `populate_sell_trend` - fallback if not optimizing for sell space. should come from strategy + +!!! Note + You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods. + Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead. + +Rarely you may also need to override: + +* `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default) +* `generate_roi_table` - for custom ROI optimization (if you need the ranges for the values in the ROI table that differ from default or the number of entries (steps) in the ROI table which differs from the default 4 steps) +* `stoploss_space` - for custom stoploss optimization (if you need the range for the stoploss parameter in the optimization hyperspace that differs from default) +* `trailing_space` - for custom trailing stop optimization (if you need the ranges for the trailing stop parameters in the optimization hyperspace that differ from default) + +#### Defining a buy signal optimization + +Let's say you are curious: should you use MACD crossings or lower Bollinger +Bands to trigger your buys. And you also wonder should you use RSI or ADX to +help with those buy decisions. If you decide to use RSI or ADX, which values +should I use for them? So let's use hyperparameter optimization to solve this +mystery. + +We will start by defining a search space: + +```python + def indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching strategy parameters + """ + return [ + Integer(20, 40, name='adx-value'), + Integer(20, 40, name='rsi-value'), + Categorical([True, False], name='adx-enabled'), + Categorical([True, False], name='rsi-enabled'), + Categorical(['bb_lower', 'macd_cross_signal'], name='trigger') + ] +``` + +Above definition says: I have five parameters I want you to randomly combine +to find the best combination. Two of them are integer values (`adx-value` and `rsi-value`) and I want you test in the range of values 20 to 40. +Then we have three category variables. First two are either `True` or `False`. +We use these to either enable or disable the ADX and RSI guards. +The last one we call `trigger` and use it to decide which buy trigger we want to use. + +So let's write the buy strategy generator using these values: + +```python + @staticmethod + def buy_strategy_generator(params: Dict[str, Any]) -> Callable: + """ + Define the buy strategy parameters to be used by Hyperopt. + """ + def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: + conditions = [] + # GUARDS AND TRENDS + if 'adx-enabled' in params and params['adx-enabled']: + conditions.append(dataframe['adx'] > params['adx-value']) + if 'rsi-enabled' in params and params['rsi-enabled']: + conditions.append(dataframe['rsi'] < params['rsi-value']) + + # TRIGGERS + if 'trigger' in params: + if params['trigger'] == 'bb_lower': + conditions.append(dataframe['close'] < dataframe['bb_lowerband']) + if params['trigger'] == 'macd_cross_signal': + conditions.append(qtpylib.crossed_above( + dataframe['macd'], dataframe['macdsignal'] + )) + + # Check that volume is not 0 + conditions.append(dataframe['volume'] > 0) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'buy'] = 1 + + return dataframe + + return populate_buy_trend +``` + +Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations. +It will use the given historical data and make buys based on the buy signals generated with the above function. +Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)). + +!!! Note + The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators. + When you want to test an indicator that isn't used by the bot currently, remember to + add it to the `populate_indicators()` method in your strategy or hyperopt file. + +#### Sell optimization + +Similar to the buy-signal above, sell-signals can also be optimized. +Place the corresponding settings into the following methods + +* Inside `sell_indicator_space()` - the parameters hyperopt shall be optimizing. +* Within `sell_strategy_generator()` - populate the nested method `populate_sell_trend()` to apply the parameters. + +The configuration and rules are the same than for buy signals. +To avoid naming collisions in the search-space, please prefix all sell-spaces with `sell-`. + +### Execute Hyperopt + +Once you have updated your hyperopt configuration you can run it. +Because hyperopt tries a lot of combinations to find the best parameters it will take time to get a good result. More time usually results in better results. + +We strongly recommend to use `screen` or `tmux` to prevent any connection loss. + +```bash +freqtrade hyperopt --config config.json --hyperopt --hyperopt-loss --strategy -e 500 --spaces all +``` + +Use `` as the name of the custom hyperopt used. + +The `-e` option will set how many evaluations hyperopt will do. Since hyperopt uses Bayesian search, running too many epochs at once may not produce greater results. Experience has shown that best results are usually not improving much after 500-1000 epochs. +Doing multiple runs (executions) with a few 1000 epochs and different random state will most likely produce different results. + +The `--spaces all` option determines that all possible parameters should be optimized. Possibilities are listed below. + +!!! Note + Hyperopt will store hyperopt results with the timestamp of the hyperopt start time. + Reading commands (`hyperopt-list`, `hyperopt-show`) can use `--hyperopt-filename ` to read and display older hyperopt results. + You can find a list of filenames with `ls -l user_data/hyperopt_results/`. + +#### Running Hyperopt using methods from a strategy + +Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided. + +```bash +freqtrade hyperopt --hyperopt AwesomeHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy AwesomeStrategy +``` + +### Understand the Hyperopt Result + +Once Hyperopt is completed you can use the result to create a new strategy. +Given the following result from hyperopt: + +``` +Best result: + + 44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367 + +Buy hyperspace params: +{ 'adx-value': 44, + 'rsi-value': 29, + 'adx-enabled': False, + 'rsi-enabled': True, + 'trigger': 'bb_lower'} +``` + +You should understand this result like: + +* The buy trigger that worked best was `bb_lower`. +* You should not use ADX because `adx-enabled: False`) +* You should **consider** using the RSI indicator (`rsi-enabled: True` and the best value is `29.0` (`rsi-value: 29.0`) + +You have to look inside your strategy file into `buy_strategy_generator()` +method, what those values match to. + +So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that translates to the following code block: + +```python +(dataframe['rsi'] < 29.0) +``` + +Translating your whole hyperopt result as the new buy-signal would then look like: + +```python +def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: + dataframe.loc[ + ( + (dataframe['rsi'] < 29.0) & # rsi-value + dataframe['close'] < dataframe['bb_lowerband'] # trigger + ), + 'buy'] = 1 + return dataframe +``` + +### Validate backtesting results + +Once the optimized parameters and conditions have been implemented into your strategy, you should backtest the strategy to make sure everything is working as expected. + +To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting. + +Should results don't match, please double-check to make sure you transferred all conditions correctly. +Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy. +You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`). + +### Sharing methods with your strategy + +Hyperopt classes provide access to the Strategy via the `strategy` class attribute. +This can be a great way to reduce code duplication if used correctly, but will also complicate usage for inexperienced users. + +``` python +from pandas import DataFrame +from freqtrade.strategy.interface import IStrategy +import freqtrade.vendor.qtpylib.indicators as qtpylib + +class MyAwesomeStrategy(IStrategy): + + buy_params = { + 'rsi-value': 30, + 'adx-value': 35, + } + + def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + return self.buy_strategy_generator(self.buy_params, dataframe, metadata) + + @staticmethod + def buy_strategy_generator(params, dataframe: DataFrame, metadata: dict) -> DataFrame: + dataframe.loc[ + ( + qtpylib.crossed_above(dataframe['rsi'], params['rsi-value']) & + dataframe['adx'] > params['adx-value']) & + dataframe['volume'] > 0 + ) + , 'buy'] = 1 + return dataframe + +class MyAwesomeHyperOpt(IHyperOpt): + ... + @staticmethod + def buy_strategy_generator(params: Dict[str, Any]) -> Callable: + """ + Define the buy strategy parameters to be used by Hyperopt. + """ + def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: + # Call strategy's buy strategy generator + return self.StrategyClass.buy_strategy_generator(params, dataframe, metadata) + + return populate_buy_trend +``` diff --git a/docs/assets/ccxt-logo.svg b/docs/assets/ccxt-logo.svg new file mode 100644 index 000000000..e52682546 --- /dev/null +++ b/docs/assets/ccxt-logo.svg @@ -0,0 +1,3 @@ + + + \ No newline at end of file diff --git a/docs/assets/freqtrade_poweredby.svg b/docs/assets/freqtrade_poweredby.svg new file mode 100644 index 000000000..957ec6401 --- /dev/null +++ b/docs/assets/freqtrade_poweredby.svg @@ -0,0 +1,44 @@ + + + + + + + + + image/svg+xml + + + + + + + + + + + + + + + + + + + + + + + + + + + + Freqtrade + + + + + poweredby + + diff --git a/docs/backtesting.md b/docs/backtesting.md index d02c59f05..2027c2079 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -15,7 +15,8 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH] [--data-format-ohlcv {json,jsongz,hdf5}] [--max-open-trades INT] [--stake-amount STAKE_AMOUNT] [--fee FLOAT] - [--eps] [--dmmp] [--enable-protections] + [-p PAIRS [PAIRS ...]] [--eps] [--dmmp] + [--enable-protections] [--dry-run-wallet DRY_RUN_WALLET] [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]] [--export EXPORT] [--export-filename PATH] @@ -23,8 +24,7 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH] optional arguments: -h, --help show this help message and exit -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME - Specify ticker interval (`1m`, `5m`, `30m`, `1h`, - `1d`). + Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`). --timerange TIMERANGE Specify what timerange of data to use. --data-format-ohlcv {json,jsongz,hdf5} @@ -38,6 +38,9 @@ optional arguments: setting. --fee FLOAT Specify fee ratio. Will be applied twice (on trade entry and exit). + -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] + Limit command to these pairs. Pairs are space- + separated. --eps, --enable-position-stacking Allow buying the same pair multiple times (position stacking). @@ -234,29 +237,29 @@ The most important in the backtesting is to understand the result. A backtesting result will look like that: ``` -========================================================= BACKTESTING REPORT ======================================================== -| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | -|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:| -| ADA/BTC | 35 | -0.11 | -3.88 | -0.00019428 | -1.94 | 4:35:00 | 14 | 0 | 21 | -| ARK/BTC | 11 | -0.41 | -4.52 | -0.00022647 | -2.26 | 2:03:00 | 3 | 0 | 8 | -| BTS/BTC | 32 | 0.31 | 9.78 | 0.00048938 | 4.89 | 5:05:00 | 18 | 0 | 14 | -| DASH/BTC | 13 | -0.08 | -1.07 | -0.00005343 | -0.53 | 4:39:00 | 6 | 0 | 7 | -| ENG/BTC | 18 | 1.36 | 24.54 | 0.00122807 | 12.27 | 2:50:00 | 8 | 0 | 10 | -| EOS/BTC | 36 | 0.08 | 3.06 | 0.00015304 | 1.53 | 3:34:00 | 16 | 0 | 20 | -| ETC/BTC | 26 | 0.37 | 9.51 | 0.00047576 | 4.75 | 6:14:00 | 11 | 0 | 15 | -| ETH/BTC | 33 | 0.30 | 9.96 | 0.00049856 | 4.98 | 7:31:00 | 16 | 0 | 17 | -| IOTA/BTC | 32 | 0.03 | 1.09 | 0.00005444 | 0.54 | 3:12:00 | 14 | 0 | 18 | -| LSK/BTC | 15 | 1.75 | 26.26 | 0.00131413 | 13.13 | 2:58:00 | 6 | 0 | 9 | -| LTC/BTC | 32 | -0.04 | -1.38 | -0.00006886 | -0.69 | 4:49:00 | 11 | 0 | 21 | -| NANO/BTC | 17 | 1.26 | 21.39 | 0.00107058 | 10.70 | 1:55:00 | 10 | 0 | 7 | -| NEO/BTC | 23 | 0.82 | 18.97 | 0.00094936 | 9.48 | 2:59:00 | 10 | 0 | 13 | -| REQ/BTC | 9 | 1.17 | 10.54 | 0.00052734 | 5.27 | 3:47:00 | 4 | 0 | 5 | -| XLM/BTC | 16 | 1.22 | 19.54 | 0.00097800 | 9.77 | 3:15:00 | 7 | 0 | 9 | -| XMR/BTC | 23 | -0.18 | -4.13 | -0.00020696 | -2.07 | 5:30:00 | 12 | 0 | 11 | -| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 | 0 | 23 | -| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 | 0 | 15 | -| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 | -========================================================= SELL REASON STATS ========================================================= +========================================================= BACKTESTING REPORT ========================================================== +| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins Draws Loss Win% | +|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:-------------|-------------------------:| +| ADA/BTC | 35 | -0.11 | -3.88 | -0.00019428 | -1.94 | 4:35:00 | 14 0 21 40.0 | +| ARK/BTC | 11 | -0.41 | -4.52 | -0.00022647 | -2.26 | 2:03:00 | 3 0 8 27.3 | +| BTS/BTC | 32 | 0.31 | 9.78 | 0.00048938 | 4.89 | 5:05:00 | 18 0 14 56.2 | +| DASH/BTC | 13 | -0.08 | -1.07 | -0.00005343 | -0.53 | 4:39:00 | 6 0 7 46.2 | +| ENG/BTC | 18 | 1.36 | 24.54 | 0.00122807 | 12.27 | 2:50:00 | 8 0 10 44.4 | +| EOS/BTC | 36 | 0.08 | 3.06 | 0.00015304 | 1.53 | 3:34:00 | 16 0 20 44.4 | +| ETC/BTC | 26 | 0.37 | 9.51 | 0.00047576 | 4.75 | 6:14:00 | 11 0 15 42.3 | +| ETH/BTC | 33 | 0.30 | 9.96 | 0.00049856 | 4.98 | 7:31:00 | 16 0 17 48.5 | +| IOTA/BTC | 32 | 0.03 | 1.09 | 0.00005444 | 0.54 | 3:12:00 | 14 0 18 43.8 | +| LSK/BTC | 15 | 1.75 | 26.26 | 0.00131413 | 13.13 | 2:58:00 | 6 0 9 40.0 | +| LTC/BTC | 32 | -0.04 | -1.38 | -0.00006886 | -0.69 | 4:49:00 | 11 0 21 34.4 | +| NANO/BTC | 17 | 1.26 | 21.39 | 0.00107058 | 10.70 | 1:55:00 | 10 0 7 58.5 | +| NEO/BTC | 23 | 0.82 | 18.97 | 0.00094936 | 9.48 | 2:59:00 | 10 0 13 43.5 | +| REQ/BTC | 9 | 1.17 | 10.54 | 0.00052734 | 5.27 | 3:47:00 | 4 0 5 44.4 | +| XLM/BTC | 16 | 1.22 | 19.54 | 0.00097800 | 9.77 | 3:15:00 | 7 0 9 43.8 | +| XMR/BTC | 23 | -0.18 | -4.13 | -0.00020696 | -2.07 | 5:30:00 | 12 0 11 52.2 | +| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 0 23 34.3 | +| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 0 15 31.8 | +| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 | +========================================================= SELL REASON STATS ========================================================== | Sell Reason | Sells | Wins | Draws | Losses | |:-------------------|--------:|------:|-------:|--------:| | trailing_stop_loss | 205 | 150 | 0 | 55 | @@ -264,11 +267,11 @@ A backtesting result will look like that: | sell_signal | 56 | 36 | 0 | 20 | | force_sell | 2 | 0 | 0 | 2 | ====================================================== LEFT OPEN TRADES REPORT ====================================================== -| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | -|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:| -| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 | 0 | 0 | -| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 | 0 | 0 | -| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 | 0 | 0 | +| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Win Draw Loss Win% | +|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:| +| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 0 0 100 | +| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 0 0 100 | +| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 0 0 100 | =============== SUMMARY METRICS =============== | Metric | Value | |-----------------------+---------------------| @@ -294,6 +297,8 @@ A backtesting result will look like that: | Days win/draw/lose | 12 / 82 / 25 | | Avg. Duration Winners | 4:23:00 | | Avg. Duration Loser | 6:55:00 | +| Zero Duration Trades | 4.6% (20) | +| Rejected Buy signals | 3089 | | | | | Min balance | 0.00945123 BTC | | Max balance | 0.01846651 BTC | @@ -315,7 +320,7 @@ The last line will give you the overall performance of your strategy, here: ``` -| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 243 | +| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 | ``` The bot has made `429` trades for an average duration of `4:12:00`, with a performance of `76.20%` (profit), that means it has @@ -381,6 +386,8 @@ It contains some useful key metrics about performance of your strategy on backte | Days win/draw/lose | 12 / 82 / 25 | | Avg. Duration Winners | 4:23:00 | | Avg. Duration Loser | 6:55:00 | +| Zero Duration Trades | 4.6% (20) | +| Rejected Buy signals | 3089 | | | | | Min balance | 0.00945123 BTC | | Max balance | 0.01846651 BTC | @@ -410,6 +417,8 @@ It contains some useful key metrics about performance of your strategy on backte - `Best day` / `Worst day`: Best and worst day based on daily profit. - `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade). - `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades. +- `Zero Duration Trades`: A number of trades that completed within same candle as they opened and had `trailing_stop_loss` sell reason. A significant amount of such trades may indicate that strategy is exploiting trailing stoploss behavior in backtesting and produces unrealistic results. +- `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached. - `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period. - `Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced). - `Drawdown high` / `Drawdown low`: Profit at the beginning and end of the largest drawdown period. A negative low value means initial capital lost. @@ -421,6 +430,7 @@ It contains some useful key metrics about performance of your strategy on backte Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions: - Buys happen at open-price +- All orders are filled at the requested price (no slippage, no unfilled orders) - Sell-signal sells happen at open-price of the consecutive candle - Sell-signal is favored over Stoploss, because sell-signals are assumed to trigger on candle's open - ROI @@ -468,11 +478,11 @@ There will be an additional table comparing win/losses of the different strategi Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy. ``` -=========================================================== STRATEGY SUMMARY =========================================================== -| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | -|:------------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:| -| Strategy1 | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 | -| Strategy2 | 1487 | -0.13 | -197.58 | -0.00988917 | -98.79 | 4:43:00 | 662 | 0 | 825 | +=========================================================== STRATEGY SUMMARY ========================================================================= +| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses | Drawdown % | +|:------------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:| +| Strategy1 | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 | 0 | 243 | 45.2 | +| Strategy2 | 1487 | -0.13 | -197.58 | -0.00988917 | -98.79 | 4:43:00 | 662 | 0 | 825 | 241.68 | ``` ## Next step diff --git a/docs/configuration.md b/docs/configuration.md index eb3351b8f..eff8fe322 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -11,7 +11,16 @@ Per default, the bot loads the configuration from the `config.json` file, locate You can specify a different configuration file used by the bot with the `-c/--config` command line option. -In some advanced use cases, multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream. +Multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream. + +!!! Tip "Use multiple configuration files to keep secrets secret" + You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself. + + ``` bash + freqtrade trade --config user_data/config.json --config user_data/config-private.json <...> + ``` + The 2nd file should only specify what you intend to override. + If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`). If you used the [Quick start](installation.md/#quick-start) method for installing the bot, the installation script should have already created the default configuration file (`config.json`) for you. @@ -59,8 +68,9 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset). [Strategy Override](#parameters-in-the-strategy).
*Defaults to `0.0` (no offset).*
**Datatype:** Float | `trailing_only_offset_is_reached` | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
*Defaults to `false`.*
**Datatype:** Boolean | `fee` | Fee used during backtesting / dry-runs. Should normally not be configured, which has freqtrade fall back to the exchange default fee. Set as ratio (e.g. 0.001 = 0.1%). Fee is applied twice for each trade, once when buying, once when selling.
**Datatype:** Float (as ratio) -| `unfilledtimeout.buy` | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Integer -| `unfilledtimeout.sell` | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Integer +| `unfilledtimeout.buy` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Integer +| `unfilledtimeout.sell` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Integer +| `unfilledtimeout.unit` | Unit to use in unfilledtimeout setting. Note: If you set unfilledtimeout.unit to "seconds", "internals.process_throttle_secs" must be inferior or equal to timeout [Strategy Override](#parameters-in-the-strategy).
*Defaults to `minutes`.*
**Datatype:** String | `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).
*Defaults to `bid`.*
**Datatype:** String (either `ask` or `bid`). | `bid_strategy.ask_last_balance` | **Required.** Interpolate the bidding price. More information [below](#buy-price-without-orderbook-enabled). | `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled).
**Datatype:** Boolean @@ -167,7 +177,7 @@ This exchange has also a limit on USD - where all orders must be > 10$ - which h To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%). -With a stoploss of 10% - we'd therefore end up with a value of ~13.8$ (`12 * (1 + 0.05 + 0.1)`). +With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)`). If we take in account a stoploss of 10% on top of that - we'd end up with a value of ~14$ (`12.6 / (1 - 0.1)`). To limit this calculation in case of large stoploss values, the calculated minimum stake-limit will never be more than 50% above the real limit. @@ -518,16 +528,27 @@ API Keys are usually only required for live trading (trading for real money, bot **Insert your Exchange API key (change them by fake api keys):** ```json -"exchange": { +{ + "exchange": { "name": "bittrex", "key": "af8ddd35195e9dc500b9a6f799f6f5c93d89193b", "secret": "08a9dc6db3d7b53e1acebd9275677f4b0a04f1a5", - ... + //"password": "", // Optional, not needed by all exchanges) + // ... + } + //... } ``` You should also make sure to read the [Exchanges](exchanges.md) section of the documentation to be aware of potential configuration details specific to your exchange. +!!! Hint "Keep your secrets secret" + To keep your secrets secret, we recommend to use a 2nd configuration for your API keys. + Simply use the above snippet in a new configuration file (e.g. `config-private.json`) and keep your settings in this file. + You can then start the bot with `freqtrade trade --config user_data/config.json --config user_data/config-private.json <...>` to have your keys loaded. + + **NEVER** share your private configuration file or your exchange keys with anyone! + ### Using proxy with Freqtrade To use a proxy with freqtrade, add the kwarg `"aiohttp_trust_env"=true` to the `"ccxt_async_kwargs"` dict in the exchange section of the configuration. diff --git a/docs/data-download.md b/docs/data-download.md index 04f444a8b..01561c89b 100644 --- a/docs/data-download.md +++ b/docs/data-download.md @@ -11,8 +11,9 @@ Otherwise `--exchange` becomes mandatory. You can use a relative timerange (`--days 20`) or an absolute starting point (`--timerange 20200101-`). For incremental downloads, the relative approach should be used. !!! Tip "Tip: Updating existing data" - If you already have backtesting data available in your data-directory and would like to refresh this data up to today, use `--days xx` with a number slightly higher than the missing number of days. Freqtrade will keep the available data and only download the missing data. - Be careful though: If the number is too small (which would result in a few missing days), the whole dataset will be removed and only xx days will be downloaded. + If you already have backtesting data available in your data-directory and would like to refresh this data up to today, do not use `--days` or `--timerange` parameters. Freqtrade will keep the available data and only download the missing data. + If you are updating existing data after inserting new pairs that you have no data for, use `--new-pairs-days xx` parameter. Specified number of days will be downloaded for new pairs while old pairs will be updated with missing data only. + If you use `--days xx` parameter alone - data for specified number of days will be downloaded for _all_ pairs. Be careful, if specified number of days is smaller than gap between now and last downloaded candle - freqtrade will delete all existing data to avoid gaps in candle data. ### Usage @@ -20,8 +21,9 @@ You can use a relative timerange (`--days 20`) or an absolute starting point (`- usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-p PAIRS [PAIRS ...]] [--pairs-file FILE] - [--days INT] [--timerange TIMERANGE] - [--dl-trades] [--exchange EXCHANGE] + [--days INT] [--new-pairs-days INT] + [--timerange TIMERANGE] [--dl-trades] + [--exchange EXCHANGE] [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]] [--erase] [--data-format-ohlcv {json,jsongz,hdf5}] @@ -30,10 +32,12 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] optional arguments: -h, --help show this help message and exit -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] - Show profits for only these pairs. Pairs are space- + Limit command to these pairs. Pairs are space- separated. --pairs-file FILE File containing a list of pairs to download. --days INT Download data for given number of days. + --new-pairs-days INT Download data of new pairs for given number of days. + Default: `None`. --timerange TIMERANGE Specify what timerange of data to use. --dl-trades Download trades instead of OHLCV data. The bot will @@ -48,10 +52,10 @@ optional arguments: exchange/pairs/timeframes. --data-format-ohlcv {json,jsongz,hdf5} Storage format for downloaded candle (OHLCV) data. - (default: `json`). + (default: `None`). --data-format-trades {json,jsongz,hdf5} Storage format for downloaded trades data. (default: - `jsongz`). + `None`). Common arguments: -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). diff --git a/docs/docker_quickstart.md b/docs/docker_quickstart.md index 017264569..3a85aa885 100644 --- a/docs/docker_quickstart.md +++ b/docs/docker_quickstart.md @@ -10,11 +10,11 @@ Start by downloading and installing Docker CE for your platform: * [Windows](https://docs.docker.com/docker-for-windows/install/) * [Linux](https://docs.docker.com/install/) -To simplify running freqtrade, please install [`docker-compose`](https://docs.docker.com/compose/install/) should be installed and available to follow the below [docker quick start guide](#docker-quick-start). +To simplify running freqtrade, [`docker-compose`](https://docs.docker.com/compose/install/) should be installed and available to follow the below [docker quick start guide](#docker-quick-start). ## Freqtrade with docker-compose -Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.com/r/freqtradeorg/freqtrade/), as well as a [docker-compose file](https://github.com/freqtrade/freqtrade/blob/develop/docker-compose.yml) ready for usage. +Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.com/r/freqtradeorg/freqtrade/), as well as a [docker-compose file](https://github.com/freqtrade/freqtrade/blob/stable/docker-compose.yml) ready for usage. !!! Note - The following section assumes that `docker` and `docker-compose` are installed and available to the logged in user. @@ -22,7 +22,7 @@ Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.co ### Docker quick start -Create a new directory and place the [docker-compose file](https://github.com/freqtrade/freqtrade/blob/develop/docker-compose.yml) in this directory. +Create a new directory and place the [docker-compose file](https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml) in this directory. === "PC/MAC/Linux" ``` bash @@ -48,6 +48,8 @@ Create a new directory and place the [docker-compose file](https://github.com/fr # Download the docker-compose file from the repository curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml + # Edit the compose file to use an image named `*_pi` (stable_pi or develop_pi) + # Pull the freqtrade image docker-compose pull @@ -65,6 +67,40 @@ Create a new directory and place the [docker-compose file](https://github.com/fr # image: freqtradeorg/freqtrade:develop_pi ``` +=== "ARM 64 Systenms (Mac M1, Raspberry Pi 4, Jetson Nano)" + In case of a Mac M1, make sure that your docker installation is running in native mode + Arm64 images are not yet provided via Docker Hub and need to be build locally first. + Depending on the device, this may take a few minutes (Apple M1) or multiple hours (Raspberry Pi) + + ``` bash + # Clone Freqtrade repository + git clone https://github.com/freqtrade/freqtrade.git + cd freqtrade + # Optionally switch to the stable version + git checkout stable + + # Modify your docker-compose file to enable building and change the image name + # (see the Note Box below for necessary changes) + + # Build image + docker-compose build + + # Create user directory structure + docker-compose run --rm freqtrade create-userdir --userdir user_data + + # Create configuration - Requires answering interactive questions + docker-compose run --rm freqtrade new-config --config user_data/config.json + ``` + + !!! Note "Change your docker Image" + You have to change the docker image in the docker-compose file for your arm64 build to work properly. + ``` yml + image: freqtradeorg/freqtrade:custom_arm64 + build: + context: . + dockerfile: "./docker/Dockerfile.aarch64" + ``` + The above snippet creates a new directory called `ft_userdata`, downloads the latest compose file and pulls the freqtrade image. The last 2 steps in the snippet create the directory with `user_data`, as well as (interactively) the default configuration based on your selections. @@ -156,8 +192,8 @@ Head over to the [Backtesting Documentation](backtesting.md) to learn more. ### Additional dependencies with docker-compose -If your strategy requires dependencies not included in the default image (like [technical](https://github.com/freqtrade/technical)) - it will be necessary to build the image on your host. -For this, please create a Dockerfile containing installation steps for the additional dependencies (have a look at [docker/Dockerfile.technical](https://github.com/freqtrade/freqtrade/blob/develop/docker/Dockerfile.technical) for an example). +If your strategy requires dependencies not included in the default image - it will be necessary to build the image on your host. +For this, please create a Dockerfile containing installation steps for the additional dependencies (have a look at [docker/Dockerfile.custom](https://github.com/freqtrade/freqtrade/blob/develop/docker/Dockerfile.custom) for an example). You'll then also need to modify the `docker-compose.yml` file and uncomment the build step, as well as rename the image to avoid naming collisions. diff --git a/docs/edge.md b/docs/edge.md index 5565ca2f9..237ff36f6 100644 --- a/docs/edge.md +++ b/docs/edge.md @@ -1,9 +1,9 @@ # Edge positioning -The `Edge Positioning` module uses probability to calculate your win rate and risk reward ratio. It will use these statistics to control your strategy trade entry points, position size and, stoploss. +The `Edge Positioning` module uses probability to calculate your win rate and risk reward ratio. It will use these statistics to control your strategy trade entry points, position size and, stoploss. !!! Warning - `Edge positioning` is not compatible with dynamic (volume-based) whitelist. + WHen using `Edge positioning` with a dynamic whitelist (VolumePairList), make sure to also use `AgeFilter` and set it to at least `calculate_since_number_of_days` to avoid problems with missing data. !!! Note `Edge Positioning` only considers *its own* buy/sell/stoploss signals. It ignores the stoploss, trailing stoploss, and ROI settings in the strategy configuration file. @@ -14,7 +14,7 @@ The `Edge Positioning` module uses probability to calculate your win rate and ri Trading strategies are not perfect. They are frameworks that are susceptible to the market and its indicators. Because the market is not at all predictable, sometimes a strategy will win and sometimes the same strategy will lose. -To obtain an edge in the market, a strategy has to make more money than it loses. Making money in trading is not only about *how often* the strategy makes or loses money. +To obtain an edge in the market, a strategy has to make more money than it loses. Making money in trading is not only about *how often* the strategy makes or loses money. !!! tip "It doesn't matter how often, but how much!" A bad strategy might make 1 penny in *ten* transactions but lose 1 dollar in *one* transaction. If one only checks the number of winning trades, it would be misleading to think that the strategy is actually making a profit. @@ -215,16 +215,20 @@ Let's say the stake currency is **ETH** and there is $10$ **ETH** on the wallet. usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-s NAME] [--strategy-path PATH] [-i TIMEFRAME] [--timerange TIMERANGE] + [--data-format-ohlcv {json,jsongz,hdf5}] [--max-open-trades INT] [--stake-amount STAKE_AMOUNT] - [--fee FLOAT] [--stoplosses STOPLOSS_RANGE] + [--fee FLOAT] [-p PAIRS [PAIRS ...]] + [--stoplosses STOPLOSS_RANGE] optional arguments: -h, --help show this help message and exit -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME - Specify ticker interval (`1m`, `5m`, `30m`, `1h`, - `1d`). + Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`). --timerange TIMERANGE Specify what timerange of data to use. + --data-format-ohlcv {json,jsongz,hdf5} + Storage format for downloaded candle (OHLCV) data. + (default: `None`). --max-open-trades INT Override the value of the `max_open_trades` configuration setting. @@ -233,6 +237,9 @@ optional arguments: setting. --fee FLOAT Specify fee ratio. Will be applied twice (on trade entry and exit). + -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] + Limit command to these pairs. Pairs are space- + separated. --stoplosses STOPLOSS_RANGE Defines a range of stoploss values against which edge will assess the strategy. The format is "min,max,step" diff --git a/docs/exchanges.md b/docs/exchanges.md index 4c7e44b06..8797ade8c 100644 --- a/docs/exchanges.md +++ b/docs/exchanges.md @@ -7,10 +7,10 @@ This page combines common gotchas and informations which are exchange-specific a !!! Tip "Stoploss on Exchange" Binance supports `stoploss_on_exchange` and uses stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it. -### Blacklists +### Binance Blacklist For Binance, please add `"BNB/"` to your blacklist to avoid issues. -Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB order unsellable as the expected amount is not there anymore. +Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore. ### Binance sites @@ -44,6 +44,10 @@ Due to the heavy rate-limiting applied by Kraken, the following configuration se Downloading kraken data will require significantly more memory (RAM) than any other exchange, as the trades-data needs to be converted into candles on your machine. It will also take a long time, as freqtrade will need to download every single trade that happened on the exchange for the pair / timerange combination, therefore please be patient. +!!! Warning "rateLimit tuning" + Please pay attention that rateLimit configuration entry holds delay in milliseconds between requests, NOT requests\sec rate. + So, in order to mitigate Kraken API "Rate limit exceeded" exception, this configuration should be increased, NOT decreased. + ## Bittrex ### Order types @@ -96,6 +100,23 @@ To use subaccounts with FTX, you need to edit the configuration and add the foll } ``` +## Kucoin + +Kucoin requries a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows: + +```json +"exchange": { + "name": "kucoin", + "key": "your_exchange_key", + "secret": "your_exchange_secret", + "password": "your_exchange_api_key_password", +``` + +### Kucoin Blacklists + +For Kucoin, please add `"KCS/"` to your blacklist to avoid issues. +Accounts having KCS accounts use this to pay for fees - if your first trade happens to be on `KCS`, further trades will consume this position and make the initial KCS trade unsellable as the expected amount is not there anymore. + ## All exchanges Should you experience constant errors with Nonce (like `InvalidNonce`), it is best to regenerate the API keys. Resetting Nonce is difficult and it's usually easier to regenerate the API keys. diff --git a/docs/faq.md b/docs/faq.md index 93b806dca..7233a92fe 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -1,5 +1,19 @@ # Freqtrade FAQ +## Supported Markets + +Freqtrade supports spot trading only. + +### Can I open short positions? + +No, Freqtrade does not support trading with margin / leverage, and cannot open short positions. + +In some cases, your exchange may provide leveraged spot tokens which can be traded with Freqtrade eg. BTCUP/USD, BTCDOWN/USD, ETHBULL/USD, ETHBEAR/USD, etc... + +### Can I trade options or futures? + +No, options and futures trading are not supported. + ## Beginner Tips & Tricks * When you work with your strategy & hyperopt file you should use a proper code editor like VSCode or PyCharm. A good code editor will provide syntax highlighting as well as line numbers, making it easy to find syntax errors (most likely pointed out by Freqtrade during startup). @@ -142,7 +156,7 @@ freqtrade hyperopt --hyperopt SampleHyperopt --hyperopt-loss SharpeHyperOptLossD ### Why does it take a long time to run hyperopt? -* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) - or the Freqtrade [discord community](https://discord.gg/X89cVG). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you. +* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) - or the Freqtrade [discord community](https://discord.gg/MA9v74M). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you. * If you wonder why it can take from 20 minutes to days to do 1000 epochs here are some answers: diff --git a/docs/hyperopt.md b/docs/hyperopt.md index 96c7354b9..d8f4a8071 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -1,19 +1,22 @@ # Hyperopt This page explains how to tune your strategy by finding the optimal -parameters, a process called hyperparameter optimization. The bot uses several -algorithms included in the `scikit-optimize` package to accomplish this. The -search will burn all your CPU cores, make your laptop sound like a fighter jet -and still take a long time. +parameters, a process called hyperparameter optimization. The bot uses algorithms included in the `scikit-optimize` package to accomplish this. +The search will burn all your CPU cores, make your laptop sound like a fighter jet and still take a long time. In general, the search for best parameters starts with a few random combinations (see [below](#reproducible-results) for more details) and then uses Bayesian search with a ML regressor algorithm (currently ExtraTreesRegressor) to quickly find a combination of parameters in the search hyperspace that minimizes the value of the [loss function](#loss-functions). -Hyperopt requires historic data to be available, just as backtesting does. +Hyperopt requires historic data to be available, just as backtesting does (hyperopt runs backtesting many times with different parameters). To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation. !!! Bug Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133) +!!! Note + Since 2021.4 release you no longer have to write a separate hyperopt class, but can configure the parameters directly in the strategy. + The legacy method is still supported, but it is no longer the recommended way of setting up hyperopt. + The legacy documentation is available at [Legacy Hyperopt](advanced-hyperopt.md#legacy-hyperopt). + ## Install hyperopt dependencies Since Hyperopt dependencies are not needed to run the bot itself, are heavy, can not be easily built on some platforms (like Raspberry PI), they are not installed by default. Before you run Hyperopt, you need to install the corresponding dependencies, as described in this section below. @@ -34,7 +37,6 @@ pip install -r requirements-hyperopt.txt ## Hyperopt command reference - ``` usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-s NAME] [--strategy-path PATH] @@ -42,8 +44,9 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--data-format-ohlcv {json,jsongz,hdf5}] [--max-open-trades INT] [--stake-amount STAKE_AMOUNT] [--fee FLOAT] - [--hyperopt NAME] [--hyperopt-path PATH] [--eps] - [--dmmp] [--enable-protections] + [-p PAIRS [PAIRS ...]] [--hyperopt NAME] + [--hyperopt-path PATH] [--eps] [--dmmp] + [--enable-protections] [--dry-run-wallet DRY_RUN_WALLET] [-e INT] [--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]] [--print-all] [--no-color] [--print-json] [-j JOBS] @@ -53,8 +56,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] optional arguments: -h, --help show this help message and exit -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME - Specify ticker interval (`1m`, `5m`, `30m`, `1h`, - `1d`). + Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`). --timerange TIMERANGE Specify what timerange of data to use. --data-format-ohlcv {json,jsongz,hdf5} @@ -68,6 +70,9 @@ optional arguments: setting. --fee FLOAT Specify fee ratio. Will be applied twice (on trade entry and exit). + -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] + Limit command to these pairs. Pairs are space- + separated. --hyperopt NAME Specify hyperopt class name which will be used by the bot. --hyperopt-path PATH Specify additional lookup path for Hyperopt and @@ -104,7 +109,8 @@ optional arguments: reproducible hyperopt results. --min-trades INT Set minimal desired number of trades for evaluations in the hyperopt optimization path (default: 1). - --hyperopt-loss NAME Specify the class name of the hyperopt loss function + --hyperopt-loss NAME, --hyperoptloss NAME + Specify the class name of the hyperopt loss function class (IHyperOptLoss). Different functions can generate completely different results, since the target for optimization is different. Built-in @@ -137,47 +143,19 @@ Strategy arguments: ``` -## Prepare Hyperopting - -Before we start digging into Hyperopt, we recommend you to take a look at -the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt.py). - -Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar. - -!!! Tip "About this page" - For this page, we will be using a fictional strategy called `AwesomeStrategy` - which will be optimized using the `AwesomeHyperopt` class. - -The simplest way to get started is to use the following, command, which will create a new hyperopt file from a template, which will be located under `user_data/hyperopts/AwesomeHyperopt.py`. - -``` bash -freqtrade new-hyperopt --hyperopt AwesomeHyperopt -``` - ### Hyperopt checklist Checklist on all tasks / possibilities in hyperopt Depending on the space you want to optimize, only some of the below are required: -* fill `buy_strategy_generator` - for buy signal optimization -* fill `indicator_space` - for buy signal optimization -* fill `sell_strategy_generator` - for sell signal optimization -* fill `sell_indicator_space` - for sell signal optimization +* define parameters with `space='buy'` - for buy signal optimization +* define parameters with `space='sell'` - for sell signal optimization !!! Note `populate_indicators` needs to create all indicators any of the spaces may use, otherwise hyperopt will not work. -Optional in hyperopt - can also be loaded from a strategy (recommended): - -* `populate_indicators` - fallback to create indicators -* `populate_buy_trend` - fallback if not optimizing for buy space. should come from strategy -* `populate_sell_trend` - fallback if not optimizing for sell space. should come from strategy - -!!! Note - You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods. - Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead. - -Rarely you may also need to override: +Rarely you may also need to create a [nested class](advanced-hyperopt.md#overriding-pre-defined-spaces) named `HyperOpt` and implement * `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default) * `generate_roi_table` - for custom ROI optimization (if you need the ranges for the values in the ROI table that differ from default or the number of entries (steps) in the ROI table which differs from the default 4 steps) @@ -185,31 +163,30 @@ Rarely you may also need to override: * `trailing_space` - for custom trailing stop optimization (if you need the ranges for the trailing stop parameters in the optimization hyperspace that differ from default) !!! Tip "Quickly optimize ROI, stoploss and trailing stoploss" - You can quickly optimize the spaces `roi`, `stoploss` and `trailing` without changing anything (i.e. without creation of a "complete" Hyperopt class with dimensions, parameters, triggers and guards, as described in this document) from the default hyperopt template by relying on your strategy to do most of the calculations. + You can quickly optimize the spaces `roi`, `stoploss` and `trailing` without changing anything in your strategy. - ```python + ``` bash # Have a working strategy at hand. - freqtrade new-hyperopt --hyperopt EmptyHyperopt - - freqtrade hyperopt --hyperopt EmptyHyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss trailing --strategy MyWorkingStrategy --config config.json -e 100 + freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss trailing --strategy MyWorkingStrategy --config config.json -e 100 ``` -### Create a Custom Hyperopt File +### Hyperopt execution logic -Let assume you want a hyperopt file `AwesomeHyperopt.py`: +Hyperopt will first load your data into memory and will then run `populate_indicators()` once per Pair to generate all indicators. -``` bash -freqtrade new-hyperopt --hyperopt AwesomeHyperopt -``` +Hyperopt will then spawn into different processes (number of processors, or `-j `), and run backtesting over and over again, changing the parameters that are part of the `--spaces` defined. -This command will create a new hyperopt file from a template, allowing you to get started quickly. +For every new set of parameters, freqtrade will run first `populate_buy_trend()` followed by `populate_sell_trend()`, and then run the regular backtesting process to simulate trades. + +After backtesting, the results are passed into the [loss function](#loss-functions), which will evaluate if this result was better or worse than previous results. +Based on the loss function result, hyperopt will determine the next set of parameters to try in the next round of backtesting. ### Configure your Guards and Triggers -There are two places you need to change in your hyperopt file to add a new buy hyperopt for testing: +There are two places you need to change in your strategy file to add a new buy hyperopt for testing: -* Inside `indicator_space()` - the parameters hyperopt shall be optimizing. -* Within `buy_strategy_generator()` - populate the nested `populate_buy_trend()` to apply the parameters. +* Define the parameters at the class level hyperopt shall be optimizing. +* Within `populate_buy_trend()` - use defined parameter values instead of raw constants. There you have two different types of indicators: 1. `guards` and 2. `triggers`. @@ -221,100 +198,106 @@ There you have two different types of indicators: 1. `guards` and 2. `triggers`. However, this guide will make this distinction to make it clear that signals should not be "sticking". Sticking signals are signals that are active for multiple candles. This can lead into buying a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning). -Hyper-optimization will, for each epoch round, pick one trigger and possibly -multiple guards. The constructed strategy will be something like "*buy exactly when close price touches lower Bollinger band, BUT only if -ADX > 10*". - -If you have updated the buy strategy, i.e. changed the contents of `populate_buy_trend()` method, you have to update the `guards` and `triggers` your hyperopt must use correspondingly. +Hyper-optimization will, for each epoch round, pick one trigger and possibly multiple guards. #### Sell optimization Similar to the buy-signal above, sell-signals can also be optimized. Place the corresponding settings into the following methods -* Inside `sell_indicator_space()` - the parameters hyperopt shall be optimizing. -* Within `sell_strategy_generator()` - populate the nested method `populate_sell_trend()` to apply the parameters. +* Define the parameters at the class level hyperopt shall be optimizing, either naming them `sell_*`, or by explicitly defining `space='sell'`. +* Within `populate_sell_trend()` - use defined parameter values instead of raw constants. The configuration and rules are the same than for buy signals. -To avoid naming collisions in the search-space, please prefix all sell-spaces with `sell-`. - -#### Using timeframe as a part of the Strategy - -The Strategy class exposes the timeframe value as the `self.timeframe` attribute. -The same value is available as class-attribute `HyperoptName.timeframe`. -In the case of the linked sample-value this would be `AwesomeHyperopt.timeframe`. ## Solving a Mystery -Let's say you are curious: should you use MACD crossings or lower Bollinger -Bands to trigger your buys. And you also wonder should you use RSI or ADX to -help with those buy decisions. If you decide to use RSI or ADX, which values -should I use for them? So let's use hyperparameter optimization to solve this -mystery. +Let's say you are curious: should you use MACD crossings or lower Bollinger Bands to trigger your buys. +And you also wonder should you use RSI or ADX to help with those buy decisions. +If you decide to use RSI or ADX, which values should I use for them? -We will start by defining a search space: +So let's use hyperparameter optimization to solve this mystery. -```python - def indicator_space() -> List[Dimension]: +### Defining indicators to be used + +We start by calculating the indicators our strategy is going to use. + +``` python +class MyAwesomeStrategy(IStrategy): + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ - Define your Hyperopt space for searching strategy parameters + Generate all indicators used by the strategy """ - return [ - Integer(20, 40, name='adx-value'), - Integer(20, 40, name='rsi-value'), - Categorical([True, False], name='adx-enabled'), - Categorical([True, False], name='rsi-enabled'), - Categorical(['bb_lower', 'macd_cross_signal'], name='trigger') - ] + dataframe['adx'] = ta.ADX(dataframe) + dataframe['rsi'] = ta.RSI(dataframe) + macd = ta.MACD(dataframe) + dataframe['macd'] = macd['macd'] + dataframe['macdsignal'] = macd['macdsignal'] + dataframe['macdhist'] = macd['macdhist'] + + bollinger = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2.0, nbdevdn=2.0) + dataframe['bb_lowerband'] = boll['lowerband'] + dataframe['bb_middleband'] = boll['middleband'] + dataframe['bb_upperband'] = boll['upperband'] + return dataframe ``` -Above definition says: I have five parameters I want you to randomly combine -to find the best combination. Two of them are integer values (`adx-value` -and `rsi-value`) and I want you test in the range of values 20 to 40. +### Hyperoptable parameters + +We continue to define hyperoptable parameters: + +```python +class MyAwesomeStrategy(IStrategy): + buy_adx = IntParameter(20, 40, default=30, space="buy") + buy_rsi = IntParameter(20, 40, default=30, space="buy") + buy_adx_enabled = CategoricalParameter([True, False], space="buy") + buy_rsi_enabled = CategoricalParameter([True, False], space="buy") + buy_trigger = CategoricalParameter(['bb_lower', 'macd_cross_signal'], space="buy") +``` + +Above definition says: I have five parameters I want to randomly combine to find the best combination. +Two of them are integer values (`buy_adx` and `buy_rsi`) and I want you test in the range of values 20 to 40. Then we have three category variables. First two are either `True` or `False`. -We use these to either enable or disable the ADX and RSI guards. The last -one we call `trigger` and use it to decide which buy trigger we want to use. +We use these to either enable or disable the ADX and RSI guards. +The last one we call `trigger` and use it to decide which buy trigger we want to use. + +!!! Note "Parameter space assignment" + Parameters must either be assigned to a variable named `buy_*` or `sell_*` - or contain `space='buy'` | `space='sell'` to be assigned to a space correctly. + If no parameter is available for a space, you'll receive the error that no space was found when running hyperopt. So let's write the buy strategy using these values: ```python - @staticmethod - def buy_strategy_generator(params: Dict[str, Any]) -> Callable: - """ - Define the buy strategy parameters to be used by Hyperopt. - """ - def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: - conditions = [] - # GUARDS AND TRENDS - if 'adx-enabled' in params and params['adx-enabled']: - conditions.append(dataframe['adx'] > params['adx-value']) - if 'rsi-enabled' in params and params['rsi-enabled']: - conditions.append(dataframe['rsi'] < params['rsi-value']) + def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + conditions = [] + # GUARDS AND TRENDS + if self.buy_adx_enabled.value: + conditions.append(dataframe['adx'] > self.buy_adx.value) + if self.buy_rsi_enabled.value: + conditions.append(dataframe['rsi'] < self.buy_rsi.value) - # TRIGGERS - if 'trigger' in params: - if params['trigger'] == 'bb_lower': - conditions.append(dataframe['close'] < dataframe['bb_lowerband']) - if params['trigger'] == 'macd_cross_signal': - conditions.append(qtpylib.crossed_above( - dataframe['macd'], dataframe['macdsignal'] - )) + # TRIGGERS + if self.buy_trigger.value == 'bb_lower': + conditions.append(dataframe['close'] < dataframe['bb_lowerband']) + if self.buy_trigger.value == 'macd_cross_signal': + conditions.append(qtpylib.crossed_above( + dataframe['macd'], dataframe['macdsignal'] + )) - # Check that volume is not 0 - conditions.append(dataframe['volume'] > 0) + # Check that volume is not 0 + conditions.append(dataframe['volume'] > 0) - if conditions: - dataframe.loc[ - reduce(lambda x, y: x & y, conditions), - 'buy'] = 1 + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'buy'] = 1 - return dataframe - - return populate_buy_trend + return dataframe ``` Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations. -It will use the given historical data and make buys based on the buy signals generated with the above function. +It will use the given historical data and simulate buys based on the buy signals generated with the above function. Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)). !!! Note @@ -322,6 +305,108 @@ Based on the results, hyperopt will tell you which parameter combination produce When you want to test an indicator that isn't used by the bot currently, remember to add it to the `populate_indicators()` method in your strategy or hyperopt file. +## Parameter types + +There are four parameter types each suited for different purposes. + +* `IntParameter` - defines an integral parameter with upper and lower boundaries of search space. +* `DecimalParameter` - defines a floating point parameter with a limited number of decimals (default 3). Should be preferred instead of `RealParameter` in most cases. +* `RealParameter` - defines a floating point parameter with upper and lower boundaries and no precision limit. Rarely used as it creates a space with a near infinite number of possibilities. +* `CategoricalParameter` - defines a parameter with a predetermined number of choices. + +!!! Tip "Disabling parameter optimization" + Each parameter takes two boolean parameters: + * `load` - when set to `False` it will not load values configured in `buy_params` and `sell_params`. + * `optimize` - when set to `False` parameter will not be included in optimization process. + Use these parameters to quickly prototype various ideas. + +!!! Warning + Hyperoptable parameters cannot be used in `populate_indicators` - as hyperopt does not recalculate indicators for each epoch, so the starting value would be used in this case. + +### Optimizing an indicator parameter + +Assuming you have a simple strategy in mind - a EMA cross strategy (2 Moving averages crossing) - and you'd like to find the ideal parameters for this strategy. + +``` python +from pandas import DataFrame +from functools import reduce + +import talib.abstract as ta + +from freqtrade.strategy import IStrategy +from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter +import freqtrade.vendor.qtpylib.indicators as qtpylib + +class MyAwesomeStrategy(IStrategy): + stoploss = -0.05 + timeframe = '15m' + # Define the parameter spaces + buy_ema_short = IntParameter(3, 50, default=5) + buy_ema_long = IntParameter(15, 200, default=50) + + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + """Generate all indicators used by the strategy""" + + # Calculate all ema_short values + for val in self.buy_ema_short.range: + dataframe[f'ema_short_{val}'] = ta.EMA(dataframe, timeperiod=val) + + # Calculate all ema_long values + for val in self.buy_ema_long.range: + dataframe[f'ema_long_{val}'] = ta.EMA(dataframe, timeperiod=val) + + return dataframe + + def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + conditions = [] + conditions.append(qtpylib.crossed_above( + dataframe[f'ema_short_{self.buy_ema_short.value}'], dataframe[f'ema_long_{self.buy_ema_long.value}'] + )) + + # Check that volume is not 0 + conditions.append(dataframe['volume'] > 0) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'buy'] = 1 + return dataframe + + def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + conditions = [] + conditions.append(qtpylib.crossed_above( + dataframe[f'ema_long_{self.buy_ema_long.value}'], dataframe[f'ema_short_{self.buy_ema_short.value}'] + )) + + # Check that volume is not 0 + conditions.append(dataframe['volume'] > 0) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'sell'] = 1 + return dataframe +``` + +Breaking it down: + +Using `self.buy_ema_short.range` will return a range object containing all entries between the Parameters low and high value. +In this case (`IntParameter(3, 50, default=5)`), the loop would run for all numbers between 3 and 50 (`[3, 4, 5, ... 49, 50]`). +By using this in a loop, hyperopt will generate 48 new columns (`['buy_ema_3', 'buy_ema_4', ... , 'buy_ema_50']`). + +Hyperopt itself will then use the selected value to create the buy and sell signals + +While this strategy is most likely too simple to provide consistent profit, it should serve as an example how optimize indicator parameters. + +!!! Note + `self.buy_ema_short.range` will act differently between hyperopt and other modes. For hyperopt, the above example may generate 48 new columns, however for all other modes (backtesting, dry/live), it will only generate the column for the selected value. You should therefore avoid using the resulting column with explicit values (values other than `self.buy_ema_short.value`). + +??? Hint "Performance tip" + By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter. + While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values). + You should however try to use space ranges as small as possible. Every new column will require more memory, and every possibility hyperopt can try will increase the search space. + ## Loss-functions Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results. @@ -343,16 +428,14 @@ Creation of a custom loss function is covered in the [Advanced Hyperopt](advance ## Execute Hyperopt Once you have updated your hyperopt configuration you can run it. -Because hyperopt tries a lot of combinations to find the best parameters it will take time to get a good result. More time usually results in better results. +Because hyperopt tries a lot of combinations to find the best parameters it will take time to get a good result. We strongly recommend to use `screen` or `tmux` to prevent any connection loss. ```bash -freqtrade hyperopt --config config.json --hyperopt --hyperopt-loss --strategy -e 500 --spaces all +freqtrade hyperopt --config config.json --hyperopt-loss --strategy -e 500 --spaces all ``` -Use `` as the name of the custom hyperopt used. - The `-e` option will set how many evaluations hyperopt will do. Since hyperopt uses Bayesian search, running too many epochs at once may not produce greater results. Experience has shown that best results are usually not improving much after 500-1000 epochs. Doing multiple runs (executions) with a few 1000 epochs and different random state will most likely produce different results. @@ -366,30 +449,23 @@ The `--spaces all` option determines that all possible parameters should be opti ### Execute Hyperopt with different historical data source If you would like to hyperopt parameters using an alternate historical data set that -you have on-disk, use the `--datadir PATH` option. By default, hyperopt -uses data from directory `user_data/data`. +you have on-disk, use the `--datadir PATH` option. By default, hyperopt uses data from directory `user_data/data`. ### Running Hyperopt with a smaller test-set Use the `--timerange` argument to change how much of the test-set you want to use. -For example, to use one month of data, pass the following parameter to the hyperopt call: +For example, to use one month of data, pass `--timerange 20210101-20210201` (from january 2021 - february 2021) to the hyperopt call. + +Full command: ```bash -freqtrade hyperopt --hyperopt --strategy --timerange 20180401-20180501 -``` - -### Running Hyperopt using methods from a strategy - -Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided. - -```bash -freqtrade hyperopt --hyperopt AwesomeHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy AwesomeStrategy +freqtrade hyperopt --hyperopt --strategy --timerange 20210101-20210201 ``` ### Running Hyperopt with Smaller Search Space Use the `--spaces` option to limit the search space used by hyperopt. -Letting Hyperopt optimize everything is a huuuuge search space. +Letting Hyperopt optimize everything is a huuuuge search space. Often it might make more sense to start by just searching for initial buy algorithm. Or maybe you just want to optimize your stoploss or roi table for that awesome new buy strategy you have. @@ -406,40 +482,9 @@ Legal values are: The default Hyperopt Search Space, used when no `--space` command line option is specified, does not include the `trailing` hyperspace. We recommend you to run optimization for the `trailing` hyperspace separately, when the best parameters for other hyperspaces were found, validated and pasted into your custom strategy. -### Position stacking and disabling max market positions - -In some situations, you may need to run Hyperopt (and Backtesting) with the -`--eps`/`--enable-position-staking` and `--dmmp`/`--disable-max-market-positions` arguments. - -By default, hyperopt emulates the behavior of the Freqtrade Live Run/Dry Run, where only one -open trade is allowed for every traded pair. The total number of trades open for all pairs -is also limited by the `max_open_trades` setting. During Hyperopt/Backtesting this may lead to -some potential trades to be hidden (or masked) by previously open trades. - -The `--eps`/`--enable-position-stacking` argument allows emulation of buying the same pair multiple times, -while `--dmmp`/`--disable-max-market-positions` disables applying `max_open_trades` -during Hyperopt/Backtesting (which is equal to setting `max_open_trades` to a very high -number). - -!!! Note - Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality. - -You can also enable position stacking in the configuration file by explicitly setting -`"position_stacking"=true`. - -### Reproducible results - -The search for optimal parameters starts with a few (currently 30) random combinations in the hyperspace of parameters, random Hyperopt epochs. These random epochs are marked with an asterisk character (`*`) in the first column in the Hyperopt output. - -The initial state for generation of these random values (random state) is controlled by the value of the `--random-state` command line option. You can set it to some arbitrary value of your choice to obtain reproducible results. - -If you have not set this value explicitly in the command line options, Hyperopt seeds the random state with some random value for you. The random state value for each Hyperopt run is shown in the log, so you can copy and paste it into the `--random-state` command line option to repeat the set of the initial random epochs used. - -If you have not changed anything in the command line options, configuration, timerange, Strategy and Hyperopt classes, historical data and the Loss Function -- you should obtain same hyper-optimization results with same random state value used. - ## Understand the Hyperopt Result -Once Hyperopt is completed you can use the result to create a new strategy. +Once Hyperopt is completed you can use the result to update your strategy. Given the following result from hyperopt: ``` @@ -447,49 +492,38 @@ Best result: 44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367 -Buy hyperspace params: -{ 'adx-value': 44, - 'rsi-value': 29, - 'adx-enabled': False, - 'rsi-enabled': True, - 'trigger': 'bb_lower'} + # Buy hyperspace params: + buy_params = { + 'buy_adx': 44, + 'buy_rsi': 29, + 'buy_adx_enabled': False, + 'buy_rsi_enabled': True, + 'buy_trigger': 'bb_lower' + } ``` You should understand this result like: -- The buy trigger that worked best was `bb_lower`. -- You should not use ADX because `adx-enabled: False`) -- You should **consider** using the RSI indicator (`rsi-enabled: True` and the best value is `29.0` (`rsi-value: 29.0`) +* The buy trigger that worked best was `bb_lower`. +* You should not use ADX because `'buy_adx_enabled': False`. +* You should **consider** using the RSI indicator (`'buy_rsi_enabled': True`) and the best value is `29.0` (`'buy_rsi': 29.0`) -You have to look inside your strategy file into `buy_strategy_generator()` -method, what those values match to. +Your strategy class can immediately take advantage of these results. Simply copy hyperopt results block and paste them at class level, replacing old parameters (if any). New parameters will automatically be loaded next time strategy is executed. -So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that translates to the following code block: +Transferring your whole hyperopt result to your strategy would then look like: ```python -(dataframe['rsi'] < 29.0) +class MyAwesomeStrategy(IStrategy): + # Buy hyperspace params: + buy_params = { + 'buy_adx': 44, + 'buy_rsi': 29, + 'buy_adx_enabled': False, + 'buy_rsi_enabled': True, + 'buy_trigger': 'bb_lower' + } ``` -Translating your whole hyperopt result as the new buy-signal would then look like: - -```python -def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: - dataframe.loc[ - ( - (dataframe['rsi'] < 29.0) & # rsi-value - dataframe['close'] < dataframe['bb_lowerband'] # trigger - ), - 'buy'] = 1 - return dataframe -``` - -By default, hyperopt prints colorized results -- epochs with positive profit are printed in the green color. This highlighting helps you find epochs that can be interesting for later analysis. Epochs with zero total profit or with negative profits (losses) are printed in the normal color. If you do not need colorization of results (for instance, when you are redirecting hyperopt output to a file) you can switch colorization off by specifying the `--no-color` option in the command line. - -You can use the `--print-all` command line option if you would like to see all results in the hyperopt output, not only the best ones. When `--print-all` is used, current best results are also colorized by default -- they are printed in bold (bright) style. This can also be switched off with the `--no-color` command line option. - -!!! Note "Windows and color output" - Windows does not support color-output natively, therefore it is automatically disabled. To have color-output for hyperopt running under windows, please consider using WSL. - ### Understand Hyperopt ROI results If you are optimizing ROI (i.e. if optimization search-space contains 'all', 'default' or 'roi'), your result will look as follows and include a ROI table: @@ -499,11 +533,13 @@ Best result: 44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367 -ROI table: -{ 0: 0.10674, - 21: 0.09158, - 78: 0.03634, - 118: 0} + # ROI table: + minimal_roi = { + 0: 0.10674, + 21: 0.09158, + 78: 0.03634, + 118: 0 + } ``` In order to use this best ROI table found by Hyperopt in backtesting and for live trades/dry-run, copy-paste it as the value of the `minimal_roi` attribute of your custom strategy: @@ -523,23 +559,26 @@ As stated in the comment, you can also use it as the value of the `minimal_roi` #### Default ROI Search Space -If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the timeframe used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point): +If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the timeframe used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 3 digits after the decimal point): -| # step | 1m | | 5m | | 1h | | 1d | | -| ------ | ------ | ----------------- | -------- | ----------- | ---------- | ----------------- | ------------ | ----------------- | -| 1 | 0 | 0.01161...0.11992 | 0 | 0.03...0.31 | 0 | 0.06883...0.71124 | 0 | 0.12178...1.25835 | -| 2 | 2...8 | 0.00774...0.04255 | 10...40 | 0.02...0.11 | 120...480 | 0.04589...0.25238 | 2880...11520 | 0.08118...0.44651 | -| 3 | 4...20 | 0.00387...0.01547 | 20...100 | 0.01...0.04 | 240...1200 | 0.02294...0.09177 | 5760...28800 | 0.04059...0.16237 | -| 4 | 6...44 | 0.0 | 30...220 | 0.0 | 360...2640 | 0.0 | 8640...63360 | 0.0 | +| # step | 1m | | 5m | | 1h | | 1d | | +| ------ | ------ | ------------- | -------- | ----------- | ---------- | ------------- | ------------ | ------------- | +| 1 | 0 | 0.011...0.119 | 0 | 0.03...0.31 | 0 | 0.068...0.711 | 0 | 0.121...1.258 | +| 2 | 2...8 | 0.007...0.042 | 10...40 | 0.02...0.11 | 120...480 | 0.045...0.252 | 2880...11520 | 0.081...0.446 | +| 3 | 4...20 | 0.003...0.015 | 20...100 | 0.01...0.04 | 240...1200 | 0.022...0.091 | 5760...28800 | 0.040...0.162 | +| 4 | 6...44 | 0.0 | 30...220 | 0.0 | 360...2640 | 0.0 | 8640...63360 | 0.0 | These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used. If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default. -Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps). +Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps). A sample for these methods can be found in [sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py). +!!! Note "Reduced search space" + To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs. + ### Understand Hyperopt Stoploss results If you are optimizing stoploss values (i.e. if optimization search-space contains 'all', 'default' or 'stoploss'), your result will look as follows and include stoploss: @@ -549,13 +588,16 @@ Best result: 44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367 -Buy hyperspace params: -{ 'adx-value': 44, - 'rsi-value': 29, - 'adx-enabled': False, - 'rsi-enabled': True, - 'trigger': 'bb_lower'} -Stoploss: -0.27996 + # Buy hyperspace params: + buy_params = { + 'buy_adx': 44, + 'buy_rsi': 29, + 'buy_adx_enabled': False, + 'buy_rsi_enabled': True, + 'buy_trigger': 'bb_lower' + } + + stoploss: -0.27996 ``` In order to use this best stoploss value found by Hyperopt in backtesting and for live trades/dry-run, copy-paste it as the value of the `stoploss` attribute of your custom strategy: @@ -576,6 +618,9 @@ If you have the `stoploss_space()` method in your custom hyperopt file, remove i Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py). +!!! Note "Reduced search space" + To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs. + ### Understand Hyperopt Trailing Stop results If you are optimizing trailing stop values (i.e. if optimization search-space contains 'all' or 'trailing'), your result will look as follows and include trailing stop parameters: @@ -585,11 +630,11 @@ Best result: 45/100: 606 trades. Avg profit 1.04%. Total profit 0.31555614 BTC ( 630.48Σ%). Avg duration 150.3 mins. Objective: -1.10161 -Trailing stop: -{ 'trailing_only_offset_is_reached': True, - 'trailing_stop': True, - 'trailing_stop_positive': 0.02001, - 'trailing_stop_positive_offset': 0.06038} + # Trailing stop: + trailing_stop = True + trailing_stop_positive = 0.02001 + trailing_stop_positive_offset = 0.06038 + trailing_only_offset_is_reached = True ``` In order to use these best trailing stop parameters found by Hyperopt in backtesting and for live trades/dry-run, copy-paste them as the values of the corresponding attributes of your custom strategy: @@ -611,6 +656,59 @@ If you are optimizing trailing stop values, Freqtrade creates the 'trailing' opt Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py). +!!! Note "Reduced search space" + To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs. + +### Reproducible results + +The search for optimal parameters starts with a few (currently 30) random combinations in the hyperspace of parameters, random Hyperopt epochs. These random epochs are marked with an asterisk character (`*`) in the first column in the Hyperopt output. + +The initial state for generation of these random values (random state) is controlled by the value of the `--random-state` command line option. You can set it to some arbitrary value of your choice to obtain reproducible results. + +If you have not set this value explicitly in the command line options, Hyperopt seeds the random state with some random value for you. The random state value for each Hyperopt run is shown in the log, so you can copy and paste it into the `--random-state` command line option to repeat the set of the initial random epochs used. + +If you have not changed anything in the command line options, configuration, timerange, Strategy and Hyperopt classes, historical data and the Loss Function -- you should obtain same hyper-optimization results with same random state value used. + +## Output formatting + +By default, hyperopt prints colorized results -- epochs with positive profit are printed in the green color. This highlighting helps you find epochs that can be interesting for later analysis. Epochs with zero total profit or with negative profits (losses) are printed in the normal color. If you do not need colorization of results (for instance, when you are redirecting hyperopt output to a file) you can switch colorization off by specifying the `--no-color` option in the command line. + +You can use the `--print-all` command line option if you would like to see all results in the hyperopt output, not only the best ones. When `--print-all` is used, current best results are also colorized by default -- they are printed in bold (bright) style. This can also be switched off with the `--no-color` command line option. + +!!! Note "Windows and color output" + Windows does not support color-output natively, therefore it is automatically disabled. To have color-output for hyperopt running under windows, please consider using WSL. + +## Position stacking and disabling max market positions + +In some situations, you may need to run Hyperopt (and Backtesting) with the +`--eps`/`--enable-position-staking` and `--dmmp`/`--disable-max-market-positions` arguments. + +By default, hyperopt emulates the behavior of the Freqtrade Live Run/Dry Run, where only one +open trade is allowed for every traded pair. The total number of trades open for all pairs +is also limited by the `max_open_trades` setting. During Hyperopt/Backtesting this may lead to +some potential trades to be hidden (or masked) by previously open trades. + +The `--eps`/`--enable-position-stacking` argument allows emulation of buying the same pair multiple times, +while `--dmmp`/`--disable-max-market-positions` disables applying `max_open_trades` +during Hyperopt/Backtesting (which is equal to setting `max_open_trades` to a very high +number). + +!!! Note + Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality. + +You can also enable position stacking in the configuration file by explicitly setting +`"position_stacking"=true`. + +## Out of Memory errors + +As hyperopt consumes a lot of memory (the complete data needs to be in memory once per parallel backtesting process), it's likely that you run into "out of memory" errors. +To combat these, you have multiple options: + +* reduce the amount of pairs +* reduce the timerange used (`--timerange `) +* reduce the number of parallel processes (`-j `) +* Increase the memory of your machine + ## Show details of Hyperopt results After you run Hyperopt for the desired amount of epochs, you can later list all results for analysis, select only best or profitable once, and show the details for any of the epochs previously evaluated. This can be done with the `hyperopt-list` and `hyperopt-show` sub-commands. The usage of these sub-commands is described in the [Utils](utils.md#list-hyperopt-results) chapter. diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md index 2653406e7..ce0cc6e57 100644 --- a/docs/includes/pairlists.md +++ b/docs/includes/pairlists.md @@ -4,7 +4,7 @@ Pairlist Handlers define the list of pairs (pairlist) that the bot should trade. In your configuration, you can use Static Pairlist (defined by the [`StaticPairList`](#static-pair-list) Pairlist Handler) and Dynamic Pairlist (defined by the [`VolumePairList`](#volume-pair-list) Pairlist Handler). -Additionally, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter) and [`SpreadFilter`](#spreadfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist. +Additionally, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter), [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist. If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You should always configure either `StaticPairList` or `VolumePairList` as the starting Pairlist Handler. @@ -29,6 +29,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged * [`ShuffleFilter`](#shufflefilter) * [`SpreadFilter`](#spreadfilter) * [`RangeStabilityFilter`](#rangestabilityfilter) +* [`VolatilityFilter`](#volatilityfilter) !!! Tip "Testing pairlists" Pairlist configurations can be quite tricky to get right. Best use the [`test-pairlist`](utils.md#test-pairlist) utility sub-command to test your configuration quickly. @@ -59,6 +60,8 @@ When used in the chain of Pairlist Handlers in a non-leading position (after Sta When used on the leading position of the chain of Pairlist Handlers, it does not consider `pair_whitelist` configuration setting, but selects the top assets from all available markets (with matching stake-currency) on the exchange. The `refresh_period` setting allows to define the period (in seconds), at which the pairlist will be refreshed. Defaults to 1800s (30 minutes). +The pairlist cache (`refresh_period`) on `VolumePairList` is only applicable to generating pairlists. +Filtering instances (not the first position in the list) will not apply any cache and will always use up-to-date data. `VolumePairList` is based on the ticker data from exchange, as reported by the ccxt library: @@ -89,6 +92,7 @@ This filter allows freqtrade to ignore pairs until they have been listed for at #### PerformanceFilter Sorts pairs by past trade performance, as follows: + 1. Positive performance. 2. No closed trades yet. 3. Negative performance. @@ -108,6 +112,7 @@ The `PriceFilter` allows filtering of pairs by price. Currently the following pr * `min_price` * `max_price` +* `max_value` * `low_price_ratio` The `min_price` setting removes pairs where the price is below the specified price. This is useful if you wish to avoid trading very low-priced pairs. @@ -116,6 +121,11 @@ This option is disabled by default, and will only apply if set to > 0. The `max_price` setting removes pairs where the price is above the specified price. This is useful if you wish to trade only low-priced pairs. This option is disabled by default, and will only apply if set to > 0. +The `max_value` setting removes pairs where the minimum value change is above a specified value. +This is useful when an exchange has unbalanced limits. For example, if step-size = 1 (so you can only buy 1, or 2, or 3, but not 1.1 Coins) - and the price is pretty high (like 20$) as the coin has risen sharply since the last limit adaption. +As a result of the above, you can only buy for 20$, or 40$ - but not for 25$. +On exchanges that deduct fees from the receiving currency (e.g. FTX) - this can result in high value coins / amounts that are unsellable as the amount is slightly below the limit. + The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio. This option is disabled by default, and will only apply if set to > 0. @@ -164,9 +174,32 @@ If the trading range over the last 10 days is <1%, remove the pair from the whit !!! Tip This Filter can be used to automatically remove stable coin pairs, which have a very low trading range, and are therefore extremely difficult to trade with profit. +#### VolatilityFilter + +Volatility is the degree of historical variation of a pairs over time, is is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)). + +This filter removes pairs if the average volatility over a `lookback_days` days is below `min_volatility` or above `max_volatility`. Since this is a filter that requires additional data, the results are cached for `refresh_period`. + +This filter can be used to narrow down your pairs to a certain volatility or avoid very volatile pairs. + +In the below example: +If the volatility over the last 10 days is not in the range of 0.05-0.50, remove the pair from the whitelist. The filter is applied every 24h. + +```json +"pairlists": [ + { + "method": "VolatilityFilter", + "lookback_days": 10, + "min_volatility": 0.05, + "max_volatility": 0.50, + "refresh_period": 86400 + } +] +``` + ### Full example of Pairlist Handlers -The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies both [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#price-filter), filtering all assets where 1 price unit is > 1%. Then the `SpreadFilter` is applied and pairs are finally shuffled with the random seed set to some predefined value. +The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#pricefilter), filtering all assets where 1 price unit is > 1%. Then the [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) is applied and pairs are finally shuffled with the random seed set to some predefined value. ```json "exchange": { @@ -177,7 +210,7 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, { "method": "VolumePairList", "number_assets": 20, - "sort_key": "quoteVolume", + "sort_key": "quoteVolume" }, {"method": "AgeFilter", "min_days_listed": 10}, {"method": "PrecisionFilter"}, @@ -189,6 +222,13 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, "min_rate_of_change": 0.01, "refresh_period": 1440 }, + { + "method": "VolatilityFilter", + "lookback_days": 10, + "min_volatility": 0.05, + "max_volatility": 0.50, + "refresh_period": 86400 + }, {"method": "ShuffleFilter", "seed": 42} ], ``` diff --git a/docs/index.md b/docs/index.md index 61f2276c3..c2b6d5629 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,4 +1,5 @@ -# Freqtrade +![freqtrade](assets/freqtrade_poweredby.svg) + [![Freqtrade CI](https://github.com/freqtrade/freqtrade/workflows/Freqtrade%20CI/badge.svg)](https://github.com/freqtrade/freqtrade/actions/) [![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop) [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability) @@ -39,7 +40,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual, - [X] [Bittrex](https://bittrex.com/) - [X] [FTX](https://ftx.com) - [X] [Kraken](https://kraken.com/) -- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_ +- [ ] [potentially many others through ccxt](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_ ### Community tested diff --git a/docs/installation.md b/docs/installation.md index d2661f88f..c19965a18 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -60,7 +60,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces sudo apt-get update # install packages - sudo apt install -y python3-pip python3-venv python3-pandas python3-pip git + sudo apt install -y python3-pip python3-venv python3-pandas git ``` === "RaspberryPi/Raspbian" @@ -269,7 +269,7 @@ git clone https://github.com/freqtrade/freqtrade.git cd freqtrade ``` -#### Freqtrade instal: Conda Environment +#### Freqtrade install: Conda Environment Prepare conda-freqtrade environment, using file `environment.yml`, which exist in main freqtrade directory diff --git a/docs/plotting.md b/docs/plotting.md index d7ed5ab1f..5d454c414 100644 --- a/docs/plotting.md +++ b/docs/plotting.md @@ -37,7 +37,7 @@ usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH] optional arguments: -h, --help show this help message and exit -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] - Show profits for only these pairs. Pairs are space- + Limit command to these pairs. Pairs are space- separated. --indicators1 INDICATORS1 [INDICATORS1 ...] Set indicators from your strategy you want in the @@ -66,8 +66,7 @@ optional arguments: --timerange TIMERANGE Specify what timerange of data to use. -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME - Specify ticker interval (`1m`, `5m`, `30m`, `1h`, - `1d`). + Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`). --no-trades Skip using trades from backtesting file and DB. Common arguments: @@ -91,6 +90,7 @@ Strategy arguments: Specify strategy class name which will be used by the bot. --strategy-path PATH Specify additional strategy lookup path. + ``` Example: @@ -245,7 +245,7 @@ usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH] optional arguments: -h, --help show this help message and exit -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...] - Show profits for only these pairs. Pairs are space- + Limit command to these pairs. Pairs are space- separated. --timerange TIMERANGE Specify what timerange of data to use. @@ -264,8 +264,7 @@ optional arguments: Specify the source for trades (Can be DB or file (backtest file)) Default: file -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME - Specify ticker interval (`1m`, `5m`, `30m`, `1h`, - `1d`). + Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`). Common arguments: -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). @@ -288,6 +287,7 @@ Strategy arguments: Specify strategy class name which will be used by the bot. --strategy-path PATH Specify additional strategy lookup path. + ``` The `-p/--pairs` argument, can be used to limit the pairs that are considered for this calculation. diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt index 0068dd5d2..3d469fde7 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,3 +1,3 @@ -mkdocs-material==7.0.6 +mkdocs-material==7.1.4 mdx_truly_sane_lists==1.2 -pymdown-extensions==8.1.1 +pymdown-extensions==8.2 diff --git a/docs/rest-api.md b/docs/rest-api.md index c41c3f24c..b9b2b29be 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -71,7 +71,10 @@ If you run your bot using docker, you'll need to have the bot listen to incoming "api_server": { "enabled": true, "listen_ip_address": "0.0.0.0", - "listen_port": 8080 + "listen_port": 8080, + "username": "Freqtrader", + "password": "SuperSecret1!", + //... }, ``` @@ -106,7 +109,10 @@ By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be use "api_server": { "enabled": true, "listen_ip_address": "0.0.0.0", - "listen_port": 8080 + "listen_port": 8080, + "username": "Freqtrader", + "password": "SuperSecret1!", + //... } } ``` @@ -124,7 +130,8 @@ python3 scripts/rest_client.py --config rest_config.json [optional par | `stop` | Stops the trader. | `stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules. | `reload_config` | Reloads the configuration file. -| `trades` | List last trades. +| `trades` | List last trades. Limited to 500 trades per call. +| `trade/` | Get specific trade. | `delete_trade ` | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange. | `show_config` | Shows part of the current configuration with relevant settings to operation. | `logs` | Shows last log messages. @@ -181,7 +188,7 @@ count Return the amount of open trades. daily - Return the amount of open trades. + Return the profits for each day, and amount of trades. delete_lock Delete (disable) lock from the database. @@ -214,7 +221,7 @@ locks logs Show latest logs. - :param limit: Limits log messages to the last logs. No limit to get all the trades. + :param limit: Limits log messages to the last logs. No limit to get the entire log. pair_candles Return live dataframe for . @@ -234,6 +241,9 @@ pair_history performance Return the performance of the different coins. +ping + simple ping + plot_config Return plot configuration if the strategy defines one. @@ -270,17 +280,22 @@ strategy :param strategy: Strategy class name -trades - Return trades history. +trade + Return specific trade - :param limit: Limits trades to the X last trades. No limit to get all the trades. + :param trade_id: Specify which trade to get. + +trades + Return trades history, sorted by id + + :param limit: Limits trades to the X last trades. Max 500 trades. + :param offset: Offset by this amount of trades. version Return the version of the bot. whitelist Show the current whitelist. - ``` ### OpenAPI interface diff --git a/docs/sql_cheatsheet.md b/docs/sql_cheatsheet.md index 569af33ff..477396931 100644 --- a/docs/sql_cheatsheet.md +++ b/docs/sql_cheatsheet.md @@ -19,7 +19,7 @@ The freqtrade docker image does contain sqlite3, so you can edit the database wi ``` bash docker-compose exec freqtrade /bin/bash -sqlite3 .sqlite +sqlite3 .sqlite ``` ## Open the DB @@ -99,3 +99,32 @@ DELETE FROM trades WHERE id = 31; !!! Warning This will remove this trade from the database. Please make sure you got the correct id and **NEVER** run this query without the `where` clause. + +## Use a different database system + +!!! Warning + By using one of the below database systems, you acknowledge that you know how to manage such a system. Freqtrade will not provide any support with setup or maintenance (or backups) of the below database systems. + +### PostgreSQL + +Freqtrade supports PostgreSQL by using SQLAlchemy, which supports multiple different database systems. + +Installation: +`pip install psycopg2` + +Usage: +`... --db-url postgresql+psycopg2://:@localhost:5432/` + +Freqtrade will automatically create the tables necessary upon startup. + +If you're running different instances of Freqtrade, you must either setup one database per Instance or use different users / schemas for your connections. + +### MariaDB / MySQL + +Freqtrade supports MariaDB by using SQLAlchemy, which supports multiple different database systems. + +Installation: +`pip install pymysql` + +Usage: +`... --db-url mysql+pymysql://:@localhost:3306/` diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md index 7fa824a5b..cb759eb2f 100644 --- a/docs/strategy-advanced.md +++ b/docs/strategy-advanced.md @@ -40,34 +40,79 @@ class AwesomeStrategy(IStrategy): !!! Note If the data is pair-specific, make sure to use pair as one of the keys in the dictionary. -*** +## Dataframe access -### Storing custom information using DatetimeIndex from `dataframe` +You may access dataframe in various strategy functions by querying it from dataprovider. -Imagine you need to store an indicator like `ATR` or `RSI` into `custom_info`. To use this in a meaningful way, you will not only need the raw data of the indicator, but probably also need to keep the right timestamps. +``` python +from freqtrade.exchange import timeframe_to_prev_date -```python -import talib.abstract as ta class AwesomeStrategy(IStrategy): - # Create custom dictionary - custom_info = {} + def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float, + rate: float, time_in_force: str, sell_reason: str, + current_time: 'datetime', **kwargs) -> bool: + # Obtain pair dataframe. + dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) - def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - # using "ATR" here as example - dataframe['atr'] = ta.ATR(dataframe) - if self.dp.runmode.value in ('backtest', 'hyperopt'): - # add indicator mapped to correct DatetimeIndex to custom_info - self.custom_info[metadata['pair']] = dataframe[['date', 'atr']].copy().set_index('date') - return dataframe + # Obtain last available candle. Do not use current_time to look up latest candle, because + # current_time points to curret incomplete candle whose data is not available. + last_candle = dataframe.iloc[-1].squeeze() + # <...> + + # In dry/live runs trade open date will not match candle open date therefore it must be + # rounded. + trade_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc) + # Look up trade candle. + trade_candle = dataframe.loc[dataframe['date'] == trade_date] + # trade_candle may be empty for trades that just opened as it is still incomplete. + if not trade_candle.empty: + trade_candle = trade_candle.squeeze() + # <...> ``` -!!! Warning - The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash. +!!! Warning "Using .iloc[-1]" + You can use `.iloc[-1]` here because `get_analyzed_dataframe()` only returns candles that backtesting is allowed to see. + This will not work in `populate_*` methods, so make sure to not use `.iloc[]` in that area. + Also, this will only work starting with version 2021.5. + +*** + +## Custom sell signal + +It is possible to define custom sell signals, indicating that specified position should be sold. This is very useful when we need to customize sell conditions for each individual trade, or if you need the trade profit to take the sell decision. + +For example you could implement a 1:2 risk-reward ROI with `custom_sell()`. + +Using custom_sell() signals in place of stoplosses though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange. !!! Note - If the data is pair-specific, make sure to use pair as one of the keys in the dictionary. + Returning a `string` or `True` from this method is equal to setting sell signal on a candle at specified time. This method is not called when sell signal is set already, or if sell signals are disabled (`use_sell_signal=False` or `sell_profit_only=True` while profit is below `sell_profit_offset`). `string` max length is 64 characters. Exceeding this limit will cause the message to be truncated to 64 characters. -See `custom_stoploss` examples below on how to access the saved dataframe columns +An example of how we can use different indicators depending on the current profit and also sell trades that were open longer than one day: + +``` python +class AwesomeStrategy(IStrategy): + def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, + current_profit: float, **kwargs): + dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) + last_candle = dataframe.iloc[-1].squeeze() + + # Above 20% profit, sell when rsi < 80 + if current_profit > 0.2: + if last_candle['rsi'] < 80: + return 'rsi_below_80' + + # Between 2% and 10%, sell if EMA-long above EMA-short + if 0.02 < current_profit < 0.1: + if last_candle['emalong'] > last_candle['emashort']: + return 'ema_long_below_80' + + # Sell any positions at a loss if they are held for more than one day. + if current_profit < 0.0 and (current_time - trade.open_date_utc).days >= 1: + return 'unclog' +``` + +See [Dataframe access](#dataframe-access) for more information about dataframe use in strategy callbacks. ## Custom stoploss @@ -110,7 +155,7 @@ class AwesomeStrategy(IStrategy): :param current_rate: Rate, calculated based on pricing settings in ask_strategy. :param current_profit: Current profit (as ratio), calculated based on current_rate. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. - :return float: New stoploss value, relative to the currentrate + :return float: New stoploss value, relative to the current rate """ return -0.04 ``` @@ -222,7 +267,6 @@ Instead of continuously trailing behind the current price, this example sets fix * Once profit is > 25% - set stoploss to 15% above open price. * Once profit is > 40% - set stoploss to 25% above open price. - ``` python from datetime import datetime from freqtrade.persistence import Trade @@ -248,56 +292,39 @@ class AwesomeStrategy(IStrategy): # return maximum stoploss value, keeping current stoploss price unchanged return 1 ``` + #### Custom stoploss using an indicator from dataframe example -Imagine you want to use `custom_stoploss()` to use a trailing indicator like e.g. "ATR" - -See: "Storing custom information using DatetimeIndex from `dataframe`" example above) on how to store the indicator into `custom_info` - -!!! Warning - only use .iat[-1] in live mode, not in backtesting/hyperopt - otherwise you will look into the future - see [Common mistakes when developing strategies](strategy-customization.md#common-mistakes-when-developing-strategies) for more info. +Absolute stoploss value may be derived from indicators stored in dataframe. Example uses parabolic SAR below the price as stoploss. ``` python -from freqtrade.persistence import Trade -from freqtrade.state import RunMode - class AwesomeStrategy(IStrategy): - # ... populate_* methods + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + # <...> + dataframe['sar'] = ta.SAR(dataframe) use_custom_stoploss = True def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: - result = 1 - if self.custom_info and pair in self.custom_info and trade: - # using current_time directly (like below) will only work in backtesting. - # so check "runmode" to make sure that it's only used in backtesting/hyperopt - if self.dp and self.dp.runmode.value in ('backtest', 'hyperopt'): - relative_sl = self.custom_info[pair].loc[current_time]['atr'] - # in live / dry-run, it'll be really the current time - else: - # but we can just use the last entry from an already analyzed dataframe instead - dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair, - timeframe=self.timeframe) - # WARNING - # only use .iat[-1] in live mode, not in backtesting/hyperopt - # otherwise you will look into the future - # see: https://www.freqtrade.io/en/latest/strategy-customization/#common-mistakes-when-developing-strategies - relative_sl = dataframe['atr'].iat[-1] + dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) + last_candle = dataframe.iloc[-1].squeeze() - if (relative_sl is not None): - # new stoploss relative to current_rate - new_stoploss = (current_rate-relative_sl)/current_rate - # turn into relative negative offset required by `custom_stoploss` return implementation - result = new_stoploss - 1 + # Use parabolic sar as absolute stoploss price + stoploss_price = last_candle['sar'] - return result + # Convert absolute price to percentage relative to current_rate + if stoploss_price < current_rate: + return (stoploss_price / current_rate) - 1 + + # return maximum stoploss value, keeping current stoploss price unchanged + return 1 ``` +See [Dataframe access](#dataframe-access) for more information about dataframe use in strategy callbacks. + --- ## Custom order timeout rules diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index 256b28990..cfea60d22 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -159,7 +159,7 @@ Edit the method `populate_buy_trend()` in your strategy file to update your buy It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected. -This will method will also define a new column, `"buy"`, which needs to contain 1 for buys, and 0 for "no action". +This method will also define a new column, `"buy"`, which needs to contain 1 for buys, and 0 for "no action". Sample from `user_data/strategies/sample_strategy.py`: @@ -193,7 +193,7 @@ Please note that the sell-signal is only used if `use_sell_signal` is set to tru It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected. -This will method will also define a new column, `"sell"`, which needs to contain 1 for sells, and 0 for "no action". +This method will also define a new column, `"sell"`, which needs to contain 1 for sells, and 0 for "no action". Sample from `user_data/strategies/sample_strategy.py`: @@ -422,10 +422,6 @@ if self.dp: Returns an empty dataframe if the requested pair was not cached. This should not happen when using whitelisted pairs. - -!!! Warning "Warning about backtesting" - This method will return an empty dataframe during backtesting. - ### *orderbook(pair, maximum)* ``` python @@ -633,7 +629,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: - # once the profit has risin above 10%, keep the stoploss at 7% above the open price + # once the profit has risen above 10%, keep the stoploss at 7% above the open price if current_profit > 0.10: return stoploss_from_open(0.07, current_profit) diff --git a/docs/strategy_analysis_example.md b/docs/strategy_analysis_example.md index 5c479aa0b..4c938500c 100644 --- a/docs/strategy_analysis_example.md +++ b/docs/strategy_analysis_example.md @@ -195,4 +195,18 @@ graph.show(renderer="browser") ``` +## Plot average profit per trade as distribution graph + + +```python +import plotly.figure_factory as ff + +hist_data = [trades.profit_ratio] +group_labels = ['profit_ratio'] # name of the dataset + +fig = ff.create_distplot(hist_data, group_labels,bin_size=0.01) +fig.show() + +``` + Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data. diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md index 340e67549..6174bf0fe 100644 --- a/docs/telegram-usage.md +++ b/docs/telegram-usage.md @@ -82,12 +82,19 @@ Example configuration showing the different settings: "buy": "silent", "sell": "on", "buy_cancel": "silent", - "sell_cancel": "on" + "sell_cancel": "on", + "buy_fill": "off", + "sell_fill": "off" }, "balance_dust_level": 0.01 }, ``` +`buy` notifications are sent when the order is placed, while `buy_fill` notifications are sent when the order is filled on the exchange. +`sell` notifications are sent when the order is placed, while `sell_fill` notifications are sent when the order is filled on the exchange. +`*_fill` notifications are off by default and must be explicitly enabled. + + `balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown. ## Create a custom keyboard (command shortcut buttons) @@ -258,13 +265,12 @@ Note that for this to work, `forcebuy_enable` needs to be set to true. ### /performance Return the performance of each crypto-currency the bot has sold. - > Performance: -> 1. `RCN/BTC 57.77%` -> 2. `PAY/BTC 56.91%` -> 3. `VIB/BTC 47.07%` -> 4. `SALT/BTC 30.24%` -> 5. `STORJ/BTC 27.24%` +> 1. `RCN/BTC 0.003 BTC (57.77%) (1)` +> 2. `PAY/BTC 0.0012 BTC (56.91%) (1)` +> 3. `VIB/BTC 0.0011 BTC (47.07%) (1)` +> 4. `SALT/BTC 0.0010 BTC (30.24%) (1)` +> 5. `STORJ/BTC 0.0009 BTC (27.24%) (1)` > ... ### /balance diff --git a/docs/utils.md b/docs/utils.md index cf7d5f1d1..8ef12e1c9 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -253,18 +253,211 @@ optional arguments: * Example: see exchanges available for the bot: ``` $ freqtrade list-exchanges -Exchanges available for Freqtrade: _1btcxe, acx, allcoin, bequant, bibox, binance, binanceje, binanceus, bitbank, bitfinex, bitfinex2, bitkk, bitlish, bitmart, bittrex, bitz, bleutrade, btcalpha, btcmarkets, btcturk, buda, cex, cobinhood, coinbaseprime, coinbasepro, coinex, cointiger, coss, crex24, digifinex, dsx, dx, ethfinex, fcoin, fcoinjp, gateio, gdax, gemini, hitbtc2, huobipro, huobiru, idex, kkex, kraken, kucoin, kucoin2, kuna, lbank, mandala, mercado, oceanex, okcoincny, okcoinusd, okex, okex3, poloniex, rightbtc, theocean, tidebit, upbit, zb +Exchanges available for Freqtrade: +Exchange name Valid reason +--------------- ------- -------------------------------------------- +aax True +ascendex True missing opt: fetchMyTrades +bequant True +bibox True +bigone True +binance True +binanceus True +bitbank True missing opt: fetchTickers +bitcoincom True +bitfinex True +bitforex True missing opt: fetchMyTrades, fetchTickers +bitget True +bithumb True missing opt: fetchMyTrades +bitkk True missing opt: fetchMyTrades +bitmart True +bitmax True missing opt: fetchMyTrades +bitpanda True +bittrex True +bitvavo True +bitz True missing opt: fetchMyTrades +btcalpha True missing opt: fetchTicker, fetchTickers +btcmarkets True missing opt: fetchTickers +buda True missing opt: fetchMyTrades, fetchTickers +bw True missing opt: fetchMyTrades, fetchL2OrderBook +bybit True +bytetrade True +cdax True +cex True missing opt: fetchMyTrades +coinbaseprime True missing opt: fetchTickers +coinbasepro True missing opt: fetchTickers +coinex True +crex24 True +deribit True +digifinex True +equos True missing opt: fetchTicker, fetchTickers +eterbase True +fcoin True missing opt: fetchMyTrades, fetchTickers +fcoinjp True missing opt: fetchMyTrades, fetchTickers +ftx True +gateio True +gemini True +gopax True +hbtc True +hitbtc True +huobijp True +huobipro True +idex True +kraken True +kucoin True +lbank True missing opt: fetchMyTrades +mercado True missing opt: fetchTickers +ndax True missing opt: fetchTickers +novadax True +okcoin True +okex True +probit True +qtrade True +stex True +timex True +upbit True missing opt: fetchMyTrades +vcc True +zb True missing opt: fetchMyTrades + ``` +!!! Note "missing opt exchanges" + Values with "missing opt:" might need special configuration (e.g. using orderbook if `fetchTickers` is missing) - but should in theory work (although we cannot guarantee they will). + * Example: see all exchanges supported by the ccxt library (including 'bad' ones, i.e. those that are known to not work with Freqtrade): ``` $ freqtrade list-exchanges -a -All exchanges supported by the ccxt library: _1btcxe, acx, adara, allcoin, anxpro, bcex, bequant, bibox, bigone, binance, binanceje, binanceus, bit2c, bitbank, bitbay, bitfinex, bitfinex2, bitflyer, bitforex, bithumb, bitkk, bitlish, bitmart, bitmex, bitso, bitstamp, bitstamp1, bittrex, bitz, bl3p, bleutrade, braziliex, btcalpha, btcbox, btcchina, btcmarkets, btctradeim, btctradeua, btcturk, buda, bxinth, cex, chilebit, cobinhood, coinbase, coinbaseprime, coinbasepro, coincheck, coinegg, coinex, coinexchange, coinfalcon, coinfloor, coingi, coinmarketcap, coinmate, coinone, coinspot, cointiger, coolcoin, coss, crex24, crypton, deribit, digifinex, dsx, dx, ethfinex, exmo, exx, fcoin, fcoinjp, flowbtc, foxbit, fybse, gateio, gdax, gemini, hitbtc, hitbtc2, huobipro, huobiru, ice3x, idex, independentreserve, indodax, itbit, kkex, kraken, kucoin, kucoin2, kuna, lakebtc, latoken, lbank, liquid, livecoin, luno, lykke, mandala, mercado, mixcoins, negociecoins, nova, oceanex, okcoincny, okcoinusd, okex, okex3, paymium, poloniex, rightbtc, southxchange, stronghold, surbitcoin, theocean, therock, tidebit, tidex, upbit, vaultoro, vbtc, virwox, xbtce, yobit, zaif, zb +All exchanges supported by the ccxt library: +Exchange name Valid reason +------------------ ------- --------------------------------------------------------------------------------------- +aax True +aofex False missing: fetchOrder +ascendex True missing opt: fetchMyTrades +bequant True +bibox True +bigone True +binance True +binanceus True +bit2c False missing: fetchOrder, fetchOHLCV +bitbank True missing opt: fetchTickers +bitbay False missing: fetchOrder +bitcoincom True +bitfinex True +bitfinex2 False missing: fetchOrder +bitflyer False missing: fetchOrder, fetchOHLCV +bitforex True missing opt: fetchMyTrades, fetchTickers +bitget True +bithumb True missing opt: fetchMyTrades +bitkk True missing opt: fetchMyTrades +bitmart True +bitmax True missing opt: fetchMyTrades +bitmex False Various reasons. +bitpanda True +bitso False missing: fetchOHLCV +bitstamp False Does not provide history. Details in https://github.com/freqtrade/freqtrade/issues/1983 +bitstamp1 False missing: fetchOrder, fetchOHLCV +bittrex True +bitvavo True +bitz True missing opt: fetchMyTrades +bl3p False missing: fetchOrder, fetchOHLCV +bleutrade False missing: fetchOrder +braziliex False missing: fetchOHLCV +btcalpha True missing opt: fetchTicker, fetchTickers +btcbox False missing: fetchOHLCV +btcmarkets True missing opt: fetchTickers +btctradeua False missing: fetchOrder, fetchOHLCV +btcturk False missing: fetchOrder +buda True missing opt: fetchMyTrades, fetchTickers +bw True missing opt: fetchMyTrades, fetchL2OrderBook +bybit True +bytetrade True +cdax True +cex True missing opt: fetchMyTrades +chilebit False missing: fetchOrder, fetchOHLCV +coinbase False missing: fetchOrder, cancelOrder, createOrder, fetchOHLCV +coinbaseprime True missing opt: fetchTickers +coinbasepro True missing opt: fetchTickers +coincheck False missing: fetchOrder, fetchOHLCV +coinegg False missing: fetchOHLCV +coinex True +coinfalcon False missing: fetchOHLCV +coinfloor False missing: fetchOrder, fetchOHLCV +coingi False missing: fetchOrder, fetchOHLCV +coinmarketcap False missing: fetchOrder, cancelOrder, createOrder, fetchBalance, fetchOHLCV +coinmate False missing: fetchOHLCV +coinone False missing: fetchOHLCV +coinspot False missing: fetchOrder, cancelOrder, fetchOHLCV +crex24 True +currencycom False missing: fetchOrder +delta False missing: fetchOrder +deribit True +digifinex True +equos True missing opt: fetchTicker, fetchTickers +eterbase True +exmo False missing: fetchOrder +exx False missing: fetchOHLCV +fcoin True missing opt: fetchMyTrades, fetchTickers +fcoinjp True missing opt: fetchMyTrades, fetchTickers +flowbtc False missing: fetchOrder, fetchOHLCV +foxbit False missing: fetchOrder, fetchOHLCV +ftx True +gateio True +gemini True +gopax True +hbtc True +hitbtc True +hollaex False missing: fetchOrder +huobijp True +huobipro True +idex True +independentreserve False missing: fetchOHLCV +indodax False missing: fetchOHLCV +itbit False missing: fetchOHLCV +kraken True +kucoin True +kuna False missing: fetchOHLCV +lakebtc False missing: fetchOrder, fetchOHLCV +latoken False missing: fetchOrder, fetchOHLCV +lbank True missing opt: fetchMyTrades +liquid False missing: fetchOHLCV +luno False missing: fetchOHLCV +lykke False missing: fetchOHLCV +mercado True missing opt: fetchTickers +mixcoins False missing: fetchOrder, fetchOHLCV +ndax True missing opt: fetchTickers +novadax True +oceanex False missing: fetchOHLCV +okcoin True +okex True +paymium False missing: fetchOrder, fetchOHLCV +phemex False Does not provide history. +poloniex False missing: fetchOrder +probit True +qtrade True +rightbtc False missing: fetchOrder +ripio False missing: fetchOHLCV +southxchange False missing: fetchOrder, fetchOHLCV +stex True +surbitcoin False missing: fetchOrder, fetchOHLCV +therock False missing: fetchOHLCV +tidebit False missing: fetchOrder +tidex False missing: fetchOHLCV +timex True +upbit True missing opt: fetchMyTrades +vbtc False missing: fetchOrder, fetchOHLCV +vcc True +wavesexchange False missing: fetchOrder +whitebit False missing: fetchOrder, cancelOrder, createOrder, fetchBalance +xbtce False missing: fetchOrder, fetchOHLCV +xena False missing: fetchOrder +yobit False missing: fetchOHLCV +zaif False missing: fetchOrder, fetchOHLCV +zb True missing opt: fetchMyTrades ``` ## List Timeframes -Use the `list-timeframes` subcommand to see the list of timeframes (ticker intervals) available for the exchange. +Use the `list-timeframes` subcommand to see the list of timeframes available for the exchange. ``` usage: freqtrade list-timeframes [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [--exchange EXCHANGE] [-1] diff --git a/docs/webhook-config.md b/docs/webhook-config.md index 2e41ad2cc..8ce6edc18 100644 --- a/docs/webhook-config.md +++ b/docs/webhook-config.md @@ -19,6 +19,11 @@ Sample configuration (tested using IFTTT). "value1": "Cancelling Open Buy Order for {pair}", "value2": "limit {limit:8f}", "value3": "{stake_amount:8f} {stake_currency}" + }, + "webhookbuyfill": { + "value1": "Buy Order for {pair} filled", + "value2": "at {open_rate:8f}", + "value3": "" }, "webhooksell": { "value1": "Selling {pair}", @@ -30,6 +35,11 @@ Sample configuration (tested using IFTTT). "value2": "limit {limit:8f}", "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})" }, + "webhooksellfill": { + "value1": "Sell Order for {pair} filled", + "value2": "at {close_rate:8f}.", + "value3": "" + }, "webhookstatus": { "value1": "Status: {status}", "value2": "", @@ -91,6 +101,21 @@ Possible parameters are: * `order_type` * `current_rate` +### Webhookbuyfill + +The fields in `webhook.webhookbuyfill` are filled when the bot filled a buy order. Parameters are filled using string.format. +Possible parameters are: + +* `trade_id` +* `exchange` +* `pair` +* `open_rate` +* `amount` +* `open_date` +* `stake_amount` +* `stake_currency` +* `fiat_currency` + ### Webhooksell The fields in `webhook.webhooksell` are filled when the bot sells a trade. Parameters are filled using string.format. @@ -103,6 +128,27 @@ Possible parameters are: * `limit` * `amount` * `open_rate` +* `profit_amount` +* `profit_ratio` +* `stake_currency` +* `fiat_currency` +* `sell_reason` +* `order_type` +* `open_date` +* `close_date` + +### Webhooksellfill + +The fields in `webhook.webhooksellfill` are filled when the bot fills a sell order (closes a Trae). Parameters are filled using string.format. +Possible parameters are: + +* `trade_id` +* `exchange` +* `pair` +* `gain` +* `close_rate` +* `amount` +* `open_rate` * `current_rate` * `profit_amount` * `profit_ratio` diff --git a/environment.yml b/environment.yml index 938b5b6b8..f58434c15 100644 --- a/environment.yml +++ b/environment.yml @@ -4,7 +4,7 @@ channels: # - defaults dependencies: # 1/4 req main - - python>=3.7 + - python>=3.7,<3.9 - numpy - pandas - pip diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index 9468a7f7d..ffd317799 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -17,7 +17,7 @@ ARGS_STRATEGY = ["strategy", "strategy_path"] ARGS_TRADE = ["db_url", "sd_notify", "dry_run", "dry_run_wallet", "fee"] ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv", - "max_open_trades", "stake_amount", "fee"] + "max_open_trades", "stake_amount", "fee", "pairs"] ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions", "enable_protections", "dry_run_wallet", @@ -60,8 +60,9 @@ ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"] ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs"] -ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "timerange", "download_trades", "exchange", - "timeframes", "erase", "dataformat_ohlcv", "dataformat_trades"] +ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "new_pairs_days", "timerange", + "download_trades", "exchange", "timeframes", "erase", "dataformat_ohlcv", + "dataformat_trades"] ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit", "db_url", "trade_source", "export", "exportfilename", diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py index 3c34ff162..03d095e12 100644 --- a/freqtrade/commands/build_config_commands.py +++ b/freqtrade/commands/build_config_commands.py @@ -1,9 +1,11 @@ import logging +import secrets from pathlib import Path from typing import Any, Dict, List from questionary import Separator, prompt +from freqtrade.configuration.directory_operations import chown_user_directory from freqtrade.constants import UNLIMITED_STAKE_AMOUNT from freqtrade.exceptions import OperationalException from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, available_exchanges @@ -138,6 +140,32 @@ def ask_user_config() -> Dict[str, Any]: "message": "Insert Telegram chat id", "when": lambda x: x['telegram'] }, + { + "type": "confirm", + "name": "api_server", + "message": "Do you want to enable the Rest API (includes FreqUI)?", + "default": False, + }, + { + "type": "text", + "name": "api_server_listen_addr", + "message": "Insert Api server Listen Address (best left untouched default!)", + "default": "127.0.0.1", + "when": lambda x: x['api_server'] + }, + { + "type": "text", + "name": "api_server_username", + "message": "Insert api-server username", + "default": "freqtrader", + "when": lambda x: x['api_server'] + }, + { + "type": "text", + "name": "api_server_password", + "message": "Insert api-server password", + "when": lambda x: x['api_server'] + }, ] answers = prompt(questions) @@ -145,6 +173,9 @@ def ask_user_config() -> Dict[str, Any]: # Interrupted questionary sessions return an empty dict. raise OperationalException("User interrupted interactive questions.") + # Force JWT token to be a random string + answers['api_server_jwt_key'] = secrets.token_hex() + return answers @@ -186,6 +217,7 @@ def start_new_config(args: Dict[str, Any]) -> None: """ config_path = Path(args['config'][0]) + chown_user_directory(config_path.parent) if config_path.exists(): overwrite = ask_user_overwrite(config_path) if overwrite: diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index 15c13cec9..b583b47ba 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -118,7 +118,7 @@ AVAILABLE_CLI_OPTIONS = { # Optimize common "timeframe": Arg( '-i', '--timeframe', '--ticker-interval', - help='Specify ticker interval (`1m`, `5m`, `30m`, `1h`, `1d`).', + help='Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).', ), "timerange": Arg( '--timerange', @@ -195,6 +195,7 @@ AVAILABLE_CLI_OPTIONS = { '--hyperopt', help='Specify hyperopt class name which will be used by the bot.', metavar='NAME', + required=False, ), "hyperopt_path": Arg( '--hyperopt-path', @@ -266,7 +267,7 @@ AVAILABLE_CLI_OPTIONS = { default=1, ), "hyperopt_loss": Arg( - '--hyperopt-loss', + '--hyperopt-loss', '--hyperoptloss', help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). ' 'Different functions can generate completely different results, ' 'since the target for optimization is different. Built-in Hyperopt-loss-functions are: ' @@ -329,7 +330,7 @@ AVAILABLE_CLI_OPTIONS = { # Script options "pairs": Arg( '-p', '--pairs', - help='Show profits for only these pairs. Pairs are space-separated.', + help='Limit command to these pairs. Pairs are space-separated.', nargs='+', ), # Download data @@ -344,6 +345,12 @@ AVAILABLE_CLI_OPTIONS = { type=check_int_positive, metavar='INT', ), + "new_pairs_days": Arg( + '--new-pairs-days', + help='Download data of new pairs for given number of days. Default: `%(default)s`.', + type=check_int_positive, + metavar='INT', + ), "download_trades": Arg( '--dl-trades', help='Download trades instead of OHLCV data. The bot will resample trades to the ' diff --git a/freqtrade/commands/data_commands.py b/freqtrade/commands/data_commands.py index 1ce02eee5..58191ddb4 100644 --- a/freqtrade/commands/data_commands.py +++ b/freqtrade/commands/data_commands.py @@ -62,8 +62,8 @@ def start_download_data(args: Dict[str, Any]) -> None: if config.get('download_trades'): pairs_not_available = refresh_backtest_trades_data( exchange, pairs=expanded_pairs, datadir=config['datadir'], - timerange=timerange, erase=bool(config.get('erase')), - data_format=config['dataformat_trades']) + timerange=timerange, new_pairs_days=config['new_pairs_days'], + erase=bool(config.get('erase')), data_format=config['dataformat_trades']) # Convert downloaded trade data to different timeframes convert_trades_to_ohlcv( @@ -75,8 +75,9 @@ def start_download_data(args: Dict[str, Any]) -> None: else: pairs_not_available = refresh_backtest_ohlcv_data( exchange, pairs=expanded_pairs, timeframes=config['timeframes'], - datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')), - data_format=config['dataformat_ohlcv']) + datadir=config['datadir'], timerange=timerange, + new_pairs_days=config['new_pairs_days'], + erase=bool(config.get('erase')), data_format=config['dataformat_ohlcv']) except KeyboardInterrupt: sys.exit("SIGINT received, aborting ...") diff --git a/freqtrade/commands/hyperopt_commands.py b/freqtrade/commands/hyperopt_commands.py index 268e3eeef..e072e12cb 100755 --- a/freqtrade/commands/hyperopt_commands.py +++ b/freqtrade/commands/hyperopt_commands.py @@ -7,6 +7,7 @@ from colorama import init as colorama_init from freqtrade.configuration import setup_utils_configuration from freqtrade.data.btanalysis import get_latest_hyperopt_file from freqtrade.exceptions import OperationalException +from freqtrade.optimize.optimize_reports import show_backtest_result from freqtrade.state import RunMode @@ -125,6 +126,12 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None: if epochs: val = epochs[n] + + metrics = val['results_metrics'] + if 'strategy_name' in metrics: + show_backtest_result(metrics['strategy_name'], metrics, + metrics['stake_currency']) + HyperoptTools.print_epoch_details(val, total_epochs, print_json, no_header, header_str="Epoch details") @@ -132,11 +139,13 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None: def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List: """ Filter our items from the list of hyperopt results + TODO: after 2021.5 remove all "legacy" mode queries. """ if filteroptions['only_best']: epochs = [x for x in epochs if x['is_best']] if filteroptions['only_profitable']: - epochs = [x for x in epochs if x['results_metrics']['profit'] > 0] + epochs = [x for x in epochs if x['results_metrics'].get( + 'profit', x['results_metrics'].get('profit_total', 0)) > 0] epochs = _hyperopt_filter_epochs_trade_count(epochs, filteroptions) @@ -153,34 +162,55 @@ def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List: return epochs +def _hyperopt_filter_epochs_trade(epochs: List, trade_count: int): + """ + Filter epochs with trade-counts > trades + """ + return [ + x for x in epochs + if x['results_metrics'].get( + 'trade_count', x['results_metrics'].get('total_trades', 0) + ) > trade_count + ] + + def _hyperopt_filter_epochs_trade_count(epochs: List, filteroptions: dict) -> List: if filteroptions['filter_min_trades'] > 0: - epochs = [ - x for x in epochs - if x['results_metrics']['trade_count'] > filteroptions['filter_min_trades'] - ] + epochs = _hyperopt_filter_epochs_trade(epochs, filteroptions['filter_min_trades']) + if filteroptions['filter_max_trades'] > 0: epochs = [ x for x in epochs - if x['results_metrics']['trade_count'] < filteroptions['filter_max_trades'] + if x['results_metrics'].get( + 'trade_count', x['results_metrics'].get('total_trades') + ) < filteroptions['filter_max_trades'] ] return epochs def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List: + def get_duration_value(x): + # Duration in minutes ... + if 'duration' in x['results_metrics']: + return x['results_metrics']['duration'] + else: + # New mode + avg = x['results_metrics']['holding_avg'] + return avg.total_seconds() // 60 + if filteroptions['filter_min_avg_time'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['duration'] > filteroptions['filter_min_avg_time'] + if get_duration_value(x) > filteroptions['filter_min_avg_time'] ] if filteroptions['filter_max_avg_time'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['duration'] < filteroptions['filter_max_avg_time'] + if get_duration_value(x) < filteroptions['filter_max_avg_time'] ] return epochs @@ -189,28 +219,36 @@ def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List: def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List: if filteroptions['filter_min_avg_profit'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['avg_profit'] > filteroptions['filter_min_avg_profit'] + if x['results_metrics'].get( + 'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100 + ) > filteroptions['filter_min_avg_profit'] ] if filteroptions['filter_max_avg_profit'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['avg_profit'] < filteroptions['filter_max_avg_profit'] + if x['results_metrics'].get( + 'avg_profit', x['results_metrics'].get('profit_mean', 0) * 100 + ) < filteroptions['filter_max_avg_profit'] ] if filteroptions['filter_min_total_profit'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['profit'] > filteroptions['filter_min_total_profit'] + if x['results_metrics'].get( + 'profit', x['results_metrics'].get('profit_total_abs', 0) + ) > filteroptions['filter_min_total_profit'] ] if filteroptions['filter_max_total_profit'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [ x for x in epochs - if x['results_metrics']['profit'] < filteroptions['filter_max_total_profit'] + if x['results_metrics'].get( + 'profit', x['results_metrics'].get('profit_total_abs', 0) + ) < filteroptions['filter_max_total_profit'] ] return epochs @@ -218,11 +256,11 @@ def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List: def _hyperopt_filter_epochs_objective(epochs: List, filteroptions: dict) -> List: if filteroptions['filter_min_objective'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [x for x in epochs if x['loss'] < filteroptions['filter_min_objective']] if filteroptions['filter_max_objective'] is not None: - epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0] + epochs = _hyperopt_filter_epochs_trade(epochs, 0) epochs = [x for x in epochs if x['loss'] > filteroptions['filter_max_objective']] diff --git a/freqtrade/commands/list_commands.py b/freqtrade/commands/list_commands.py index 9e6076dfb..fa4bc1066 100644 --- a/freqtrade/commands/list_commands.py +++ b/freqtrade/commands/list_commands.py @@ -13,7 +13,7 @@ from tabulate import tabulate from freqtrade.configuration import setup_utils_configuration from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES from freqtrade.exceptions import OperationalException -from freqtrade.exchange import available_exchanges, ccxt_exchanges, market_is_active +from freqtrade.exchange import market_is_active, validate_exchanges from freqtrade.misc import plural from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.state import RunMode @@ -28,14 +28,18 @@ def start_list_exchanges(args: Dict[str, Any]) -> None: :param args: Cli args from Arguments() :return: None """ - exchanges = ccxt_exchanges() if args['list_exchanges_all'] else available_exchanges() + exchanges = validate_exchanges(args['list_exchanges_all']) + if args['print_one_column']: - print('\n'.join(exchanges)) + print('\n'.join([e[0] for e in exchanges])) else: if args['list_exchanges_all']: - print(f"All exchanges supported by the ccxt library: {', '.join(exchanges)}") + print("All exchanges supported by the ccxt library:") else: - print(f"Exchanges available for Freqtrade: {', '.join(exchanges)}") + print("Exchanges available for Freqtrade:") + exchanges = [e for e in exchanges if e[1] is not False] + + print(tabulate(exchanges, headers=['Exchange name', 'Valid', 'reason'])) def _print_objs_tabular(objs: List, print_colorized: bool) -> None: @@ -99,7 +103,7 @@ def start_list_hyperopts(args: Dict[str, Any]) -> None: def start_list_timeframes(args: Dict[str, Any]) -> None: """ - Print ticker intervals (timeframes) available on Exchange + Print timeframes available on Exchange """ config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE) # Do not use timeframe set in the config @@ -177,7 +181,7 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None: # human-readable formats. print() - if len(pairs): + if pairs: if args.get('print_list', False): # print data as a list, with human-readable summary print(f"{summary_str}: {', '.join(pairs.keys())}.") diff --git a/freqtrade/configuration/check_exchange.py b/freqtrade/configuration/check_exchange.py index aa36de3ff..832caf153 100644 --- a/freqtrade/configuration/check_exchange.py +++ b/freqtrade/configuration/check_exchange.py @@ -2,8 +2,8 @@ import logging from typing import Any, Dict from freqtrade.exceptions import OperationalException -from freqtrade.exchange import (available_exchanges, get_exchange_bad_reason, is_exchange_bad, - is_exchange_known_ccxt, is_exchange_officially_supported) +from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt, + is_exchange_officially_supported, validate_exchange) from freqtrade.state import RunMode @@ -57,9 +57,13 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool: f'{", ".join(available_exchanges())}' ) - if check_for_bad and is_exchange_bad(exchange): - raise OperationalException(f'Exchange "{exchange}" is known to not work with the bot yet. ' - f'Reason: {get_exchange_bad_reason(exchange)}') + valid, reason = validate_exchange(exchange) + if not valid: + if check_for_bad: + raise OperationalException(f'Exchange "{exchange}" will not work with Freqtrade. ' + f'Reason: {reason}') + else: + logger.warning(f'Exchange "{exchange}" will not work with Freqtrade. Reason: {reason}') if is_exchange_officially_supported(exchange): logger.info(f'Exchange "{exchange}" is officially supported ' diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py index c7e49f33d..31e38d572 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -149,11 +149,6 @@ def _validate_edge(conf: Dict[str, Any]) -> None: if not conf.get('edge', {}).get('enabled'): return - if conf.get('pairlist', {}).get('method') == 'VolumePairList': - raise OperationalException( - "Edge and VolumePairList are incompatible, " - "Edge will override whatever pairs VolumePairlist selects." - ) if not conf.get('ask_strategy', {}).get('use_sell_signal', True): raise OperationalException( "Edge requires `use_sell_signal` to be True, otherwise no sells will happen." diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index a40a4fd83..f6d0520c5 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -11,10 +11,10 @@ from freqtrade import constants from freqtrade.configuration.check_exchange import check_exchange from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir -from freqtrade.configuration.load_config import load_config_file +from freqtrade.configuration.load_config import load_config_file, load_file from freqtrade.exceptions import OperationalException from freqtrade.loggers import setup_logging -from freqtrade.misc import deep_merge_dicts, json_load +from freqtrade.misc import deep_merge_dicts from freqtrade.state import NON_UTIL_MODES, TRADING_MODES, RunMode @@ -75,8 +75,6 @@ class Configuration: # Normalize config if 'internals' not in config: config['internals'] = {} - # TODO: This can be deleted along with removal of deprecated - # experimental settings if 'ask_strategy' not in config: config['ask_strategy'] = {} @@ -108,6 +106,8 @@ class Configuration: self._process_plot_options(config) + self._process_data_options(config) + # Check if the exchange set by the user is supported check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True)) @@ -399,6 +399,11 @@ class Configuration: self._args_to_config(config, argname='dataformat_trades', logstring='Using "{}" to store trades data.') + def _process_data_options(self, config: Dict[str, Any]) -> None: + + self._args_to_config(config, argname='new_pairs_days', + logstring='Detected --new-pairs-days: {}') + def _process_runmode(self, config: Dict[str, Any]) -> None: self._args_to_config(config, argname='dry_run', @@ -445,6 +450,7 @@ class Configuration: """ if "pairs" in config: + config['exchange']['pair_whitelist'] = config['pairs'] return if "pairs_file" in self.args and self.args["pairs_file"]: @@ -454,9 +460,8 @@ class Configuration: # or if pairs file is specified explicitely if not pairs_file.exists(): raise OperationalException(f'No pairs file found with path "{pairs_file}".') - with pairs_file.open('r') as f: - config['pairs'] = json_load(f) - config['pairs'].sort() + config['pairs'] = load_file(pairs_file) + config['pairs'].sort() return if 'config' in self.args and self.args['config']: @@ -466,7 +471,6 @@ class Configuration: # Fall back to /dl_path/pairs.json pairs_file = config['datadir'] / 'pairs.json' if pairs_file.exists(): - with pairs_file.open('r') as f: - config['pairs'] = json_load(f) + config['pairs'] = load_file(pairs_file) if 'pairs' in config: config['pairs'].sort() diff --git a/freqtrade/configuration/directory_operations.py b/freqtrade/configuration/directory_operations.py index 51310f013..ca305c260 100644 --- a/freqtrade/configuration/directory_operations.py +++ b/freqtrade/configuration/directory_operations.py @@ -24,6 +24,21 @@ def create_datadir(config: Dict[str, Any], datadir: Optional[str] = None) -> Pat return folder +def chown_user_directory(directory: Path) -> None: + """ + Use Sudo to change permissions of the home-directory if necessary + Only applies when running in docker! + """ + import os + if os.environ.get('FT_APP_ENV') == 'docker': + try: + import subprocess + subprocess.check_output( + ['sudo', 'chown', '-R', 'ftuser:', str(directory.resolve())]) + except Exception: + logger.warning(f"Could not chown {directory}") + + def create_userdata_dir(directory: str, create_dir: bool = False) -> Path: """ Create userdata directory structure. @@ -37,6 +52,7 @@ def create_userdata_dir(directory: str, create_dir: bool = False) -> Path: sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "logs", "notebooks", "plot", "strategies", ] folder = Path(directory) + chown_user_directory(folder) if not folder.is_dir(): if create_dir: folder.mkdir(parents=True) @@ -72,6 +88,5 @@ def copy_sample_files(directory: Path, overwrite: bool = False) -> None: if not overwrite: logger.warning(f"File `{targetfile}` exists already, not deploying sample file.") continue - else: - logger.warning(f"File `{targetfile}` exists already, overwriting.") + logger.warning(f"File `{targetfile}` exists already, overwriting.") shutil.copy(str(sourcedir / source), str(targetfile)) diff --git a/freqtrade/configuration/load_config.py b/freqtrade/configuration/load_config.py index 726126034..1320a375f 100644 --- a/freqtrade/configuration/load_config.py +++ b/freqtrade/configuration/load_config.py @@ -38,6 +38,15 @@ def log_config_error_range(path: str, errmsg: str) -> str: return '' +def load_file(path: Path) -> Dict[str, Any]: + try: + with path.open('r') as file: + config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE) + except FileNotFoundError: + raise OperationalException(f'File file "{path}" not found!') + return config + + def load_config_file(path: str) -> Dict[str, Any]: """ Loads a config file from the given path diff --git a/freqtrade/configuration/timerange.py b/freqtrade/configuration/timerange.py index 6072e296c..6979c8cd1 100644 --- a/freqtrade/configuration/timerange.py +++ b/freqtrade/configuration/timerange.py @@ -3,6 +3,7 @@ This module contains the argument manager class """ import logging import re +from datetime import datetime from typing import Optional import arrow @@ -43,7 +44,7 @@ class TimeRange: self.startts = self.startts - seconds def adjust_start_if_necessary(self, timeframe_secs: int, startup_candles: int, - min_date: arrow.Arrow) -> None: + min_date: datetime) -> None: """ Adjust startts by candles. Applies only if no startup-candles have been available. @@ -54,11 +55,11 @@ class TimeRange: :return: None (Modifies the object in place) """ if (not self.starttype or (startup_candles - and min_date.int_timestamp >= self.startts)): + and min_date.timestamp() >= self.startts)): # If no startts was defined, or backtest-data starts at the defined backtest-date logger.warning("Moving start-date by %s candles to account for startup time.", startup_candles) - self.startts = (min_date.int_timestamp + timeframe_secs * startup_candles) + self.startts = int(min_date.timestamp() + timeframe_secs * startup_candles) self.starttype = 'date' @staticmethod diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 3a2ed98e9..5ec60eb59 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -11,6 +11,7 @@ DEFAULT_EXCHANGE = 'bittrex' PROCESS_THROTTLE_SECS = 5 # sec HYPEROPT_EPOCH = 100 # epochs RETRY_TIMEOUT = 30 # sec +TIMEOUT_UNITS = ['minutes', 'seconds'] DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite' DEFAULT_DB_DRYRUN_URL = 'sqlite:///tradesv3.dryrun.sqlite' UNLIMITED_STAKE_AMOUNT = 'unlimited' @@ -26,7 +27,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss', AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'AgeFilter', 'PerformanceFilter', 'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter', 'ShuffleFilter', - 'SpreadFilter'] + 'SpreadFilter', 'VolatilityFilter'] AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard'] AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5'] DRY_RUN_WALLET = 1000 @@ -96,6 +97,7 @@ CONF_SCHEMA = { 'type': 'object', 'properties': { 'max_open_trades': {'type': ['integer', 'number'], 'minimum': -1}, + 'new_pairs_days': {'type': 'integer', 'default': 30}, 'timeframe': {'type': 'string'}, 'stake_currency': {'type': 'string'}, 'stake_amount': { @@ -136,7 +138,8 @@ CONF_SCHEMA = { 'type': 'object', 'properties': { 'buy': {'type': 'number', 'minimum': 1}, - 'sell': {'type': 'number', 'minimum': 1} + 'sell': {'type': 'number', 'minimum': 1}, + 'unit': {'type': 'string', 'enum': TIMEOUT_UNITS, 'default': 'minutes'} } }, 'bid_strategy': { @@ -176,7 +179,7 @@ CONF_SCHEMA = { 'order_book_max': {'type': 'integer', 'minimum': 1, 'maximum': 50}, 'use_sell_signal': {'type': 'boolean'}, 'sell_profit_only': {'type': 'boolean'}, - 'sell_profit_offset': {'type': 'number', 'minimum': 0.0}, + 'sell_profit_offset': {'type': 'number'}, 'ignore_roi_if_buy_signal': {'type': 'boolean'} } }, @@ -246,14 +249,24 @@ CONF_SCHEMA = { 'balance_dust_level': {'type': 'number', 'minimum': 0.0}, 'notification_settings': { 'type': 'object', + 'default': {}, 'properties': { 'status': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, 'warning': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, 'startup': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, 'buy': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, - 'sell': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, 'buy_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, - 'sell_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS} + 'buy_fill': {'type': 'string', + 'enum': TELEGRAM_SETTING_OPTIONS, + 'default': 'off' + }, + 'sell': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, + 'sell_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}, + 'sell_fill': { + 'type': 'string', + 'enum': TELEGRAM_SETTING_OPTIONS, + 'default': 'off' + }, } } }, diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index c98477f4e..e7af5eab8 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -156,33 +156,35 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non data = data['strategy'][strategy]['trades'] df = pd.DataFrame(data) - df['open_date'] = pd.to_datetime(df['open_date'], - utc=True, - infer_datetime_format=True - ) - df['close_date'] = pd.to_datetime(df['close_date'], - utc=True, - infer_datetime_format=True - ) + if not df.empty: + df['open_date'] = pd.to_datetime(df['open_date'], + utc=True, + infer_datetime_format=True + ) + df['close_date'] = pd.to_datetime(df['close_date'], + utc=True, + infer_datetime_format=True + ) else: # old format - only with lists. df = pd.DataFrame(data, columns=BT_DATA_COLUMNS_OLD) - - df['open_date'] = pd.to_datetime(df['open_date'], - unit='s', - utc=True, - infer_datetime_format=True - ) - df['close_date'] = pd.to_datetime(df['close_date'], - unit='s', - utc=True, - infer_datetime_format=True - ) - # Create compatibility with new format - df['profit_abs'] = df['close_rate'] - df['open_rate'] - if 'profit_ratio' not in df.columns: - df['profit_ratio'] = df['profit_percent'] - df = df.sort_values("open_date").reset_index(drop=True) + if not df.empty: + df['open_date'] = pd.to_datetime(df['open_date'], + unit='s', + utc=True, + infer_datetime_format=True + ) + df['close_date'] = pd.to_datetime(df['close_date'], + unit='s', + utc=True, + infer_datetime_format=True + ) + # Create compatibility with new format + df['profit_abs'] = df['close_rate'] - df['open_rate'] + if not df.empty: + if 'profit_ratio' not in df.columns: + df['profit_ratio'] = df['profit_percent'] + df = df.sort_values("open_date").reset_index(drop=True) return df @@ -337,7 +339,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, """ Adds a column `col_name` with the cumulative profit for the given trades array. :param df: DataFrame with date index - :param trades: DataFrame containing trades (requires columns close_date and profit_ratio) + :param trades: DataFrame containing trades (requires columns close_date and profit_abs) :param col_name: Column name that will be assigned the results :param timeframe: Timeframe used during the operations :return: Returns df with one additional column, col_name, containing the cumulative profit. @@ -349,8 +351,8 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, timeframe_minutes = timeframe_to_minutes(timeframe) # Resample to timeframe to make sure trades match candles _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_date' - )[['profit_ratio']].sum() - df.loc[:, col_name] = _trades_sum['profit_ratio'].cumsum() + )[['profit_abs']].sum() + df.loc[:, col_name] = _trades_sum['profit_abs'].cumsum() # Set first value to 0 df.loc[df.iloc[0].name, col_name] = 0 # FFill to get continuous diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py index d4053abaa..ffee0c52c 100644 --- a/freqtrade/data/converter.py +++ b/freqtrade/data/converter.py @@ -110,28 +110,62 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) df.reset_index(inplace=True) len_before = len(dataframe) len_after = len(df) + pct_missing = (len_after - len_before) / len_before if len_before > 0 else 0 if len_before != len_after: - logger.info(f"Missing data fillup for {pair}: before: {len_before} - after: {len_after}") + message = (f"Missing data fillup for {pair}: before: {len_before} - after: {len_after}" + f" - {round(pct_missing * 100, 2)}%") + if pct_missing > 0.01: + logger.info(message) + else: + # Don't be verbose if only a small amount is missing + logger.debug(message) return df -def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date') -> DataFrame: +def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date', + startup_candles: int = 0) -> DataFrame: """ Trim dataframe based on given timerange :param df: Dataframe to trim :param timerange: timerange (use start and end date if available) - :param: df_date_col: Column in the dataframe to use as Date column + :param df_date_col: Column in the dataframe to use as Date column + :param startup_candles: When not 0, is used instead the timerange start date :return: trimmed dataframe """ - if timerange.starttype == 'date': - start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) - df = df.loc[df[df_date_col] >= start, :] + if startup_candles: + # Trim candles instead of timeframe in case of given startup_candle count + df = df.iloc[startup_candles:, :] + else: + if timerange.starttype == 'date': + start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) + df = df.loc[df[df_date_col] >= start, :] if timerange.stoptype == 'date': stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc) df = df.loc[df[df_date_col] <= stop, :] return df +def trim_dataframes(preprocessed: Dict[str, DataFrame], timerange, + startup_candles: int) -> Dict[str, DataFrame]: + """ + Trim startup period from analyzed dataframes + :param preprocessed: Dict of pair: dataframe + :param timerange: timerange (use start and end date if available) + :param startup_candles: Startup-candles that should be removed + :return: Dict of trimmed dataframes + """ + processed: Dict[str, DataFrame] = {} + + for pair, df in preprocessed.items(): + trimed_df = trim_dataframe(df, timerange, startup_candles=startup_candles) + if not trimed_df.empty: + processed[pair] = trimed_df + else: + logger.warning(f'{pair} has no data left after adjusting for startup candles, ' + f'skipping.') + return processed + + def order_book_to_dataframe(bids: list, asks: list) -> DataFrame: """ TODO: This should get a dedicated test diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index a035b7c3b..1a86eece5 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -19,14 +19,25 @@ from freqtrade.state import RunMode logger = logging.getLogger(__name__) +NO_EXCHANGE_EXCEPTION = 'Exchange is not available to DataProvider.' +MAX_DATAFRAME_CANDLES = 1000 + class DataProvider: - def __init__(self, config: dict, exchange: Exchange, pairlists=None) -> None: + def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} + self.__slice_index: Optional[int] = None + + def _set_dataframe_max_index(self, limit_index: int): + """ + Limit analyzed dataframe to max specified index. + :param limit_index: dataframe index. + """ + self.__slice_index = limit_index def _set_cached_df(self, pair: str, timeframe: str, dataframe: DataFrame) -> None: """ @@ -45,40 +56,6 @@ class DataProvider: """ self._pairlists = pairlists - def refresh(self, - pairlist: ListPairsWithTimeframes, - helping_pairs: ListPairsWithTimeframes = None) -> None: - """ - Refresh data, called with each cycle - """ - if helping_pairs: - self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs) - else: - self._exchange.refresh_latest_ohlcv(pairlist) - - @property - def available_pairs(self) -> ListPairsWithTimeframes: - """ - Return a list of tuples containing (pair, timeframe) for which data is currently cached. - Should be whitelist + open trades. - """ - return list(self._exchange._klines.keys()) - - def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame: - """ - Get candle (OHLCV) data for the given pair as DataFrame - Please use the `available_pairs` method to verify which pairs are currently cached. - :param pair: pair to get the data for - :param timeframe: Timeframe to get data for - :param copy: copy dataframe before returning if True. - Use False only for read-only operations (where the dataframe is not modified) - """ - if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): - return self._exchange.klines((pair, timeframe or self._config['timeframe']), - copy=copy) - else: - return DataFrame() - def historic_ohlcv(self, pair: str, timeframe: str = None) -> DataFrame: """ Get stored historical candle (OHLCV) data @@ -111,47 +88,27 @@ class DataProvider: def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]: """ + Retrieve the analyzed dataframe. Returns the full dataframe in trade mode (live / dry), + and the last 1000 candles (up to the time evaluated at this moment) in all other modes. :param pair: pair to get the data for :param timeframe: timeframe to get data for :return: Tuple of (Analyzed Dataframe, lastrefreshed) for the requested pair / timeframe combination. Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached. """ - if (pair, timeframe) in self.__cached_pairs: - return self.__cached_pairs[(pair, timeframe)] + pair_key = (pair, timeframe) + if pair_key in self.__cached_pairs: + if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): + df, date = self.__cached_pairs[pair_key] + else: + df, date = self.__cached_pairs[pair_key] + if self.__slice_index is not None: + max_index = self.__slice_index + df = df.iloc[max(0, max_index - MAX_DATAFRAME_CANDLES):max_index] + return df, date else: - return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) - def market(self, pair: str) -> Optional[Dict[str, Any]]: - """ - Return market data for the pair - :param pair: Pair to get the data for - :return: Market data dict from ccxt or None if market info is not available for the pair - """ - return self._exchange.markets.get(pair) - - def ticker(self, pair: str): - """ - Return last ticker data from exchange - :param pair: Pair to get the data for - :return: Ticker dict from exchange or empty dict if ticker is not available for the pair - """ - try: - return self._exchange.fetch_ticker(pair) - except ExchangeError: - return {} - - def orderbook(self, pair: str, maximum: int) -> Dict[str, List]: - """ - Fetch latest l2 orderbook data - Warning: Does a network request - so use with common sense. - :param pair: pair to get the data for - :param maximum: Maximum number of orderbook entries to query - :return: dict including bids/asks with a total of `maximum` entries. - """ - return self._exchange.fetch_l2_order_book(pair, maximum) - @property def runmode(self) -> RunMode: """ @@ -170,6 +127,89 @@ class DataProvider: """ if self._pairlists: - return self._pairlists.whitelist + return self._pairlists.whitelist.copy() else: raise OperationalException("Dataprovider was not initialized with a pairlist provider.") + + def clear_cache(self): + """ + Clear pair dataframe cache. + """ + self.__cached_pairs = {} + + # Exchange functions + + def refresh(self, + pairlist: ListPairsWithTimeframes, + helping_pairs: ListPairsWithTimeframes = None) -> None: + """ + Refresh data, called with each cycle + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + if helping_pairs: + self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs) + else: + self._exchange.refresh_latest_ohlcv(pairlist) + + @property + def available_pairs(self) -> ListPairsWithTimeframes: + """ + Return a list of tuples containing (pair, timeframe) for which data is currently cached. + Should be whitelist + open trades. + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + return list(self._exchange._klines.keys()) + + def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame: + """ + Get candle (OHLCV) data for the given pair as DataFrame + Please use the `available_pairs` method to verify which pairs are currently cached. + :param pair: pair to get the data for + :param timeframe: Timeframe to get data for + :param copy: copy dataframe before returning if True. + Use False only for read-only operations (where the dataframe is not modified) + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): + return self._exchange.klines((pair, timeframe or self._config['timeframe']), + copy=copy) + else: + return DataFrame() + + def market(self, pair: str) -> Optional[Dict[str, Any]]: + """ + Return market data for the pair + :param pair: Pair to get the data for + :return: Market data dict from ccxt or None if market info is not available for the pair + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + return self._exchange.markets.get(pair) + + def ticker(self, pair: str): + """ + Return last ticker data from exchange + :param pair: Pair to get the data for + :return: Ticker dict from exchange or empty dict if ticker is not available for the pair + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + try: + return self._exchange.fetch_ticker(pair) + except ExchangeError: + return {} + + def orderbook(self, pair: str, maximum: int) -> Dict[str, List]: + """ + Fetch latest l2 orderbook data + Warning: Does a network request - so use with common sense. + :param pair: pair to get the data for + :param maximum: Maximum number of orderbook entries to query + :return: dict including bids/asks with a total of `maximum` entries. + """ + if self._exchange is None: + raise OperationalException(NO_EXCHANGE_EXCEPTION) + return self._exchange.fetch_l2_order_book(pair, maximum) diff --git a/freqtrade/data/history/hdf5datahandler.py b/freqtrade/data/history/hdf5datahandler.py index d116637e7..e80cfeba2 100644 --- a/freqtrade/data/history/hdf5datahandler.py +++ b/freqtrade/data/history/hdf5datahandler.py @@ -89,7 +89,7 @@ class HDF5DataHandler(IDataHandler): if timerange.starttype == 'date': where.append(f"date >= Timestamp({timerange.startts * 1e9})") if timerange.stoptype == 'date': - where.append(f"date < Timestamp({timerange.stopts * 1e9})") + where.append(f"date <= Timestamp({timerange.stopts * 1e9})") pairdata = pd.read_hdf(filename, key=key, mode="r", where=where) diff --git a/freqtrade/data/history/history_utils.py b/freqtrade/data/history/history_utils.py index 3b8b5a2f0..86e9f75e6 100644 --- a/freqtrade/data/history/history_utils.py +++ b/freqtrade/data/history/history_utils.py @@ -155,6 +155,7 @@ def _load_cached_data_for_updating(pair: str, timeframe: str, timerange: Optiona def _download_pair_history(datadir: Path, exchange: Exchange, pair: str, *, + new_pairs_days: int = 30, timeframe: str = '5m', timerange: Optional[TimeRange] = None, data_handler: IDataHandler = None) -> bool: @@ -193,7 +194,7 @@ def _download_pair_history(datadir: Path, timeframe=timeframe, since_ms=since_ms if since_ms else int(arrow.utcnow().shift( - days=-30).float_timestamp) * 1000 + days=-new_pairs_days).float_timestamp) * 1000 ) # TODO: Maybe move parsing to exchange class (?) new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair, @@ -223,7 +224,8 @@ def _download_pair_history(datadir: Path, def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str], datadir: Path, timerange: Optional[TimeRange] = None, - erase: bool = False, data_format: str = None) -> List[str]: + new_pairs_days: int = 30, erase: bool = False, + data_format: str = None) -> List[str]: """ Refresh stored ohlcv data for backtesting and hyperopt operations. Used by freqtrade download-data subcommand. @@ -246,12 +248,14 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes logger.info(f'Downloading pair {pair}, interval {timeframe}.') _download_pair_history(datadir=datadir, exchange=exchange, pair=pair, timeframe=str(timeframe), + new_pairs_days=new_pairs_days, timerange=timerange, data_handler=data_handler) return pairs_not_available def _download_trades_history(exchange: Exchange, pair: str, *, + new_pairs_days: int = 30, timerange: Optional[TimeRange] = None, data_handler: IDataHandler ) -> bool: @@ -261,9 +265,13 @@ def _download_trades_history(exchange: Exchange, """ try: - since = timerange.startts * 1000 if \ - (timerange and timerange.starttype == 'date') else int(arrow.utcnow().shift( - days=-30).float_timestamp) * 1000 + until = None + if (timerange and timerange.starttype == 'date'): + since = timerange.startts * 1000 + if timerange.stoptype == 'date': + until = timerange.stopts * 1000 + else: + since = int(arrow.utcnow().shift(days=-new_pairs_days).float_timestamp) * 1000 trades = data_handler.trades_load(pair) @@ -291,6 +299,7 @@ def _download_trades_history(exchange: Exchange, # Default since_ms to 30 days if nothing is given new_trades = exchange.get_historic_trades(pair=pair, since=since, + until=until, from_id=from_id, ) trades.extend(new_trades[1]) @@ -311,8 +320,8 @@ def _download_trades_history(exchange: Exchange, def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path, - timerange: TimeRange, erase: bool = False, - data_format: str = 'jsongz') -> List[str]: + timerange: TimeRange, new_pairs_days: int = 30, + erase: bool = False, data_format: str = 'jsongz') -> List[str]: """ Refresh stored trades data for backtesting and hyperopt operations. Used by freqtrade download-data subcommand. @@ -333,6 +342,7 @@ def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: logger.info(f'Downloading trades for pair {pair}.') _download_trades_history(exchange=exchange, pair=pair, + new_pairs_days=new_pairs_days, timerange=timerange, data_handler=data_handler) return pairs_not_available @@ -362,7 +372,7 @@ def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str], logger.exception(f'Could not convert {pair} to OHLCV.') -def get_timerange(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]: +def get_timerange(data: Dict[str, DataFrame]) -> Tuple[datetime, datetime]: """ Get the maximum common timerange for the given backtest data. @@ -370,7 +380,7 @@ def get_timerange(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow] :return: tuple containing min_date, max_date """ timeranges = [ - (arrow.get(frame['date'].min()), arrow.get(frame['date'].max())) + (frame['date'].min().to_pydatetime(), frame['date'].max().to_pydatetime()) for frame in data.values() ] return (min(timeranges, key=operator.itemgetter(0))[0], diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py index ff86e522e..4bc0d660b 100644 --- a/freqtrade/edge/edge_positioning.py +++ b/freqtrade/edge/edge_positioning.py @@ -1,6 +1,8 @@ # pragma pylint: disable=W0603 """ Edge positioning package """ import logging +from collections import defaultdict +from copy import deepcopy from typing import Any, Dict, List, NamedTuple import arrow @@ -12,8 +14,10 @@ from freqtrade.configuration import TimeRange from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT from freqtrade.data.history import get_timerange, load_data, refresh_data from freqtrade.exceptions import OperationalException +from freqtrade.exchange.exchange import timeframe_to_seconds from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist -from freqtrade.strategy.interface import SellType +from freqtrade.state import RunMode +from freqtrade.strategy.interface import IStrategy, SellType logger = logging.getLogger(__name__) @@ -45,7 +49,7 @@ class Edge: self.config = config self.exchange = exchange - self.strategy = strategy + self.strategy: IStrategy = strategy self.edge_config = self.config.get('edge', {}) self._cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs @@ -81,12 +85,16 @@ class Edge: if config.get('fee'): self.fee = config['fee'] else: - self.fee = self.exchange.get_fee(symbol=expand_pairlist( - self.config['exchange']['pair_whitelist'], list(self.exchange.markets))[0]) + try: + self.fee = self.exchange.get_fee(symbol=expand_pairlist( + self.config['exchange']['pair_whitelist'], list(self.exchange.markets))[0]) + except IndexError: + self.fee = None + + def calculate(self, pairs: List[str]) -> bool: + if self.fee is None and pairs: + self.fee = self.exchange.get_fee(pairs[0]) - def calculate(self) -> bool: - pairs = expand_pairlist(self.config['exchange']['pair_whitelist'], - list(self.exchange.markets)) heartbeat = self.edge_config.get('process_throttle_secs') if (self._last_updated > 0) and ( @@ -98,14 +106,33 @@ class Edge: logger.info('Using local backtesting data (using whitelist in given config) ...') if self._refresh_pairs: + timerange_startup = deepcopy(self._timerange) + timerange_startup.subtract_start(timeframe_to_seconds( + self.strategy.timeframe) * self.strategy.startup_candle_count) refresh_data( datadir=self.config['datadir'], pairs=pairs, exchange=self.exchange, timeframe=self.strategy.timeframe, - timerange=self._timerange, + timerange=timerange_startup, data_format=self.config.get('dataformat_ohlcv', 'json'), ) + # Download informative pairs too + res = defaultdict(list) + for p, t in self.strategy.informative_pairs(): + res[t].append(p) + for timeframe, inf_pairs in res.items(): + timerange_startup = deepcopy(self._timerange) + timerange_startup.subtract_start(timeframe_to_seconds( + timeframe) * self.strategy.startup_candle_count) + refresh_data( + datadir=self.config['datadir'], + pairs=inf_pairs, + exchange=self.exchange, + timeframe=timeframe, + timerange=timerange_startup, + data_format=self.config.get('dataformat_ohlcv', 'json'), + ) data = load_data( datadir=self.config['datadir'], @@ -121,8 +148,11 @@ class Edge: self._cached_pairs = {} logger.critical("No data found. Edge is stopped ...") return False - + # Fake run-mode to Edge + prior_rm = self.config['runmode'] + self.config['runmode'] = RunMode.EDGE preprocessed = self.strategy.ohlcvdata_to_dataframe(data) + self.config['runmode'] = prior_rm # Print timeframe min_date, max_date = get_timerange(preprocessed) @@ -179,7 +209,7 @@ class Edge: if pair in self._cached_pairs: return self._cached_pairs[pair].stoploss else: - logger.warning('tried to access stoploss of a non-existing pair, ' + logger.warning(f'Tried to access stoploss of non-existing pair {pair}, ' 'strategy stoploss is returned instead.') return self.strategy.stoploss @@ -210,7 +240,7 @@ class Edge: return self._final_pairs - def accepted_pairs(self) -> list: + def accepted_pairs(self) -> List[Dict[str, Any]]: """ return a list of accepted pairs along with their winrate, expectancy and stoploss """ diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py index 15ba7b9f6..23ba2eb10 100644 --- a/freqtrade/exchange/__init__.py +++ b/freqtrade/exchange/__init__.py @@ -8,10 +8,12 @@ from freqtrade.exchange.binance import Binance from freqtrade.exchange.bittrex import Bittrex from freqtrade.exchange.bybit import Bybit from freqtrade.exchange.exchange import (available_exchanges, ccxt_exchanges, - get_exchange_bad_reason, is_exchange_bad, is_exchange_known_ccxt, is_exchange_officially_supported, market_is_active, timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date, timeframe_to_prev_date, - timeframe_to_seconds) + timeframe_to_seconds, validate_exchange, + validate_exchanges) from freqtrade.exchange.ftx import Ftx +from freqtrade.exchange.hitbtc import Hitbtc from freqtrade.exchange.kraken import Kraken +from freqtrade.exchange.kucoin import Kucoin diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py index 26ec30a8a..0bcfa5e17 100644 --- a/freqtrade/exchange/binance.py +++ b/freqtrade/exchange/binance.py @@ -52,7 +52,7 @@ class Binance(Exchange): 'In stoploss limit order, stop price should be more than limit price') if self._config['dry_run']: - dry_order = self.dry_run_order( + dry_order = self.create_dry_run_order( pair, ordertype, "sell", amount, stop_price) return dry_order diff --git a/freqtrade/exchange/bittrex.py b/freqtrade/exchange/bittrex.py index fd7d47668..69e2f2b8d 100644 --- a/freqtrade/exchange/bittrex.py +++ b/freqtrade/exchange/bittrex.py @@ -12,10 +12,6 @@ class Bittrex(Exchange): """ Bittrex exchange class. Contains adjustments needed for Freqtrade to work with this exchange. - - Please note that this exchange is not included in the list of exchanges - officially supported by the Freqtrade development team. So some features - may still not work as expected. """ _ft_has: Dict = { diff --git a/freqtrade/exchange/common.py b/freqtrade/exchange/common.py index c66db860f..694aa3aa2 100644 --- a/freqtrade/exchange/common.py +++ b/freqtrade/exchange/common.py @@ -18,78 +18,8 @@ BAD_EXCHANGES = { "bitmex": "Various reasons.", "bitstamp": "Does not provide history. " "Details in https://github.com/freqtrade/freqtrade/issues/1983", - "hitbtc": "This API cannot be used with Freqtrade. " - "Use `hitbtc2` exchange id to access this exchange.", "phemex": "Does not provide history. ", "poloniex": "Does not provide fetch_order endpoint to fetch both open and closed orders.", - **dict.fromkeys([ - 'adara', - 'anxpro', - 'bigone', - 'coinbase', - 'coinexchange', - 'coinmarketcap', - 'lykke', - 'xbtce', - ], "Does not provide timeframes. ccxt fetchOHLCV: False"), - **dict.fromkeys([ - 'bcex', - 'bit2c', - 'bitbay', - 'bitflyer', - 'bitforex', - 'bithumb', - 'bitso', - 'bitstamp1', - 'bl3p', - 'braziliex', - 'btcbox', - 'btcchina', - 'btctradeim', - 'btctradeua', - 'bxinth', - 'chilebit', - 'coincheck', - 'coinegg', - 'coinfalcon', - 'coinfloor', - 'coingi', - 'coinmate', - 'coinone', - 'coinspot', - 'coolcoin', - 'crypton', - 'deribit', - 'exmo', - 'exx', - 'flowbtc', - 'foxbit', - 'fybse', - # 'hitbtc', - 'ice3x', - 'independentreserve', - 'indodax', - 'itbit', - 'lakebtc', - 'latoken', - 'liquid', - 'livecoin', - 'luno', - 'mixcoins', - 'negociecoins', - 'nova', - 'paymium', - 'southxchange', - 'stronghold', - 'surbitcoin', - 'therock', - 'tidex', - 'vaultoro', - 'vbtc', - 'virwox', - 'yobit', - 'zaif', - ], "Does not provide timeframes. ccxt fetchOHLCV: emulated"), } MAP_EXCHANGE_CHILDCLASS = { @@ -98,6 +28,29 @@ MAP_EXCHANGE_CHILDCLASS = { } +EXCHANGE_HAS_REQUIRED = [ + # Required / private + 'fetchOrder', + 'cancelOrder', + 'createOrder', + # 'createLimitOrder', 'createMarketOrder', + 'fetchBalance', + + # Public endpoints + 'loadMarkets', + 'fetchOHLCV', +] + +EXCHANGE_HAS_OPTIONAL = [ + # Private + 'fetchMyTrades', # Trades for order - fee detection + # Public + 'fetchOrderBook', 'fetchL2OrderBook', 'fetchTicker', # OR for pricing + 'fetchTickers', # For volumepairlist? + 'fetchTrades', # Downloading trades data +] + + def calculate_backoff(retrycount, max_retries): """ Calculate backoff @@ -140,7 +93,7 @@ def retrier(_func=None, retries=API_RETRY_COUNT): logger.warning('retrying %s() still for %s times', f.__name__, count) count -= 1 kwargs.update({'count': count}) - if isinstance(ex, DDosProtection) or isinstance(ex, RetryableOrderError): + if isinstance(ex, (DDosProtection, RetryableOrderError)): # increasing backoff backoff_delay = calculate_backoff(count + 1, retries) logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}") diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 5b6e2b20d..93d8f7584 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -14,6 +14,7 @@ from typing import Any, Dict, List, Optional, Tuple import arrow import ccxt import ccxt.async_support as ccxt_async +from cachetools import TTLCache from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision) from pandas import DataFrame @@ -23,7 +24,8 @@ from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError, InvalidOrderException, OperationalException, RetryableOrderError, TemporaryError) -from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, retrier, +from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, + EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, retrier, retrier_async) from freqtrade.misc import deep_merge_dicts, safe_value_fallback2 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist @@ -57,11 +59,13 @@ class Exchange: _ft_has_default: Dict = { "stoploss_on_exchange": False, "order_time_in_force": ["gtc"], + "ohlcv_params": {}, "ohlcv_candle_limit": 500, "ohlcv_partial_candle": True, "trades_pagination": "time", # Possible are "time" or "id" "trades_pagination_arg": "since", "l2_limit_range": None, + "l2_limit_range_required": True, # Allow Empty L2 limit (kucoin) } _ft_has: Dict = {} @@ -82,6 +86,9 @@ class Exchange: # Timestamp of last markets refresh self._last_markets_refresh: int = 0 + # Cache for 10 minutes ... + self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=1, ttl=60 * 10) + # Holds candles self._klines: Dict[Tuple[str, str], DataFrame] = {} @@ -357,7 +364,6 @@ class Exchange: invalid_pairs = [] for pair in extended_pairs: # Note: ccxt has BaseCurrency/QuoteCurrency format for pairs - # TODO: add a support for having coins in BTC/USDT format if self.markets and pair not in self.markets: raise OperationalException( f'Pair {pair} is not available on {self.name}. ' @@ -460,7 +466,7 @@ class Exchange: def amount_to_precision(self, pair: str, amount: float) -> float: ''' Returns the amount to buy or sell to a precision the Exchange accepts - Reimplementation of ccxt internal methods - ensuring we can test the result is correct + Re-implementation of ccxt internal methods - ensuring we can test the result is correct based on our definitions. ''' if self.markets[pair]['precision']['amount']: @@ -474,7 +480,7 @@ class Exchange: def price_to_precision(self, pair: str, price: float) -> float: ''' Returns the price rounded up to the precision the Exchange accepts. - Partial Reimplementation of ccxt internal method decimal_to_precision(), + Partial Re-implementation of ccxt internal method decimal_to_precision(), which does not support rounding up TODO: If ccxt supports ROUND_UP for decimal_to_precision(), we could remove this and align with amount_to_precision(). @@ -533,7 +539,9 @@ class Exchange: # reserve some percent defined in config (5% default) + stoploss amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent', DEFAULT_AMOUNT_RESERVE_PERCENT) - amount_reserve_percent += abs(stoploss) + amount_reserve_percent = ( + amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5 + ) # it should not be more than 50% amount_reserve_percent = max(min(amount_reserve_percent, 1.5), 1) @@ -542,8 +550,8 @@ class Exchange: # See also #2575 at github. return max(min_stake_amounts) * amount_reserve_percent - def dry_run_order(self, pair: str, ordertype: str, side: str, amount: float, - rate: float, params: Dict = {}) -> Dict[str, Any]: + def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float, + rate: float, params: Dict = {}) -> Dict[str, Any]: order_id = f'dry_run_{side}_{datetime.now().timestamp()}' _amount = self.amount_to_precision(pair, amount) dry_order = { @@ -617,7 +625,7 @@ class Exchange: rate: float, time_in_force: str) -> Dict: if self._config['dry_run']: - dry_order = self.dry_run_order(pair, ordertype, "buy", amount, rate) + dry_order = self.create_dry_run_order(pair, ordertype, "buy", amount, rate) return dry_order params = self._params.copy() @@ -630,7 +638,7 @@ class Exchange: rate: float, time_in_force: str = 'gtc') -> Dict: if self._config['dry_run']: - dry_order = self.dry_run_order(pair, ordertype, "sell", amount, rate) + dry_order = self.create_dry_run_order(pair, ordertype, "sell", amount, rate) return dry_order params = self._params.copy() @@ -659,23 +667,8 @@ class Exchange: raise OperationalException(f"stoploss is not implemented for {self.name}.") - @retrier - def get_balance(self, currency: str) -> float: - if self._config['dry_run']: - return self._config['dry_run_wallet'] - - # ccxt exception is already handled by get_balances - balances = self.get_balances() - balance = balances.get(currency) - if balance is None: - raise TemporaryError( - f'Could not get {currency} balance due to malformed exchange response: {balances}') - return balance['free'] - @retrier def get_balances(self) -> dict: - if self._config['dry_run']: - return {} try: balances = self._api.fetch_balance() @@ -695,9 +688,19 @@ class Exchange: raise OperationalException(e) from e @retrier - def get_tickers(self) -> Dict: + def get_tickers(self, cached: bool = False) -> Dict: + """ + :param cached: Allow cached result + :return: fetch_tickers result + """ + if cached: + tickers = self._fetch_tickers_cache.get('fetch_tickers') + if tickers: + return tickers try: - return self._api.fetch_tickers() + tickers = self._api.fetch_tickers() + self._fetch_tickers_cache['fetch_tickers'] = tickers + return tickers except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching tickers in batch. ' @@ -806,7 +809,7 @@ class Exchange: # Gather coroutines to run for pair, timeframe in set(pair_list): - if (not ((pair, timeframe) in self._klines) + if (((pair, timeframe) not in self._klines) or self._now_is_time_to_refresh(pair, timeframe)): input_coroutines.append(self._async_get_candle_history(pair, timeframe, since_ms=since_ms)) @@ -860,10 +863,11 @@ class Exchange: "Fetching pair %s, interval %s, since %s %s...", pair, timeframe, since_ms, s ) - + params = self._ft_has.get('ohlcv_params', {}) data = await self._api_async.fetch_ohlcv(pair, timeframe=timeframe, since=since_ms, - limit=self.ohlcv_candle_limit(timeframe)) + limit=self.ohlcv_candle_limit(timeframe), + params=params) # Some exchanges sort OHLCV in ASC order and others in DESC. # Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last) @@ -958,7 +962,7 @@ class Exchange: while True: t = await self._async_fetch_trades(pair, params={self._trades_pagination_arg: from_id}) - if len(t): + if t: # Skip last id since its the key for the next call trades.extend(t[:-1]) if from_id == t[-1][1] or t[-1][0] > until: @@ -990,7 +994,7 @@ class Exchange: # DEFAULT_TRADES_COLUMNS: 1 -> id while True: t = await self._async_fetch_trades(pair, since=since) - if len(t): + if t: since = t[-1][0] trades.extend(t) # Reached the end of the defined-download period @@ -1116,6 +1120,27 @@ class Exchange: return order + def cancel_stoploss_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict: + """ + Cancel stoploss order returning a result. + Creates a fake result if cancel order returns a non-usable result + and fetch_order does not work (certain exchanges don't return cancelled orders) + :param order_id: stoploss-order-id to cancel + :param pair: Pair corresponding to order_id + :param amount: Amount to use for fake response + :return: Result from either cancel_order if usable, or fetch_order + """ + corder = self.cancel_stoploss_order(order_id, pair) + if self.is_cancel_order_result_suitable(corder): + return corder + try: + order = self.fetch_stoploss_order(order_id, pair) + except InvalidOrderException: + logger.warning(f"Could not fetch cancelled stoploss order {order_id}.") + order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}} + + return order + @retrier(retries=API_FETCH_ORDER_RETRY_COUNT) def fetch_order(self, order_id: str, pair: str) -> Dict: if self._config['dry_run']: @@ -1157,14 +1182,20 @@ class Exchange: return self.fetch_order(order_id, pair) @staticmethod - def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]]): + def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]], + range_required: bool = True): """ Get next greater value in the list. Used by fetch_l2_order_book if the api only supports a limited range """ if not limit_range: return limit - return min([x for x in limit_range if limit <= x] + [max(limit_range)]) + + result = min([x for x in limit_range if limit <= x] + [max(limit_range)]) + if not range_required and limit > result: + # Range is not required - we can use None as parameter. + return None + return result @retrier def fetch_l2_order_book(self, pair: str, limit: int = 100) -> dict: @@ -1174,7 +1205,8 @@ class Exchange: Returns a dict in the format {'asks': [price, volume], 'bids': [price, volume]} """ - limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range']) + limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range'], + self._ft_has['l2_limit_range_required']) try: return self._api.fetch_l2_order_book(pair, limit1) @@ -1228,6 +1260,9 @@ class Exchange: except ccxt.BaseError as e: raise OperationalException(e) from e + def get_order_id_conditional(self, order: Dict[str, Any]) -> str: + return order['id'] + @retrier def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1, price: float = 1, taker_or_maker: str = 'maker') -> float: @@ -1306,14 +1341,6 @@ class Exchange: self.calculate_fee_rate(order)) -def is_exchange_bad(exchange_name: str) -> bool: - return exchange_name in BAD_EXCHANGES - - -def get_exchange_bad_reason(exchange_name: str) -> str: - return BAD_EXCHANGES.get(exchange_name, "") - - def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool: return exchange_name in ccxt_exchanges(ccxt_module) @@ -1334,7 +1361,36 @@ def available_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]: Return exchanges available to the bot, i.e. non-bad exchanges in the ccxt list """ exchanges = ccxt_exchanges(ccxt_module) - return [x for x in exchanges if not is_exchange_bad(x)] + return [x for x in exchanges if validate_exchange(x)[0]] + + +def validate_exchange(exchange: str) -> Tuple[bool, str]: + ex_mod = getattr(ccxt, exchange.lower())() + if not ex_mod or not ex_mod.has: + return False, '' + missing = [k for k in EXCHANGE_HAS_REQUIRED if ex_mod.has.get(k) is not True] + if missing: + return False, f"missing: {', '.join(missing)}" + + missing_opt = [k for k in EXCHANGE_HAS_OPTIONAL if not ex_mod.has.get(k)] + + if exchange.lower() in BAD_EXCHANGES: + return False, BAD_EXCHANGES.get(exchange.lower(), '') + if missing_opt: + return True, f"missing opt: {', '.join(missing_opt)}" + + return True, '' + + +def validate_exchanges(all_exchanges: bool) -> List[Tuple[str, bool, str]]: + """ + :return: List of tuples with exchangename, valid, reason. + """ + exchanges = ccxt_exchanges() if all_exchanges else available_exchanges() + exchanges_valid = [ + (e, *validate_exchange(e)) for e in exchanges + ] + return exchanges_valid def timeframe_to_seconds(timeframe: str) -> int: diff --git a/freqtrade/exchange/ftx.py b/freqtrade/exchange/ftx.py index f05490cbb..9009e9492 100644 --- a/freqtrade/exchange/ftx.py +++ b/freqtrade/exchange/ftx.py @@ -8,6 +8,7 @@ from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, Invali OperationalException, TemporaryError) from freqtrade.exchange import Exchange from freqtrade.exchange.common import API_FETCH_ORDER_RETRY_COUNT, retrier +from freqtrade.misc import safe_value_fallback2 logger = logging.getLogger(__name__) @@ -53,7 +54,7 @@ class Ftx(Exchange): stop_price = self.price_to_precision(pair, stop_price) if self._config['dry_run']: - dry_order = self.dry_run_order( + dry_order = self.create_dry_run_order( pair, ordertype, "sell", amount, stop_price) return dry_order @@ -63,10 +64,11 @@ class Ftx(Exchange): # set orderPrice to place limit order, otherwise it's a market order params['orderPrice'] = limit_rate + params['stopPrice'] = stop_price amount = self.amount_to_precision(pair, amount) order = self._api.create_order(symbol=pair, type=ordertype, side='sell', - amount=amount, price=stop_price, params=params) + amount=amount, params=params) logger.info('stoploss order added for %s. ' 'stop price: %s.', pair, stop_price) return order @@ -134,3 +136,8 @@ class Ftx(Exchange): f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e + + def get_order_id_conditional(self, order: Dict[str, Any]) -> str: + if order['type'] == 'stop': + return safe_value_fallback2(order['info'], order, 'orderId', 'id') + return order['id'] diff --git a/freqtrade/exchange/hitbtc.py b/freqtrade/exchange/hitbtc.py new file mode 100644 index 000000000..763535263 --- /dev/null +++ b/freqtrade/exchange/hitbtc.py @@ -0,0 +1,24 @@ +import logging +from typing import Dict + +from freqtrade.exchange import Exchange + + +logger = logging.getLogger(__name__) + + +class Hitbtc(Exchange): + """ + Hitbtc exchange class. Contains adjustments needed for Freqtrade to work + with this exchange. + + Please note that this exchange is not included in the list of exchanges + officially supported by the Freqtrade development team. So some features + may still not work as expected. + """ + + # fetchCurrencies API point requires authentication for Hitbtc, + _ft_has: Dict = { + "ohlcv_candle_limit": 1000, + "ohlcv_params": {"sort": "DESC"} + } diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py index 724b11189..6f1fa409a 100644 --- a/freqtrade/exchange/kraken.py +++ b/freqtrade/exchange/kraken.py @@ -53,6 +53,8 @@ class Kraken(Exchange): # x["side"], x["amount"], ) for x in orders] for bal in balances: + if not isinstance(balances[bal], dict): + continue balances[bal]['used'] = sum(order[1] for order in order_list if order[0] == bal) balances[bal]['free'] = balances[bal]['total'] - balances[bal]['used'] @@ -92,7 +94,7 @@ class Kraken(Exchange): stop_price = self.price_to_precision(pair, stop_price) if self._config['dry_run']: - dry_order = self.dry_run_order( + dry_order = self.create_dry_run_order( pair, ordertype, "sell", amount, stop_price) return dry_order diff --git a/freqtrade/exchange/kucoin.py b/freqtrade/exchange/kucoin.py new file mode 100644 index 000000000..22886a1d8 --- /dev/null +++ b/freqtrade/exchange/kucoin.py @@ -0,0 +1,24 @@ +""" Kucoin exchange subclass """ +import logging +from typing import Dict + +from freqtrade.exchange import Exchange + + +logger = logging.getLogger(__name__) + + +class Kucoin(Exchange): + """ + Kucoin exchange class. Contains adjustments needed for Freqtrade to work + with this exchange. + + Please note that this exchange is not included in the list of exchanges + officially supported by the Freqtrade development team. So some features + may still not work as expected. + """ + + _ft_has: Dict = { + "l2_limit_range": [20, 100], + "l2_limit_range_required": False, + } diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 73f4c91be..1c3a759f4 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -28,7 +28,7 @@ from freqtrade.plugins.protectionmanager import ProtectionManager from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.rpc import RPCManager, RPCMessageType from freqtrade.state import State -from freqtrade.strategy.interface import IStrategy, SellType +from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.wallets import Wallets @@ -113,7 +113,7 @@ class FreqtradeBot(LoggingMixin): via RPC about changes in the bot status. """ self.rpc.send_msg({ - 'type': RPCMessageType.STATUS_NOTIFICATION, + 'type': RPCMessageType.STATUS, 'status': msg }) @@ -187,7 +187,7 @@ class FreqtradeBot(LoggingMixin): if self.get_free_open_trades(): self.enter_positions() - Trade.session.flush() + Trade.query.session.flush() def process_stopped(self) -> None: """ @@ -205,7 +205,7 @@ class FreqtradeBot(LoggingMixin): if len(open_trades) != 0: msg = { - 'type': RPCMessageType.WARNING_NOTIFICATION, + 'type': RPCMessageType.WARNING, 'status': f"{len(open_trades)} open trades active.\n\n" f"Handle these trades manually on {self.exchange.name}, " f"or '/start' the bot again and use '/stopbuy' " @@ -225,7 +225,7 @@ class FreqtradeBot(LoggingMixin): # Calculating Edge positioning if self.edge: - self.edge.calculate() + self.edge.calculate(_whitelist) _whitelist = self.edge.adjust(_whitelist) if trades: @@ -267,7 +267,7 @@ class FreqtradeBot(LoggingMixin): def update_closed_trades_without_assigned_fees(self): """ Update closed trades without close fees assigned. - Only acts when Orders are in the database, otherwise the last orderid is unknown. + Only acts when Orders are in the database, otherwise the last order-id is unknown. """ if self.config['dry_run']: # Updating open orders in dry-run does not make sense and will fail. @@ -378,7 +378,7 @@ class FreqtradeBot(LoggingMixin): if lock: self.log_once(f"Global pairlock active until " f"{lock.lock_end_time.strftime(constants.DATETIME_PRINT_FORMAT)}. " - "Not creating new trades.", logger.info) + f"Not creating new trades, reason: {lock.reason}.", logger.info) else: self.log_once("Global pairlock active. Not creating new trades.", logger.info) return trades_created @@ -410,9 +410,7 @@ class FreqtradeBot(LoggingMixin): bid_strategy = self.config.get('bid_strategy', {}) if 'use_order_book' in bid_strategy and bid_strategy.get('use_order_book', False): - logger.info( - f"Getting price from order book {bid_strategy['price_side'].capitalize()} side." - ) + order_book_top = bid_strategy.get('order_book_top', 1) order_book = self.exchange.fetch_l2_order_book(pair, order_book_top) logger.debug('order_book %s', order_book) @@ -425,7 +423,8 @@ class FreqtradeBot(LoggingMixin): f"Orderbook: {order_book}" ) raise PricingError from e - logger.info(f'...top {order_book_top} order book buy rate {rate_from_l2:.8f}') + logger.info(f"Buy price from orderbook {bid_strategy['price_side'].capitalize()} side " + f"- top {order_book_top} order book buy rate {rate_from_l2:.8f}") used_rate = rate_from_l2 else: logger.info(f"Using Last {bid_strategy['price_side'].capitalize()} / Last Price") @@ -457,7 +456,8 @@ class FreqtradeBot(LoggingMixin): lock = PairLocks.get_pair_longest_lock(pair, nowtime) if lock: self.log_once(f"Pair {pair} is still locked until " - f"{lock.lock_end_time.strftime(constants.DATETIME_PRINT_FORMAT)}.", + f"{lock.lock_end_time.strftime(constants.DATETIME_PRINT_FORMAT)} " + f"due to {lock.reason}.", logger.info) else: self.log_once(f"Pair {pair} is still locked.", logger.info) @@ -473,25 +473,22 @@ class FreqtradeBot(LoggingMixin): (buy, sell) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df) if buy and not sell: - stake_amount = self.wallets.get_trade_stake_amount(pair, self.get_free_open_trades(), - self.edge) + stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge) if not stake_amount: logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.") return False - logger.info(f"Buy signal found: about create a new trade with stake_amount: " + logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: " f"{stake_amount} ...") bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {}) if ((bid_check_dom.get('enabled', False)) and (bid_check_dom.get('bids_to_ask_delta', 0) > 0)): if self._check_depth_of_market_buy(pair, bid_check_dom): - logger.info(f'Executing Buy for {pair}.') return self.execute_buy(pair, stake_amount) else: return False - logger.info(f'Executing Buy for {pair}') return self.execute_buy(pair, stake_amount) else: return False @@ -555,7 +552,7 @@ class FreqtradeBot(LoggingMixin): if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)( pair=pair, order_type=order_type, amount=amount, rate=buy_limit_requested, - time_in_force=time_in_force): + time_in_force=time_in_force, current_time=datetime.now(timezone.utc)): logger.info(f"User requested abortion of buying {pair}") return False amount = self.exchange.amount_to_precision(pair, amount) @@ -621,8 +618,8 @@ class FreqtradeBot(LoggingMixin): if order_status == 'closed': self.update_trade_state(trade, order_id, order) - Trade.session.add(trade) - Trade.session.flush() + Trade.query.session.add(trade) + Trade.query.session.flush() # Updating wallets self.wallets.update() @@ -633,11 +630,11 @@ class FreqtradeBot(LoggingMixin): def _notify_buy(self, trade: Trade, order_type: str) -> None: """ - Sends rpc notification when a buy occured. + Sends rpc notification when a buy occurred. """ msg = { 'trade_id': trade.id, - 'type': RPCMessageType.BUY_NOTIFICATION, + 'type': RPCMessageType.BUY, 'exchange': self.exchange.name.capitalize(), 'pair': trade.pair, 'limit': trade.open_rate, @@ -655,13 +652,13 @@ class FreqtradeBot(LoggingMixin): def _notify_buy_cancel(self, trade: Trade, order_type: str, reason: str) -> None: """ - Sends rpc notification when a buy cancel occured. + Sends rpc notification when a buy cancel occurred. """ current_rate = self.get_buy_rate(trade.pair, False) msg = { 'trade_id': trade.id, - 'type': RPCMessageType.BUY_CANCEL_NOTIFICATION, + 'type': RPCMessageType.BUY_CANCEL, 'exchange': self.exchange.name.capitalize(), 'pair': trade.pair, 'limit': trade.open_rate, @@ -678,6 +675,21 @@ class FreqtradeBot(LoggingMixin): # Send the message self.rpc.send_msg(msg) + def _notify_buy_fill(self, trade: Trade) -> None: + msg = { + 'trade_id': trade.id, + 'type': RPCMessageType.BUY_FILL, + 'exchange': self.exchange.name.capitalize(), + 'pair': trade.pair, + 'open_rate': trade.open_rate, + 'stake_amount': trade.stake_amount, + 'stake_currency': self.config['stake_currency'], + 'fiat_currency': self.config.get('fiat_display_currency', None), + 'amount': trade.amount, + 'open_date': trade.open_date, + } + self.rpc.send_msg(msg) + # # SELL / exit positions / close trades logic and methods # @@ -701,7 +713,7 @@ class FreqtradeBot(LoggingMixin): except DependencyException as exception: logger.warning('Unable to sell trade %s: %s', trade.pair, exception) - # Updating wallets if any trade occured + # Updating wallets if any trade occurred if trades_closed: self.wallets.update() @@ -838,7 +850,8 @@ class FreqtradeBot(LoggingMixin): trade.stoploss_order_id = None logger.error(f'Unable to place a stoploss order on exchange. {e}') logger.warning('Selling the trade forcefully') - self.execute_sell(trade, trade.stop_loss, sell_reason=SellType.EMERGENCY_SELL) + self.execute_sell(trade, trade.stop_loss, sell_reason=SellCheckTuple( + sell_type=SellType.EMERGENCY_SELL)) except ExchangeError: trade.stoploss_order_id = None @@ -919,14 +932,15 @@ class FreqtradeBot(LoggingMixin): :return: None """ if self.exchange.stoploss_adjust(trade.stop_loss, order): - # we check if the update is neccesary + # we check if the update is necessary update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60) if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat: # cancelling the current stoploss on exchange first logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} " f"(orderid:{order['id']}) in order to add another one ...") try: - co = self.exchange.cancel_stoploss_order(order['id'], trade.pair) + co = self.exchange.cancel_stoploss_order_with_result(order['id'], trade.pair, + trade.amount) trade.update_order(co) except InvalidOrderException: logger.exception(f"Could not cancel stoploss order {order['id']} " @@ -949,7 +963,7 @@ class FreqtradeBot(LoggingMixin): if should_sell.sell_flag: logger.info(f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}') - self.execute_sell(trade, sell_rate, should_sell.sell_type) + self.execute_sell(trade, sell_rate, should_sell) return True return False @@ -960,15 +974,16 @@ class FreqtradeBot(LoggingMixin): timeout = self.config.get('unfilledtimeout', {}).get(side) ordertime = arrow.get(order['datetime']).datetime if timeout is not None: - timeout_threshold = arrow.utcnow().shift(minutes=-timeout).datetime - + timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes') + timeout_kwargs = {timeout_unit: -timeout} + timeout_threshold = arrow.utcnow().shift(**timeout_kwargs).datetime return (order['status'] == 'open' and order['side'] == side and ordertime < timeout_threshold) return False def check_handle_timedout(self) -> None: """ - Check if any orders are timed out and cancel if neccessary + Check if any orders are timed out and cancel if necessary :param timeoutvalue: Number of minutes until order is considered timed out :return: None """ @@ -1030,6 +1045,16 @@ class FreqtradeBot(LoggingMixin): # Cancelled orders may have the status of 'canceled' or 'closed' if order['status'] not in ('cancelled', 'canceled', 'closed'): + filled_val = order.get('filled', 0.0) or 0.0 + filled_stake = filled_val * trade.open_rate + minstake = self.exchange.get_min_pair_stake_amount( + trade.pair, trade.open_rate, self.strategy.stoploss) + + if filled_val > 0 and filled_stake < minstake: + logger.warning( + f"Order {trade.open_order_id} for {trade.pair} not cancelled, " + f"as the filled amount of {filled_val} would result in an unsellable trade.") + return False corder = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, trade.amount) # Avoid race condition where the order could not be cancelled coz its already filled. @@ -1138,16 +1163,16 @@ class FreqtradeBot(LoggingMixin): raise DependencyException( f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}") - def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> bool: + def execute_sell(self, trade: Trade, limit: float, sell_reason: SellCheckTuple) -> bool: """ Executes a limit sell for the given trade and limit :param trade: Trade instance :param limit: limit rate for the sell order - :param sellreason: Reason the sell was triggered + :param sell_reason: Reason the sell was triggered :return: True if it succeeds (supported) False (not supported) """ sell_type = 'sell' - if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS): + if sell_reason.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS): sell_type = 'stoploss' # if stoploss is on exchange and we are on dry_run mode, @@ -1159,15 +1184,17 @@ class FreqtradeBot(LoggingMixin): # First cancelling stoploss on exchange ... if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id: try: - self.exchange.cancel_stoploss_order(trade.stoploss_order_id, trade.pair) + co = self.exchange.cancel_stoploss_order_with_result(trade.stoploss_order_id, + trade.pair, trade.amount) + trade.update_order(co) except InvalidOrderException: logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}") order_type = self.strategy.order_types[sell_type] - if sell_reason == SellType.EMERGENCY_SELL: + if sell_reason.sell_type == SellType.EMERGENCY_SELL: # Emergency sells (default to market!) order_type = self.strategy.order_types.get("emergencysell", "market") - if sell_reason == SellType.FORCE_SELL: + if sell_reason.sell_type == SellType.FORCE_SELL: # Force sells (default to the sell_type defined in the strategy, # but we allow this value to be changed) order_type = self.strategy.order_types.get("forcesell", order_type) @@ -1177,8 +1204,8 @@ class FreqtradeBot(LoggingMixin): if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)( pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit, - time_in_force=time_in_force, - sell_reason=sell_reason.value): + time_in_force=time_in_force, sell_reason=sell_reason.sell_reason, + current_time=datetime.now(timezone.utc)): logger.info(f"User requested abortion of selling {trade.pair}") return False @@ -1201,13 +1228,13 @@ class FreqtradeBot(LoggingMixin): trade.open_order_id = order['id'] trade.sell_order_status = '' trade.close_rate_requested = limit - trade.sell_reason = sell_reason.value + trade.sell_reason = sell_reason.sell_reason # In case of market sell orders the order can be closed immediately if order.get('status', 'unknown') == 'closed': self.update_trade_state(trade, trade.open_order_id, order) - Trade.session.flush() + Trade.query.session.flush() - # Lock pair for one candle to prevent immediate rebuys + # Lock pair for one candle to prevent immediate re-buys self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc), reason='Auto lock') @@ -1215,19 +1242,20 @@ class FreqtradeBot(LoggingMixin): return True - def _notify_sell(self, trade: Trade, order_type: str) -> None: + def _notify_sell(self, trade: Trade, order_type: str, fill: bool = False) -> None: """ - Sends rpc notification when a sell occured. + Sends rpc notification when a sell occurred. """ profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested profit_trade = trade.calc_profit(rate=profit_rate) # Use cached rates here - it was updated seconds ago. - current_rate = self.get_sell_rate(trade.pair, False) + current_rate = self.get_sell_rate(trade.pair, False) if not fill else None profit_ratio = trade.calc_profit_ratio(profit_rate) gain = "profit" if profit_ratio > 0 else "loss" msg = { - 'type': RPCMessageType.SELL_NOTIFICATION, + 'type': (RPCMessageType.SELL_FILL if fill + else RPCMessageType.SELL), 'trade_id': trade.id, 'exchange': trade.exchange.capitalize(), 'pair': trade.pair, @@ -1236,6 +1264,7 @@ class FreqtradeBot(LoggingMixin): 'order_type': order_type, 'amount': trade.amount, 'open_rate': trade.open_rate, + 'close_rate': trade.close_rate, 'current_rate': current_rate, 'profit_amount': profit_trade, 'profit_ratio': profit_ratio, @@ -1256,7 +1285,7 @@ class FreqtradeBot(LoggingMixin): def _notify_sell_cancel(self, trade: Trade, order_type: str, reason: str) -> None: """ - Sends rpc notification when a sell cancel occured. + Sends rpc notification when a sell cancel occurred. """ if trade.sell_order_status == reason: return @@ -1270,7 +1299,7 @@ class FreqtradeBot(LoggingMixin): gain = "profit" if profit_ratio > 0 else "loss" msg = { - 'type': RPCMessageType.SELL_CANCEL_NOTIFICATION, + 'type': RPCMessageType.SELL_CANCEL, 'trade_id': trade.id, 'exchange': trade.exchange.capitalize(), 'pair': trade.pair, @@ -1309,7 +1338,7 @@ class FreqtradeBot(LoggingMixin): Handles closing both buy and sell orders. :param trade: Trade object of the trade we're analyzing :param order_id: Order-id of the order we're analyzing - :param action_order: Already aquired order object + :param action_order: Already acquired order object :return: True if order has been cancelled without being filled partially, False otherwise """ if not order_id: @@ -1347,9 +1376,15 @@ class FreqtradeBot(LoggingMixin): # Updating wallets when order is closed if not trade.is_open: + if not stoploss_order and not trade.open_order_id: + self._notify_sell(trade, '', True) self.protections.stop_per_pair(trade.pair) self.protections.global_stop() self.wallets.update() + elif not trade.open_order_id: + # Buy fill + self._notify_buy_fill(trade) + return False def apply_fee_conditional(self, trade: Trade, trade_base_currency: str, @@ -1373,7 +1408,7 @@ class FreqtradeBot(LoggingMixin): def get_real_amount(self, trade: Trade, order: Dict) -> float: """ Detect and update trade fee. - Calls trade.update_fee() uppon correct detection. + Calls trade.update_fee() upon correct detection. Returns modified amount if the fee was taken from the destination currency. Necessary for exchanges which charge fees in base currency (e.g. binance) :return: identical (or new) amount for the trade @@ -1406,8 +1441,8 @@ class FreqtradeBot(LoggingMixin): """ fee-detection fallback to Trades. Parses result of fetch_my_trades to get correct fee. """ - trades = self.exchange.get_trades_for_order(order['id'], trade.pair, - trade.open_date) + trades = self.exchange.get_trades_for_order(self.exchange.get_order_id_conditional(order), + trade.pair, trade.open_date) if len(trades) == 0: logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade) diff --git a/freqtrade/misc.py b/freqtrade/misc.py index 7bbc24056..2e255901e 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -6,7 +6,7 @@ import logging import re from datetime import datetime from pathlib import Path -from typing import Any +from typing import Any, Iterator, List from typing.io import IO import rapidjson @@ -81,7 +81,7 @@ def json_load(datafile: IO) -> Any: """ load data with rapidjson Use this to have a consistent experience, - sete number_mode to "NM_NATIVE" for greatest speed + set number_mode to "NM_NATIVE" for greatest speed """ return rapidjson.load(datafile, number_mode=rapidjson.NM_NATIVE) @@ -202,3 +202,14 @@ def render_template_with_fallback(templatefile: str, templatefallbackfile: str, return render_template(templatefile, arguments) except TemplateNotFound: return render_template(templatefallbackfile, arguments) + + +def chunks(lst: List[Any], n: int) -> Iterator[List[Any]]: + """ + Split lst into chunks of the size n. + :param lst: list to split into chunks + :param n: number of max elements per chunk + :return: None + """ + for chunk in range(0, len(lst), n): + yield (lst[chunk:chunk + n]) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 765e2844a..cbc0995aa 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -15,7 +15,7 @@ from freqtrade.configuration import TimeRange, remove_credentials, validate_conf from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.data import history from freqtrade.data.btanalysis import trade_list_to_dataframe -from freqtrade.data.converter import trim_dataframe +from freqtrade.data.converter import trim_dataframes from freqtrade.data.dataprovider import DataProvider from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds @@ -63,9 +63,7 @@ class Backtesting: self.all_results: Dict[str, Dict] = {} self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config) - - dataprovider = DataProvider(self.config, self.exchange) - IStrategy.dp = dataprovider + self.dataprovider = DataProvider(self.config, None) if self.config.get('strategy_list', None): for strat in list(self.config['strategy_list']): @@ -96,7 +94,7 @@ class Backtesting: "PrecisionFilter not allowed for backtesting multiple strategies." ) - dataprovider.add_pairlisthandler(self.pairlists) + self.dataprovider.add_pairlisthandler(self.pairlists) self.pairlists.refresh_pairlist() if len(self.pairlists.whitelist) == 0: @@ -112,15 +110,11 @@ class Backtesting: PairLocks.timeframe = self.config['timeframe'] PairLocks.use_db = False PairLocks.reset_locks() - if self.config.get('enable_protections', False): - self.protections = ProtectionManager(self.config) self.wallets = Wallets(self.config, self.exchange, log=False) # Get maximum required startup period self.required_startup = max([strat.startup_candle_count for strat in self.strategylist]) - # Load one (first) strategy - self._set_strategy(self.strategylist[0]) def __del__(self): LoggingMixin.show_output = True @@ -132,10 +126,17 @@ class Backtesting: Load strategy into backtesting """ self.strategy: IStrategy = strategy + strategy.dp = self.dataprovider # Set stoploss_on_exchange to false for backtesting, # since a "perfect" stoploss-sell is assumed anyway # And the regular "stoploss" function would not apply to that case self.strategy.order_types['stoploss_on_exchange'] = False + if self.config.get('enable_protections', False): + conf = self.config + if hasattr(strategy, 'protections'): + conf = deepcopy(conf) + conf['protections'] = strategy.protections + self.protections = ProtectionManager(conf) def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]: """ @@ -159,7 +160,7 @@ class Backtesting: logger.info(f'Loading data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'({(max_date - min_date).days} days)..') + f'({(max_date - min_date).days} days).') # Adjust startts forward if not enough data is available timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe), @@ -176,6 +177,8 @@ class Backtesting: Trade.use_db = False PairLocks.reset_locks() Trade.reset_trades() + self.rejected_trades = 0 + self.dataprovider.clear_cache() def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]: """ @@ -189,8 +192,9 @@ class Backtesting: data: Dict = {} # Create dict with data for pair, pair_data in processed.items(): - pair_data.loc[:, 'buy'] = 0 # cleanup from previous run - pair_data.loc[:, 'sell'] = 0 # cleanup from previous run + if not pair_data.empty: + pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist + pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist df_analyzed = self.strategy.advise_sell( self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy() @@ -214,6 +218,12 @@ class Backtesting: """ # Special handling if high or low hit STOP_LOSS or ROI if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS): + if trade.stop_loss > sell_row[HIGH_IDX]: + # our stoploss was already higher than candle high, + # possibly due to a cancelled trade exit. + # sell at open price. + return sell_row[OPEN_IDX] + # Set close_rate to stoploss return trade.stop_loss elif sell.sell_type == (SellType.ROI): @@ -239,7 +249,7 @@ class Backtesting: # Use the maximum between close_rate and low as we # cannot sell outside of a candle. # Applies when a new ROI setting comes in place and the whole candle is above that. - return max(close_rate, sell_row[LOW_IDX]) + return min(max(close_rate, sell_row[LOW_IDX]), sell_row[HIGH_IDX]) else: # This should not be reached... @@ -250,12 +260,13 @@ class Backtesting: def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]: sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], # type: ignore - sell_row[DATE_IDX], sell_row[BUY_IDX], sell_row[SELL_IDX], + sell_row[DATE_IDX].to_pydatetime(), sell_row[BUY_IDX], + sell_row[SELL_IDX], low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX]) if sell.sell_flag: - trade.close_date = sell_row[DATE_IDX] - trade.sell_reason = sell.sell_type.value + trade.close_date = sell_row[DATE_IDX].to_pydatetime() + trade.sell_reason = sell.sell_reason trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60) closerate = self._get_close_rate(sell_row, trade, sell, trade_dur) @@ -265,7 +276,8 @@ class Backtesting: pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount, rate=closerate, time_in_force=time_in_force, - sell_reason=sell.sell_type.value): + sell_reason=sell.sell_reason, + current_time=sell_row[DATE_IDX].to_pydatetime()): return None trade.close(closerate, show_msg=False) @@ -273,11 +285,9 @@ class Backtesting: return None - def _enter_trade(self, pair: str, row: List, max_open_trades: int, - open_trade_count: int) -> Optional[LocalTrade]: + def _enter_trade(self, pair: str, row: List) -> Optional[LocalTrade]: try: - stake_amount = self.wallets.get_trade_stake_amount( - pair, max_open_trades - open_trade_count, None) + stake_amount = self.wallets.get_trade_stake_amount(pair, None) except DependencyException: return None min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) @@ -287,7 +297,7 @@ class Backtesting: # Confirm trade entry: if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)( pair=pair, order_type=order_type, amount=stake_amount, rate=row[OPEN_IDX], - time_in_force=time_in_force): + time_in_force=time_in_force, current_time=row[DATE_IDX].to_pydatetime()): return None if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount): @@ -295,7 +305,7 @@ class Backtesting: trade = LocalTrade( pair=pair, open_rate=row[OPEN_IDX], - open_date=row[DATE_IDX], + open_date=row[DATE_IDX].to_pydatetime(), stake_amount=stake_amount, amount=round(stake_amount / row[OPEN_IDX], 8), fee_open=self.fee, @@ -317,7 +327,7 @@ class Backtesting: for trade in open_trades[pair]: sell_row = data[pair][-1] - trade.close_date = sell_row[DATE_IDX] + trade.close_date = sell_row[DATE_IDX].to_pydatetime() trade.sell_reason = SellType.FORCE_SELL.value trade.close(sell_row[OPEN_IDX], show_msg=False) LocalTrade.close_bt_trade(trade) @@ -327,10 +337,18 @@ class Backtesting: trades.append(trade1) return trades + def trade_slot_available(self, max_open_trades: int, open_trade_count: int) -> bool: + # Always allow trades when max_open_trades is enabled. + if max_open_trades <= 0 or open_trade_count < max_open_trades: + return True + # Rejected trade + self.rejected_trades += 1 + return False + def backtest(self, processed: Dict, start_date: datetime, end_date: datetime, max_open_trades: int = 0, position_stacking: bool = False, - enable_protections: bool = False) -> DataFrame: + enable_protections: bool = False) -> Dict[str, Any]: """ Implement backtesting functionality @@ -349,12 +367,16 @@ class Backtesting: trades: List[LocalTrade] = [] self.prepare_backtest(enable_protections) + # Update dataprovider cache + for pair, dataframe in processed.items(): + self.dataprovider._set_cached_df(pair, self.timeframe, dataframe) + # Use dict of lists with data for performance # (looping lists is a lot faster than pandas DataFrames) data: Dict = self._get_ohlcv_as_lists(processed) # Indexes per pair, so some pairs are allowed to have a missing start. - indexes: Dict = {} + indexes: Dict = defaultdict(int) tmp = start_date + timedelta(minutes=self.timeframe_min) open_trades: Dict[str, List[LocalTrade]] = defaultdict(list) @@ -365,11 +387,9 @@ class Backtesting: open_trade_count_start = open_trade_count for i, pair in enumerate(data): - if pair not in indexes: - indexes[pair] = 0 - + row_index = indexes[pair] try: - row = data[pair][indexes[pair]] + row = data[pair][row_index] except IndexError: # missing Data for one pair at the end. # Warnings for this are shown during data loading @@ -378,17 +398,23 @@ class Backtesting: # Waits until the time-counter reaches the start of the data for this pair. if row[DATE_IDX] > tmp: continue - indexes[pair] += 1 + + row_index += 1 + self.dataprovider._set_dataframe_max_index(row_index) + indexes[pair] = row_index # without positionstacking, we can only have one open trade per pair. # max_open_trades must be respected # don't open on the last row - if ((position_stacking or len(open_trades[pair]) == 0) - and (max_open_trades <= 0 or open_trade_count_start < max_open_trades) - and tmp != end_date - and row[BUY_IDX] == 1 and row[SELL_IDX] != 1 - and not PairLocks.is_pair_locked(pair, row[DATE_IDX])): - trade = self._enter_trade(pair, row, max_open_trades, open_trade_count_start) + if ( + (position_stacking or len(open_trades[pair]) == 0) + and self.trade_slot_available(max_open_trades, open_trade_count_start) + and tmp != end_date + and row[BUY_IDX] == 1 + and row[SELL_IDX] != 1 + and not PairLocks.is_pair_locked(pair, row[DATE_IDX]) + ): + trade = self._enter_trade(pair, row) if trade: # TODO: hacky workaround to avoid opening > max_open_trades # This emulates previous behaviour - not sure if this is correct @@ -420,7 +446,14 @@ class Backtesting: trades += self.handle_left_open(open_trades, data=data) self.wallets.update() - return trade_list_to_dataframe(trades) + results = trade_list_to_dataframe(trades) + return { + 'results': results, + 'config': self.strategy.config, + 'locks': PairLocks.get_all_locks(), + 'rejected_signals': self.rejected_trades, + 'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']), + } def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any], timerange: TimeRange): logger.info("Running backtesting for Strategy %s", strat.get_strategy_name()) @@ -442,31 +475,32 @@ class Backtesting: preprocessed = self.strategy.ohlcvdata_to_dataframe(data) # Trim startup period from analyzed dataframe - for pair, df in preprocessed.items(): - preprocessed[pair] = trim_dataframe(df, timerange) - min_date, max_date = history.get_timerange(preprocessed) + preprocessed = trim_dataframes(preprocessed, timerange, self.required_startup) + if not preprocessed: + raise OperationalException( + "No data left after adjusting for startup candles.") + + min_date, max_date = history.get_timerange(preprocessed) logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'({(max_date - min_date).days} days)..') + f'({(max_date - min_date).days} days).') # Execute backtest and store results results = self.backtest( processed=preprocessed, - start_date=min_date.datetime, - end_date=max_date.datetime, + start_date=min_date, + end_date=max_date, max_open_trades=max_open_trades, position_stacking=self.config.get('position_stacking', False), enable_protections=self.config.get('enable_protections', False), ) backtest_end_time = datetime.now(timezone.utc) - self.all_results[self.strategy.get_strategy_name()] = { - 'results': results, - 'config': self.strategy.config, - 'locks': PairLocks.get_all_locks(), - 'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']), + results.update({ 'backtest_start_time': int(backtest_start_time.timestamp()), 'backtest_end_time': int(backtest_end_time.timestamp()), - } + }) + self.all_results[self.strategy.get_strategy_name()] = results + return min_date, max_date def start(self) -> None: @@ -477,6 +511,7 @@ class Backtesting: data: Dict[str, Any] = {} data, timerange = self.load_bt_data() + logger.info("Dataload complete. Calculating indicators") for strat in self.strategylist: min_date, max_date = self.backtest_one_strategy(strat, data, timerange) diff --git a/freqtrade/optimize/edge_cli.py b/freqtrade/optimize/edge_cli.py index a5f505bee..aab7def05 100644 --- a/freqtrade/optimize/edge_cli.py +++ b/freqtrade/optimize/edge_cli.py @@ -44,7 +44,7 @@ class EdgeCli: 'timerange') is None else str(self.config.get('timerange'))) def start(self) -> None: - result = self.edge.calculate() + result = self.edge.calculate(self.config['exchange']['pair_whitelist']) if result: print('') # blank line for readability print(generate_edge_table(self.edge._cached_pairs)) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index 03f34a511..cf5559a24 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -4,33 +4,33 @@ This module contains the hyperopt logic """ -import locale import logging import random import warnings -from datetime import datetime +from datetime import datetime, timezone from math import ceil -from operator import itemgetter from pathlib import Path from typing import Any, Dict, List, Optional import progressbar +import rapidjson from colorama import Fore, Style from colorama import init as colorama_init from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects from pandas import DataFrame from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN -from freqtrade.data.converter import trim_dataframe +from freqtrade.data.converter import trim_dataframes from freqtrade.data.history import get_timerange from freqtrade.misc import file_dump_json, plural from freqtrade.optimize.backtesting import Backtesting # Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules +from freqtrade.optimize.hyperopt_auto import HyperOptAuto from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401 from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401 from freqtrade.optimize.hyperopt_tools import HyperoptTools +from freqtrade.optimize.optimize_reports import generate_strategy_stats from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver -from freqtrade.strategy import IStrategy # Suppress scikit-learn FutureWarnings from skopt @@ -61,22 +61,33 @@ class Hyperopt: hyperopt = Hyperopt(config) hyperopt.start() """ + custom_hyperopt: IHyperOpt def __init__(self, config: Dict[str, Any]) -> None: + self.buy_space: List[Dimension] = [] + self.sell_space: List[Dimension] = [] + self.roi_space: List[Dimension] = [] + self.stoploss_space: List[Dimension] = [] + self.trailing_space: List[Dimension] = [] + self.dimensions: List[Dimension] = [] + self.config = config self.backtesting = Backtesting(self.config) - self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) - self.custom_hyperopt.__class__.strategy = self.backtesting.strategy + if not self.config.get('hyperopt'): + self.custom_hyperopt = HyperOptAuto(self.config) + else: + self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) + self.backtesting._set_strategy(self.backtesting.strategylist[0]) + self.custom_hyperopt.strategy = self.backtesting.strategy self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config) self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function time_now = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") strategy = str(self.config['strategy']) - self.results_file = (self.config['user_data_dir'] / - 'hyperopt_results' / - f'strategy_{strategy}_hyperopt_results_{time_now}.pickle') + self.results_file: Path = (self.config['user_data_dir'] / 'hyperopt_results' / + f'strategy_{strategy}_{time_now}.fthypt') self.data_pickle_file = (self.config['user_data_dir'] / 'hyperopt_results' / 'hyperopt_tickerdata.pkl') self.total_epochs = config.get('epochs', 0) @@ -86,9 +97,7 @@ class Hyperopt: self.clean_hyperopt() self.num_epochs_saved = 0 - - # Previous evaluations - self.epochs: List = [] + self.current_best_epoch: Optional[Dict[str, Any]] = None # Populate functions here (hasattr is slow so should not be run during "regular" operations) if hasattr(self.custom_hyperopt, 'populate_indicators'): @@ -109,7 +118,7 @@ class Hyperopt: self.max_open_trades = 0 self.position_stacking = self.config.get('position_stacking', False) - if self.has_space('sell'): + if HyperoptTools.has_space(self.config, 'sell'): # Make sure use_sell_signal is enabled if 'ask_strategy' not in self.config: self.config['ask_strategy'] = {} @@ -135,9 +144,7 @@ class Hyperopt: logger.info(f"Removing `{p}`.") p.unlink() - def _get_params_dict(self, raw_params: List[Any]) -> Dict: - - dimensions: List[Dimension] = self.dimensions + def _get_params_dict(self, dimensions: List[Dimension], raw_params: List[Any]) -> Dict: # Ensure the number of dimensions match # the number of parameters in the list. @@ -148,21 +155,24 @@ class Hyperopt: # and the values are taken from the list of parameters. return {d.name: v for d, v in zip(dimensions, raw_params)} - def _save_results(self) -> None: + def _save_result(self, epoch: Dict) -> None: """ Save hyperopt results to file + Store one line per epoch. + While not a valid json object - this allows appending easily. + :param epoch: result dictionary for this epoch. """ - num_epochs = len(self.epochs) - if num_epochs > self.num_epochs_saved: - logger.debug(f"Saving {num_epochs} {plural(num_epochs, 'epoch')}.") - dump(self.epochs, self.results_file) - self.num_epochs_saved = num_epochs - logger.debug(f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} " - f"saved to '{self.results_file}'.") - # Store hyperopt filename - latest_filename = Path.joinpath(self.results_file.parent, LAST_BT_RESULT_FN) - file_dump_json(latest_filename, {'latest_hyperopt': str(self.results_file.name)}, - log=False) + with self.results_file.open('a') as f: + rapidjson.dump(epoch, f, default=str, number_mode=rapidjson.NM_NATIVE) + f.write("\n") + + self.num_epochs_saved += 1 + logger.debug(f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} " + f"saved to '{self.results_file}'.") + # Store hyperopt filename + latest_filename = Path.joinpath(self.results_file.parent, LAST_BT_RESULT_FN) + file_dump_json(latest_filename, {'latest_hyperopt': str(self.results_file.name)}, + log=False) def _get_params_details(self, params: Dict) -> Dict: """ @@ -170,18 +180,16 @@ class Hyperopt: """ result: Dict = {} - if self.has_space('buy'): - result['buy'] = {p.name: params.get(p.name) - for p in self.hyperopt_space('buy')} - if self.has_space('sell'): - result['sell'] = {p.name: params.get(p.name) - for p in self.hyperopt_space('sell')} - if self.has_space('roi'): - result['roi'] = self.custom_hyperopt.generate_roi_table(params) - if self.has_space('stoploss'): - result['stoploss'] = {p.name: params.get(p.name) - for p in self.hyperopt_space('stoploss')} - if self.has_space('trailing'): + if HyperoptTools.has_space(self.config, 'buy'): + result['buy'] = {p.name: params.get(p.name) for p in self.buy_space} + if HyperoptTools.has_space(self.config, 'sell'): + result['sell'] = {p.name: params.get(p.name) for p in self.sell_space} + if HyperoptTools.has_space(self.config, 'roi'): + result['roi'] = {str(k): v for k, v in + self.custom_hyperopt.generate_roi_table(params).items()} + if HyperoptTools.has_space(self.config, 'stoploss'): + result['stoploss'] = {p.name: params.get(p.name) for p in self.stoploss_space} + if HyperoptTools.has_space(self.config, 'trailing'): result['trailing'] = self.custom_hyperopt.generate_trailing_params(params) return result @@ -203,71 +211,58 @@ class Hyperopt: ) self.hyperopt_table_header = 2 - def has_space(self, space: str) -> bool: + def init_spaces(self): """ - Tell if the space value is contained in the configuration + Assign the dimensions in the hyperoptimization space. """ - # The 'trailing' space is not included in the 'default' set of spaces - if space == 'trailing': - return any(s in self.config['spaces'] for s in [space, 'all']) - else: - return any(s in self.config['spaces'] for s in [space, 'all', 'default']) - def hyperopt_space(self, space: Optional[str] = None) -> List[Dimension]: - """ - Return the dimensions in the hyperoptimization space. - :param space: Defines hyperspace to return dimensions for. - If None, then the self.has_space() will be used to return dimensions - for all hyperspaces used. - """ - spaces: List[Dimension] = [] - - if space == 'buy' or (space is None and self.has_space('buy')): + if HyperoptTools.has_space(self.config, 'buy'): logger.debug("Hyperopt has 'buy' space") - spaces += self.custom_hyperopt.indicator_space() + self.buy_space = self.custom_hyperopt.indicator_space() - if space == 'sell' or (space is None and self.has_space('sell')): + if HyperoptTools.has_space(self.config, 'sell'): logger.debug("Hyperopt has 'sell' space") - spaces += self.custom_hyperopt.sell_indicator_space() + self.sell_space = self.custom_hyperopt.sell_indicator_space() - if space == 'roi' or (space is None and self.has_space('roi')): + if HyperoptTools.has_space(self.config, 'roi'): logger.debug("Hyperopt has 'roi' space") - spaces += self.custom_hyperopt.roi_space() + self.roi_space = self.custom_hyperopt.roi_space() - if space == 'stoploss' or (space is None and self.has_space('stoploss')): + if HyperoptTools.has_space(self.config, 'stoploss'): logger.debug("Hyperopt has 'stoploss' space") - spaces += self.custom_hyperopt.stoploss_space() + self.stoploss_space = self.custom_hyperopt.stoploss_space() - if space == 'trailing' or (space is None and self.has_space('trailing')): + if HyperoptTools.has_space(self.config, 'trailing'): logger.debug("Hyperopt has 'trailing' space") - spaces += self.custom_hyperopt.trailing_space() - - return spaces + self.trailing_space = self.custom_hyperopt.trailing_space() + self.dimensions = (self.buy_space + self.sell_space + self.roi_space + + self.stoploss_space + self.trailing_space) def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict: """ Used Optimize function. Called once per epoch to optimize whatever is configured. Keep this function as optimized as possible! """ - params_dict = self._get_params_dict(raw_params) - params_details = self._get_params_details(params_dict) + backtest_start_time = datetime.now(timezone.utc) + params_dict = self._get_params_dict(self.dimensions, raw_params) - if self.has_space('roi'): + # Apply parameters + if HyperoptTools.has_space(self.config, 'roi'): self.backtesting.strategy.minimal_roi = ( # type: ignore self.custom_hyperopt.generate_roi_table(params_dict)) - if self.has_space('buy'): + if HyperoptTools.has_space(self.config, 'buy'): self.backtesting.strategy.advise_buy = ( # type: ignore self.custom_hyperopt.buy_strategy_generator(params_dict)) - if self.has_space('sell'): + if HyperoptTools.has_space(self.config, 'sell'): self.backtesting.strategy.advise_sell = ( # type: ignore self.custom_hyperopt.sell_strategy_generator(params_dict)) - if self.has_space('stoploss'): + if HyperoptTools.has_space(self.config, 'stoploss'): self.backtesting.strategy.stoploss = params_dict['stoploss'] - if self.has_space('trailing'): + if HyperoptTools.has_space(self.config, 'trailing'): d = self.custom_hyperopt.generate_trailing_params(params_dict) self.backtesting.strategy.trailing_stop = d['trailing_stop'] self.backtesting.strategy.trailing_stop_positive = d['trailing_stop_positive'] @@ -276,30 +271,42 @@ class Hyperopt: self.backtesting.strategy.trailing_only_offset_is_reached = \ d['trailing_only_offset_is_reached'] - processed = load(self.data_pickle_file) - - min_date, max_date = get_timerange(processed) - - backtesting_results = self.backtesting.backtest( + with self.data_pickle_file.open('rb') as f: + processed = load(f, mmap_mode='r') + bt_results = self.backtesting.backtest( processed=processed, - start_date=min_date.datetime, - end_date=max_date.datetime, + start_date=self.min_date, + end_date=self.max_date, max_open_trades=self.max_open_trades, position_stacking=self.position_stacking, enable_protections=self.config.get('enable_protections', False), - ) - return self._get_results_dict(backtesting_results, min_date, max_date, - params_dict, params_details, + backtest_end_time = datetime.now(timezone.utc) + bt_results.update({ + 'backtest_start_time': int(backtest_start_time.timestamp()), + 'backtest_end_time': int(backtest_end_time.timestamp()), + }) + + return self._get_results_dict(bt_results, self.min_date, self.max_date, + params_dict, processed=processed) def _get_results_dict(self, backtesting_results, min_date, max_date, - params_dict, params_details, processed: Dict[str, DataFrame]): - results_metrics = self._calculate_results_metrics(backtesting_results) - results_explanation = self._format_results_explanation_string(results_metrics) + params_dict, processed: Dict[str, DataFrame] + ) -> Dict[str, Any]: + params_details = self._get_params_details(params_dict) - trade_count = results_metrics['trade_count'] - total_profit = results_metrics['total_profit'] + strat_stats = generate_strategy_stats( + processed, self.backtesting.strategy.get_strategy_name(), + backtesting_results, min_date, max_date, market_change=0 + ) + results_explanation = HyperoptTools.format_results_explanation_string( + strat_stats, self.config['stake_currency']) + + not_optimized = self.backtesting.strategy.get_params_dict() + + trade_count = strat_stats['total_trades'] + total_profit = strat_stats['profit_total'] # If this evaluation contains too short amount of trades to be # interesting -- consider it as 'bad' (assigned max. loss value) @@ -307,50 +314,20 @@ class Hyperopt: # path. We do not want to optimize 'hodl' strategies. loss: float = MAX_LOSS if trade_count >= self.config['hyperopt_min_trades']: - loss = self.calculate_loss(results=backtesting_results, trade_count=trade_count, - min_date=min_date.datetime, max_date=max_date.datetime, + loss = self.calculate_loss(results=backtesting_results['results'], + trade_count=trade_count, + min_date=min_date, max_date=max_date, config=self.config, processed=processed) return { 'loss': loss, 'params_dict': params_dict, 'params_details': params_details, - 'results_metrics': results_metrics, + 'params_not_optimized': not_optimized, + 'results_metrics': strat_stats, 'results_explanation': results_explanation, 'total_profit': total_profit, } - def _calculate_results_metrics(self, backtesting_results: DataFrame) -> Dict: - wins = len(backtesting_results[backtesting_results['profit_ratio'] > 0]) - draws = len(backtesting_results[backtesting_results['profit_ratio'] == 0]) - losses = len(backtesting_results[backtesting_results['profit_ratio'] < 0]) - return { - 'trade_count': len(backtesting_results.index), - 'wins': wins, - 'draws': draws, - 'losses': losses, - 'winsdrawslosses': f"{wins:>4} {draws:>4} {losses:>4}", - 'avg_profit': backtesting_results['profit_ratio'].mean() * 100.0, - 'median_profit': backtesting_results['profit_ratio'].median() * 100.0, - 'total_profit': backtesting_results['profit_abs'].sum(), - 'profit': backtesting_results['profit_ratio'].sum() * 100.0, - 'duration': backtesting_results['trade_duration'].mean(), - } - - def _format_results_explanation_string(self, results_metrics: Dict) -> str: - """ - Return the formatted results explanation in a string - """ - stake_cur = self.config['stake_currency'] - return (f"{results_metrics['trade_count']:6d} trades. " - f"{results_metrics['wins']}/{results_metrics['draws']}" - f"/{results_metrics['losses']} Wins/Draws/Losses. " - f"Avg profit {results_metrics['avg_profit']: 6.2f}%. " - f"Median profit {results_metrics['median_profit']: 6.2f}%. " - f"Total profit {results_metrics['total_profit']: 11.8f} {stake_cur} " - f"({results_metrics['profit']: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). " - f"Avg duration {results_metrics['duration']:5.1f} min." - ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8') - def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer: return Optimizer( dimensions, @@ -369,24 +346,31 @@ class Hyperopt: def _set_random_state(self, random_state: Optional[int]) -> int: return random_state or random.randint(1, 2**16 - 1) - def start(self) -> None: - self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None)) - logger.info(f"Using optimizer random state: {self.random_state}") - self.hyperopt_table_header = -1 + def prepare_hyperopt_data(self) -> None: data, timerange = self.backtesting.load_bt_data() + logger.info("Dataload complete. Calculating indicators") preprocessed = self.backtesting.strategy.ohlcvdata_to_dataframe(data) # Trim startup period from analyzed dataframe - for pair, df in preprocessed.items(): - preprocessed[pair] = trim_dataframe(df, timerange) - min_date, max_date = get_timerange(preprocessed) + processed = trim_dataframes(preprocessed, timerange, self.backtesting.required_startup) - logger.info(f'Hyperopting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} ' - f'({(max_date - min_date).days} days)..') + self.min_date, self.max_date = get_timerange(processed) - dump(preprocessed, self.data_pickle_file) + logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} ' + f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} ' + f'({(self.max_date - self.min_date).days} days)..') + + dump(processed, self.data_pickle_file) + + def start(self) -> None: + self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None)) + logger.info(f"Using optimizer random state: {self.random_state}") + self.hyperopt_table_header = -1 + # Initialize spaces ... + self.init_spaces() + + self.prepare_hyperopt_data() # We don't need exchange instance anymore while running hyperopt self.backtesting.exchange.close() @@ -394,15 +378,12 @@ class Hyperopt: self.backtesting.exchange._api_async = None # type: ignore # self.backtesting.exchange = None # type: ignore self.backtesting.pairlists = None # type: ignore - self.backtesting.strategy.dp = None # type: ignore - IStrategy.dp = None # type: ignore cpus = cpu_count() logger.info(f"Found {cpus} CPU cores. Let's make them scream!") config_jobs = self.config.get('hyperopt_jobs', -1) logger.info(f'Number of parallel jobs set as: {config_jobs}') - self.dimensions: List[Dimension] = self.hyperopt_space() self.opt = self.get_optimizer(self.dimensions, config_jobs) if self.print_colorized: @@ -468,25 +449,21 @@ class Hyperopt: if is_best: self.current_best_loss = val['loss'] - self.epochs.append(val) + self.current_best_epoch = val - # Save results after each best epoch and every 100 epochs - if is_best or current % 100 == 0: - self._save_results() + self._save_result(val) pbar.update(current) except KeyboardInterrupt: print('User interrupted..') - self._save_results() logger.info(f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} " f"saved to '{self.results_file}'.") - if self.epochs: - sorted_epochs = sorted(self.epochs, key=itemgetter('loss')) - best_epoch = sorted_epochs[0] - HyperoptTools.print_epoch_details(best_epoch, self.total_epochs, self.print_json) + if self.current_best_epoch: + HyperoptTools.print_epoch_details(self.current_best_epoch, self.total_epochs, + self.print_json) else: # This is printed when Ctrl+C is pressed quickly, before first epochs have # a chance to be evaluated. diff --git a/freqtrade/optimize/hyperopt_auto.py b/freqtrade/optimize/hyperopt_auto.py new file mode 100644 index 000000000..f86204406 --- /dev/null +++ b/freqtrade/optimize/hyperopt_auto.py @@ -0,0 +1,89 @@ +""" +HyperOptAuto class. +This module implements a convenience auto-hyperopt class, which can be used together with strategies + that implement IHyperStrategy interface. +""" +from contextlib import suppress +from typing import Any, Callable, Dict, List + +from pandas import DataFrame + + +with suppress(ImportError): + from skopt.space import Dimension + +from freqtrade.optimize.hyperopt_interface import IHyperOpt + + +class HyperOptAuto(IHyperOpt): + """ + This class delegates functionality to Strategy(IHyperStrategy) and Strategy.HyperOpt classes. + Most of the time Strategy.HyperOpt class would only implement indicator_space and + sell_indicator_space methods, but other hyperopt methods can be overridden as well. + """ + + def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable: + def populate_buy_trend(dataframe: DataFrame, metadata: dict): + for attr_name, attr in self.strategy.enumerate_parameters('buy'): + if attr.optimize: + # noinspection PyProtectedMember + attr.value = params[attr_name] + return self.strategy.populate_buy_trend(dataframe, metadata) + + return populate_buy_trend + + def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable: + def populate_sell_trend(dataframe: DataFrame, metadata: dict): + for attr_name, attr in self.strategy.enumerate_parameters('sell'): + if attr.optimize: + # noinspection PyProtectedMember + attr.value = params[attr_name] + return self.strategy.populate_sell_trend(dataframe, metadata) + + return populate_sell_trend + + def _get_func(self, name) -> Callable: + """ + Return a function defined in Strategy.HyperOpt class, or one defined in super() class. + :param name: function name. + :return: a requested function. + """ + hyperopt_cls = getattr(self.strategy, 'HyperOpt', None) + default_func = getattr(super(), name) + if hyperopt_cls: + return getattr(hyperopt_cls, name, default_func) + else: + return default_func + + def _generate_indicator_space(self, category): + for attr_name, attr in self.strategy.enumerate_parameters(category): + if attr.optimize: + yield attr.get_space(attr_name) + + def _get_indicator_space(self, category, fallback_method_name): + indicator_space = list(self._generate_indicator_space(category)) + if len(indicator_space) > 0: + return indicator_space + else: + return self._get_func(fallback_method_name)() + + def indicator_space(self) -> List['Dimension']: + return self._get_indicator_space('buy', 'indicator_space') + + def sell_indicator_space(self) -> List['Dimension']: + return self._get_indicator_space('sell', 'sell_indicator_space') + + def generate_roi_table(self, params: Dict) -> Dict[int, float]: + return self._get_func('generate_roi_table')(params) + + def roi_space(self) -> List['Dimension']: + return self._get_func('roi_space')() + + def stoploss_space(self) -> List['Dimension']: + return self._get_func('stoploss_space')() + + def generate_trailing_params(self, params: Dict) -> Dict: + return self._get_func('generate_trailing_params')(params) + + def trailing_space(self) -> List['Dimension']: + return self._get_func('trailing_space')() diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py index 561fb8e11..889854cad 100644 --- a/freqtrade/optimize/hyperopt_interface.py +++ b/freqtrade/optimize/hyperopt_interface.py @@ -7,11 +7,12 @@ import math from abc import ABC from typing import Any, Callable, Dict, List -from skopt.space import Categorical, Dimension, Integer, Real +from skopt.space import Categorical, Dimension, Integer from freqtrade.exceptions import OperationalException from freqtrade.exchange import timeframe_to_minutes from freqtrade.misc import round_dict +from freqtrade.optimize.space import SKDecimal from freqtrade.strategy import IStrategy @@ -31,7 +32,7 @@ class IHyperOpt(ABC): Defines the mandatory structure must follow any custom hyperopt Class attributes you can use: - ticker_interval -> int: value of the ticker interval to use for the strategy + timeframe -> int: value of the timeframe to use for the strategy """ ticker_interval: str # DEPRECATED timeframe: str @@ -44,36 +45,31 @@ class IHyperOpt(ABC): IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED IHyperOpt.timeframe = str(config['timeframe']) - @staticmethod - def buy_strategy_generator(params: Dict[str, Any]) -> Callable: + def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable: """ Create a buy strategy generator. """ raise OperationalException(_format_exception_message('buy_strategy_generator', 'buy')) - @staticmethod - def sell_strategy_generator(params: Dict[str, Any]) -> Callable: + def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable: """ Create a sell strategy generator. """ raise OperationalException(_format_exception_message('sell_strategy_generator', 'sell')) - @staticmethod - def indicator_space() -> List[Dimension]: + def indicator_space(self) -> List[Dimension]: """ Create an indicator space. """ raise OperationalException(_format_exception_message('indicator_space', 'buy')) - @staticmethod - def sell_indicator_space() -> List[Dimension]: + def sell_indicator_space(self) -> List[Dimension]: """ Create a sell indicator space. """ raise OperationalException(_format_exception_message('sell_indicator_space', 'sell')) - @staticmethod - def generate_roi_table(params: Dict) -> Dict[int, float]: + def generate_roi_table(self, params: Dict) -> Dict[int, float]: """ Create a ROI table. @@ -88,8 +84,7 @@ class IHyperOpt(ABC): return roi_table - @staticmethod - def roi_space() -> List[Dimension]: + def roi_space(self) -> List[Dimension]: """ Create a ROI space. @@ -97,7 +92,7 @@ class IHyperOpt(ABC): This method implements adaptive roi hyperspace with varied ranges for parameters which automatically adapts to the - ticker interval used. + timeframe used. It's used by Freqtrade by default, if no custom roi_space method is defined. """ @@ -109,7 +104,7 @@ class IHyperOpt(ABC): roi_t_alpha = 1.0 roi_p_alpha = 1.0 - timeframe_min = timeframe_to_minutes(IHyperOpt.ticker_interval) + timeframe_min = timeframe_to_minutes(self.timeframe) # We define here limits for the ROI space parameters automagically adapted to the # timeframe used by the bot: @@ -119,7 +114,7 @@ class IHyperOpt(ABC): # * 'roi_p' (limits for the ROI value steps) components are scaled logarithmically. # # The scaling is designed so that it maps exactly to the legacy Freqtrade roi_space() - # method for the 5m ticker interval. + # method for the 5m timeframe. roi_t_scale = timeframe_min / 5 roi_p_scale = math.log1p(timeframe_min) / math.log1p(5) roi_limits = { @@ -145,7 +140,7 @@ class IHyperOpt(ABC): 'roi_p2': roi_limits['roi_p2_min'], 'roi_p3': roi_limits['roi_p3_min'], } - logger.info(f"Min roi table: {round_dict(IHyperOpt.generate_roi_table(p), 5)}") + logger.info(f"Min roi table: {round_dict(self.generate_roi_table(p), 3)}") p = { 'roi_t1': roi_limits['roi_t1_max'], 'roi_t2': roi_limits['roi_t2_max'], @@ -154,19 +149,21 @@ class IHyperOpt(ABC): 'roi_p2': roi_limits['roi_p2_max'], 'roi_p3': roi_limits['roi_p3_max'], } - logger.info(f"Max roi table: {round_dict(IHyperOpt.generate_roi_table(p), 5)}") + logger.info(f"Max roi table: {round_dict(self.generate_roi_table(p), 3)}") return [ Integer(roi_limits['roi_t1_min'], roi_limits['roi_t1_max'], name='roi_t1'), Integer(roi_limits['roi_t2_min'], roi_limits['roi_t2_max'], name='roi_t2'), Integer(roi_limits['roi_t3_min'], roi_limits['roi_t3_max'], name='roi_t3'), - Real(roi_limits['roi_p1_min'], roi_limits['roi_p1_max'], name='roi_p1'), - Real(roi_limits['roi_p2_min'], roi_limits['roi_p2_max'], name='roi_p2'), - Real(roi_limits['roi_p3_min'], roi_limits['roi_p3_max'], name='roi_p3'), + SKDecimal(roi_limits['roi_p1_min'], roi_limits['roi_p1_max'], decimals=3, + name='roi_p1'), + SKDecimal(roi_limits['roi_p2_min'], roi_limits['roi_p2_max'], decimals=3, + name='roi_p2'), + SKDecimal(roi_limits['roi_p3_min'], roi_limits['roi_p3_max'], decimals=3, + name='roi_p3'), ] - @staticmethod - def stoploss_space() -> List[Dimension]: + def stoploss_space(self) -> List[Dimension]: """ Create a stoploss space. @@ -174,11 +171,10 @@ class IHyperOpt(ABC): You may override it in your custom Hyperopt class. """ return [ - Real(-0.35, -0.02, name='stoploss'), + SKDecimal(-0.35, -0.02, decimals=3, name='stoploss'), ] - @staticmethod - def generate_trailing_params(params: Dict) -> Dict: + def generate_trailing_params(self, params: Dict) -> Dict: """ Create dict with trailing stop parameters. """ @@ -190,8 +186,7 @@ class IHyperOpt(ABC): 'trailing_only_offset_is_reached': params['trailing_only_offset_is_reached'], } - @staticmethod - def trailing_space() -> List[Dimension]: + def trailing_space(self) -> List[Dimension]: """ Create a trailing stoploss space. @@ -206,14 +201,14 @@ class IHyperOpt(ABC): # other 'trailing' hyperspace parameters. Categorical([True], name='trailing_stop'), - Real(0.01, 0.35, name='trailing_stop_positive'), + SKDecimal(0.01, 0.35, decimals=3, name='trailing_stop_positive'), # 'trailing_stop_positive_offset' should be greater than 'trailing_stop_positive', # so this intermediate parameter is used as the value of the difference between # them. The value of the 'trailing_stop_positive_offset' is constructed in the # generate_trailing_params() method. # This is similar to the hyperspace dimensions used for constructing the ROI tables. - Real(0.001, 0.1, name='trailing_stop_positive_offset_p1'), + SKDecimal(0.001, 0.1, decimals=3, name='trailing_stop_positive_offset_p1'), Categorical([True, False], name='trailing_only_offset_is_reached'), ] diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py index d4c347f80..49e70913f 100644 --- a/freqtrade/optimize/hyperopt_tools.py +++ b/freqtrade/optimize/hyperopt_tools.py @@ -1,19 +1,18 @@ import io +import locale import logging from collections import OrderedDict from pathlib import Path -from pprint import pformat -from typing import Dict, List +from typing import Any, Dict, List import rapidjson import tabulate from colorama import Fore, Style -from joblib import load from pandas import isna, json_normalize from freqtrade.exceptions import OperationalException -from freqtrade.misc import round_dict +from freqtrade.misc import round_coin_value, round_dict logger = logging.getLogger(__name__) @@ -21,13 +20,38 @@ logger = logging.getLogger(__name__) class HyperoptTools(): + @staticmethod + def has_space(config: Dict[str, Any], space: str) -> bool: + """ + Tell if the space value is contained in the configuration + """ + # The 'trailing' space is not included in the 'default' set of spaces + if space == 'trailing': + return any(s in config['spaces'] for s in [space, 'all']) + else: + return any(s in config['spaces'] for s in [space, 'all', 'default']) + + @staticmethod + def _read_results_pickle(results_file: Path) -> List: + """ + Read hyperopt results from pickle file + LEGACY method - new files are written as json and cannot be read with this method. + """ + from joblib import load + + logger.info(f"Reading pickled epochs from '{results_file}'") + data = load(results_file) + return data + @staticmethod def _read_results(results_file: Path) -> List: """ Read hyperopt results from file """ - logger.info("Reading epochs from '%s'", results_file) - data = load(results_file) + import rapidjson + logger.info(f"Reading epochs from '{results_file}'") + with results_file.open('r') as f: + data = [rapidjson.loads(line) for line in f] return data @staticmethod @@ -37,7 +61,10 @@ class HyperoptTools(): """ epochs: List = [] if results_file.is_file() and results_file.stat().st_size > 0: - epochs = HyperoptTools._read_results(results_file) + if results_file.suffix == '.pickle': + epochs = HyperoptTools._read_results_pickle(results_file) + else: + epochs = HyperoptTools._read_results(results_file) # Detection of some old format, without 'is_best' field saved if epochs[0].get('is_best') is None: raise OperationalException( @@ -53,6 +80,7 @@ class HyperoptTools(): Display details of the hyperopt result """ params = results.get('params_details', {}) + non_optimized = results.get('params_not_optimized', {}) # Default header string if header_str is None: @@ -69,8 +97,10 @@ class HyperoptTools(): print(rapidjson.dumps(result_dict, default=str, number_mode=rapidjson.NM_NATIVE)) else: - HyperoptTools._params_pretty_print(params, 'buy', "Buy hyperspace params:") - HyperoptTools._params_pretty_print(params, 'sell', "Sell hyperspace params:") + HyperoptTools._params_pretty_print(params, 'buy', "Buy hyperspace params:", + non_optimized) + HyperoptTools._params_pretty_print(params, 'sell', "Sell hyperspace params:", + non_optimized) HyperoptTools._params_pretty_print(params, 'roi', "ROI table:") HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:") HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:") @@ -96,12 +126,12 @@ class HyperoptTools(): result_dict.update(space_params) @staticmethod - def _params_pretty_print(params, space: str, header: str) -> None: - if space in params: + def _params_pretty_print(params, space: str, header: str, non_optimized={}) -> None: + if space in params or space in non_optimized: space_params = HyperoptTools._space_params(params, space, 5) - params_result = f"\n# {header}\n" + result = f"\n# {header}\n" if space == 'stoploss': - params_result += f"stoploss = {space_params.get('stoploss')}" + result += f"stoploss = {space_params.get('stoploss')}" elif space == 'roi': # TODO: get rid of OrderedDict when support for python 3.6 will be # dropped (dicts keep the order as the language feature) @@ -110,28 +140,64 @@ class HyperoptTools(): (str(k), v) for k, v in space_params.items() ), default=str, indent=4, number_mode=rapidjson.NM_NATIVE) - params_result += f"minimal_roi = {minimal_roi_result}" + result += f"minimal_roi = {minimal_roi_result}" elif space == 'trailing': for k, v in space_params.items(): - params_result += f'{k} = {v}\n' + result += f'{k} = {v}\n' else: - params_result += f"{space}_params = {pformat(space_params, indent=4)}" - params_result = params_result.replace("}", "\n}").replace("{", "{\n ") + no_params = HyperoptTools._space_params(non_optimized, space, 5) - params_result = params_result.replace("\n", "\n ") - print(params_result) + result += f"{space}_params = {HyperoptTools._pprint(space_params, no_params)}" + + result = result.replace("\n", "\n ") + print(result) @staticmethod def _space_params(params, space: str, r: int = None) -> Dict: - d = params[space] - # Round floats to `r` digits after the decimal point if requested - return round_dict(d, r) if r else d + d = params.get(space) + if d: + # Round floats to `r` digits after the decimal point if requested + return round_dict(d, r) if r else d + return {} + + @staticmethod + def _pprint(params, non_optimized, indent: int = 4): + """ + Pretty-print hyperopt results (based on 2 dicts - with add. comment) + """ + p = params.copy() + p.update(non_optimized) + result = '{\n' + + for k, param in p.items(): + result += " " * indent + f'"{k}": ' + result += f'"{param}",' if isinstance(param, str) else f'{param},' + if k in non_optimized: + result += " # value loaded from strategy" + result += "\n" + result += '}' + return result @staticmethod def is_best_loss(results, current_best_loss: float) -> bool: - return results['loss'] < current_best_loss + return bool(results['loss'] < current_best_loss) + + @staticmethod + def format_results_explanation_string(results_metrics: Dict, stake_currency: str) -> str: + """ + Return the formatted results explanation in a string + """ + return (f"{results_metrics['total_trades']:6d} trades. " + f"{results_metrics['wins']}/{results_metrics['draws']}" + f"/{results_metrics['losses']} Wins/Draws/Losses. " + f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. " + f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. " + f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} " + f"({results_metrics['profit_total'] * 100: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). " + f"Avg duration {results_metrics['holding_avg']} min." + ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8') @staticmethod def _format_explanation_string(results, total_epochs) -> str: @@ -156,12 +222,27 @@ class HyperoptTools(): if 'results_metrics.winsdrawslosses' not in trials.columns: # Ensure compatibility with older versions of hyperopt results trials['results_metrics.winsdrawslosses'] = 'N/A' + legacy_mode = True + + if 'results_metrics.total_trades' in trials: + legacy_mode = False + # New mode, using backtest result for metrics + trials['results_metrics.winsdrawslosses'] = trials.apply( + lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} " + f"{x['results_metrics.losses']:>4}", axis=1) + trials = trials[['Best', 'current_epoch', 'results_metrics.total_trades', + 'results_metrics.winsdrawslosses', + 'results_metrics.profit_mean', 'results_metrics.profit_total_abs', + 'results_metrics.profit_total', 'results_metrics.holding_avg', + 'loss', 'is_initial_point', 'is_best']] + else: + # Legacy mode + trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count', + 'results_metrics.winsdrawslosses', + 'results_metrics.avg_profit', 'results_metrics.total_profit', + 'results_metrics.profit', 'results_metrics.duration', + 'loss', 'is_initial_point', 'is_best']] - trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count', - 'results_metrics.winsdrawslosses', - 'results_metrics.avg_profit', 'results_metrics.total_profit', - 'results_metrics.profit', 'results_metrics.duration', - 'loss', 'is_initial_point', 'is_best']] trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit', 'Total profit', 'Profit', 'Avg duration', 'Objective', 'is_initial_point', 'is_best'] @@ -171,26 +252,28 @@ class HyperoptTools(): trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best' trials.loc[trials['Total profit'] > 0, 'is_profit'] = True trials['Trades'] = trials['Trades'].astype(str) - + perc_multi = 1 if legacy_mode else 100 trials['Epoch'] = trials['Epoch'].apply( lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs) ) trials['Avg profit'] = trials['Avg profit'].apply( - lambda x: '{:,.2f}%'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ') + lambda x: f'{x * perc_multi:,.2f}%'.rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ') ) trials['Avg duration'] = trials['Avg duration'].apply( - lambda x: '{:,.1f} m'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ') + lambda x: f'{x:,.1f} m'.rjust(7, ' ') if isinstance(x, float) else f"{x}" + if not isna(x) else "--".rjust(7, ' ') ) trials['Objective'] = trials['Objective'].apply( - lambda x: '{:,.5f}'.format(x).rjust(8, ' ') if x != 100000 else "N/A".rjust(8, ' ') + lambda x: f'{x:,.5f}'.rjust(8, ' ') if x != 100000 else "N/A".rjust(8, ' ') ) + stake_currency = config['stake_currency'] trials['Profit'] = trials.apply( - lambda x: '{:,.8f} {} {}'.format( - x['Total profit'], config['stake_currency'], - '({:,.2f}%)'.format(x['Profit']).rjust(10, ' ') - ).rjust(25+len(config['stake_currency'])) - if x['Total profit'] != 0.0 else '--'.rjust(25+len(config['stake_currency'])), + lambda x: '{} {}'.format( + round_coin_value(x['Total profit'], stake_currency), + '({:,.2f}%)'.format(x['Profit'] * perc_multi).rjust(10, ' ') + ).rjust(25+len(stake_currency)) + if x['Total profit'] != 0.0 else '--'.rjust(25+len(stake_currency)), axis=1 ) trials = trials.drop(columns=['Total profit']) @@ -251,11 +334,21 @@ class HyperoptTools(): trials['Best'] = '' trials['Stake currency'] = config['stake_currency'] - base_metrics = ['Best', 'current_epoch', 'results_metrics.trade_count', - 'results_metrics.avg_profit', 'results_metrics.median_profit', - 'results_metrics.total_profit', - 'Stake currency', 'results_metrics.profit', 'results_metrics.duration', - 'loss', 'is_initial_point', 'is_best'] + if 'results_metrics.total_trades' in trials: + base_metrics = ['Best', 'current_epoch', 'results_metrics.total_trades', + 'results_metrics.profit_mean', 'results_metrics.profit_median', + 'results_metrics.profit_total', + 'Stake currency', + 'results_metrics.profit_total_abs', 'results_metrics.holding_avg', + 'loss', 'is_initial_point', 'is_best'] + perc_multi = 100 + else: + perc_multi = 1 + base_metrics = ['Best', 'current_epoch', 'results_metrics.trade_count', + 'results_metrics.avg_profit', 'results_metrics.median_profit', + 'results_metrics.total_profit', + 'Stake currency', 'results_metrics.profit', 'results_metrics.duration', + 'loss', 'is_initial_point', 'is_best'] param_metrics = [("params_dict."+param) for param in results[0]['params_dict'].keys()] trials = trials[base_metrics + param_metrics] @@ -272,21 +365,23 @@ class HyperoptTools(): trials.loc[trials['Total profit'] > 0, 'is_profit'] = True trials['Epoch'] = trials['Epoch'].astype(str) trials['Trades'] = trials['Trades'].astype(str) + trials['Median profit'] = trials['Median profit'] * perc_multi trials['Total profit'] = trials['Total profit'].apply( - lambda x: '{:,.8f}'.format(x) if x != 0.0 else "" + lambda x: f'{x:,.8f}' if x != 0.0 else "" ) trials['Profit'] = trials['Profit'].apply( - lambda x: '{:,.2f}'.format(x) if not isna(x) else "" + lambda x: f'{x:,.2f}' if not isna(x) else "" ) trials['Avg profit'] = trials['Avg profit'].apply( - lambda x: '{:,.2f}%'.format(x) if not isna(x) else "" + lambda x: f'{x * perc_multi:,.2f}%' if not isna(x) else "" ) trials['Avg duration'] = trials['Avg duration'].apply( - lambda x: '{:,.1f} m'.format(x) if not isna(x) else "" + lambda x: f'{x:,.1f} m' if isinstance( + x, float) else f"{x.total_seconds() // 60:,.1f} m" if not isna(x) else "" ) trials['Objective'] = trials['Objective'].apply( - lambda x: '{:,.5f}'.format(x) if x != 100000 else "" + lambda x: f'{x:,.5f}' if x != 100000 else "" ) trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit']) diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 099976aa9..5822fc627 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -3,7 +3,6 @@ from datetime import datetime, timedelta, timezone from pathlib import Path from typing import Any, Dict, List, Union -from arrow import Arrow from numpy import int64 from pandas import DataFrame from tabulate import tabulate @@ -44,7 +43,7 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]: Generate floatformat (goes in line with _generate_result_line()) """ return ['s', 'd', '.2f', '.2f', f'.{decimals_per_coin(stake_currency)}f', - '.2f', 'd', 'd', 'd', 'd'] + '.2f', 'd', 's', 's'] def _get_line_header(first_column: str, stake_currency: str) -> List[str]: @@ -53,7 +52,17 @@ def _get_line_header(first_column: str, stake_currency: str) -> List[str]: """ return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %', f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration', - 'Wins', 'Draws', 'Losses'] + 'Win Draw Loss Win%'] + + +def _generate_wins_draws_losses(wins, draws, losses): + if wins > 0 and losses == 0: + wl_ratio = '100' + elif wins == 0: + wl_ratio = '0' + else: + wl_ratio = f'{100.0 / (wins + draws + losses) * wins:.1f}' if losses > 0 else '100' + return f'{wins:>4} {draws:>4} {losses:>4} {wl_ratio:>4}' def _generate_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict: @@ -110,6 +119,9 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b tabular_data.append(_generate_result_line(result, starting_balance, pair)) + # Sort by total profit %: + tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True) + # Append Total tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL')) return tabular_data @@ -150,7 +162,7 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List return tabular_data -def generate_strategy_metrics(all_results: Dict) -> List[Dict]: +def generate_strategy_comparison(all_results: Dict) -> List[Dict]: """ Generate summary per strategy :param all_results: Dict of containing results for all strategies @@ -162,6 +174,17 @@ def generate_strategy_metrics(all_results: Dict) -> List[Dict]: tabular_data.append(_generate_result_line( results['results'], results['config']['dry_run_wallet'], strategy) ) + try: + max_drawdown_per, _, _, _, _ = calculate_max_drawdown(results['results'], + value_col='profit_ratio') + max_drawdown_abs, _, _, _, _ = calculate_max_drawdown(results['results'], + value_col='profit_abs') + except ValueError: + max_drawdown_per = 0 + max_drawdown_abs = 0 + tabular_data[-1]['max_drawdown_per'] = round(max_drawdown_per * 100, 2) + tabular_data[-1]['max_drawdown_abs'] = \ + round_coin_value(max_drawdown_abs, results['config']['stake_currency'], False) return tabular_data @@ -191,7 +214,40 @@ def generate_edge_table(results: dict) -> str: floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore +def generate_trading_stats(results: DataFrame) -> Dict[str, Any]: + """ Generate overall trade statistics """ + if len(results) == 0: + return { + 'wins': 0, + 'losses': 0, + 'draws': 0, + 'holding_avg': timedelta(), + 'winner_holding_avg': timedelta(), + 'loser_holding_avg': timedelta(), + } + + winning_trades = results.loc[results['profit_ratio'] > 0] + draw_trades = results.loc[results['profit_ratio'] == 0] + losing_trades = results.loc[results['profit_ratio'] < 0] + zero_duration_trades = len(results.loc[(results['trade_duration'] == 0) & + (results['sell_reason'] == 'trailing_stop_loss')]) + + return { + 'wins': len(winning_trades), + 'losses': len(losing_trades), + 'draws': len(draw_trades), + 'holding_avg': (timedelta(minutes=round(results['trade_duration'].mean())) + if not results.empty else timedelta()), + 'winner_holding_avg': (timedelta(minutes=round(winning_trades['trade_duration'].mean())) + if not winning_trades.empty else timedelta()), + 'loser_holding_avg': (timedelta(minutes=round(losing_trades['trade_duration'].mean())) + if not losing_trades.empty else timedelta()), + 'zero_duration_trades': zero_duration_trades, + } + + def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: + """ Generate daily statistics """ if len(results) == 0: return { 'backtest_best_day': 0, @@ -201,8 +257,6 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: 'winning_days': 0, 'draw_days': 0, 'losing_days': 0, - 'winner_holding_avg': timedelta(), - 'loser_holding_avg': timedelta(), } daily_profit_rel = results.resample('1d', on='close_date')['profit_ratio'].sum() daily_profit = results.resample('1d', on='close_date')['profit_abs'].sum().round(10) @@ -214,9 +268,6 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: draw_days = sum(daily_profit == 0) losing_days = sum(daily_profit < 0) - winning_trades = results.loc[results['profit_ratio'] > 0] - losing_trades = results.loc[results['profit_ratio'] < 0] - return { 'backtest_best_day': best_rel, 'backtest_worst_day': worst_rel, @@ -225,16 +276,152 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: 'winning_days': winning_days, 'draw_days': draw_days, 'losing_days': losing_days, - 'winner_holding_avg': (timedelta(minutes=round(winning_trades['trade_duration'].mean())) - if not winning_trades.empty else timedelta()), - 'loser_holding_avg': (timedelta(minutes=round(losing_trades['trade_duration'].mean())) - if not losing_trades.empty else timedelta()), } +def generate_strategy_stats(btdata: Dict[str, DataFrame], + strategy: str, + content: Dict[str, Any], + min_date: datetime, max_date: datetime, + market_change: float + ) -> Dict[str, Any]: + """ + :param btdata: Backtest data + :param strategy: Strategy name + :param content: Backtest result data in the format: + {'results: results, 'config: config}}. + :param min_date: Backtest start date + :param max_date: Backtest end date + :param market_change: float indicating the market change + :return: Dictionary containing results per strategy and a stratgy summary. + """ + results: Dict[str, DataFrame] = content['results'] + if not isinstance(results, DataFrame): + return {} + config = content['config'] + max_open_trades = min(config['max_open_trades'], len(btdata.keys())) + starting_balance = config['dry_run_wallet'] + stake_currency = config['stake_currency'] + + pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency, + starting_balance=starting_balance, + results=results, skip_nan=False) + sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades, + results=results) + left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency, + starting_balance=starting_balance, + results=results.loc[results['is_open']], + skip_nan=True) + daily_stats = generate_daily_stats(results) + trade_stats = generate_trading_stats(results) + best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'], + key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None + worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'], + key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None + results['open_timestamp'] = results['open_date'].astype(int64) // 1e6 + results['close_timestamp'] = results['close_date'].astype(int64) // 1e6 + + backtest_days = (max_date - min_date).days + strat_stats = { + 'trades': results.to_dict(orient='records'), + 'locks': [lock.to_json() for lock in content['locks']], + 'best_pair': best_pair, + 'worst_pair': worst_pair, + 'results_per_pair': pair_results, + 'sell_reason_summary': sell_reason_stats, + 'left_open_trades': left_open_results, + 'total_trades': len(results), + 'total_volume': float(results['stake_amount'].sum()), + 'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0, + 'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0, + 'profit_median': results['profit_ratio'].median() if len(results) > 0 else 0, + 'profit_total': results['profit_abs'].sum() / starting_balance, + 'profit_total_abs': results['profit_abs'].sum(), + 'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT), + 'backtest_start_ts': int(min_date.timestamp() * 1000), + 'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT), + 'backtest_end_ts': int(max_date.timestamp() * 1000), + 'backtest_days': backtest_days, + + 'backtest_run_start_ts': content['backtest_start_time'], + 'backtest_run_end_ts': content['backtest_end_time'], + + 'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0, + 'market_change': market_change, + 'pairlist': list(btdata.keys()), + 'stake_amount': config['stake_amount'], + 'stake_currency': config['stake_currency'], + 'stake_currency_decimals': decimals_per_coin(config['stake_currency']), + 'starting_balance': starting_balance, + 'dry_run_wallet': starting_balance, + 'final_balance': content['final_balance'], + 'rejected_signals': content['rejected_signals'], + 'max_open_trades': max_open_trades, + 'max_open_trades_setting': (config['max_open_trades'] + if config['max_open_trades'] != float('inf') else -1), + 'timeframe': config['timeframe'], + 'timerange': config.get('timerange', ''), + 'enable_protections': config.get('enable_protections', False), + 'strategy_name': strategy, + # Parameters relevant for backtesting + 'stoploss': config['stoploss'], + 'trailing_stop': config.get('trailing_stop', False), + 'trailing_stop_positive': config.get('trailing_stop_positive'), + 'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset', 0.0), + 'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False), + 'use_custom_stoploss': config.get('use_custom_stoploss', False), + 'minimal_roi': config['minimal_roi'], + 'use_sell_signal': config['ask_strategy']['use_sell_signal'], + 'sell_profit_only': config['ask_strategy']['sell_profit_only'], + 'sell_profit_offset': config['ask_strategy']['sell_profit_offset'], + 'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'], + **daily_stats, + **trade_stats + } + + try: + max_drawdown, _, _, _, _ = calculate_max_drawdown( + results, value_col='profit_ratio') + drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown( + results, value_col='profit_abs') + strat_stats.update({ + 'max_drawdown': max_drawdown, + 'max_drawdown_abs': drawdown_abs, + 'drawdown_start': drawdown_start.strftime(DATETIME_PRINT_FORMAT), + 'drawdown_start_ts': drawdown_start.timestamp() * 1000, + 'drawdown_end': drawdown_end.strftime(DATETIME_PRINT_FORMAT), + 'drawdown_end_ts': drawdown_end.timestamp() * 1000, + + 'max_drawdown_low': low_val, + 'max_drawdown_high': high_val, + }) + + csum_min, csum_max = calculate_csum(results, starting_balance) + strat_stats.update({ + 'csum_min': csum_min, + 'csum_max': csum_max + }) + + except ValueError: + strat_stats.update({ + 'max_drawdown': 0.0, + 'max_drawdown_abs': 0.0, + 'max_drawdown_low': 0.0, + 'max_drawdown_high': 0.0, + 'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc), + 'drawdown_start_ts': 0, + 'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc), + 'drawdown_end_ts': 0, + 'csum_min': 0, + 'csum_max': 0 + }) + + return strat_stats + + def generate_backtest_stats(btdata: Dict[str, DataFrame], all_results: Dict[str, Dict[str, Union[DataFrame, Dict]]], - min_date: Arrow, max_date: Arrow + min_date: datetime, max_date: datetime ) -> Dict[str, Any]: """ :param btdata: Backtest data @@ -242,132 +429,17 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], { Strategy: {'results: results, 'config: config}}. :param min_date: Backtest start date :param max_date: Backtest end date - :return: - Dictionary containing results per strategy and a stratgy summary. + :return: Dictionary containing results per strategy and a stratgy summary. """ result: Dict[str, Any] = {'strategy': {}} market_change = calculate_market_change(btdata, 'close') for strategy, content in all_results.items(): - results: Dict[str, DataFrame] = content['results'] - if not isinstance(results, DataFrame): - continue - config = content['config'] - max_open_trades = min(config['max_open_trades'], len(btdata.keys())) - starting_balance = config['dry_run_wallet'] - stake_currency = config['stake_currency'] - - pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency, - starting_balance=starting_balance, - results=results, skip_nan=False) - sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades, - results=results) - left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency, - starting_balance=starting_balance, - results=results.loc[results['is_open']], - skip_nan=True) - daily_stats = generate_daily_stats(results) - best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'], - key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None - worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'], - key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None - results['open_timestamp'] = results['open_date'].astype(int64) // 1e6 - results['close_timestamp'] = results['close_date'].astype(int64) // 1e6 - - backtest_days = (max_date - min_date).days - strat_stats = { - 'trades': results.to_dict(orient='records'), - 'locks': [lock.to_json() for lock in content['locks']], - 'best_pair': best_pair, - 'worst_pair': worst_pair, - 'results_per_pair': pair_results, - 'sell_reason_summary': sell_reason_stats, - 'left_open_trades': left_open_results, - 'total_trades': len(results), - 'total_volume': float(results['stake_amount'].sum()), - 'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0, - 'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0, - 'profit_total': results['profit_abs'].sum() / starting_balance, - 'profit_total_abs': results['profit_abs'].sum(), - 'backtest_start': min_date.datetime, - 'backtest_start_ts': min_date.int_timestamp * 1000, - 'backtest_end': max_date.datetime, - 'backtest_end_ts': max_date.int_timestamp * 1000, - 'backtest_days': backtest_days, - - 'backtest_run_start_ts': content['backtest_start_time'], - 'backtest_run_end_ts': content['backtest_end_time'], - - 'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0, - 'market_change': market_change, - 'pairlist': list(btdata.keys()), - 'stake_amount': config['stake_amount'], - 'stake_currency': config['stake_currency'], - 'stake_currency_decimals': decimals_per_coin(config['stake_currency']), - 'starting_balance': starting_balance, - 'dry_run_wallet': starting_balance, - 'final_balance': content['final_balance'], - 'max_open_trades': max_open_trades, - 'max_open_trades_setting': (config['max_open_trades'] - if config['max_open_trades'] != float('inf') else -1), - 'timeframe': config['timeframe'], - 'timerange': config.get('timerange', ''), - 'enable_protections': config.get('enable_protections', False), - 'strategy_name': strategy, - # Parameters relevant for backtesting - 'stoploss': config['stoploss'], - 'trailing_stop': config.get('trailing_stop', False), - 'trailing_stop_positive': config.get('trailing_stop_positive'), - 'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset', 0.0), - 'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False), - 'use_custom_stoploss': config.get('use_custom_stoploss', False), - 'minimal_roi': config['minimal_roi'], - 'use_sell_signal': config['ask_strategy']['use_sell_signal'], - 'sell_profit_only': config['ask_strategy']['sell_profit_only'], - 'sell_profit_offset': config['ask_strategy']['sell_profit_offset'], - 'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'], - **daily_stats, - } + strat_stats = generate_strategy_stats(btdata, strategy, content, + min_date, max_date, market_change=market_change) result['strategy'][strategy] = strat_stats - try: - max_drawdown, _, _, _, _ = calculate_max_drawdown( - results, value_col='profit_ratio') - drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown( - results, value_col='profit_abs') - strat_stats.update({ - 'max_drawdown': max_drawdown, - 'max_drawdown_abs': drawdown_abs, - 'drawdown_start': drawdown_start, - 'drawdown_start_ts': drawdown_start.timestamp() * 1000, - 'drawdown_end': drawdown_end, - 'drawdown_end_ts': drawdown_end.timestamp() * 1000, - - 'max_drawdown_low': low_val, - 'max_drawdown_high': high_val, - }) - - csum_min, csum_max = calculate_csum(results, starting_balance) - strat_stats.update({ - 'csum_min': csum_min, - 'csum_max': csum_max - }) - - except ValueError: - strat_stats.update({ - 'max_drawdown': 0.0, - 'max_drawdown_abs': 0.0, - 'max_drawdown_low': 0.0, - 'max_drawdown_high': 0.0, - 'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc), - 'drawdown_start_ts': 0, - 'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc), - 'drawdown_end_ts': 0, - 'csum_min': 0, - 'csum_max': 0 - }) - - strategy_results = generate_strategy_metrics(all_results=all_results) + strategy_results = generate_strategy_comparison(all_results=all_results) result['strategy_comparison'] = strategy_results @@ -390,7 +462,8 @@ def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: st floatfmt = _get_line_floatfmt(stake_currency) output = [[ t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], - t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] + t['profit_total_pct'], t['duration_avg'], + _generate_wins_draws_losses(t['wins'], t['draws'], t['losses']) ] for t in pair_results] # Ignore type as floatfmt does allow tuples but mypy does not know that return tabulate(output, headers=headers, @@ -407,9 +480,7 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren headers = [ 'Sell Reason', 'Sells', - 'Wins', - 'Draws', - 'Losses', + 'Win Draws Loss Win%', 'Avg Profit %', 'Cum Profit %', f'Tot Profit {stake_currency}', @@ -417,7 +488,8 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren ] output = [[ - t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'], + t['sell_reason'], t['trades'], + _generate_wins_draws_losses(t['wins'], t['draws'], t['losses']), t['profit_mean_pct'], t['profit_sum_pct'], round_coin_value(t['profit_total_abs'], stake_currency, False), t['profit_total_pct'], @@ -435,11 +507,22 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str: """ floatfmt = _get_line_floatfmt(stake_currency) headers = _get_line_header('Strategy', stake_currency) + # _get_line_header() is also used for per-pair summary. Per-pair drawdown is mostly useless + # therefore we slip this column in only for strategy summary here. + headers.append('Drawdown') + + # Align drawdown string on the center two space separator. + drawdown = [f'{t["max_drawdown_per"]:.2f}' for t in strategy_results] + dd_pad_abs = max([len(t['max_drawdown_abs']) for t in strategy_results]) + dd_pad_per = max([len(dd) for dd in drawdown]) + drawdown = [f'{t["max_drawdown_abs"]:>{dd_pad_abs}} {stake_currency} {dd:>{dd_pad_per}}%' + for t, dd in zip(strategy_results, drawdown)] output = [[ t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], - t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] - ] for t in strategy_results] + t['profit_total_pct'], t['duration_avg'], + _generate_wins_draws_losses(t['wins'], t['draws'], t['losses']), drawdown] + for t, drawdown in zip(strategy_results, drawdown)] # Ignore type as floatfmt does allow tuples but mypy does not know that return tabulate(output, headers=headers, floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") @@ -449,9 +532,21 @@ def text_table_add_metrics(strat_results: Dict) -> str: if len(strat_results['trades']) > 0: best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio']) worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio']) + + # Newly added fields should be ignored if they are missing in strat_results. hyperopt-show + # command stores these results and newer version of freqtrade must be able to handle old + # results with missing new fields. + zero_duration_trades = '--' + + if 'zero_duration_trades' in strat_results: + zero_duration_trades_per = \ + 100.0 / strat_results['total_trades'] * strat_results['zero_duration_trades'] + zero_duration_trades = f'{zero_duration_trades_per:.2f}% ' \ + f'({strat_results["zero_duration_trades"]})' + metrics = [ - ('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)), - ('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)), + ('Backtesting from', strat_results['backtest_start']), + ('Backtesting to', strat_results['backtest_end']), ('Max open trades', strat_results['max_open_trades']), ('', ''), # Empty line to improve readability ('Total trades', strat_results['total_trades']), @@ -461,13 +556,12 @@ def text_table_add_metrics(strat_results: Dict) -> str: strat_results['stake_currency'])), ('Absolute profit ', round_coin_value(strat_results['profit_total_abs'], strat_results['stake_currency'])), - ('Total profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"), + ('Total profit %', f"{round(strat_results['profit_total'] * 100, 2):}%"), ('Trades per day', strat_results['trades_per_day']), ('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'], strat_results['stake_currency'])), ('Total trade volume', round_coin_value(strat_results['total_volume'], strat_results['stake_currency'])), - ('', ''), # Empty line to improve readability ('Best Pair', f"{strat_results['best_pair']['key']} " f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"), @@ -485,6 +579,8 @@ def text_table_add_metrics(strat_results: Dict) -> str: f"{strat_results['draw_days']} / {strat_results['losing_days']}"), ('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"), ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"), + ('Zero Duration Trades', zero_duration_trades), + ('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')), ('', ''), # Empty line to improve readability ('Min balance', round_coin_value(strat_results['csum_min'], @@ -499,8 +595,8 @@ def text_table_add_metrics(strat_results: Dict) -> str: strat_results['stake_currency'])), ('Drawdown low', round_coin_value(strat_results['max_drawdown_low'], strat_results['stake_currency'])), - ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)), - ('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)), + ('Drawdown Start', strat_results['drawdown_start']), + ('Drawdown End', strat_results['drawdown_end']), ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"), ] @@ -519,37 +615,43 @@ def text_table_add_metrics(strat_results: Dict) -> str: return message +def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str): + """ + Print results for one strategy + """ + # Print results + print(f"Result for strategy {strategy}") + table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency) + if isinstance(table, str): + print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '=')) + print(table) + + table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'], + stake_currency=stake_currency) + if isinstance(table, str) and len(table) > 0: + print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '=')) + print(table) + + table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency) + if isinstance(table, str) and len(table) > 0: + print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '=')) + print(table) + + table = text_table_add_metrics(results) + if isinstance(table, str) and len(table) > 0: + print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '=')) + print(table) + + if isinstance(table, str) and len(table) > 0: + print('=' * len(table.splitlines()[0])) + print() + + def show_backtest_results(config: Dict, backtest_stats: Dict): stake_currency = config['stake_currency'] for strategy, results in backtest_stats['strategy'].items(): - - # Print results - print(f"Result for strategy {strategy}") - table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency) - if isinstance(table, str): - print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '=')) - print(table) - - table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'], - stake_currency=stake_currency) - if isinstance(table, str) and len(table) > 0: - print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '=')) - print(table) - - table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency) - if isinstance(table, str) and len(table) > 0: - print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '=')) - print(table) - - table = text_table_add_metrics(results) - if isinstance(table, str) and len(table) > 0: - print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '=')) - print(table) - - if isinstance(table, str) and len(table) > 0: - print('=' * len(table.splitlines()[0])) - print() + show_backtest_result(strategy, results, stake_currency) if len(backtest_stats['strategy']) > 1: # Print Strategy summary table diff --git a/freqtrade/optimize/space/__init__.py b/freqtrade/optimize/space/__init__.py new file mode 100644 index 000000000..bbdac4ab9 --- /dev/null +++ b/freqtrade/optimize/space/__init__.py @@ -0,0 +1,4 @@ +# flake8: noqa: F401 +from skopt.space import Categorical, Dimension, Integer, Real + +from .decimalspace import SKDecimal diff --git a/freqtrade/optimize/space/decimalspace.py b/freqtrade/optimize/space/decimalspace.py new file mode 100644 index 000000000..643999cc1 --- /dev/null +++ b/freqtrade/optimize/space/decimalspace.py @@ -0,0 +1,33 @@ +import numpy as np +from skopt.space import Integer + + +class SKDecimal(Integer): + + def __init__(self, low, high, decimals=3, prior="uniform", base=10, transform=None, + name=None, dtype=np.int64): + self.decimals = decimals + _low = int(low * pow(10, self.decimals)) + _high = int(high * pow(10, self.decimals)) + # trunc to precision to avoid points out of space + self.low_orig = round(_low * pow(0.1, self.decimals), self.decimals) + self.high_orig = round(_high * pow(0.1, self.decimals), self.decimals) + + super().__init__(_low, _high, prior, base, transform, name, dtype) + + def __repr__(self): + return "Decimal(low={}, high={}, decimals={}, prior='{}', transform='{}')".format( + self.low_orig, self.high_orig, self.decimals, self.prior, self.transform_) + + def __contains__(self, point): + if isinstance(point, list): + point = np.array(point) + return self.low_orig <= point <= self.high_orig + + def transform(self, Xt): + aa = [int(x * pow(10, self.decimals)) for x in Xt] + return super().transform(aa) + + def inverse_transform(self, Xt): + res = super().inverse_transform(Xt) + return [round(x * pow(0.1, self.decimals), self.decimals) for x in res] diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index 961363b0e..d89256baf 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -123,6 +123,27 @@ def migrate_open_orders_to_trades(engine): """) +def migrate_orders_table(decl_base, inspector, engine, table_back_name: str, cols: List): + # Schema migration necessary + engine.execute(f"alter table orders rename to {table_back_name}") + # drop indexes on backup table + for index in inspector.get_indexes(table_back_name): + engine.execute(f"drop index {index['name']}") + + # let SQLAlchemy create the schema as required + decl_base.metadata.create_all(engine) + + engine.execute(f""" + insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, + symbol, order_type, side, price, amount, filled, average, remaining, cost, order_date, + order_filled_date, order_update_date) + select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status, + symbol, order_type, side, price, amount, filled, null average, remaining, cost, order_date, + order_filled_date, order_update_date + from {table_back_name} + """) + + def check_migrate(engine, decl_base, previous_tables) -> None: """ Checks if migration is necessary and migrates if necessary @@ -145,6 +166,11 @@ def check_migrate(engine, decl_base, previous_tables) -> None: logger.info('Moving open orders to Orders table.') migrate_open_orders_to_trades(engine) else: - pass - # Empty for now - as there is only one iteration of the orders table so far. - # table_back_name = get_backup_name(tabs, 'orders_bak') + cols_order = inspector.get_columns('orders') + + if not has_column(cols_order, 'average'): + tabs = get_table_names_for_table(inspector, 'orders') + # Empty for now - as there is only one iteration of the orders table so far. + table_back_name = get_backup_name(tabs, 'orders_bak') + + migrate_orders_table(decl_base, inspector, engine, table_back_name, cols) diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py index 78f45de0b..f2e7a10c4 100644 --- a/freqtrade/persistence/models.py +++ b/freqtrade/persistence/models.py @@ -6,7 +6,6 @@ from datetime import datetime, timezone from decimal import Decimal from typing import Any, Dict, List, Optional -import arrow from sqlalchemy import (Boolean, Column, DateTime, Float, ForeignKey, Integer, String, create_engine, desc, func, inspect) from sqlalchemy.exc import NoSuchModuleError @@ -59,13 +58,10 @@ def init_db(db_url: str, clean_open_orders: bool = False) -> None: # https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope # Scoped sessions proxy requests to the appropriate thread-local session. # We should use the scoped_session object - not a seperately initialized version - Trade.session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True)) - Trade.query = Trade.session.query_property() - # Copy session attributes to order object too - Order.session = Trade.session - Order.query = Order.session.query_property() - PairLock.session = Trade.session - PairLock.query = PairLock.session.query_property() + Trade._session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True)) + Trade.query = Trade._session.query_property() + Order.query = Trade._session.query_property() + PairLock.query = Trade._session.query_property() previous_tables = inspect(engine).get_table_names() _DECL_BASE.metadata.create_all(engine) @@ -81,7 +77,7 @@ def cleanup_db() -> None: Flushes all pending operations to disk. :return: None """ - Trade.session.flush() + Trade.query.session.flush() def clean_dry_run_db() -> None: @@ -116,16 +112,17 @@ class Order(_DECL_BASE): trade = relationship("Trade", back_populates="orders") - ft_order_side = Column(String, nullable=False) - ft_pair = Column(String, nullable=False) + ft_order_side = Column(String(25), nullable=False) + ft_pair = Column(String(25), nullable=False) ft_is_open = Column(Boolean, nullable=False, default=True, index=True) - order_id = Column(String, nullable=False, index=True) - status = Column(String, nullable=True) - symbol = Column(String, nullable=True) - order_type = Column(String, nullable=True) - side = Column(String, nullable=True) + order_id = Column(String(255), nullable=False, index=True) + status = Column(String(255), nullable=True) + symbol = Column(String(25), nullable=True) + order_type = Column(String(50), nullable=True) + side = Column(String(25), nullable=True) price = Column(Float, nullable=True) + average = Column(Float, nullable=True) amount = Column(Float, nullable=True) filled = Column(Float, nullable=True) remaining = Column(Float, nullable=True) @@ -154,6 +151,7 @@ class Order(_DECL_BASE): self.price = order.get('price', self.price) self.amount = order.get('amount', self.amount) self.filled = order.get('filled', self.filled) + self.average = order.get('average', self.average) self.remaining = order.get('remaining', self.remaining) self.cost = order.get('cost', self.cost) if 'timestamp' in order and order['timestamp'] is not None: @@ -163,8 +161,8 @@ class Order(_DECL_BASE): if self.status in ('closed', 'canceled', 'cancelled'): self.ft_is_open = False if order.get('filled', 0) > 0: - self.order_filled_date = arrow.utcnow().datetime - self.order_update_date = arrow.utcnow().datetime + self.order_filled_date = datetime.now(timezone.utc) + self.order_update_date = datetime.now(timezone.utc) @staticmethod def update_orders(orders: List['Order'], order: Dict[str, Any]): @@ -297,15 +295,12 @@ class LocalTrade(): 'fee_close_cost': self.fee_close_cost, 'fee_close_currency': self.fee_close_currency, - 'open_date_hum': arrow.get(self.open_date).humanize(), 'open_date': self.open_date.strftime(DATETIME_PRINT_FORMAT), 'open_timestamp': int(self.open_date.replace(tzinfo=timezone.utc).timestamp() * 1000), 'open_rate': self.open_rate, 'open_rate_requested': self.open_rate_requested, 'open_trade_value': round(self.open_trade_value, 8), - 'close_date_hum': (arrow.get(self.close_date).humanize() - if self.close_date else None), 'close_date': (self.close_date.strftime(DATETIME_PRINT_FORMAT) if self.close_date else None), 'close_timestamp': int(self.close_date.replace( @@ -554,6 +549,8 @@ class LocalTrade(): rate=(rate or self.close_rate), fee=(fee or self.fee_close) ) + if self.open_trade_value == 0.0: + return 0.0 profit_ratio = (close_trade_value / self.open_trade_value) - 1 return float(f"{profit_ratio:.8f}") @@ -572,23 +569,6 @@ class LocalTrade(): else: return None - @staticmethod - def get_trades(trade_filter=None) -> Query: - """ - Helper function to query Trades using filters. - :param trade_filter: Optional filter to apply to trades - Can be either a Filter object, or a List of filters - e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])` - e.g. `(trade_filter=Trade.id == trade_id)` - :return: unsorted query object - """ - if trade_filter is not None: - if not isinstance(trade_filter, list): - trade_filter = [trade_filter] - return Trade.query.filter(*trade_filter) - else: - return Trade.query - @staticmethod def get_trades_proxy(*, pair: str = None, is_open: bool = None, open_date: datetime = None, close_date: datetime = None, @@ -611,7 +591,7 @@ class LocalTrade(): else: # Not used during backtesting, but might be used by a strategy - sel_trades = [trade for trade in LocalTrade.trades + LocalTrade.trades_open] + sel_trades = list(LocalTrade.trades + LocalTrade.trades_open) if pair: sel_trades = [trade for trade in sel_trades if trade.pair == pair] @@ -641,83 +621,7 @@ class LocalTrade(): """ Query trades from persistence layer """ - return Trade.get_trades(Trade.is_open.is_(True)).all() - - @staticmethod - def get_open_order_trades(): - """ - Returns all open trades - """ - return Trade.get_trades(Trade.open_order_id.isnot(None)).all() - - @staticmethod - def get_open_trades_without_assigned_fees(): - """ - Returns all open trades which don't have open fees set correctly - """ - return Trade.get_trades([Trade.fee_open_currency.is_(None), - Trade.orders.any(), - Trade.is_open.is_(True), - ]).all() - - @staticmethod - def get_sold_trades_without_assigned_fees(): - """ - Returns all closed trades which don't have fees set correctly - """ - return Trade.get_trades([Trade.fee_close_currency.is_(None), - Trade.orders.any(), - Trade.is_open.is_(False), - ]).all() - - @staticmethod - def total_open_trades_stakes() -> float: - """ - Calculates total invested amount in open trades - in stake currency - """ - if Trade.use_db: - total_open_stake_amount = Trade.session.query( - func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True)).scalar() - else: - total_open_stake_amount = sum( - t.stake_amount for t in Trade.get_trades_proxy(is_open=True)) - return total_open_stake_amount or 0 - - @staticmethod - def get_overall_performance() -> List[Dict[str, Any]]: - """ - Returns List of dicts containing all Trades, including profit and trade count - """ - pair_rates = Trade.session.query( - Trade.pair, - func.sum(Trade.close_profit).label('profit_sum'), - func.count(Trade.pair).label('count') - ).filter(Trade.is_open.is_(False))\ - .group_by(Trade.pair) \ - .order_by(desc('profit_sum')) \ - .all() - return [ - { - 'pair': pair, - 'profit': rate, - 'count': count - } - for pair, rate, count in pair_rates - ] - - @staticmethod - def get_best_pair(): - """ - Get best pair with closed trade. - :returns: Tuple containing (pair, profit_sum) - """ - best_pair = Trade.session.query( - Trade.pair, func.sum(Trade.close_profit).label('profit_sum') - ).filter(Trade.is_open.is_(False)) \ - .group_by(Trade.pair) \ - .order_by(desc('profit_sum')).first() - return best_pair + return Trade.get_trades_proxy(is_open=True) @staticmethod def stoploss_reinitialization(desired_stoploss): @@ -754,15 +658,15 @@ class Trade(_DECL_BASE, LocalTrade): orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan") - exchange = Column(String, nullable=False) - pair = Column(String, nullable=False, index=True) + exchange = Column(String(25), nullable=False) + pair = Column(String(25), nullable=False, index=True) is_open = Column(Boolean, nullable=False, default=True, index=True) fee_open = Column(Float, nullable=False, default=0.0) fee_open_cost = Column(Float, nullable=True) - fee_open_currency = Column(String, nullable=True) + fee_open_currency = Column(String(25), nullable=True) fee_close = Column(Float, nullable=False, default=0.0) fee_close_cost = Column(Float, nullable=True) - fee_close_currency = Column(String, nullable=True) + fee_close_currency = Column(String(25), nullable=True) open_rate = Column(Float) open_rate_requested = Column(Float) # open_trade_value - calculated via _calc_open_trade_value @@ -776,7 +680,7 @@ class Trade(_DECL_BASE, LocalTrade): amount_requested = Column(Float) open_date = Column(DateTime, nullable=False, default=datetime.utcnow) close_date = Column(DateTime) - open_order_id = Column(String) + open_order_id = Column(String(255)) # absolute value of the stop loss stop_loss = Column(Float, nullable=True, default=0.0) # percentage value of the stop loss @@ -786,16 +690,16 @@ class Trade(_DECL_BASE, LocalTrade): # percentage value of the initial stop loss initial_stop_loss_pct = Column(Float, nullable=True) # stoploss order id which is on exchange - stoploss_order_id = Column(String, nullable=True, index=True) + stoploss_order_id = Column(String(255), nullable=True, index=True) # last update time of the stoploss order on exchange stoploss_last_update = Column(DateTime, nullable=True) # absolute value of the highest reached price max_rate = Column(Float, nullable=True, default=0.0) # Lowest price reached min_rate = Column(Float, nullable=True) - sell_reason = Column(String, nullable=True) - sell_order_status = Column(String, nullable=True) - strategy = Column(String, nullable=True) + sell_reason = Column(String(100), nullable=True) + sell_order_status = Column(String(100), nullable=True) + strategy = Column(String(100), nullable=True) timeframe = Column(Integer, nullable=True) def __init__(self, **kwargs): @@ -805,17 +709,17 @@ class Trade(_DECL_BASE, LocalTrade): def delete(self) -> None: for order in self.orders: - Order.session.delete(order) + Order.query.session.delete(order) - Trade.session.delete(self) - Trade.session.flush() + Trade.query.session.delete(self) + Trade.query.session.flush() @staticmethod def get_trades_proxy(*, pair: str = None, is_open: bool = None, open_date: datetime = None, close_date: datetime = None, ) -> List['LocalTrade']: """ - Helper function to query Trades. + Helper function to query Trades.j Returns a List of trades, filtered on the parameters given. In live mode, converts the filter to a database query and returns all rows In Backtest mode, uses filters on Trade.trades to get the result. @@ -840,6 +744,109 @@ class Trade(_DECL_BASE, LocalTrade): close_date=close_date ) + @staticmethod + def get_trades(trade_filter=None) -> Query: + """ + Helper function to query Trades using filters. + NOTE: Not supported in Backtesting. + :param trade_filter: Optional filter to apply to trades + Can be either a Filter object, or a List of filters + e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])` + e.g. `(trade_filter=Trade.id == trade_id)` + :return: unsorted query object + """ + if not Trade.use_db: + raise NotImplementedError('`Trade.get_trades()` not supported in backtesting mode.') + if trade_filter is not None: + if not isinstance(trade_filter, list): + trade_filter = [trade_filter] + return Trade.query.filter(*trade_filter) + else: + return Trade.query + + @staticmethod + def get_open_order_trades(): + """ + Returns all open trades + NOTE: Not supported in Backtesting. + """ + return Trade.get_trades(Trade.open_order_id.isnot(None)).all() + + @staticmethod + def get_open_trades_without_assigned_fees(): + """ + Returns all open trades which don't have open fees set correctly + NOTE: Not supported in Backtesting. + """ + return Trade.get_trades([Trade.fee_open_currency.is_(None), + Trade.orders.any(), + Trade.is_open.is_(True), + ]).all() + + @staticmethod + def get_sold_trades_without_assigned_fees(): + """ + Returns all closed trades which don't have fees set correctly + NOTE: Not supported in Backtesting. + """ + return Trade.get_trades([Trade.fee_close_currency.is_(None), + Trade.orders.any(), + Trade.is_open.is_(False), + ]).all() + + @staticmethod + def total_open_trades_stakes() -> float: + """ + Calculates total invested amount in open trades + in stake currency + """ + if Trade.use_db: + total_open_stake_amount = Trade.query.with_entities( + func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True)).scalar() + else: + total_open_stake_amount = sum( + t.stake_amount for t in LocalTrade.get_trades_proxy(is_open=True)) + return total_open_stake_amount or 0 + + @staticmethod + def get_overall_performance() -> List[Dict[str, Any]]: + """ + Returns List of dicts containing all Trades, including profit and trade count + NOTE: Not supported in Backtesting. + """ + pair_rates = Trade.query.with_entities( + Trade.pair, + func.sum(Trade.close_profit).label('profit_sum'), + func.sum(Trade.close_profit_abs).label('profit_sum_abs'), + func.count(Trade.pair).label('count') + ).filter(Trade.is_open.is_(False))\ + .group_by(Trade.pair) \ + .order_by(desc('profit_sum_abs')) \ + .all() + return [ + { + 'pair': pair, + 'profit': profit, + 'profit_abs': profit_abs, + 'count': count + } + for pair, profit, profit_abs, count in pair_rates + ] + + @staticmethod + def get_best_pair(): + """ + Get best pair with closed trade. + NOTE: Not supported in Backtesting. + :returns: Tuple containing (pair, profit_sum) + """ + best_pair = Trade.query.with_entities( + Trade.pair, func.sum(Trade.close_profit).label('profit_sum') + ).filter(Trade.is_open.is_(False)) \ + .group_by(Trade.pair) \ + .order_by(desc('profit_sum')).first() + return best_pair + class PairLock(_DECL_BASE): """ @@ -849,8 +856,8 @@ class PairLock(_DECL_BASE): id = Column(Integer, primary_key=True) - pair = Column(String, nullable=False, index=True) - reason = Column(String, nullable=True) + pair = Column(String(25), nullable=False, index=True) + reason = Column(String(255), nullable=True) # Time the pair was locked (start time) lock_time = Column(DateTime, nullable=False) # Time until the pair is locked (end time) diff --git a/freqtrade/persistence/pairlock_middleware.py b/freqtrade/persistence/pairlock_middleware.py index f0048bb52..245f7cdab 100644 --- a/freqtrade/persistence/pairlock_middleware.py +++ b/freqtrade/persistence/pairlock_middleware.py @@ -48,8 +48,8 @@ class PairLocks(): active=True ) if PairLocks.use_db: - PairLock.session.add(lock) - PairLock.session.flush() + PairLock.query.session.add(lock) + PairLock.query.session.flush() else: PairLocks.locks.append(lock) @@ -99,7 +99,7 @@ class PairLocks(): for lock in locks: lock.active = False if PairLocks.use_db: - PairLock.session.flush() + PairLock.query.session.flush() @staticmethod def is_global_lock(now: Optional[datetime] = None) -> bool: diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py index 682c2b018..bb4283406 100644 --- a/freqtrade/plot/plotting.py +++ b/freqtrade/plot/plotting.py @@ -77,7 +77,8 @@ def init_plotscript(config, markets: List, startup_candles: int = 0): ) except ValueError as e: raise OperationalException(e) from e - trades = trim_dataframe(trades, timerange, 'open_date') + if not trades.empty: + trades = trim_dataframe(trades, timerange, 'open_date') return {"ohlcv": data, "trades": trades, @@ -441,7 +442,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame], - trades: pd.DataFrame, timeframe: str) -> go.Figure: + trades: pd.DataFrame, timeframe: str, stake_currency: str) -> go.Figure: # Combine close-values for all pairs, rename columns to "pair" df_comb = combine_dataframes_with_mean(data, "close") @@ -466,8 +467,8 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame], subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"]) fig['layout'].update(title="Freqtrade Profit plot") fig['layout']['yaxis1'].update(title='Price') - fig['layout']['yaxis2'].update(title='Profit') - fig['layout']['yaxis3'].update(title='Profit') + fig['layout']['yaxis2'].update(title=f'Profit {stake_currency}') + fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}') fig['layout']['xaxis']['rangeslider'].update(visible=False) fig.add_trace(avgclose, 1, 1) @@ -540,8 +541,11 @@ def load_and_plot_trades(config: Dict[str, Any]): df_analyzed = strategy.analyze_ticker(data, {'pair': pair}) df_analyzed = trim_dataframe(df_analyzed, timerange) - trades_pair = trades.loc[trades['pair'] == pair] - trades_pair = extract_trades_of_period(df_analyzed, trades_pair) + if not trades.empty: + trades_pair = trades.loc[trades['pair'] == pair] + trades_pair = extract_trades_of_period(df_analyzed, trades_pair) + else: + trades_pair = trades fig = generate_candlestick_graph( pair=pair, @@ -581,6 +585,7 @@ def plot_profit(config: Dict[str, Any]) -> None: # Create an average close price of all the pairs that were involved. # this could be useful to gauge the overall market trend fig = generate_profit_graph(plot_elements['pairs'], plot_elements['ohlcv'], - trades, config.get('timeframe', '5m')) + trades, config.get('timeframe', '5m'), + config.get('stake_currency', '')) store_plot_file(fig, filename='freqtrade-profit-plot.html', directory=config['user_data_dir'] / 'plot', auto_open=True) diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py index 8a5379ca6..8f623b062 100644 --- a/freqtrade/plugins/pairlist/AgeFilter.py +++ b/freqtrade/plugins/pairlist/AgeFilter.py @@ -71,14 +71,14 @@ class AgeFilter(IPairList): daily_candles = candles[(p, '1d')] if (p, '1d') in candles else None if not self._validate_pair_loc(p, daily_candles): pairlist.remove(p) - logger.info(f"Validated {len(pairlist)} pairs.") + self.log_once(f"Validated {len(pairlist)} pairs.", logger.info) return pairlist def _validate_pair_loc(self, pair: str, daily_candles: Optional[DataFrame]) -> bool: """ Validate age for the ticker :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ # Check symbol in cache @@ -86,7 +86,7 @@ class AgeFilter(IPairList): return True if daily_candles is not None: - if len(daily_candles) > self._min_days_listed: + if len(daily_candles) >= self._min_days_listed: # We have fetched at least the minimum required number of daily candles # Add to cache, store the time we last checked this symbol self._symbolsChecked[pair] = int(arrow.utcnow().float_timestamp) * 1000 diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py index 184feff9e..74348b1a7 100644 --- a/freqtrade/plugins/pairlist/IPairList.py +++ b/freqtrade/plugins/pairlist/IPairList.py @@ -7,7 +7,7 @@ from copy import deepcopy from typing import Any, Dict, List from freqtrade.exceptions import OperationalException -from freqtrade.exchange import market_is_active +from freqtrade.exchange import Exchange, market_is_active from freqtrade.mixins import LoggingMixin @@ -16,7 +16,7 @@ logger = logging.getLogger(__name__) class IPairList(LoggingMixin, ABC): - def __init__(self, exchange, pairlistmanager, + def __init__(self, exchange: Exchange, pairlistmanager, config: Dict[str, Any], pairlistconfig: Dict[str, Any], pairlist_pos: int) -> None: """ @@ -28,7 +28,7 @@ class IPairList(LoggingMixin, ABC): """ self._enabled = True - self._exchange = exchange + self._exchange: Exchange = exchange self._pairlistmanager = pairlistmanager self._config = config self._pairlistconfig = pairlistconfig @@ -68,12 +68,12 @@ class IPairList(LoggingMixin, ABC): filter_pairlist() method. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ raise NotImplementedError() - def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist. @@ -84,8 +84,7 @@ class IPairList(LoggingMixin, ABC): it will raise the exception if a Pairlist Handler is used at the first position in the chain. - :param cached_pairlist: Previously generated pairlist (cached) - :param tickers: Tickers (from exchange.get_tickers()). + :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: List of pairs """ raise OperationalException("This Pairlist Handler should not be used " diff --git a/freqtrade/plugins/pairlist/PerformanceFilter.py b/freqtrade/plugins/pairlist/PerformanceFilter.py index 7d91bb77c..bf474cb21 100644 --- a/freqtrade/plugins/pairlist/PerformanceFilter.py +++ b/freqtrade/plugins/pairlist/PerformanceFilter.py @@ -2,7 +2,7 @@ Performance pair list filter """ import logging -from typing import Any, Dict, List +from typing import Dict, List import pandas as pd @@ -15,11 +15,6 @@ logger = logging.getLogger(__name__) class PerformanceFilter(IPairList): - def __init__(self, exchange, pairlistmanager, - config: Dict[str, Any], pairlistconfig: Dict[str, Any], - pairlist_pos: int) -> None: - super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) - @property def needstickers(self) -> bool: """ @@ -44,7 +39,12 @@ class PerformanceFilter(IPairList): :return: new allowlist """ # Get the trading performance for pairs from database - performance = pd.DataFrame(Trade.get_overall_performance()) + try: + performance = pd.DataFrame(Trade.get_overall_performance()) + except AttributeError: + # Performancefilter does not work in backtesting. + self.log_once("PerformanceFilter is not available in this mode.", logger.warning) + return pairlist # Skip performance-based sorting if no performance data is available if len(performance) == 0: diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py index 519337f29..a3c262e8c 100644 --- a/freqtrade/plugins/pairlist/PrecisionFilter.py +++ b/freqtrade/plugins/pairlist/PrecisionFilter.py @@ -48,7 +48,7 @@ class PrecisionFilter(IPairList): Check if pair has enough room to add a stoploss to avoid "unsellable" buys of very low value pairs. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ stop_price = ticker['ask'] * self._stoploss diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index a0579b196..5b5afb557 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -27,9 +27,13 @@ class PriceFilter(IPairList): self._max_price = pairlistconfig.get('max_price', 0) if self._max_price < 0: raise OperationalException("PriceFilter requires max_price to be >= 0") + self._max_value = pairlistconfig.get('max_value', 0) + if self._max_value < 0: + raise OperationalException("PriceFilter requires max_value to be >= 0") self._enabled = ((self._low_price_ratio > 0) or (self._min_price > 0) or - (self._max_price > 0)) + (self._max_price > 0) or + (self._max_value > 0)) @property def needstickers(self) -> bool: @@ -51,6 +55,8 @@ class PriceFilter(IPairList): active_price_filters.append(f"below {self._min_price:.8f}") if self._max_price != 0: active_price_filters.append(f"above {self._max_price:.8f}") + if self._max_value != 0: + active_price_filters.append(f"Value above {self._max_value:.8f}") if len(active_price_filters): return f"{self.name} - Filtering pairs priced {' or '.join(active_price_filters)}." @@ -61,7 +67,7 @@ class PriceFilter(IPairList): """ Check if if one price-step (pip) is > than a certain barrier. :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ if ticker.get('last', None) is None or ticker.get('last') == 0: @@ -79,6 +85,32 @@ class PriceFilter(IPairList): f"because 1 unit is {changeperc * 100:.3f}%", logger.info) return False + # Perform low_amount check + if self._max_value != 0: + price = ticker['last'] + market = self._exchange.markets[pair] + limits = market['limits'] + if ('amount' in limits and 'min' in limits['amount'] + and limits['amount']['min'] is not None): + min_amount = limits['amount']['min'] + min_precision = market['precision']['amount'] + + min_value = min_amount * price + if self._exchange.precisionMode == 4: + # tick size + next_value = (min_amount + min_precision) * price + else: + # Decimal places + min_precision = pow(0.1, min_precision) + next_value = (min_amount + min_precision) * price + diff = next_value - min_value + + if diff > self._max_value: + self.log_once(f"Removed {pair} from whitelist, " + f"because min value change of {diff} > {self._max_value}.", + logger.info) + return False + # Perform min_price check. if self._min_price != 0: if ticker['last'] < self._min_price: @@ -89,7 +121,7 @@ class PriceFilter(IPairList): # Perform max_price check. if self._max_price != 0: if ticker['last'] > self._max_price: - self.log_once(f"Removed {ticker['symbol']} from whitelist, " + self.log_once(f"Removed {pair} from whitelist, " f"because last price > {self._max_price:.8f}", logger.info) return False diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py index 9fa211750..1b152774b 100644 --- a/freqtrade/plugins/pairlist/SpreadFilter.py +++ b/freqtrade/plugins/pairlist/SpreadFilter.py @@ -40,7 +40,7 @@ class SpreadFilter(IPairList): """ Validate spread for the ticker :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ if 'bid' in ticker and 'ask' in ticker and ticker['ask']: diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py index c5ced48c9..d8623e13d 100644 --- a/freqtrade/plugins/pairlist/StaticPairList.py +++ b/freqtrade/plugins/pairlist/StaticPairList.py @@ -42,11 +42,10 @@ class StaticPairList(IPairList): """ return f"{self.name}" - def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist - :param cached_pairlist: Previously generated pairlist (cached) - :param tickers: Tickers (from exchange.get_tickers()). + :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: List of pairs """ if self._allow_inactive: diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py new file mode 100644 index 000000000..bc617a1db --- /dev/null +++ b/freqtrade/plugins/pairlist/VolatilityFilter.py @@ -0,0 +1,121 @@ +""" +Volatility pairlist filter +""" +import logging +import sys +from copy import deepcopy +from typing import Any, Dict, List, Optional + +import arrow +import numpy as np +from cachetools.ttl import TTLCache +from pandas import DataFrame + +from freqtrade.exceptions import OperationalException +from freqtrade.misc import plural +from freqtrade.plugins.pairlist.IPairList import IPairList + + +logger = logging.getLogger(__name__) + + +class VolatilityFilter(IPairList): + ''' + Filters pairs by volatility + ''' + + def __init__(self, exchange, pairlistmanager, + config: Dict[str, Any], pairlistconfig: Dict[str, Any], + pairlist_pos: int) -> None: + super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos) + + self._days = pairlistconfig.get('lookback_days', 10) + self._min_volatility = pairlistconfig.get('min_volatility', 0) + self._max_volatility = pairlistconfig.get('max_volatility', sys.maxsize) + self._refresh_period = pairlistconfig.get('refresh_period', 1440) + + self._pair_cache: TTLCache = TTLCache(maxsize=1000, ttl=self._refresh_period) + + if self._days < 1: + raise OperationalException("VolatilityFilter requires lookback_days to be >= 1") + if self._days > exchange.ohlcv_candle_limit('1d'): + raise OperationalException("VolatilityFilter requires lookback_days to not " + "exceed exchange max request size " + f"({exchange.ohlcv_candle_limit('1d')})") + + @property + def needstickers(self) -> bool: + """ + Boolean property defining if tickers are necessary. + If no Pairlist requires tickers, an empty List is passed + as tickers argument to filter_pairlist + """ + return False + + def short_desc(self) -> str: + """ + Short whitelist method description - used for startup-messages + """ + return (f"{self.name} - Filtering pairs with volatility range " + f"{self._min_volatility}-{self._max_volatility} " + f" the last {self._days} {plural(self._days, 'day')}.") + + def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]: + """ + Validate trading range + :param pairlist: pairlist to filter or sort + :param tickers: Tickers (from exchange.get_tickers()). May be cached. + :return: new allowlist + """ + needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache] + + since_ms = int(arrow.utcnow() + .floor('day') + .shift(days=-self._days - 1) + .float_timestamp) * 1000 + # Get all candles + candles = {} + if needed_pairs: + candles = self._exchange.refresh_latest_ohlcv(needed_pairs, since_ms=since_ms, + cache=False) + + if self._enabled: + for p in deepcopy(pairlist): + daily_candles = candles[(p, '1d')] if (p, '1d') in candles else None + if not self._validate_pair_loc(p, daily_candles): + pairlist.remove(p) + return pairlist + + def _validate_pair_loc(self, pair: str, daily_candles: Optional[DataFrame]) -> bool: + """ + Validate trading range + :param pair: Pair that's currently validated + :param ticker: ticker dict as returned from ccxt.fetch_tickers() + :return: True if the pair can stay, false if it should be removed + """ + # Check symbol in cache + cached_res = self._pair_cache.get(pair, None) + if cached_res is not None: + return cached_res + + result = False + if daily_candles is not None and not daily_candles.empty: + returns = (np.log(daily_candles.close / daily_candles.close.shift(-1))) + returns.fillna(0, inplace=True) + + volatility_series = returns.rolling(window=self._days).std()*np.sqrt(self._days) + volatility_avg = volatility_series.mean() + + if self._min_volatility <= volatility_avg <= self._max_volatility: + result = True + else: + self.log_once(f"Removed {pair} from whitelist, because volatility " + f"over {self._days} {plural(self._days, 'day')} " + f"is: {volatility_avg:.3f} " + f"which is not in the configured range of " + f"{self._min_volatility}-{self._max_volatility}.", + logger.info) + result = False + self._pair_cache[pair] = result + + return result diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py index dd8fc64fd..8eff137b0 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -4,9 +4,10 @@ Volume PairList provider Provides dynamic pair list based on trade volumes """ import logging -from datetime import datetime from typing import Any, Dict, List +from cachetools.ttl import TTLCache + from freqtrade.exceptions import OperationalException from freqtrade.plugins.pairlist.IPairList import IPairList @@ -33,7 +34,8 @@ class VolumePairList(IPairList): self._number_pairs = self._pairlistconfig['number_assets'] self._sort_key = self._pairlistconfig.get('sort_key', 'quoteVolume') self._min_value = self._pairlistconfig.get('min_value', 0) - self.refresh_period = self._pairlistconfig.get('refresh_period', 1800) + self._refresh_period = self._pairlistconfig.get('refresh_period', 1800) + self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period) if not self._exchange.exchange_has('fetchTickers'): raise OperationalException( @@ -63,17 +65,19 @@ class VolumePairList(IPairList): """ return f"{self.name} - top {self._pairlistconfig['number_assets']} volume pairs." - def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]: + def gen_pairlist(self, tickers: Dict) -> List[str]: """ Generate the pairlist - :param cached_pairlist: Previously generated pairlist (cached) - :param tickers: Tickers (from exchange.get_tickers()). + :param tickers: Tickers (from exchange.get_tickers()). May be cached. :return: List of pairs """ # Generate dynamic whitelist # Must always run if this pairlist is not the first in the list. - if self._last_refresh + self.refresh_period < datetime.now().timestamp(): - self._last_refresh = int(datetime.now().timestamp()) + pairlist = self._pair_cache.get('pairlist') + if pairlist: + # Item found - no refresh necessary + return pairlist + else: # Use fresh pairlist # Check if pair quote currency equals to the stake currency. @@ -82,9 +86,9 @@ class VolumePairList(IPairList): if (self._exchange.get_pair_quote_currency(k) == self._stake_currency and v[self._sort_key] is not None)] pairlist = [s['symbol'] for s in filtered_tickers] - else: - # Use the cached pairlist if it's not time yet to refresh - pairlist = cached_pairlist + + pairlist = self.filter_pairlist(pairlist, tickers) + self._pair_cache['pairlist'] = pairlist return pairlist diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py index a1430a223..8be61166b 100644 --- a/freqtrade/plugins/pairlist/rangestabilityfilter.py +++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py @@ -83,12 +83,13 @@ class RangeStabilityFilter(IPairList): """ Validate trading range :param pair: Pair that's currently validated - :param ticker: ticker dict as returned from ccxt.load_markets() + :param ticker: ticker dict as returned from ccxt.fetch_tickers() :return: True if the pair can stay, false if it should be removed """ # Check symbol in cache - if pair in self._pair_cache: - return self._pair_cache[pair] + cached_res = self._pair_cache.get(pair, None) + if cached_res is not None: + return cached_res result = False if daily_candles is not None and not daily_candles.empty: diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index 4e4135981..d1cdd2c5b 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -3,7 +3,7 @@ PairList manager class """ import logging from copy import deepcopy -from typing import Any, Dict, List +from typing import Dict, List from cachetools import TTLCache, cached @@ -79,11 +79,8 @@ class PairListManager(): if self._tickers_needed: tickers = self._get_cached_tickers() - # Adjust whitelist if filters are using tickers - pairlist = self._prepare_whitelist(self._whitelist.copy(), tickers) - # Generate the pairlist with first Pairlist Handler in the chain - pairlist = self._pairlist_handlers[0].gen_pairlist(self._whitelist, tickers) + pairlist = self._pairlist_handlers[0].gen_pairlist(tickers) # Process all Pairlist Handlers in the chain for pairlist_handler in self._pairlist_handlers: @@ -95,19 +92,6 @@ class PairListManager(): self._whitelist = pairlist - def _prepare_whitelist(self, pairlist: List[str], tickers: Dict[str, Any]) -> List[str]: - """ - Prepare sanitized pairlist for Pairlist Handlers that use tickers data - remove - pairs that do not have ticker available - """ - if self._tickers_needed: - # Copy list since we're modifying this list - for p in deepcopy(pairlist): - if p not in tickers: - pairlist.remove(p) - - return pairlist - def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]: """ Verify and remove items from pairlist - returning a filtered pairlist. diff --git a/freqtrade/plugins/protections/cooldown_period.py b/freqtrade/plugins/protections/cooldown_period.py index f74f83885..a2d8eca34 100644 --- a/freqtrade/plugins/protections/cooldown_period.py +++ b/freqtrade/plugins/protections/cooldown_period.py @@ -1,7 +1,6 @@ import logging from datetime import datetime, timedelta -from typing import Any, Dict from freqtrade.persistence import Trade from freqtrade.plugins.protections import IProtection, ProtectionReturn @@ -15,9 +14,6 @@ class CooldownPeriod(IProtection): has_global_stop: bool = False has_local_stop: bool = True - def __init__(self, config: Dict[str, Any], protection_config: Dict[str, Any]) -> None: - super().__init__(config, protection_config) - def _reason(self) -> str: """ LockReason to use diff --git a/freqtrade/plugins/protections/max_drawdown_protection.py b/freqtrade/plugins/protections/max_drawdown_protection.py index d1c6b192d..67e204039 100644 --- a/freqtrade/plugins/protections/max_drawdown_protection.py +++ b/freqtrade/plugins/protections/max_drawdown_protection.py @@ -61,7 +61,7 @@ class MaxDrawdown(IProtection): if drawdown > self._max_allowed_drawdown: self.log_once( - f"Trading stopped due to Max Drawdown {drawdown:.2f} < {self._max_allowed_drawdown}" + f"Trading stopped due to Max Drawdown {drawdown:.2f} > {self._max_allowed_drawdown}" f" within {self.lookback_period_str}.", logger.info) until = self.calculate_lock_end(trades, self._stop_duration) diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index 37cfd70e6..b51795e9e 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -61,7 +61,7 @@ class IResolver: module = importlib.util.module_from_spec(spec) try: spec.loader.exec_module(module) # type: ignore # importlib does not use typehints - except (ModuleNotFoundError, SyntaxError, ImportError) as err: + except (ModuleNotFoundError, SyntaxError, ImportError, NameError) as err: # Catch errors in case a specific module is not installed logger.warning(f"Could not import {module_path} due to '{err}'") if enum_failed: diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py index b1b66e3ae..05fbac10d 100644 --- a/freqtrade/resolvers/strategy_resolver.py +++ b/freqtrade/resolvers/strategy_resolver.py @@ -196,9 +196,9 @@ class StrategyResolver(IResolver): strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args) strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args) strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args) - if any([x == 2 for x in [strategy._populate_fun_len, - strategy._buy_fun_len, - strategy._sell_fun_len]]): + if any(x == 2 for x in [strategy._populate_fun_len, + strategy._buy_fun_len, + strategy._sell_fun_len]): strategy.INTERFACE_VERSION = 1 return strategy diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py index 32a1c8597..4d06d3ecf 100644 --- a/freqtrade/rpc/api_server/api_schemas.py +++ b/freqtrade/rpc/api_server/api_schemas.py @@ -57,6 +57,7 @@ class Count(BaseModel): class PerformanceEntry(BaseModel): pair: str profit: float + profit_abs: float count: int @@ -151,13 +152,11 @@ class TradeSchema(BaseModel): fee_close: Optional[float] fee_close_cost: Optional[float] fee_close_currency: Optional[str] - open_date_hum: str open_date: str open_timestamp: int open_rate: float open_rate_requested: Optional[float] open_trade_value: float - close_date_hum: Optional[str] close_date: Optional[str] close_timestamp: Optional[int] close_rate: Optional[float] @@ -168,6 +167,7 @@ class TradeSchema(BaseModel): profit_ratio: Optional[float] profit_pct: Optional[float] profit_abs: Optional[float] + profit_fiat: Optional[float] sell_reason: Optional[str] sell_order_status: Optional[str] stop_loss_abs: Optional[float] @@ -190,7 +190,6 @@ class OpenTradeSchema(TradeSchema): stoploss_current_dist_ratio: Optional[float] stoploss_entry_dist: Optional[float] stoploss_entry_dist_ratio: Optional[float] - base_currency: str current_profit: float current_profit_abs: float current_profit_pct: float @@ -201,6 +200,7 @@ class OpenTradeSchema(TradeSchema): class TradeResponse(BaseModel): trades: List[TradeSchema] trades_count: int + total_trades: int class ForceBuyResponse(BaseModel): @@ -269,7 +269,7 @@ class DeleteTrade(BaseModel): class PlotConfig_(BaseModel): main_plot: Dict[str, Any] - subplots: Optional[Dict[str, Any]] + subplots: Dict[str, Any] class PlotConfig(BaseModel): diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index b983402e9..e907b92f0 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -17,8 +17,7 @@ from freqtrade.rpc.api_server.api_schemas import (AvailablePairs, Balances, Blac OpenTradeSchema, PairHistory, PerformanceEntry, Ping, PlotConfig, Profit, ResultMsg, ShowConfig, Stats, StatusMsg, StrategyListResponse, - StrategyResponse, TradeResponse, Version, - WhitelistResponse) + StrategyResponse, Version, WhitelistResponse) from freqtrade.rpc.api_server.deps import get_config, get_rpc, get_rpc_optional from freqtrade.rpc.rpc import RPCException @@ -83,9 +82,19 @@ def status(rpc: RPC = Depends(get_rpc)): return [] -@router.get('/trades', response_model=TradeResponse, tags=['info', 'trading']) -def trades(limit: int = 0, rpc: RPC = Depends(get_rpc)): - return rpc._rpc_trade_history(limit) +# Using the responsemodel here will cause a ~100% increase in response time (from 1s to 2s) +# on big databases. Correct response model: response_model=TradeResponse, +@router.get('/trades', tags=['info', 'trading']) +def trades(limit: int = 500, offset: int = 0, rpc: RPC = Depends(get_rpc)): + return rpc._rpc_trade_history(limit, offset=offset, order_by_id=True) + + +@router.get('/trade/{tradeid}', response_model=OpenTradeSchema, tags=['info', 'trading']) +def trade(tradeid: int = 0, rpc: RPC = Depends(get_rpc)): + try: + return rpc._rpc_trade_status([tradeid])[0] + except (RPCException, KeyError): + raise HTTPException(status_code=404, detail='Trade not found.') @router.delete('/trades/{tradeid}', response_model=DeleteTrade, tags=['info', 'trading']) diff --git a/freqtrade/rpc/api_server/web_ui.py b/freqtrade/rpc/api_server/web_ui.py index 13d22a63e..a8c737e04 100644 --- a/freqtrade/rpc/api_server/web_ui.py +++ b/freqtrade/rpc/api_server/web_ui.py @@ -13,6 +13,11 @@ async def favicon(): return FileResponse(str(Path(__file__).parent / 'ui/favicon.ico')) +@router_ui.get('/fallback_file.html', include_in_schema=False) +async def fallback(): + return FileResponse(str(Path(__file__).parent / 'ui/fallback_file.html')) + + @router_ui.get('/{rest_of_path:path}', include_in_schema=False) async def index_html(rest_of_path: str): """ diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py index 4e26432d4..5ae20afa1 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -3,11 +3,13 @@ Module that define classes to convert Crypto-currency to FIAT e.g BTC to USD """ +import datetime import logging -import time -from typing import Dict, List +from typing import Dict +from cachetools.ttl import TTLCache from pycoingecko import CoinGeckoAPI +from requests.exceptions import RequestException from freqtrade.constants import SUPPORTED_FIAT @@ -15,51 +17,6 @@ from freqtrade.constants import SUPPORTED_FIAT logger = logging.getLogger(__name__) -class CryptoFiat: - """ - Object to describe what is the price of Crypto-currency in a FIAT - """ - # Constants - CACHE_DURATION = 6 * 60 * 60 # 6 hours - - def __init__(self, crypto_symbol: str, fiat_symbol: str, price: float) -> None: - """ - Create an object that will contains the price for a crypto-currency in fiat - :param crypto_symbol: Crypto-currency you want to convert (e.g BTC) - :param fiat_symbol: FIAT currency you want to convert to (e.g USD) - :param price: Price in FIAT - """ - - # Public attributes - self.crypto_symbol = None - self.fiat_symbol = None - self.price = 0.0 - - # Private attributes - self._expiration = 0.0 - - self.crypto_symbol = crypto_symbol.lower() - self.fiat_symbol = fiat_symbol.lower() - self.set_price(price=price) - - def set_price(self, price: float) -> None: - """ - Set the price of the Crypto-currency in FIAT and set the expiration time - :param price: Price of the current Crypto currency in the fiat - :return: None - """ - self.price = price - self._expiration = time.time() + self.CACHE_DURATION - - def is_expired(self) -> bool: - """ - Return if the current price is still valid or needs to be refreshed - :return: bool, true the price is expired and needs to be refreshed, false the price is - still valid - """ - return self._expiration - time.time() <= 0 - - class CryptoToFiatConverter: """ Main class to initiate Crypto to FIAT. @@ -70,6 +27,7 @@ class CryptoToFiatConverter: _coingekko: CoinGeckoAPI = None _cryptomap: Dict = {} + _backoff: float = 0.0 def __new__(cls): """ @@ -84,14 +42,29 @@ class CryptoToFiatConverter: return CryptoToFiatConverter.__instance def __init__(self) -> None: - self._pairs: List[CryptoFiat] = [] + # Timeout: 6h + self._pair_price: TTLCache = TTLCache(maxsize=500, ttl=6 * 60 * 60) + self._load_cryptomap() def _load_cryptomap(self) -> None: try: coinlistings = self._coingekko.get_coins_list() - # Create mapping table from synbol to coingekko_id + # Create mapping table from symbol to coingekko_id self._cryptomap = {x['symbol']: x['id'] for x in coinlistings} + except RequestException as request_exception: + if "429" in str(request_exception): + logger.warning( + "Too many requests for Coingecko API, backing off and trying again later.") + # Set backoff timestamp to 60 seconds in the future + self._backoff = datetime.datetime.now().timestamp() + 60 + return + # If the request is not a 429 error we want to raise the normal error + logger.error( + "Could not load FIAT Cryptocurrency map for the following problem: {}".format( + request_exception + ) + ) except (Exception) as exception: logger.error( f"Could not load FIAT Cryptocurrency map for the following problem: {exception}") @@ -118,49 +91,31 @@ class CryptoToFiatConverter: """ crypto_symbol = crypto_symbol.lower() fiat_symbol = fiat_symbol.lower() + inverse = False + if crypto_symbol == 'usd': + # usd corresponds to "uniswap-state-dollar" for coingecko. + # We'll therefore need to "swap" the currencies + logger.info(f"reversing Rates {crypto_symbol}, {fiat_symbol}") + crypto_symbol = fiat_symbol + fiat_symbol = 'usd' + inverse = True + + symbol = f"{crypto_symbol}/{fiat_symbol}" # Check if the fiat convertion you want is supported if not self._is_supported_fiat(fiat=fiat_symbol): raise ValueError(f'The fiat {fiat_symbol} is not supported.') - # Get the pair that interest us and return the price in fiat - for pair in self._pairs: - if pair.crypto_symbol == crypto_symbol and pair.fiat_symbol == fiat_symbol: - # If the price is expired we refresh it, avoid to call the API all the time - if pair.is_expired(): - pair.set_price( - price=self._find_price( - crypto_symbol=pair.crypto_symbol, - fiat_symbol=pair.fiat_symbol - ) - ) + price = self._pair_price.get(symbol, None) - # return the last price we have for this pair - return pair.price - - # The pair does not exist, so we create it and return the price - return self._add_pair( - crypto_symbol=crypto_symbol, - fiat_symbol=fiat_symbol, - price=self._find_price( + if not price: + price = self._find_price( crypto_symbol=crypto_symbol, fiat_symbol=fiat_symbol ) - ) - - def _add_pair(self, crypto_symbol: str, fiat_symbol: str, price: float) -> float: - """ - :param crypto_symbol: Crypto-currency you want to convert (e.g BTC) - :param fiat_symbol: FIAT currency you want to convert to (e.g USD) - :return: price in FIAT - """ - self._pairs.append( - CryptoFiat( - crypto_symbol=crypto_symbol, - fiat_symbol=fiat_symbol, - price=price - ) - ) + if inverse and price != 0.0: + price = 1 / price + self._pair_price[symbol] = price return price @@ -188,6 +143,15 @@ class CryptoToFiatConverter: if crypto_symbol == fiat_symbol: return 1.0 + if self._cryptomap == {}: + if self._backoff <= datetime.datetime.now().timestamp(): + self._load_cryptomap() + # return 0.0 if we still dont have data to check, no reason to proceed + if self._cryptomap == {}: + return 0.0 + else: + return 0.0 + if crypto_symbol not in self._cryptomap: # return 0 for unsupported stake currencies (fiat-convert should not break the bot) logger.warning("unsupported crypto-symbol %s - returning 0.0", crypto_symbol) diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 62f1c2592..3f26619a9 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -24,20 +24,22 @@ from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.rpc.fiat_convert import CryptoToFiatConverter from freqtrade.state import State -from freqtrade.strategy.interface import SellType +from freqtrade.strategy.interface import SellCheckTuple, SellType logger = logging.getLogger(__name__) class RPCMessageType(Enum): - STATUS_NOTIFICATION = 'status' - WARNING_NOTIFICATION = 'warning' - STARTUP_NOTIFICATION = 'startup' - BUY_NOTIFICATION = 'buy' - BUY_CANCEL_NOTIFICATION = 'buy_cancel' - SELL_NOTIFICATION = 'sell' - SELL_CANCEL_NOTIFICATION = 'sell_cancel' + STATUS = 'status' + WARNING = 'warning' + STARTUP = 'startup' + BUY = 'buy' + BUY_FILL = 'buy_fill' + BUY_CANCEL = 'buy_cancel' + SELL = 'sell' + SELL_FILL = 'sell_fill' + SELL_CANCEL = 'sell_cancel' def __repr__(self): return self.value @@ -167,12 +169,24 @@ class RPC: if trade.open_order_id: order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair) # calculate profit and send message to user - try: - current_rate = self._freqtrade.get_sell_rate(trade.pair, False) - except (ExchangeError, PricingError): - current_rate = NAN + if trade.is_open: + try: + current_rate = self._freqtrade.get_sell_rate(trade.pair, False) + except (ExchangeError, PricingError): + current_rate = NAN + else: + current_rate = trade.close_rate current_profit = trade.calc_profit_ratio(current_rate) current_profit_abs = trade.calc_profit(current_rate) + current_profit_fiat: Optional[float] = None + # Calculate fiat profit + if self._fiat_converter: + current_profit_fiat = self._fiat_converter.convert_amount( + current_profit_abs, + self._freqtrade.config['stake_currency'], + self._freqtrade.config['fiat_display_currency'] + ) + # Calculate guaranteed profit (in case of trailing stop) stoploss_entry_dist = trade.calc_profit(trade.stop_loss) stoploss_entry_dist_ratio = trade.calc_profit_ratio(trade.stop_loss) @@ -191,6 +205,7 @@ class RPC: profit_ratio=current_profit, profit_pct=round(current_profit * 100, 2), profit_abs=current_profit_abs, + profit_fiat=current_profit_fiat, stoploss_current_dist=stoploss_current_dist, stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8), @@ -205,12 +220,13 @@ class RPC: return results def _rpc_status_table(self, stake_currency: str, - fiat_display_currency: str) -> Tuple[List, List]: + fiat_display_currency: str) -> Tuple[List, List, float]: trades = Trade.get_open_trades() if not trades: raise RPCException('no active trade') else: trades_list = [] + fiat_profit_sum = NAN for trade in trades: # calculate profit and send message to user try: @@ -228,6 +244,8 @@ class RPC: ) if fiat_profit and not isnan(fiat_profit): profit_str += f" ({fiat_profit:.2f})" + fiat_profit_sum = fiat_profit if isnan(fiat_profit_sum) \ + else fiat_profit_sum + fiat_profit trades_list.append([ trade.id, trade.pair + ('*' if (trade.open_order_id is not None @@ -241,7 +259,7 @@ class RPC: profitcol += " (" + fiat_display_currency + ")" columns = ['ID', 'Pair', 'Since', profitcol] - return trades_list, columns + return trades_list, columns, fiat_profit_sum def _rpc_daily_profit( self, timescale: int, @@ -285,11 +303,12 @@ class RPC: 'data': data } - def _rpc_trade_history(self, limit: int) -> Dict: + def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict: """ Returns the X last trades """ - if limit > 0: + order_by = Trade.id if order_by_id else Trade.close_date.desc() + if limit: trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( - Trade.close_date.desc()).limit(limit) + order_by).limit(limit).offset(offset) else: trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( Trade.close_date.desc()).all() @@ -298,7 +317,8 @@ class RPC: return { "trades": output, - "trades_count": len(output) + "trades_count": len(output), + "total_trades": Trade.get_trades([Trade.is_open.is_(False)]).count(), } def _rpc_stats(self) -> Dict[str, Any]: @@ -432,7 +452,7 @@ class RPC: output = [] total = 0.0 try: - tickers = self._freqtrade.exchange.get_tickers() + tickers = self._freqtrade.exchange.get_tickers(cached=True) except (ExchangeError): raise RPCException('Error getting current tickers.') @@ -537,7 +557,8 @@ class RPC: if not fully_canceled: # Get current rate and execute sell current_rate = self._freqtrade.get_sell_rate(trade.pair, False) - self._freqtrade.execute_sell(trade, current_rate, SellType.FORCE_SELL) + sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL) + self._freqtrade.execute_sell(trade, current_rate, sell_reason) # ---- EOF def _exec_forcesell ---- if self._freqtrade.state != State.RUNNING: @@ -548,7 +569,7 @@ class RPC: # Execute sell for all open orders for trade in Trade.get_open_trades(): _exec_forcesell(trade) - Trade.session.flush() + Trade.query.session.flush() self._freqtrade.wallets.update() return {'result': 'Created sell orders for all open trades.'} @@ -561,7 +582,7 @@ class RPC: raise RPCException('invalid argument') _exec_forcesell(trade) - Trade.session.flush() + Trade.query.session.flush() self._freqtrade.wallets.update() return {'result': f'Created sell order for trade {trade_id}.'} @@ -590,8 +611,7 @@ class RPC: raise RPCException(f'position for {pair} already open - id: {trade.id}') # gen stake amount - stakeamount = self._freqtrade.wallets.get_trade_stake_amount( - pair, self._freqtrade.get_free_open_trades()) + stakeamount = self._freqtrade.wallets.get_trade_stake_amount(pair) # execute buy if self._freqtrade.execute_buy(pair, stakeamount, price, forcebuy=True): @@ -686,7 +706,7 @@ class RPC: lock.lock_end_time = datetime.now(timezone.utc) # session is always the same - PairLock.session.flush() + PairLock.query.session.flush() return self._rpc_locks() @@ -828,5 +848,7 @@ class RPC: df_analyzed, arrow.Arrow.utcnow().datetime) def _rpc_plot_config(self) -> Dict[str, Any]: - + if (self._freqtrade.strategy.plot_config and + 'subplots' not in self._freqtrade.strategy.plot_config): + self._freqtrade.strategy.plot_config['subplots'] = {} return self._freqtrade.strategy.plot_config diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py index 7977d68de..f819b55b4 100644 --- a/freqtrade/rpc/rpc_manager.py +++ b/freqtrade/rpc/rpc_manager.py @@ -67,7 +67,7 @@ class RPCManager: def startup_messages(self, config: Dict[str, Any], pairlist, protections) -> None: if config['dry_run']: self.send_msg({ - 'type': RPCMessageType.WARNING_NOTIFICATION, + 'type': RPCMessageType.WARNING, 'status': 'Dry run is enabled. All trades are simulated.' }) stake_currency = config['stake_currency'] @@ -79,7 +79,7 @@ class RPCManager: exchange_name = config['exchange']['name'] strategy_name = config.get('strategy', '') self.send_msg({ - 'type': RPCMessageType.STARTUP_NOTIFICATION, + 'type': RPCMessageType.STARTUP, 'status': f'*Exchange:* `{exchange_name}`\n' f'*Stake per trade:* `{stake_amount} {stake_currency}`\n' f'*Minimum ROI:* `{minimal_roi}`\n' @@ -88,13 +88,13 @@ class RPCManager: f'*Strategy:* `{strategy_name}`' }) self.send_msg({ - 'type': RPCMessageType.STARTUP_NOTIFICATION, + 'type': RPCMessageType.STARTUP, 'status': f'Searching for {stake_currency} pairs to buy and sell ' f'based on {pairlist.short_desc()}' }) if len(protections.name_list) > 0: prots = '\n'.join([p for prot in protections.short_desc() for k, p in prot.items()]) self.send_msg({ - 'type': RPCMessageType.STARTUP_NOTIFICATION, + 'type': RPCMessageType.STARTUP, 'status': f'Using Protections: \n{prots}' }) diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py index 0d978cc6e..b9e90dc8d 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -8,6 +8,7 @@ import logging from datetime import timedelta from html import escape from itertools import chain +from math import isnan from typing import Any, Callable, Dict, List, Optional, Union, cast import arrow @@ -21,7 +22,7 @@ from telegram.utils.helpers import escape_markdown from freqtrade.__init__ import __version__ from freqtrade.constants import DUST_PER_COIN from freqtrade.exceptions import OperationalException -from freqtrade.misc import round_coin_value +from freqtrade.misc import chunks, round_coin_value from freqtrade.rpc import RPC, RPCException, RPCHandler, RPCMessageType @@ -160,10 +161,10 @@ class Telegram(RPCHandler): for handle in handles: self._updater.dispatcher.add_handler(handle) self._updater.start_polling( - clean=True, bootstrap_retries=-1, timeout=30, read_latency=60, + drop_pending_updates=True, ) logger.info( 'rpc.telegram is listening for following commands: %s', @@ -182,6 +183,53 @@ class Telegram(RPCHandler): """ self._updater.stop() + def _format_buy_msg(self, msg: Dict[str, Any]) -> str: + if self._rpc._fiat_converter: + msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount( + msg['stake_amount'], msg['stake_currency'], msg['fiat_currency']) + else: + msg['stake_amount_fiat'] = 0 + + message = (f"\N{LARGE BLUE CIRCLE} *{msg['exchange']}:* Buying {msg['pair']}" + f" (#{msg['trade_id']})\n" + f"*Amount:* `{msg['amount']:.8f}`\n" + f"*Open Rate:* `{msg['limit']:.8f}`\n" + f"*Current Rate:* `{msg['current_rate']:.8f}`\n" + f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}") + + if msg.get('fiat_currency', None): + message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}" + message += ")`" + return message + + def _format_sell_msg(self, msg: Dict[str, Any]) -> str: + msg['amount'] = round(msg['amount'], 8) + msg['profit_percent'] = round(msg['profit_ratio'] * 100, 2) + msg['duration'] = msg['close_date'].replace( + microsecond=0) - msg['open_date'].replace(microsecond=0) + msg['duration_min'] = msg['duration'].total_seconds() / 60 + + msg['emoji'] = self._get_sell_emoji(msg) + + message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n" + "*Amount:* `{amount:.8f}`\n" + "*Open Rate:* `{open_rate:.8f}`\n" + "*Current Rate:* `{current_rate:.8f}`\n" + "*Close Rate:* `{limit:.8f}`\n" + "*Sell Reason:* `{sell_reason}`\n" + "*Duration:* `{duration} ({duration_min:.1f} min)`\n" + "*Profit:* `{profit_percent:.2f}%`").format(**msg) + + # Check if all sell properties are available. + # This might not be the case if the message origin is triggered by /forcesell + if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency']) + and self._rpc._fiat_converter): + msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount( + msg['profit_amount'], msg['stake_currency'], msg['fiat_currency']) + message += (' `({gain}: {profit_amount:.8f} {stake_currency}' + ' / {profit_fiat:.3f} {fiat_currency})`').format(**msg) + return message + def send_msg(self, msg: Dict[str, Any]) -> None: """ Send a message to telegram channel """ @@ -192,67 +240,33 @@ class Telegram(RPCHandler): # Notification disabled return - if msg['type'] == RPCMessageType.BUY_NOTIFICATION: - if self._rpc._fiat_converter: - msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount( - msg['stake_amount'], msg['stake_currency'], msg['fiat_currency']) - else: - msg['stake_amount_fiat'] = 0 + if msg['type'] == RPCMessageType.BUY: + message = self._format_buy_msg(msg) - message = (f"\N{LARGE BLUE CIRCLE} *{msg['exchange']}:* Buying {msg['pair']}" - f" (#{msg['trade_id']})\n" - f"*Amount:* `{msg['amount']:.8f}`\n" - f"*Open Rate:* `{msg['limit']:.8f}`\n" - f"*Current Rate:* `{msg['current_rate']:.8f}`\n" - f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}") - - if msg.get('fiat_currency', None): - message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}" - message += ")`" - - elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION: + elif msg['type'] in (RPCMessageType.BUY_CANCEL, RPCMessageType.SELL_CANCEL): + msg['message_side'] = 'buy' if msg['type'] == RPCMessageType.BUY_CANCEL else 'sell' message = ("\N{WARNING SIGN} *{exchange}:* " - "Cancelling open buy Order for {pair} (#{trade_id}). " + "Cancelling open {message_side} Order for {pair} (#{trade_id}). " "Reason: {reason}.".format(**msg)) - elif msg['type'] == RPCMessageType.SELL_NOTIFICATION: - msg['amount'] = round(msg['amount'], 8) - msg['profit_percent'] = round(msg['profit_ratio'] * 100, 2) - msg['duration'] = msg['close_date'].replace( - microsecond=0) - msg['open_date'].replace(microsecond=0) - msg['duration_min'] = msg['duration'].total_seconds() / 60 + elif msg['type'] == RPCMessageType.BUY_FILL: + message = ("\N{LARGE CIRCLE} *{exchange}:* " + "Buy order for {pair} (#{trade_id}) filled " + "for {open_rate}.".format(**msg)) + elif msg['type'] == RPCMessageType.SELL_FILL: + message = ("\N{LARGE CIRCLE} *{exchange}:* " + "Sell order for {pair} (#{trade_id}) filled " + "for {close_rate}.".format(**msg)) + elif msg['type'] == RPCMessageType.SELL: + message = self._format_sell_msg(msg) - msg['emoji'] = self._get_sell_emoji(msg) - - message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n" - "*Amount:* `{amount:.8f}`\n" - "*Open Rate:* `{open_rate:.8f}`\n" - "*Current Rate:* `{current_rate:.8f}`\n" - "*Close Rate:* `{limit:.8f}`\n" - "*Sell Reason:* `{sell_reason}`\n" - "*Duration:* `{duration} ({duration_min:.1f} min)`\n" - "*Profit:* `{profit_percent:.2f}%`").format(**msg) - - # Check if all sell properties are available. - # This might not be the case if the message origin is triggered by /forcesell - if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency']) - and self._rpc._fiat_converter): - msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount( - msg['profit_amount'], msg['stake_currency'], msg['fiat_currency']) - message += (' `({gain}: {profit_amount:.8f} {stake_currency}' - ' / {profit_fiat:.3f} {fiat_currency})`').format(**msg) - - elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION: - message = ("\N{WARNING SIGN} *{exchange}:* Cancelling Open Sell Order " - "for {pair} (#{trade_id}). Reason: {reason}").format(**msg) - - elif msg['type'] == RPCMessageType.STATUS_NOTIFICATION: + elif msg['type'] == RPCMessageType.STATUS: message = '*Status:* `{status}`'.format(**msg) - elif msg['type'] == RPCMessageType.WARNING_NOTIFICATION: + elif msg['type'] == RPCMessageType.WARNING: message = '\N{WARNING SIGN} *Warning:* `{status}`'.format(**msg) - elif msg['type'] == RPCMessageType.STARTUP_NOTIFICATION: + elif msg['type'] == RPCMessageType.STARTUP: message = '{status}'.format(**msg) else: @@ -300,6 +314,7 @@ class Telegram(RPCHandler): messages = [] for r in results: + r['open_date_hum'] = arrow.get(r['open_date']).humanize() lines = [ "*Trade ID:* `{trade_id}` `(since {open_date_hum})`", "*Current Pair:* {pair}", @@ -346,19 +361,31 @@ class Telegram(RPCHandler): :return: None """ try: - statlist, head = self._rpc._rpc_status_table( - self._config['stake_currency'], self._config.get('fiat_display_currency', '')) + fiat_currency = self._config.get('fiat_display_currency', '') + statlist, head, fiat_profit_sum = self._rpc._rpc_status_table( + self._config['stake_currency'], fiat_currency) + show_total = not isnan(fiat_profit_sum) and len(statlist) > 1 max_trades_per_msg = 50 """ Calculate the number of messages of 50 trades per message 0.99 is used to make sure that there are no extra (empty) messages As an example with 50 trades, there will be int(50/50 + 0.99) = 1 message """ - for i in range(0, max(int(len(statlist) / max_trades_per_msg + 0.99), 1)): - message = tabulate(statlist[i * max_trades_per_msg:(i + 1) * max_trades_per_msg], + messages_count = max(int(len(statlist) / max_trades_per_msg + 0.99), 1) + for i in range(0, messages_count): + trades = statlist[i * max_trades_per_msg:(i + 1) * max_trades_per_msg] + if show_total and i == messages_count - 1: + # append total line + trades.append(["Total", "", "", f"{fiat_profit_sum:.2f} {fiat_currency}"]) + + message = tabulate(trades, headers=head, tablefmt='simple') + if show_total and i == messages_count - 1: + # insert separators line between Total + lines = message.split("\n") + message = "\n".join(lines[:-1] + [lines[1]] + [lines[-1]]) self._send_msg(f"
{message}
", parse_mode=ParseMode.HTML) except RPCException as e: self._send_msg(str(e)) @@ -723,14 +750,21 @@ class Telegram(RPCHandler): """ try: trades = self._rpc._rpc_performance() - stats = '\n'.join('{index}.\t{pair}\t{profit:.2f}% ({count})'.format( - index=i + 1, - pair=trade['pair'], - profit=trade['profit'], - count=trade['count'] - ) for i, trade in enumerate(trades)) - message = 'Performance:\n{}'.format(stats) - self._send_msg(message, parse_mode=ParseMode.HTML) + output = "Performance:\n" + for i, trade in enumerate(trades): + stat_line = ( + f"{i+1}.\t {trade['pair']}\t" + f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} " + f"({trade['profit']:.2f}%) " + f"({trade['count']})\n") + + if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH: + self._send_msg(output, parse_mode=ParseMode.HTML) + output = stat_line + else: + output += stat_line + + self._send_msg(output, parse_mode=ParseMode.HTML) except RPCException as e: self._send_msg(str(e)) @@ -760,17 +794,21 @@ class Telegram(RPCHandler): Handler for /locks. Returns the currently active locks """ - locks = self._rpc._rpc_locks() - message = tabulate([[ - lock['id'], - lock['pair'], - lock['lock_end_time'], - lock['reason']] for lock in locks['locks']], - headers=['ID', 'Pair', 'Until', 'Reason'], - tablefmt='simple') - message = f"
{escape(message)}
" - logger.debug(message) - self._send_msg(message, parse_mode=ParseMode.HTML) + rpc_locks = self._rpc._rpc_locks() + if not rpc_locks['locks']: + self._send_msg('No active locks.', parse_mode=ParseMode.HTML) + + for locks in chunks(rpc_locks['locks'], 25): + message = tabulate([[ + lock['id'], + lock['pair'], + lock['lock_end_time'], + lock['reason']] for lock in locks], + headers=['ID', 'Pair', 'Until', 'Reason'], + tablefmt='simple') + message = f"
{escape(message)}
" + logger.debug(message) + self._send_msg(message, parse_mode=ParseMode.HTML) @authorized_only def _delete_locks(self, update: Update, context: CallbackContext) -> None: @@ -870,9 +908,17 @@ class Telegram(RPCHandler): """ try: edge_pairs = self._rpc._rpc_edge() - edge_pairs_tab = tabulate(edge_pairs, headers='keys', tablefmt='simple') - message = f'Edge only validated following pairs:\n
{edge_pairs_tab}
' - self._send_msg(message, parse_mode=ParseMode.HTML) + if not edge_pairs: + message = 'Edge only validated following pairs:' + self._send_msg(message, parse_mode=ParseMode.HTML) + + for chunk in chunks(edge_pairs, 25): + edge_pairs_tab = tabulate(chunk, headers='keys', tablefmt='simple') + message = (f'Edge only validated following pairs:\n' + f'
{edge_pairs_tab}
') + + self._send_msg(message, parse_mode=ParseMode.HTML) + except RPCException as e: self._send_msg(str(e)) diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py index 5a30a9be8..24e1348f1 100644 --- a/freqtrade/rpc/webhook.py +++ b/freqtrade/rpc/webhook.py @@ -45,17 +45,21 @@ class Webhook(RPCHandler): """ Send a message to telegram channel """ try: - if msg['type'] == RPCMessageType.BUY_NOTIFICATION: + if msg['type'] == RPCMessageType.BUY: valuedict = self._config['webhook'].get('webhookbuy', None) - elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION: + elif msg['type'] == RPCMessageType.BUY_CANCEL: valuedict = self._config['webhook'].get('webhookbuycancel', None) - elif msg['type'] == RPCMessageType.SELL_NOTIFICATION: + elif msg['type'] == RPCMessageType.BUY_FILL: + valuedict = self._config['webhook'].get('webhookbuyfill', None) + elif msg['type'] == RPCMessageType.SELL: valuedict = self._config['webhook'].get('webhooksell', None) - elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION: + elif msg['type'] == RPCMessageType.SELL_FILL: + valuedict = self._config['webhook'].get('webhooksellfill', None) + elif msg['type'] == RPCMessageType.SELL_CANCEL: valuedict = self._config['webhook'].get('webhooksellcancel', None) - elif msg['type'] in (RPCMessageType.STATUS_NOTIFICATION, - RPCMessageType.STARTUP_NOTIFICATION, - RPCMessageType.WARNING_NOTIFICATION): + elif msg['type'] in (RPCMessageType.STATUS, + RPCMessageType.STARTUP, + RPCMessageType.WARNING): valuedict = self._config['webhook'].get('webhookstatus', None) else: raise NotImplementedError('Unknown message type: {}'.format(msg['type'])) diff --git a/freqtrade/strategy/__init__.py b/freqtrade/strategy/__init__.py index 85148b6ea..bd49165df 100644 --- a/freqtrade/strategy/__init__.py +++ b/freqtrade/strategy/__init__.py @@ -1,5 +1,7 @@ # flake8: noqa: F401 from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date, timeframe_to_prev_date, timeframe_to_seconds) +from freqtrade.strategy.hyper import (CategoricalParameter, DecimalParameter, IntParameter, + RealParameter) from freqtrade.strategy.interface import IStrategy from freqtrade.strategy.strategy_helper import merge_informative_pair, stoploss_from_open diff --git a/freqtrade/strategy/hyper.py b/freqtrade/strategy/hyper.py new file mode 100644 index 000000000..7dee47d87 --- /dev/null +++ b/freqtrade/strategy/hyper.py @@ -0,0 +1,335 @@ +""" +IHyperStrategy interface, hyperoptable Parameter class. +This module defines a base class for auto-hyperoptable strategies. +""" +import logging +from abc import ABC, abstractmethod +from contextlib import suppress +from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union + +from freqtrade.optimize.hyperopt_tools import HyperoptTools + + +with suppress(ImportError): + from skopt.space import Integer, Real, Categorical + from freqtrade.optimize.space import SKDecimal + +from freqtrade.exceptions import OperationalException +from freqtrade.state import RunMode + + +logger = logging.getLogger(__name__) + + +class BaseParameter(ABC): + """ + Defines a parameter that can be optimized by hyperopt. + """ + category: Optional[str] + default: Any + value: Any + in_space: bool = False + name: str + + def __init__(self, *, default: Any, space: Optional[str] = None, + optimize: bool = True, load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable parameter. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter field + name is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical). + """ + if 'name' in kwargs: + raise OperationalException( + 'Name is determined by parameter field name and can not be specified manually.') + self.category = space + self._space_params = kwargs + self.value = default + self.optimize = optimize + self.load = load + + def __repr__(self): + return f'{self.__class__.__name__}({self.value})' + + @abstractmethod + def get_space(self, name: str) -> Union['Integer', 'Real', 'SKDecimal', 'Categorical']: + """ + Get-space - will be used by Hyperopt to get the hyperopt Space + """ + + +class NumericParameter(BaseParameter): + """ Internal parameter used for Numeric purposes """ + float_or_int = Union[int, float] + default: float_or_int + value: float_or_int + + def __init__(self, low: Union[float_or_int, Sequence[float_or_int]], + high: Optional[float_or_int] = None, *, default: float_or_int, + space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable numeric parameter. + Cannot be instantiated, but provides the validation for other numeric parameters + :param low: Lower end (inclusive) of optimization space or [low, high]. + :param high: Upper end (inclusive) of optimization space. + Must be none of entire range is passed first parameter. + :param default: A default value. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter fieldname is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.*. + """ + if high is not None and isinstance(low, Sequence): + raise OperationalException(f'{self.__class__.__name__} space invalid.') + if high is None or isinstance(low, Sequence): + if not isinstance(low, Sequence) or len(low) != 2: + raise OperationalException(f'{self.__class__.__name__} space must be [low, high]') + self.low, self.high = low + else: + self.low = low + self.high = high + + super().__init__(default=default, space=space, optimize=optimize, + load=load, **kwargs) + + +class IntParameter(NumericParameter): + default: int + value: int + + def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int, + space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable integer parameter. + :param low: Lower end (inclusive) of optimization space or [low, high]. + :param high: Upper end (inclusive) of optimization space. + Must be none of entire range is passed first parameter. + :param default: A default value. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter fieldname is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.Integer. + """ + + super().__init__(low=low, high=high, default=default, space=space, optimize=optimize, + load=load, **kwargs) + + def get_space(self, name: str) -> 'Integer': + """ + Create skopt optimization space. + :param name: A name of parameter field. + """ + return Integer(low=self.low, high=self.high, name=name, **self._space_params) + + @property + def range(self): + """ + Get each value in this space as list. + Returns a List from low to high (inclusive) in Hyperopt mode. + Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid + calculating 100ds of indicators. + """ + if self.in_space and self.optimize: + # Scikit-optimize ranges are "inclusive", while python's "range" is exclusive + return range(self.low, self.high + 1) + else: + return range(self.value, self.value + 1) + + +class RealParameter(NumericParameter): + default: float + value: float + + def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *, + default: float, space: Optional[str] = None, optimize: bool = True, + load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable floating point parameter with unlimited precision. + :param low: Lower end (inclusive) of optimization space or [low, high]. + :param high: Upper end (inclusive) of optimization space. + Must be none if entire range is passed first parameter. + :param default: A default value. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter fieldname is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.Real. + """ + super().__init__(low=low, high=high, default=default, space=space, optimize=optimize, + load=load, **kwargs) + + def get_space(self, name: str) -> 'Real': + """ + Create skopt optimization space. + :param name: A name of parameter field. + """ + return Real(low=self.low, high=self.high, name=name, **self._space_params) + + +class DecimalParameter(NumericParameter): + default: float + value: float + + def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *, + default: float, decimals: int = 3, space: Optional[str] = None, + optimize: bool = True, load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable decimal parameter with a limited precision. + :param low: Lower end (inclusive) of optimization space or [low, high]. + :param high: Upper end (inclusive) of optimization space. + Must be none if entire range is passed first parameter. + :param default: A default value. + :param decimals: A number of decimals after floating point to be included in testing. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter fieldname is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.Integer. + """ + self._decimals = decimals + default = round(default, self._decimals) + + super().__init__(low=low, high=high, default=default, space=space, optimize=optimize, + load=load, **kwargs) + + def get_space(self, name: str) -> 'SKDecimal': + """ + Create skopt optimization space. + :param name: A name of parameter field. + """ + return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name, + **self._space_params) + + +class CategoricalParameter(BaseParameter): + default: Any + value: Any + opt_range: Sequence[Any] + + def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None, + space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs): + """ + Initialize hyperopt-optimizable parameter. + :param categories: Optimization space, [a, b, ...]. + :param default: A default value. If not specified, first item from specified space will be + used. + :param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if + parameter field + name is prefixed with 'buy_' or 'sell_'. + :param optimize: Include parameter in hyperopt optimizations. + :param load: Load parameter value from {space}_params. + :param kwargs: Extra parameters to skopt.space.Categorical. + """ + if len(categories) < 2: + raise OperationalException( + 'CategoricalParameter space must be [a, b, ...] (at least two parameters)') + self.opt_range = categories + super().__init__(default=default, space=space, optimize=optimize, + load=load, **kwargs) + + def get_space(self, name: str) -> 'Categorical': + """ + Create skopt optimization space. + :param name: A name of parameter field. + """ + return Categorical(self.opt_range, name=name, **self._space_params) + + +class HyperStrategyMixin(object): + """ + A helper base class which allows HyperOptAuto class to reuse implementations of of buy/sell + strategy logic. + """ + + def __init__(self, config: Dict[str, Any], *args, **kwargs): + """ + Initialize hyperoptable strategy mixin. + """ + self.config = config + self.ft_buy_params: List[BaseParameter] = [] + self.ft_sell_params: List[BaseParameter] = [] + + self._load_hyper_params(config.get('runmode') == RunMode.HYPEROPT) + + def enumerate_parameters(self, category: str = None) -> Iterator[Tuple[str, BaseParameter]]: + """ + Find all optimizeable parameters and return (name, attr) iterator. + :param category: + :return: + """ + if category not in ('buy', 'sell', None): + raise OperationalException('Category must be one of: "buy", "sell", None.') + + if category is None: + params = self.ft_buy_params + self.ft_sell_params + else: + params = getattr(self, f"ft_{category}_params") + + for par in params: + yield par.name, par + + def _detect_parameters(self, category: str) -> Iterator[Tuple[str, BaseParameter]]: + """ Detect all parameters for 'category' """ + for attr_name in dir(self): + if not attr_name.startswith('__'): # Ignore internals, not strictly necessary. + attr = getattr(self, attr_name) + if issubclass(attr.__class__, BaseParameter): + if (attr_name.startswith(category + '_') + and attr.category is not None and attr.category != category): + raise OperationalException( + f'Inconclusive parameter name {attr_name}, category: {attr.category}.') + if (category == attr.category or + (attr_name.startswith(category + '_') and attr.category is None)): + yield attr_name, attr + + def _load_hyper_params(self, hyperopt: bool = False) -> None: + """ + Load Hyperoptable parameters + """ + self._load_params(getattr(self, 'buy_params', None), 'buy', hyperopt) + self._load_params(getattr(self, 'sell_params', None), 'sell', hyperopt) + + def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None: + """ + Set optimizeable parameter values. + :param params: Dictionary with new parameter values. + """ + if not params: + logger.info(f"No params for {space} found, using default values.") + param_container: List[BaseParameter] = getattr(self, f"ft_{space}_params") + + for attr_name, attr in self._detect_parameters(space): + attr.name = attr_name + attr.in_space = hyperopt and HyperoptTools.has_space(self.config, space) + if not attr.category: + attr.category = space + + param_container.append(attr) + + if params and attr_name in params: + if attr.load: + attr.value = params[attr_name] + logger.info(f'Strategy Parameter: {attr_name} = {attr.value}') + else: + logger.warning(f'Parameter "{attr_name}" exists, but is disabled. ' + f'Default value "{attr.value}" used.') + else: + logger.info(f'Strategy Parameter(default): {attr_name} = {attr.value}') + + def get_params_dict(self): + """ + Returns list of Parameters that are not part of the current optimize job + """ + params = { + 'buy': {}, + 'sell': {} + } + for name, p in self.enumerate_parameters(): + if not p.optimize or not p.in_space: + params[p.category][name] = p.value + return params diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 6d40e56cc..e2cde52eb 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -7,7 +7,7 @@ import warnings from abc import ABC, abstractmethod from datetime import datetime, timedelta, timezone from enum import Enum -from typing import Dict, List, NamedTuple, Optional, Tuple +from typing import Dict, List, Optional, Tuple, Union import arrow from pandas import DataFrame @@ -18,11 +18,13 @@ from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds from freqtrade.exchange.exchange import timeframe_to_next_date from freqtrade.persistence import PairLocks, Trade +from freqtrade.strategy.hyper import HyperStrategyMixin from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.wallets import Wallets logger = logging.getLogger(__name__) +CUSTOM_SELL_MAX_LENGTH = 64 class SignalType(Enum): @@ -44,6 +46,7 @@ class SellType(Enum): SELL_SIGNAL = "sell_signal" FORCE_SELL = "force_sell" EMERGENCY_SELL = "emergency_sell" + CUSTOM_SELL = "custom_sell" NONE = "" def __str__(self): @@ -51,15 +54,23 @@ class SellType(Enum): return self.value -class SellCheckTuple(NamedTuple): +class SellCheckTuple(object): """ NamedTuple for Sell type + reason """ - sell_flag: bool sell_type: SellType + sell_reason: str = '' + + def __init__(self, sell_type: SellType, sell_reason: str = ''): + self.sell_type = sell_type + self.sell_reason = sell_reason or sell_type.value + + @property + def sell_flag(self): + return self.sell_type != SellType.NONE -class IStrategy(ABC): +class IStrategy(ABC, HyperStrategyMixin): """ Interface for freqtrade strategies Defines the mandatory structure must follow any custom strategies @@ -140,6 +151,7 @@ class IStrategy(ABC): self.config = config # Dict to determine if analysis is necessary self._last_candle_seen_per_pair: Dict[str, datetime] = {} + super().__init__(config) @abstractmethod def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: @@ -149,6 +161,7 @@ class IStrategy(ABC): :param metadata: Additional information, like the currently traded pair :return: a Dataframe with all mandatory indicators for the strategies """ + return dataframe @abstractmethod def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: @@ -158,6 +171,7 @@ class IStrategy(ABC): :param metadata: Additional information, like the currently traded pair :return: DataFrame with buy column """ + return dataframe @abstractmethod def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: @@ -167,6 +181,7 @@ class IStrategy(ABC): :param metadata: Additional information, like the currently traded pair :return: DataFrame with sell column """ + return dataframe def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool: """ @@ -214,7 +229,7 @@ class IStrategy(ABC): pass def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, - time_in_force: str, **kwargs) -> bool: + time_in_force: str, current_time: datetime, **kwargs) -> bool: """ Called right before placing a buy order. Timing for this function is critical, so avoid doing heavy computations or @@ -229,6 +244,7 @@ class IStrategy(ABC): :param amount: Amount in target (quote) currency that's going to be traded. :param rate: Rate that's going to be used when using limit orders :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled). + :param current_time: datetime object, containing the current datetime :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :return bool: When True is returned, then the buy-order is placed on the exchange. False aborts the process @@ -236,7 +252,8 @@ class IStrategy(ABC): return True def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, - rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool: + rate: float, time_in_force: str, sell_reason: str, + current_time: datetime, **kwargs) -> bool: """ Called right before placing a regular sell order. Timing for this function is critical, so avoid doing heavy computations or @@ -255,6 +272,7 @@ class IStrategy(ABC): :param sell_reason: Sell reason. Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss', 'sell_signal', 'force_sell', 'emergency_sell'] + :param current_time: datetime object, containing the current datetime :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :return bool: When True is returned, then the sell-order is placed on the exchange. False aborts the process @@ -283,6 +301,30 @@ class IStrategy(ABC): """ return self.stoploss + def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, + current_profit: float, **kwargs) -> Optional[Union[str, bool]]: + """ + Custom sell signal logic indicating that specified position should be sold. Returning a + string or True from this method is equal to setting sell signal on a candle at specified + time. This method is not called when sell signal is set. + + This method should be overridden to create sell signals that depend on trade parameters. For + example you could implement a stoploss relative to candle when trade was opened, or a custom + 1:2 risk-reward ROI. + + Custom sell reason max length is 64. Exceeding this limit will raise OperationalException. + + :param pair: Pair that's currently analyzed + :param trade: trade object. + :param current_time: datetime object, containing the current datetime + :param current_rate: Rate, calculated based on pricing settings in ask_strategy. + :param current_profit: Current profit (as ratio), calculated based on current_rate. + :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. + :return: To execute sell, return a string with custom sell reason or True. Otherwise return + None or False. + """ + return None + def informative_pairs(self) -> ListPairsWithTimeframes: """ Define additional, informative pair/interval combinations to be cached from the exchange. @@ -529,12 +571,33 @@ class IStrategy(ABC): and self.min_roi_reached(trade=trade, current_profit=current_profit, current_time=date)) + sell_signal = SellType.NONE + custom_reason = '' + # use provided rate in backtesting, not high/low. + current_rate = rate + current_profit = trade.calc_profit_ratio(current_rate) + if (ask_strategy.get('sell_profit_only', False) and current_profit <= ask_strategy.get('sell_profit_offset', 0)): # sell_profit_only and profit doesn't reach the offset - ignore sell signal - sell_signal = False - else: - sell_signal = sell and not buy and ask_strategy.get('use_sell_signal', True) + pass + elif ask_strategy.get('use_sell_signal', True) and not buy: + if sell: + sell_signal = SellType.SELL_SIGNAL + else: + custom_reason = strategy_safe_wrapper(self.custom_sell, default_retval=False)( + pair=trade.pair, trade=trade, current_time=date, current_rate=current_rate, + current_profit=current_profit) + if custom_reason: + sell_signal = SellType.CUSTOM_SELL + if isinstance(custom_reason, str): + if len(custom_reason) > CUSTOM_SELL_MAX_LENGTH: + logger.warning(f'Custom sell reason returned from custom_sell is too ' + f'long and was trimmed to {CUSTOM_SELL_MAX_LENGTH} ' + f'characters.') + custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH] + else: + custom_reason = None # TODO: return here if sell-signal should be favored over ROI # Start evaluations @@ -543,24 +606,23 @@ class IStrategy(ABC): # Sell-signal # Stoploss if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS: - logger.debug(f"{trade.pair} - Required profit reached. sell_flag=True, " - f"sell_type=SellType.ROI") - return SellCheckTuple(sell_flag=True, sell_type=SellType.ROI) + logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI") + return SellCheckTuple(sell_type=SellType.ROI) - if sell_signal: - logger.debug(f"{trade.pair} - Sell signal received. sell_flag=True, " - f"sell_type=SellType.SELL_SIGNAL") - return SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL) + if sell_signal != SellType.NONE: + logger.debug(f"{trade.pair} - Sell signal received. " + f"sell_type=SellType.{sell_signal.name}" + + (f", custom_reason={custom_reason}" if custom_reason else "")) + return SellCheckTuple(sell_type=sell_signal, sell_reason=custom_reason) if stoplossflag.sell_flag: - logger.debug(f"{trade.pair} - Stoploss hit. sell_flag=True, " - f"sell_type={stoplossflag.sell_type}") + logger.debug(f"{trade.pair} - Stoploss hit. sell_type={stoplossflag.sell_type}") return stoplossflag # This one is noisy, commented out... - # logger.debug(f"{trade.pair} - No sell signal. sell_flag=False") - return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE) + # logger.debug(f"{trade.pair} - No sell signal.") + return SellCheckTuple(sell_type=SellType.NONE) def stop_loss_reached(self, current_rate: float, trade: Trade, current_time: datetime, current_profit: float, @@ -624,9 +686,9 @@ class IStrategy(ABC): logger.debug(f"{trade.pair} - Trailing stop saved " f"{trade.stop_loss - trade.initial_stop_loss:.6f}") - return SellCheckTuple(sell_flag=True, sell_type=sell_type) + return SellCheckTuple(sell_type=sell_type) - return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE) + return SellCheckTuple(sell_type=SellType.NONE) def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]: """ diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2 index 226bf1a81..8933ebc6a 100644 --- a/freqtrade/templates/base_config.json.j2 +++ b/freqtrade/templates/base_config.json.j2 @@ -9,7 +9,8 @@ "cancel_open_orders_on_exit": false, "unfilledtimeout": { "buy": 10, - "sell": 30 + "sell": 30, + "unit": "minutes" }, "bid_strategy": { "price_side": "bid", @@ -54,15 +55,15 @@ "chat_id": "{{ telegram_chat_id }}" }, "api_server": { - "enabled": false, - "listen_ip_address": "127.0.0.1", + "enabled": {{ api_server | lower }}, + "listen_ip_address": "{{ api_server_listen_addr | default("127.0.0.1", true) }}", "listen_port": 8080, "verbosity": "error", "enable_openapi": false, - "jwt_secret_key": "somethingrandom", + "jwt_secret_key": "{{ api_server_jwt_key }}", "CORS_origins": [], - "username": "", - "password": "" + "username": "{{ api_server_username }}", + "password": "{{ api_server_password }}" }, "bot_name": "freqtrade", "initial_state": "running", diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2 index db73d4da3..13fc0853a 100644 --- a/freqtrade/templates/base_strategy.py.j2 +++ b/freqtrade/templates/base_strategy.py.j2 @@ -1,4 +1,5 @@ # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement +# flake8: noqa: F401 # --- Do not remove these libs --- import numpy as np # noqa @@ -6,6 +7,7 @@ import pandas as pd # noqa from pandas import DataFrame from freqtrade.strategy import IStrategy +from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter # -------------------------------- # Add your lib to import here @@ -16,7 +18,7 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib class {{ strategy }}(IStrategy): """ This is a strategy template to get you started. - More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md + More information in https://www.freqtrade.io/en/latest/strategy-customization/ You can: :return: a Dataframe with all mandatory indicators for the strategies diff --git a/freqtrade/templates/sample_hyperopt_advanced.py b/freqtrade/templates/sample_hyperopt_advanced.py index 7736570f7..cc13b6ba3 100644 --- a/freqtrade/templates/sample_hyperopt_advanced.py +++ b/freqtrade/templates/sample_hyperopt_advanced.py @@ -7,7 +7,7 @@ from typing import Any, Callable, Dict, List import numpy as np # noqa import pandas as pd # noqa from pandas import DataFrame -from skopt.space import Categorical, Dimension, Integer, Real # noqa +from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal, Real # noqa from freqtrade.optimize.hyperopt_interface import IHyperOpt @@ -223,9 +223,9 @@ class AdvancedSampleHyperOpt(IHyperOpt): Integer(10, 120, name='roi_t1'), Integer(10, 60, name='roi_t2'), Integer(10, 40, name='roi_t3'), - Real(0.01, 0.04, name='roi_p1'), - Real(0.01, 0.07, name='roi_p2'), - Real(0.01, 0.20, name='roi_p3'), + SKDecimal(0.01, 0.04, decimals=3, name='roi_p1'), + SKDecimal(0.01, 0.07, decimals=3, name='roi_p2'), + SKDecimal(0.01, 0.20, decimals=3, name='roi_p3'), ] @staticmethod @@ -237,7 +237,7 @@ class AdvancedSampleHyperOpt(IHyperOpt): 'stoploss' optimization hyperspace. """ return [ - Real(-0.35, -0.02, name='stoploss'), + SKDecimal(-0.35, -0.02, decimals=3, name='stoploss'), ] @staticmethod @@ -256,14 +256,14 @@ class AdvancedSampleHyperOpt(IHyperOpt): # other 'trailing' hyperspace parameters. Categorical([True], name='trailing_stop'), - Real(0.01, 0.35, name='trailing_stop_positive'), + SKDecimal(0.01, 0.35, decimals=3, name='trailing_stop_positive'), # 'trailing_stop_positive_offset' should be greater than 'trailing_stop_positive', # so this intermediate parameter is used as the value of the difference between # them. The value of the 'trailing_stop_positive_offset' is constructed in the # generate_trailing_params() method. # This is similar to the hyperspace dimensions used for constructing the ROI tables. - Real(0.001, 0.1, name='trailing_stop_positive_offset_p1'), + SKDecimal(0.001, 0.1, decimals=3, name='trailing_stop_positive_offset_p1'), Categorical([True, False], name='trailing_only_offset_is_reached'), ] diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index 5dfa42bcc..e51feff1e 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -1,4 +1,5 @@ # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement +# flake8: noqa: F401 # isort: skip_file # --- Do not remove these libs --- import numpy as np # noqa @@ -6,6 +7,7 @@ import pandas as pd # noqa from pandas import DataFrame from freqtrade.strategy import IStrategy +from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter # -------------------------------- # Add your lib to import here @@ -53,7 +55,11 @@ class SampleStrategy(IStrategy): # trailing_stop_positive = 0.01 # trailing_stop_positive_offset = 0.0 # Disabled / not configured - # Optimal ticker interval for the strategy. + # Hyperoptable parameters + buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) + sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True) + + # Optimal timeframe for the strategy. timeframe = '5m' # Run "populate_indicators()" only for new candle. @@ -340,7 +346,8 @@ class SampleStrategy(IStrategy): """ dataframe.loc[ ( - (qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30 + # Signal: RSI crosses above 30 + (qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) & (dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle (dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising (dataframe['volume'] > 0) # Make sure Volume is not 0 @@ -354,11 +361,12 @@ class SampleStrategy(IStrategy): Based on TA indicators, populates the sell signal for the given dataframe :param dataframe: DataFrame populated with indicators :param metadata: Additional information, like the currently traded pair - :return: DataFrame with buy column + :return: DataFrame with sell column """ dataframe.loc[ ( - (qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70 + # Signal: RSI crosses above 70 + (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) & (dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle (dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling (dataframe['volume'] > 0) # Make sure Volume is not 0 diff --git a/freqtrade/templates/strategy_analysis_example.ipynb b/freqtrade/templates/strategy_analysis_example.ipynb index 491afbdd7..0bc593e2d 100644 --- a/freqtrade/templates/strategy_analysis_example.ipynb +++ b/freqtrade/templates/strategy_analysis_example.ipynb @@ -282,6 +282,28 @@ "graph.show(renderer=\"browser\")\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot average profit per trade as distribution graph" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.figure_factory as ff\n", + "\n", + "hist_data = [trades.profit_ratio]\n", + "group_labels = ['profit_ratio'] # name of the dataset\n", + "\n", + "fig = ff.create_distplot(hist_data, group_labels,bin_size=0.01)\n", + "fig.show()\n" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 index 53ededa19..2a9ac0690 100644 --- a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 +++ b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 @@ -14,8 +14,9 @@ def bot_loop_start(self, **kwargs) -> None: use_custom_stoploss = True -def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, - current_profit: float, **kwargs) -> float: +def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', + current_rate: float, current_profit: float, dataframe: DataFrame, + **kwargs) -> float: """ Custom stoploss logic, returning the new distance relative to current_rate (as ratio). e.g. returning -0.05 would create a stoploss 5% below current_rate. @@ -31,13 +32,14 @@ def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', c :param current_time: datetime object, containing the current datetime :param current_rate: Rate, calculated based on pricing settings in ask_strategy. :param current_profit: Current profit (as ratio), calculated based on current_rate. + :param dataframe: Analyzed dataframe for this pair. Can contain future data in backtesting. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :return float: New stoploss value, relative to the currentrate """ return self.stoploss def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, - time_in_force: str, **kwargs) -> bool: + time_in_force: str, current_time: 'datetime', **kwargs) -> bool: """ Called right before placing a buy order. Timing for this function is critical, so avoid doing heavy computations or @@ -52,6 +54,7 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f :param amount: Amount in target (quote) currency that's going to be traded. :param rate: Rate that's going to be used when using limit orders :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled). + :param current_time: datetime object, containing the current datetime :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :return bool: When True is returned, then the buy-order is placed on the exchange. False aborts the process @@ -59,7 +62,8 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f return True def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float, - rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool: + rate: float, time_in_force: str, sell_reason: str, + current_time: 'datetime', **kwargs) -> bool: """ Called right before placing a regular sell order. Timing for this function is critical, so avoid doing heavy computations or @@ -78,6 +82,7 @@ def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: :param sell_reason: Sell reason. Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss', 'sell_signal', 'force_sell', 'emergency_sell'] + :param current_time: datetime object, containing the current datetime :param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :return bool: When True is returned, then the sell-order is placed on the exchange. False aborts the process diff --git a/freqtrade/wallets.py b/freqtrade/wallets.py index f4432e932..d5f979c24 100644 --- a/freqtrade/wallets.py +++ b/freqtrade/wallets.py @@ -99,12 +99,13 @@ class Wallets: balances = self._exchange.get_balances() for currency in balances: - self._wallets[currency] = Wallet( - currency, - balances[currency].get('free', None), - balances[currency].get('used', None), - balances[currency].get('total', None) - ) + if isinstance(balances[currency], dict): + self._wallets[currency] = Wallet( + currency, + balances[currency].get('free', None), + balances[currency].get('used', None), + balances[currency].get('total', None) + ) # Remove currencies no longer in get_balances output for currency in deepcopy(self._wallets): if currency not in balances: @@ -130,14 +131,13 @@ class Wallets: def get_all_balances(self) -> Dict[str, Any]: return self._wallets - def _get_available_stake_amount(self) -> float: + def _get_available_stake_amount(self, val_tied_up: float) -> float: """ Return the total currently available balance in stake currency, respecting tradable_balance_ratio. Calculated as - ( + free amount ) * tradable_balance_ratio - + ( + free amount) * tradable_balance_ratio - """ - val_tied_up = Trade.total_open_trades_stakes() # Ensure % is used from the overall balance # Otherwise we'd risk lowering stakes with each open trade. @@ -146,26 +146,26 @@ class Wallets: self._config['tradable_balance_ratio']) - val_tied_up return available_amount - def _calculate_unlimited_stake_amount(self, free_open_trades: int) -> float: + def _calculate_unlimited_stake_amount(self, available_amount: float, + val_tied_up: float) -> float: """ Calculate stake amount for "unlimited" stake amount :return: 0 if max number of trades reached, else stake_amount to use. """ - if not free_open_trades: + if self._config['max_open_trades'] == 0: return 0 - available_amount = self._get_available_stake_amount() + possible_stake = (available_amount + val_tied_up) / self._config['max_open_trades'] + # Theoretical amount can be above available amount - therefore limit to available amount! + return min(possible_stake, available_amount) - return available_amount / free_open_trades - - def _check_available_stake_amount(self, stake_amount: float) -> float: + def _check_available_stake_amount(self, stake_amount: float, available_amount: float) -> float: """ Check if stake amount can be fulfilled with the available balance for the stake currency :return: float: Stake amount :raise: DependencyException if balance is lower than stake-amount """ - available_amount = self._get_available_stake_amount() if self._config['amend_last_stake_amount']: # Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio @@ -183,7 +183,7 @@ class Wallets: return stake_amount - def get_trade_stake_amount(self, pair: str, free_open_trades: int, edge=None) -> float: + def get_trade_stake_amount(self, pair: str, edge=None) -> float: """ Calculate stake amount for the trade :return: float: Stake amount @@ -192,17 +192,20 @@ class Wallets: stake_amount: float # Ensure wallets are uptodate. self.update() + val_tied_up = Trade.total_open_trades_stakes() + available_amount = self._get_available_stake_amount(val_tied_up) if edge: stake_amount = edge.stake_amount( pair, self.get_free(self._config['stake_currency']), self.get_total(self._config['stake_currency']), - Trade.total_open_trades_stakes() + val_tied_up ) else: stake_amount = self._config['stake_amount'] if stake_amount == UNLIMITED_STAKE_AMOUNT: - stake_amount = self._calculate_unlimited_stake_amount(free_open_trades) + stake_amount = self._calculate_unlimited_stake_amount( + available_amount, val_tied_up) - return self._check_available_stake_amount(stake_amount) + return self._check_available_stake_amount(stake_amount, available_amount) diff --git a/requirements-dev.txt b/requirements-dev.txt index 02f7fbca8..4fbf21260 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -4,14 +4,14 @@ -r requirements-hyperopt.txt coveralls==3.0.1 -flake8==3.9.0 +flake8==3.9.2 flake8-type-annotations==0.1.0 -flake8-tidy-imports==4.2.1 +flake8-tidy-imports==4.3.0 mypy==0.812 -pytest==6.2.2 -pytest-asyncio==0.14.0 -pytest-cov==2.11.1 -pytest-mock==3.5.1 +pytest==6.2.4 +pytest-asyncio==0.15.1 +pytest-cov==2.12.0 +pytest-mock==3.6.1 pytest-random-order==1.0.4 isort==5.8.0 diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt index 8cdb6fd28..5e7e9d9d2 100644 --- a/requirements-hyperopt.txt +++ b/requirements-hyperopt.txt @@ -2,8 +2,8 @@ -r requirements.txt # Required for hyperopt -scipy==1.6.1 -scikit-learn==0.24.1 +scipy==1.6.3 +scikit-learn==0.24.2 scikit-optimize==0.8.1 filelock==3.0.12 joblib==1.0.1 diff --git a/requirements.txt b/requirements.txt index 56ada691f..f55cc0bdc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,22 +1,23 @@ -numpy==1.20.1 -pandas==1.2.3 +numpy==1.20.3 +pandas==1.2.4 -ccxt==1.43.89 +ccxt==1.50.6 # Pin cryptography for now due to rust build errors with piwheels -cryptography==3.4.6 +cryptography==3.4.7 aiohttp==3.7.4.post0 -SQLAlchemy==1.4.2 -python-telegram-bot==13.4.1 -arrow==1.0.3 -cachetools==4.2.1 +SQLAlchemy==1.4.15 +python-telegram-bot==13.5 +arrow==1.1.0 +cachetools==4.2.2 requests==2.25.1 urllib3==1.26.4 wrapt==1.12.1 jsonschema==3.2.0 TA-Lib==0.4.19 +technical==1.3.0 tabulate==0.8.9 -pycoingecko==1.4.0 -jinja2==2.11.3 +pycoingecko==2.0.0 +jinja2==3.0.0 tables==3.6.1 blosc==1.10.2 @@ -30,13 +31,13 @@ python-rapidjson==1.0 sdnotify==0.3.2 # API Server -fastapi==0.63.0 +fastapi==0.65.1 uvicorn==0.13.4 -pyjwt==2.0.1 -aiofiles==0.6.0 +pyjwt==2.1.0 +aiofiles==0.7.0 # Support for colorized terminal output colorama==0.4.4 # Building config files interactively questionary==1.9.0 -prompt-toolkit==3.0.17 +prompt-toolkit==3.0.18 diff --git a/scripts/rest_client.py b/scripts/rest_client.py index 4d667879d..ece0a253e 100755 --- a/scripts/rest_client.py +++ b/scripts/rest_client.py @@ -127,7 +127,7 @@ class FtRestClient(): return self._delete("locks/{}".format(lock_id)) def daily(self, days=None): - """Return the amount of open trades. + """Return the profits for each day, and amount of trades. :return: json object """ @@ -195,18 +195,32 @@ class FtRestClient(): def logs(self, limit=None): """Show latest logs. - :param limit: Limits log messages to the last logs. No limit to get all the trades. + :param limit: Limits log messages to the last logs. No limit to get the entire log. :return: json object """ return self._get("logs", params={"limit": limit} if limit else 0) - def trades(self, limit=None): - """Return trades history. + def trades(self, limit=None, offset=None): + """Return trades history, sorted by id - :param limit: Limits trades to the X last trades. No limit to get all the trades. + :param limit: Limits trades to the X last trades. Max 500 trades. + :param offset: Offset by this amount of trades. :return: json object """ - return self._get("trades", params={"limit": limit} if limit else 0) + params = {} + if limit: + params['limit'] = limit + if offset: + params['offset'] = offset + return self._get("trades", params) + + def trade(self, trade_id): + """Return specific trade + + :param trade_id: Specify which trade to get. + :return: json object + """ + return self._get("trade/{}".format(trade_id)) def delete_trade(self, trade_id): """Delete trade from the database. @@ -382,7 +396,7 @@ def main(args): sys.exit() config = load_config(args['config']) - url = config.get('api_server', {}).get('server_url', '127.0.0.1') + url = config.get('api_server', {}).get('listen_ip_address', '127.0.0.1') port = config.get('api_server', {}).get('listen_port', '8080') username = config.get('api_server', {}).get('username') password = config.get('api_server', {}).get('password') diff --git a/setup.py b/setup.py index 118bc8485..54a2e01b5 100644 --- a/setup.py +++ b/setup.py @@ -69,7 +69,7 @@ setup(name='freqtrade', # from requirements.txt 'ccxt>=1.24.96', 'SQLAlchemy', - 'python-telegram-bot', + 'python-telegram-bot>=13.4', 'arrow>=0.17.0', 'cachetools', 'requests', @@ -77,6 +77,7 @@ setup(name='freqtrade', 'wrapt', 'jsonschema', 'TA-Lib', + 'technical', 'tabulate', 'pycoingecko', 'py_find_1st', diff --git a/setup.sh b/setup.sh index d0ca1f643..631c31df2 100755 --- a/setup.sh +++ b/setup.sh @@ -138,7 +138,7 @@ function install_macos() { # Install bot Debian_ubuntu function install_debian() { sudo apt-get update - sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git + sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git libpython3-dev install_talib } diff --git a/tests/commands/test_build_config.py b/tests/commands/test_build_config.py index 291720f4b..66c750e79 100644 --- a/tests/commands/test_build_config.py +++ b/tests/commands/test_build_config.py @@ -50,6 +50,10 @@ def test_start_new_config(mocker, caplog, exchange): 'telegram': False, 'telegram_token': 'asdf1244', 'telegram_chat_id': '1144444', + 'api_server': False, + 'api_server_listen_addr': '127.0.0.1', + 'api_server_username': 'freqtrader', + 'api_server_password': 'MoneyMachine', } mocker.patch('freqtrade.commands.build_config_commands.ask_user_config', return_value=sample_selections) diff --git a/tests/commands/test_commands.py b/tests/commands/test_commands.py index e21ef4dd1..4d3937d87 100644 --- a/tests/commands/test_commands.py +++ b/tests/commands/test_commands.py @@ -66,8 +66,8 @@ def test_list_exchanges(capsys): start_list_exchanges(get_args(args)) captured = capsys.readouterr() assert re.match(r"Exchanges available for Freqtrade.*", captured.out) - assert re.match(r".*binance,.*", captured.out) - assert re.match(r".*bittrex,.*", captured.out) + assert re.search(r".*binance.*", captured.out) + assert re.search(r".*bittrex.*", captured.out) # Test with --one-column args = [ @@ -89,9 +89,9 @@ def test_list_exchanges(capsys): start_list_exchanges(get_args(args)) captured = capsys.readouterr() assert re.match(r"All exchanges supported by the ccxt library.*", captured.out) - assert re.match(r".*binance,.*", captured.out) - assert re.match(r".*bittrex,.*", captured.out) - assert re.match(r".*bitmex,.*", captured.out) + assert re.search(r".*binance.*", captured.out) + assert re.search(r".*bittrex.*", captured.out) + assert re.search(r".*bitmex.*", captured.out) # Test with --one-column --all args = [ @@ -116,7 +116,7 @@ def test_list_timeframes(mocker, capsys): '1h': 'hour', '1d': 'day', } - patch_exchange(mocker, api_mock=api_mock) + patch_exchange(mocker, api_mock=api_mock, id='bittrex') args = [ "list-timeframes", ] @@ -201,7 +201,7 @@ def test_list_markets(mocker, markets, capsys): api_mock = MagicMock() api_mock.markets = markets - patch_exchange(mocker, api_mock=api_mock) + patch_exchange(mocker, api_mock=api_mock, id='bittrex') # Test with no --config args = [ @@ -918,242 +918,244 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys): captured.out) -def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): +def test_hyperopt_list(mocker, capsys, caplog, saved_hyperopt_results, + saved_hyperopt_results_legacy): + for _ in (saved_hyperopt_results, saved_hyperopt_results_legacy): + mocker.patch( + 'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results', + MagicMock(return_value=saved_hyperopt_results_legacy) + ) + + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", + " 6/12", " 7/12", " 8/12", " 9/12", " 10/12", + " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--best", + "--no-details", + "--no-color", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 1/12", " 5/12", " 10/12"]) + assert all(x not in captured.out + for x in [" 2/12", " 3/12", " 4/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--profitable", + "--no-details", + "--no-color", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 2/12", " 10/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--profitable", + "--no-color", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 2/12", " 10/12", "Best result:", "Buy hyperspace params", + "Sell hyperspace params", "ROI table", "Stoploss"]) + assert all(x not in captured.out + for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--min-trades", "20", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 3/12", " 6/12", " 7/12", " 9/12", " 11/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 2/12", " 4/12", " 5/12", " 8/12", " 10/12", " 12/12"]) + args = [ + "hyperopt-list", + "--profitable", + "--no-details", + "--no-color", + "--max-trades", "20", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 2/12", " 10/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--profitable", + "--no-details", + "--no-color", + "--min-avg-profit", "0.11", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 2/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 10/12", " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--max-avg-profit", "0.10", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 1/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", + " 11/12"]) + assert all(x not in captured.out + for x in [" 2/12", " 4/12", " 10/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--min-total-profit", "0.4", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 10/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", + " 9/12", " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--max-total-profit", "0.4", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", + " 9/12", " 11/12"]) + assert all(x not in captured.out + for x in [" 4/12", " 10/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--min-objective", "0.1", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 10/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", + " 9/12", " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--max-objective", "0.1", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", + " 9/12", " 11/12"]) + assert all(x not in captured.out + for x in [" 4/12", " 10/12", " 12/12"]) + args = [ + "hyperopt-list", + "--profitable", + "--no-details", + "--no-color", + "--min-avg-time", "2000", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 10/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", + " 8/12", " 9/12", " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--max-avg-time", "1500", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + assert all(x in captured.out + for x in [" 2/12", " 6/12"]) + assert all(x not in captured.out + for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 7/12", " 8/12" + " 9/12", " 10/12", " 11/12", " 12/12"]) + args = [ + "hyperopt-list", + "--no-details", + "--no-color", + "--export-csv", "test_file.csv", + ] + pargs = get_args(args) + pargs['config'] = None + start_hyperopt_list(pargs) + captured = capsys.readouterr() + log_has("CSV file created: test_file.csv", caplog) + f = Path("test_file.csv") + assert 'Best,1,2,-1.25%,-1.2222,-0.00125625,,-2.51,"3,930.0 m",0.43662' in f.read_text() + assert f.is_file() + f.unlink() + + +def test_hyperopt_show(mocker, capsys, saved_hyperopt_results): mocker.patch( 'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results', - MagicMock(return_value=hyperopt_results) - ) - - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", - " 6/12", " 7/12", " 8/12", " 9/12", " 10/12", - " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--best", - "--no-details", - "--no-color", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 1/12", " 5/12", " 10/12"]) - assert all(x not in captured.out - for x in [" 2/12", " 3/12", " 4/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--profitable", - "--no-details", - "--no-color", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 2/12", " 10/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--profitable", - "--no-color", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 2/12", " 10/12", "Best result:", "Buy hyperspace params", - "Sell hyperspace params", "ROI table", "Stoploss"]) - assert all(x not in captured.out - for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--min-trades", "20", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 3/12", " 6/12", " 7/12", " 9/12", " 11/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 2/12", " 4/12", " 5/12", " 8/12", " 10/12", " 12/12"]) - args = [ - "hyperopt-list", - "--profitable", - "--no-details", - "--no-color", - "--max-trades", "20", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 2/12", " 10/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--profitable", - "--no-details", - "--no-color", - "--min-avg-profit", "0.11", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 2/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 10/12", " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--max-avg-profit", "0.10", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 1/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12", - " 11/12"]) - assert all(x not in captured.out - for x in [" 2/12", " 4/12", " 10/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--min-total-profit", "0.4", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 10/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", - " 9/12", " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--max-total-profit", "0.4", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", - " 9/12", " 11/12"]) - assert all(x not in captured.out - for x in [" 4/12", " 10/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--min-objective", "0.1", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 10/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", - " 9/12", " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--max-objective", "0.1", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", - " 9/12", " 11/12"]) - assert all(x not in captured.out - for x in [" 4/12", " 10/12", " 12/12"]) - args = [ - "hyperopt-list", - "--profitable", - "--no-details", - "--no-color", - "--min-avg-time", "2000", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 10/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", - " 8/12", " 9/12", " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--max-avg-time", "1500", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - assert all(x in captured.out - for x in [" 2/12", " 6/12"]) - assert all(x not in captured.out - for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 7/12", " 8/12" - " 9/12", " 10/12", " 11/12", " 12/12"]) - args = [ - "hyperopt-list", - "--no-details", - "--no-color", - "--export-csv", "test_file.csv", - ] - pargs = get_args(args) - pargs['config'] = None - start_hyperopt_list(pargs) - captured = capsys.readouterr() - log_has("CSV file created: test_file.csv", caplog) - f = Path("test_file.csv") - assert 'Best,1,2,-1.25%,-1.2222,-0.00125625,,-2.51,"3,930.0 m",0.43662' in f.read_text() - assert f.is_file() - f.unlink() - - -def test_hyperopt_show(mocker, capsys, hyperopt_results): - mocker.patch( - 'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results', - MagicMock(return_value=hyperopt_results) + MagicMock(return_value=saved_hyperopt_results) ) args = [ diff --git a/tests/config_test_comments.json b/tests/config_test_comments.json index 4f201f86c..48a087dec 100644 --- a/tests/config_test_comments.json +++ b/tests/config_test_comments.json @@ -59,7 +59,7 @@ } }, "exchange": { - "name": "bittrex", + "name": "binance", "sandbox": false, "key": "your_exchange_key", "secret": "your_exchange_secret", diff --git a/tests/conftest.py b/tests/conftest.py index 3522ef02d..ef2bd0613 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -3,7 +3,7 @@ import json import logging import re from copy import deepcopy -from datetime import datetime +from datetime import datetime, timedelta from functools import reduce from pathlib import Path from unittest.mock import MagicMock, Mock, PropertyMock @@ -21,6 +21,7 @@ from freqtrade.exchange import Exchange from freqtrade.freqtradebot import FreqtradeBot from freqtrade.persistence import LocalTrade, Trade, init_db from freqtrade.resolvers import ExchangeResolver +from freqtrade.state import RunMode from freqtrade.worker import Worker from tests.conftest_trades import (mock_trade_1, mock_trade_2, mock_trade_3, mock_trade_4, mock_trade_5, mock_trade_6) @@ -79,7 +80,7 @@ def patched_configuration_load_config_file(mocker, config) -> None: ) -def patch_exchange(mocker, api_mock=None, id='bittrex', mock_markets=True) -> None: +def patch_exchange(mocker, api_mock=None, id='binance', mock_markets=True) -> None: mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={})) mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock()) mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock()) @@ -98,7 +99,7 @@ def patch_exchange(mocker, api_mock=None, id='bittrex', mock_markets=True) -> No mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock()) -def get_patched_exchange(mocker, config, api_mock=None, id='bittrex', +def get_patched_exchange(mocker, config, api_mock=None, id='binance', mock_markets=True) -> Exchange: patch_exchange(mocker, api_mock, id, mock_markets) config['exchange']['name'] = id @@ -197,7 +198,7 @@ def create_mock_trades(fee, use_db: bool = True): """ def add_trade(trade): if use_db: - Trade.session.add(trade) + Trade.query.session.add(trade) else: LocalTrade.add_bt_trade(trade) @@ -220,6 +221,9 @@ def create_mock_trades(fee, use_db: bool = True): trade = mock_trade_6(fee) add_trade(trade) + if use_db: + Trade.query.session.flush() + @pytest.fixture(autouse=True) def patch_coingekko(mocker) -> None: @@ -290,7 +294,7 @@ def get_default_conf(testdatadir): "order_book_max": 1 }, "exchange": { - "name": "bittrex", + "name": "binance", "enabled": True, "key": "key", "secret": "secret", @@ -311,7 +315,8 @@ def get_default_conf(testdatadir): "telegram": { "enabled": True, "token": "token", - "chat_id": "0" + "chat_id": "0", + "notification_settings": {}, }, "datadir": str(testdatadir), "initial_state": "running", @@ -1673,6 +1678,7 @@ def buy_order_fee(): @pytest.fixture(scope="function") def edge_conf(default_conf): conf = deepcopy(default_conf) + conf['runmode'] = RunMode.DRY_RUN conf['max_open_trades'] = -1 conf['tradable_balance_ratio'] = 0.5 conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT @@ -1762,7 +1768,7 @@ def open_trade(): return Trade( pair='ETH/BTC', open_rate=0.00001099, - exchange='bittrex', + exchange='binance', open_order_id='123456789', amount=90.99181073, fee_open=0.0, @@ -1774,7 +1780,7 @@ def open_trade(): @pytest.fixture -def hyperopt_results(): +def saved_hyperopt_results_legacy(): return [ { 'loss': 0.4366182531161519, @@ -1903,3 +1909,136 @@ def hyperopt_results(): 'is_best': False } ] + + +@pytest.fixture +def saved_hyperopt_results(): + return [ + { + 'loss': 0.4366182531161519, + 'params_dict': { + 'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1190, 'roi_t2': 541, 'roi_t3': 408, 'roi_p1': 0.026035863879169705, 'roi_p2': 0.12508730043628782, 'roi_p3': 0.27766427921605896, 'stoploss': -0.2562930402099556}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4287874435315165, 408: 0.15112316431545753, 949: 0.026035863879169705, 2139: 0}, 'stoploss': {'stoploss': -0.2562930402099556}}, # noqa: E501 + 'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0)}, # noqa: E501 + 'results_explanation': ' 2 trades. Avg profit -1.25%. Total profit -0.00125625 BTC ( -2.51Σ%). Avg duration 3930.0 min.', # noqa: E501 + 'total_profit': -0.00125625, + 'current_epoch': 1, + 'is_initial_point': True, + 'is_best': True + }, { + 'loss': 20.0, + 'params_dict': { + 'mfi-value': 17, 'fastd-value': 38, 'adx-value': 48, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 96, 'sell-fastd-value': 68, 'sell-adx-value': 63, 'sell-rsi-value': 81, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 334, 'roi_t2': 683, 'roi_t3': 140, 'roi_p1': 0.06403981740598495, 'roi_p2': 0.055519840060645045, 'roi_p3': 0.3253712811342459, 'stoploss': -0.338070047333259}, # noqa: E501 + 'params_details': { + 'buy': {'mfi-value': 17, 'fastd-value': 38, 'adx-value': 48, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, # noqa: E501 + 'sell': {'sell-mfi-value': 96, 'sell-fastd-value': 68, 'sell-adx-value': 63, 'sell-rsi-value': 81, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, # noqa: E501 + 'roi': {0: 0.4449309386008759, 140: 0.11955965746663, 823: 0.06403981740598495, 1157: 0}, # noqa: E501 + 'stoploss': {'stoploss': -0.338070047333259}}, + 'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 0, 'losses': 1, 'profit_mean': 0.012357, 'profit_median': -0.012222, 'profit_total': 6.185e-05, 'profit_total_abs': 0.12357, 'holding_avg': timedelta(minutes=1200.0)}, # noqa: E501 + 'results_explanation': ' 1 trades. Avg profit 0.12%. Total profit 0.00006185 BTC ( 0.12Σ%). Avg duration 1200.0 min.', # noqa: E501 + 'total_profit': 6.185e-05, + 'current_epoch': 2, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 14.241196856510731, + 'params_dict': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 889, 'roi_t2': 533, 'roi_t3': 263, 'roi_p1': 0.04759065393663096, 'roi_p2': 0.1488819964638463, 'roi_p3': 0.4102801822104605, 'stoploss': -0.05394588767607611}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.6067528326109377, 263: 0.19647265040047726, 796: 0.04759065393663096, 1685: 0}, 'stoploss': {'stoploss': -0.05394588767607611}}, # noqa: E501 + 'results_metrics': {'total_trades': 621, 'wins': 320, 'draws': 0, 'losses': 301, 'profit_mean': -0.043883302093397747, 'profit_median': -0.012222, 'profit_total': -0.13639474, 'profit_total_abs': -272.515306, 'holding_avg': timedelta(minutes=1691.207729468599)}, # noqa: E501 + 'results_explanation': ' 621 trades. Avg profit -0.44%. Total profit -0.13639474 BTC (-272.52Σ%). Avg duration 1691.2 min.', # noqa: E501 + 'total_profit': -0.13639474, + 'current_epoch': 3, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 100000, + 'params_dict': {'mfi-value': 13, 'fastd-value': 35, 'adx-value': 39, 'rsi-value': 29, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 87, 'sell-fastd-value': 54, 'sell-adx-value': 63, 'sell-rsi-value': 93, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1402, 'roi_t2': 676, 'roi_t3': 215, 'roi_p1': 0.06264755784937427, 'roi_p2': 0.14258587851894644, 'roi_p3': 0.20671291201040828, 'stoploss': -0.11818343570194478}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 13, 'fastd-value': 35, 'adx-value': 39, 'rsi-value': 29, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 54, 'sell-adx-value': 63, 'sell-rsi-value': 93, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.411946348378729, 215: 0.2052334363683207, 891: 0.06264755784937427, 2293: 0}, 'stoploss': {'stoploss': -0.11818343570194478}}, # noqa: E501 + 'results_metrics': {'total_trades': 0, 'wins': 0, 'draws': 0, 'losses': 0, 'profit_mean': None, 'profit_median': None, 'profit_total': 0, 'profit': 0.0, 'holding_avg': timedelta()}, # noqa: E501 + 'results_explanation': ' 0 trades. Avg profit nan%. Total profit 0.00000000 BTC ( 0.00Σ%). Avg duration nan min.', # noqa: E501 + 'total_profit': 0, 'current_epoch': 4, 'is_initial_point': True, 'is_best': False + }, { + 'loss': 0.22195522184191518, + 'params_dict': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 1269, 'roi_t2': 601, 'roi_t3': 444, 'roi_p1': 0.07280999507931168, 'roi_p2': 0.08946698095898986, 'roi_p3': 0.1454876733325284, 'stoploss': -0.18181041180901014}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3077646493708299, 444: 0.16227697603830155, 1045: 0.07280999507931168, 2314: 0}, 'stoploss': {'stoploss': -0.18181041180901014}}, # noqa: E501 + 'results_metrics': {'total_trades': 14, 'wins': 6, 'draws': 0, 'losses': 8, 'profit_mean': -0.003539515, 'profit_median': -0.012222, 'profit_total': -0.002480140000000001, 'profit_total_abs': -4.955321, 'holding_avg': timedelta(minutes=3402.8571428571427)}, # noqa: E501 + 'results_explanation': ' 14 trades. Avg profit -0.35%. Total profit -0.00248014 BTC ( -4.96Σ%). Avg duration 3402.9 min.', # noqa: E501 + 'total_profit': -0.002480140000000001, + 'current_epoch': 5, + 'is_initial_point': True, + 'is_best': True + }, { + 'loss': 0.545315889154162, + 'params_dict': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower', 'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 319, 'roi_t2': 556, 'roi_t3': 216, 'roi_p1': 0.06251955472249589, 'roi_p2': 0.11659519602202795, 'roi_p3': 0.0953744132197762, 'stoploss': -0.024551752215582423}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.2744891639643, 216: 0.17911475074452382, 772: 0.06251955472249589, 1091: 0}, 'stoploss': {'stoploss': -0.024551752215582423}}, # noqa: E501 + 'results_metrics': {'total_trades': 39, 'wins': 20, 'draws': 0, 'losses': 19, 'profit_mean': -0.0021400679487179478, 'profit_median': -0.012222, 'profit_total': -0.0041773, 'profit_total_abs': -8.346264999999997, 'holding_avg': timedelta(minutes=636.9230769230769)}, # noqa: E501 + 'results_explanation': ' 39 trades. Avg profit -0.21%. Total profit -0.00417730 BTC ( -8.35Σ%). Avg duration 636.9 min.', # noqa: E501 + 'total_profit': -0.0041773, + 'current_epoch': 6, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 4.713497421432944, + 'params_dict': {'mfi-value': 13, 'fastd-value': 41, 'adx-value': 21, 'rsi-value': 29, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower', 'sell-mfi-value': 99, 'sell-fastd-value': 60, 'sell-adx-value': 81, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 771, 'roi_t2': 620, 'roi_t3': 145, 'roi_p1': 0.0586919200378493, 'roi_p2': 0.04984118697312542, 'roi_p3': 0.37521058680247044, 'stoploss': -0.14613268022709905}, # noqa: E501 + 'params_details': { + 'buy': {'mfi-value': 13, 'fastd-value': 41, 'adx-value': 21, 'rsi-value': 29, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 99, 'sell-fastd-value': 60, 'sell-adx-value': 81, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.4837436938134452, 145: 0.10853310701097472, 765: 0.0586919200378493, 1536: 0}, # noqa: E501 + 'stoploss': {'stoploss': -0.14613268022709905}}, # noqa: E501 + 'results_metrics': {'total_trades': 318, 'wins': 100, 'draws': 0, 'losses': 218, 'profit_mean': -0.0039833954716981146, 'profit_median': -0.012222, 'profit_total': -0.06339929, 'profit_total_abs': -126.67197600000004, 'holding_avg': timedelta(minutes=3140.377358490566)}, # noqa: E501 + 'results_explanation': ' 318 trades. Avg profit -0.40%. Total profit -0.06339929 BTC (-126.67Σ%). Avg duration 3140.4 min.', # noqa: E501 + 'total_profit': -0.06339929, + 'current_epoch': 7, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 20.0, # noqa: E501 + 'params_dict': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal', 'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 1149, 'roi_t2': 375, 'roi_t3': 289, 'roi_p1': 0.05571820757172588, 'roi_p2': 0.0606240398618907, 'roi_p3': 0.1729012220156157, 'stoploss': -0.1588514289110401}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.2892434694492323, 289: 0.11634224743361658, 664: 0.05571820757172588, 1813: 0}, 'stoploss': {'stoploss': -0.1588514289110401}}, # noqa: E501 + 'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 1, 'losses': 0, 'profit_mean': 0.0, 'profit_median': 0.0, 'profit_total': 0.0, 'profit_total_abs': 0.0, 'holding_avg': timedelta(minutes=5340.0)}, # noqa: E501 + 'results_explanation': ' 1 trades. Avg profit 0.00%. Total profit 0.00000000 BTC ( 0.00Σ%). Avg duration 5340.0 min.', # noqa: E501 + 'total_profit': 0.0, + 'current_epoch': 8, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 2.4731817780991223, + 'params_dict': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1012, 'roi_t2': 584, 'roi_t3': 422, 'roi_p1': 0.036764323603472565, 'roi_p2': 0.10335480573205287, 'roi_p3': 0.10322347377503042, 'stoploss': -0.2780610808108503}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.2433426031105559, 422: 0.14011912933552545, 1006: 0.036764323603472565, 2018: 0}, 'stoploss': {'stoploss': -0.2780610808108503}}, # noqa: E501 + 'results_metrics': {'total_trades': 229, 'wins': 150, 'draws': 0, 'losses': 79, 'profit_mean': -0.0038433433624454144, 'profit_median': -0.012222, 'profit_total': -0.044050070000000004, 'profit_total_abs': -88.01256299999999, 'holding_avg': timedelta(minutes=6505.676855895196)}, # noqa: E501 + 'results_explanation': ' 229 trades. Avg profit -0.38%. Total profit -0.04405007 BTC ( -88.01Σ%). Avg duration 6505.7 min.', # noqa: E501 + 'total_profit': -0.044050070000000004, # noqa: E501 + 'current_epoch': 9, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': -0.2604606005845212, # noqa: E501 + 'params_dict': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 792, 'roi_t2': 464, 'roi_t3': 215, 'roi_p1': 0.04594053535385903, 'roi_p2': 0.09623192684243963, 'roi_p3': 0.04428219070850663, 'stoploss': -0.16992287161634415}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.18645465290480528, 215: 0.14217246219629864, 679: 0.04594053535385903, 1471: 0}, 'stoploss': {'stoploss': -0.16992287161634415}}, # noqa: E501 + 'results_metrics': {'total_trades': 4, 'wins': 0, 'draws': 0, 'losses': 4, 'profit_mean': 0.001080385, 'profit_median': -0.012222, 'profit_total': 0.00021629, 'profit_total_abs': 0.432154, 'holding_avg': timedelta(minutes=2850.0)}, # noqa: E501 + 'results_explanation': ' 4 trades. Avg profit 0.11%. Total profit 0.00021629 BTC ( 0.43Σ%). Avg duration 2850.0 min.', # noqa: E501 + 'total_profit': 0.00021629, + 'current_epoch': 10, + 'is_initial_point': True, + 'is_best': True + }, { + 'loss': 4.876465945994304, # noqa: E501 + 'params_dict': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower', 'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 579, 'roi_t2': 614, 'roi_t3': 273, 'roi_p1': 0.05307643172744114, 'roi_p2': 0.1352282078262871, 'roi_p3': 0.1913307406325751, 'stoploss': -0.25728526022513887}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3796353801863034, 273: 0.18830463955372825, 887: 0.05307643172744114, 1466: 0}, 'stoploss': {'stoploss': -0.25728526022513887}}, # noqa: E501 + # New Hyperopt mode! + 'results_metrics': {'total_trades': 117, 'wins': 67, 'draws': 0, 'losses': 50, 'profit_mean': -0.012698609145299145, 'profit_median': -0.012222, 'profit_total': -0.07436117, 'profit_total_abs': -148.573727, 'holding_avg': timedelta(minutes=4282.5641025641025)}, # noqa: E501 + 'results_explanation': ' 117 trades. Avg profit -1.27%. Total profit -0.07436117 BTC (-148.57Σ%). Avg duration 4282.6 min.', # noqa: E501 + 'total_profit': -0.07436117, + 'current_epoch': 11, + 'is_initial_point': True, + 'is_best': False + }, { + 'loss': 100000, + 'params_dict': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1156, 'roi_t2': 581, 'roi_t3': 408, 'roi_p1': 0.06860454019988212, 'roi_p2': 0.12473718444931989, 'roi_p3': 0.2896360635226823, 'stoploss': -0.30889015124682806}, # noqa: E501 + 'params_details': {'buy': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4829777881718843, 408: 0.19334172464920202, 989: 0.06860454019988212, 2145: 0}, 'stoploss': {'stoploss': -0.30889015124682806}}, # noqa: E501 + 'results_metrics': {'total_trades': 0, 'wins': 0, 'draws': 0, 'losses': 0, 'profit_mean': None, 'profit_median': None, 'profit_total': 0, 'profit_total_abs': 0.0, 'holding_avg': timedelta()}, # noqa: E501 + 'results_explanation': ' 0 trades. Avg profit nan%. Total profit 0.00000000 BTC ( 0.00Σ%). Avg duration nan min.', # noqa: E501 + 'total_profit': 0, + 'current_epoch': 12, + 'is_initial_point': True, + 'is_best': False + } + ] diff --git a/tests/conftest_trades.py b/tests/conftest_trades.py index 8e4be9165..b92b51144 100644 --- a/tests/conftest_trades.py +++ b/tests/conftest_trades.py @@ -31,7 +31,7 @@ def mock_trade_1(fee): is_open=True, open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=17), open_rate=0.123, - exchange='bittrex', + exchange='binance', open_order_id='dry_run_buy_12345', strategy='DefaultStrategy', timeframe=5, @@ -84,7 +84,7 @@ def mock_trade_2(fee): close_rate=0.128, close_profit=0.005, close_profit_abs=0.000584127, - exchange='bittrex', + exchange='binance', is_open=False, open_order_id='dry_run_sell_12345', strategy='DefaultStrategy', @@ -144,7 +144,7 @@ def mock_trade_3(fee): close_rate=0.06, close_profit=0.01, close_profit_abs=0.000155, - exchange='bittrex', + exchange='binance', is_open=False, strategy='DefaultStrategy', timeframe=5, @@ -187,7 +187,7 @@ def mock_trade_4(fee): open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=14), is_open=True, open_rate=0.123, - exchange='bittrex', + exchange='binance', open_order_id='prod_buy_12345', strategy='DefaultStrategy', timeframe=5, @@ -239,9 +239,10 @@ def mock_trade_5(fee): open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=12), is_open=True, open_rate=0.123, - exchange='bittrex', + exchange='binance', strategy='SampleStrategy', - stoploss_order_id='prod_stoploss_3455' + stoploss_order_id='prod_stoploss_3455', + timeframe=5, ) o = Order.parse_from_ccxt_object(mock_order_5(), 'XRP/BTC', 'buy') trade.orders.append(o) @@ -292,9 +293,10 @@ def mock_trade_6(fee): fee_close=fee.return_value, is_open=True, open_rate=0.15, - exchange='bittrex', + exchange='binance', strategy='SampleStrategy', open_order_id="prod_sell_6", + timeframe=5, ) o = Order.parse_from_ccxt_object(mock_order_6(), 'LTC/BTC', 'buy') trade.orders.append(o) diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index e42c13e18..6bde60926 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -1,3 +1,4 @@ +from math import isclose from pathlib import Path from unittest.mock import MagicMock @@ -246,7 +247,7 @@ def test_create_cum_profit(testdatadir): "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 - assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005 + assert isclose(cum_profits.iloc[-1]['cum_profits'], 8.723007518796964e-06) def test_create_cum_profit1(testdatadir): @@ -264,7 +265,7 @@ def test_create_cum_profit1(testdatadir): "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 - assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005 + assert isclose(cum_profits.iloc[-1]['cum_profits'], 8.723007518796964e-06) with pytest.raises(ValueError, match='Trade dataframe empty.'): create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'NOTAPAIR'], diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py index 4fdcce4d2..68960af1c 100644 --- a/tests/data/test_converter.py +++ b/tests/data/test_converter.py @@ -10,7 +10,7 @@ from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_forma trades_to_ohlcv, trim_dataframe) from freqtrade.data.history import (get_timerange, load_data, load_pair_history, validate_backtest_data) -from tests.conftest import log_has +from tests.conftest import log_has, log_has_re from tests.data.test_history import _backup_file, _clean_test_file @@ -62,8 +62,8 @@ def test_ohlcv_fill_up_missing_data(testdatadir, caplog): # Column names should not change assert (data.columns == data2.columns).all() - assert log_has(f"Missing data fillup for UNITTEST/BTC: before: " - f"{len(data)} - after: {len(data2)}", caplog) + assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: " + f"{len(data)} - after: {len(data2)}.*", caplog) # Test fillup actually fixes invalid backtest data min_date, max_date = get_timerange({'UNITTEST/BTC': data}) @@ -125,8 +125,8 @@ def test_ohlcv_fill_up_missing_data2(caplog): # Column names should not change assert (data.columns == data2.columns).all() - assert log_has(f"Missing data fillup for UNITTEST/BTC: before: " - f"{len(data)} - after: {len(data2)}", caplog) + assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: " + f"{len(data)} - after: {len(data2)}.*", caplog) def test_ohlcv_drop_incomplete(caplog): @@ -197,6 +197,16 @@ def test_trim_dataframe(testdatadir) -> None: assert all(data_modify.iloc[-1] == data.iloc[-1]) assert all(data_modify.iloc[0] == data.iloc[30]) + data_modify = data.copy() + tr = TimeRange('date', None, min_date + 1800, 0) + # Remove first 20 candles - ignores min date + data_modify = trim_dataframe(data_modify, tr, startup_candles=20) + assert not data_modify.equals(data) + assert len(data_modify) < len(data) + assert len(data_modify) == len(data) - 20 + assert all(data_modify.iloc[-1] == data.iloc[-1]) + assert all(data_modify.iloc[0] == data.iloc[20]) + data_modify = data.copy() # Remove last 30 minutes (1800 s) tr = TimeRange(None, 'date', 0, max_date - 1800) diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py index ee2e551b6..b87258c64 100644 --- a/tests/data/test_dataprovider.py +++ b/tests/data/test_dataprovider.py @@ -214,8 +214,8 @@ def test_current_whitelist(mocker, default_conf, tickers): pairlist.refresh_pairlist() assert dp.current_whitelist() == pairlist._whitelist - # The identity of the 2 lists should be identical - assert dp.current_whitelist() is pairlist._whitelist + # The identity of the 2 lists should not be identical, but a copy + assert dp.current_whitelist() is not pairlist._whitelist with pytest.raises(OperationalException): dp = DataProvider(default_conf, exchange) @@ -246,3 +246,46 @@ def test_get_analyzed_dataframe(mocker, default_conf, ohlcv_history): assert dataframe.empty assert isinstance(time, datetime) assert time == datetime(1970, 1, 1, tzinfo=timezone.utc) + + # Test backtest mode + default_conf["runmode"] = RunMode.BACKTEST + dp._set_dataframe_max_index(1) + dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe) + + assert len(dataframe) == 1 + + dp._set_dataframe_max_index(2) + dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe) + assert len(dataframe) == 2 + + dp._set_dataframe_max_index(3) + dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe) + assert len(dataframe) == 3 + + dp._set_dataframe_max_index(500) + dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe) + assert len(dataframe) == len(ohlcv_history) + + +def test_no_exchange_mode(default_conf): + dp = DataProvider(default_conf, None) + + message = "Exchange is not available to DataProvider." + + with pytest.raises(OperationalException, match=message): + dp.refresh([()]) + + with pytest.raises(OperationalException, match=message): + dp.ohlcv('XRP/USDT', '5m') + + with pytest.raises(OperationalException, match=message): + dp.market('XRP/USDT') + + with pytest.raises(OperationalException, match=message): + dp.ticker('XRP/USDT') + + with pytest.raises(OperationalException, match=message): + dp.orderbook('XRP/USDT', 20) + + with pytest.raises(OperationalException, match=message): + dp.available_pairs() diff --git a/tests/edge/test_edge.py b/tests/edge/test_edge.py index c30bce6a4..c4620e1c7 100644 --- a/tests/edge/test_edge.py +++ b/tests/edge/test_edge.py @@ -266,7 +266,7 @@ def test_edge_heartbeat_calculate(mocker, edge_conf): # should not recalculate if heartbeat not reached edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1 - assert edge.calculate() is False + assert edge.calculate(edge_conf['exchange']['pair_whitelist']) is False def mocked_load_data(datadir, pairs=[], timeframe='0m', @@ -310,7 +310,7 @@ def test_edge_process_downloaded_data(mocker, edge_conf): mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) - assert edge.calculate() + assert edge.calculate(edge_conf['exchange']['pair_whitelist']) assert len(edge._cached_pairs) == 2 assert edge._last_updated <= arrow.utcnow().int_timestamp + 2 @@ -322,7 +322,7 @@ def test_edge_process_no_data(mocker, edge_conf, caplog): mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={})) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) - assert not edge.calculate() + assert not edge.calculate(edge_conf['exchange']['pair_whitelist']) assert len(edge._cached_pairs) == 0 assert log_has("No data found. Edge is stopped ...", caplog) assert edge._last_updated == 0 @@ -330,18 +330,37 @@ def test_edge_process_no_data(mocker, edge_conf, caplog): def test_edge_process_no_trades(mocker, edge_conf, caplog): freqtrade = get_patched_freqtradebot(mocker, edge_conf) - mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001)) - mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock()) + mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001) + mocker.patch('freqtrade.edge.edge_positioning.refresh_data', ) mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data) # Return empty - mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', MagicMock(return_value=[])) + mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[]) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) - assert not edge.calculate() + assert not edge.calculate(edge_conf['exchange']['pair_whitelist']) assert len(edge._cached_pairs) == 0 assert log_has("No trades found.", caplog) +def test_edge_process_no_pairs(mocker, edge_conf, caplog): + edge_conf['exchange']['pair_whitelist'] = [] + mocker.patch('freqtrade.freqtradebot.validate_config_consistency') + + freqtrade = get_patched_freqtradebot(mocker, edge_conf) + fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', return_value=0.001) + mocker.patch('freqtrade.edge.edge_positioning.refresh_data') + mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data) + # Return empty + mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', return_value=[]) + edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) + assert fee_mock.call_count == 0 + assert edge.fee is None + + assert not edge.calculate(['XRP/USDT']) + assert fee_mock.call_count == 1 + assert edge.fee == 0.001 + + def test_edge_init_error(mocker, edge_conf,): edge_conf['stake_amount'] = 0.5 mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001)) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 870e6cabd..dce10da84 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -36,7 +36,12 @@ EXCHANGES = { 'pair': 'BTC/USDT', 'hasQuoteVolume': True, 'timeframe': '5m', - } + }, + 'kucoin': { + 'pair': 'BTC/USDT', + 'hasQuoteVolume': True, + 'timeframe': '5m', + }, } @@ -100,14 +105,16 @@ class TestCCXTExchange(): assert 'asks' in l2 assert 'bids' in l2 l2_limit_range = exchange._ft_has['l2_limit_range'] + l2_limit_range_required = exchange._ft_has['l2_limit_range_required'] for val in [1, 2, 5, 25, 100]: l2 = exchange.fetch_l2_order_book(pair, val) if not l2_limit_range or val in l2_limit_range: assert len(l2['asks']) == val assert len(l2['bids']) == val else: - next_limit = exchange.get_next_limit_in_list(val, l2_limit_range) - if next_limit > 200: + next_limit = exchange.get_next_limit_in_list( + val, l2_limit_range, l2_limit_range_required) + if next_limit is None or next_limit > 200: # Large orderbook sizes can be a problem for some exchanges (bitrex ...) assert len(l2['asks']) > 200 assert len(l2['asks']) > 200 diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 3439c7a09..b6b395802 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -371,7 +371,7 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None: PropertyMock(return_value=markets) ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) - assert isclose(result, 2 * 1.1) + assert isclose(result, 2 * (1+0.05) / (1-abs(stoploss))) # min amount is set markets["ETH/BTC"]["limits"] = { @@ -383,7 +383,7 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None: PropertyMock(return_value=markets) ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) - assert isclose(result, 2 * 2 * 1.1) + assert isclose(result, 2 * 2 * (1+0.05) / (1-abs(stoploss))) # min amount and cost are set (cost is minimal) markets["ETH/BTC"]["limits"] = { @@ -395,7 +395,7 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None: PropertyMock(return_value=markets) ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) - assert isclose(result, max(2, 2 * 2) * 1.1) + assert isclose(result, max(2, 2 * 2) * (1+0.05) / (1-abs(stoploss))) # min amount and cost are set (amount is minial) markets["ETH/BTC"]["limits"] = { @@ -407,10 +407,10 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None: PropertyMock(return_value=markets) ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) - assert isclose(result, max(8, 2 * 2) * 1.1) + assert isclose(result, max(8, 2 * 2) * (1+0.05) / (1-abs(stoploss))) result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -0.4) - assert isclose(result, max(8, 2 * 2) * 1.45) + assert isclose(result, max(8, 2 * 2) * 1.5) # Really big stoploss result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1) @@ -432,7 +432,10 @@ def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None: PropertyMock(return_value=markets) ) result = exchange.get_min_pair_stake_amount('ETH/BTC', 0.020405, stoploss) - assert round(result, 8) == round(max(0.0001, 0.001 * 0.020405) * 1.1, 8) + assert round(result, 8) == round( + max(0.0001, 0.001 * 0.020405) * (1+0.05) / (1-abs(stoploss)), + 8 + ) def test_set_sandbox(default_conf, mocker): @@ -931,11 +934,11 @@ def test_exchange_has(default_conf, mocker): ("sell") ]) @pytest.mark.parametrize("exchange_name", EXCHANGES) -def test_dry_run_order(default_conf, mocker, side, exchange_name): +def test_create_dry_run_order(default_conf, mocker, side, exchange_name): default_conf['dry_run'] = True exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) - order = exchange.dry_run_order( + order = exchange.create_dry_run_order( pair='ETH/BTC', ordertype='limit', side=side, amount=1, rate=200) assert 'id' in order assert f'dry_run_{side}_' in order["id"] @@ -1245,44 +1248,6 @@ def test_sell_considers_time_in_force(default_conf, mocker, exchange_name): assert "timeInForce" not in api_mock.create_order.call_args[0][5] -def test_get_balance_dry_run(default_conf, mocker): - default_conf['dry_run'] = True - default_conf['dry_run_wallet'] = 999.9 - - exchange = get_patched_exchange(mocker, default_conf) - assert exchange.get_balance(currency='BTC') == 999.9 - - -@pytest.mark.parametrize("exchange_name", EXCHANGES) -def test_get_balance_prod(default_conf, mocker, exchange_name): - api_mock = MagicMock() - api_mock.fetch_balance = MagicMock(return_value={'BTC': {'free': 123.4, 'total': 123.4}}) - default_conf['dry_run'] = False - - exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) - - assert exchange.get_balance(currency='BTC') == 123.4 - - with pytest.raises(OperationalException): - api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError("Unknown error")) - exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) - - exchange.get_balance(currency='BTC') - - with pytest.raises(TemporaryError, match=r'.*balance due to malformed exchange response:.*'): - exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) - mocker.patch('freqtrade.exchange.Exchange.get_balances', MagicMock(return_value={})) - mocker.patch('freqtrade.exchange.Kraken.get_balances', MagicMock(return_value={})) - exchange.get_balance(currency='BTC') - - -@pytest.mark.parametrize("exchange_name", EXCHANGES) -def test_get_balances_dry_run(default_conf, mocker, exchange_name): - default_conf['dry_run'] = True - exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) - assert exchange.get_balances() == {} - - @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_get_balances_prod(default_conf, mocker, exchange_name): balance_item = { @@ -1334,6 +1299,16 @@ def test_get_tickers(default_conf, mocker, exchange_name): assert tickers['ETH/BTC']['ask'] == 1 assert tickers['BCH/BTC']['bid'] == 0.6 assert tickers['BCH/BTC']['ask'] == 0.5 + assert api_mock.fetch_tickers.call_count == 1 + + api_mock.fetch_tickers.reset_mock() + + # Cached ticker should not call api again + tickers2 = exchange.get_tickers(cached=True) + assert tickers2 == tickers + assert api_mock.fetch_tickers.call_count == 0 + tickers2 = exchange.get_tickers(cached=False) + assert api_mock.fetch_tickers.call_count == 1 ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name, "get_tickers", "fetch_tickers") @@ -1656,6 +1631,9 @@ def test_get_next_limit_in_list(): # Going over the limit ... assert Exchange.get_next_limit_in_list(1001, limit_range) == 1000 assert Exchange.get_next_limit_in_list(2000, limit_range) == 1000 + # Without required range + assert Exchange.get_next_limit_in_list(2000, limit_range, False) is None + assert Exchange.get_next_limit_in_list(15, limit_range, False) == 20 assert Exchange.get_next_limit_in_list(21, None) == 21 assert Exchange.get_next_limit_in_list(100, None) == 100 @@ -2106,6 +2084,46 @@ def test_cancel_stoploss_order(default_conf, mocker, exchange_name): order_id='_', pair='TKN/BTC') +@pytest.mark.parametrize("exchange_name", EXCHANGES) +def test_cancel_stoploss_order_with_result(default_conf, mocker, exchange_name): + default_conf['dry_run'] = False + mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', return_value={'for': 123}) + mocker.patch('freqtrade.exchange.Ftx.fetch_stoploss_order', return_value={'for': 123}) + exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) + + mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', + return_value={'fee': {}, 'status': 'canceled', 'amount': 1234}) + mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', + return_value={'fee': {}, 'status': 'canceled', 'amount': 1234}) + co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555) + assert co == {'fee': {}, 'status': 'canceled', 'amount': 1234} + + mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', + return_value='canceled') + mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', + return_value='canceled') + # Fall back to fetch_stoploss_order + co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555) + assert co == {'for': 123} + + mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', + side_effect=InvalidOrderException("")) + mocker.patch('freqtrade.exchange.Ftx.fetch_stoploss_order', + side_effect=InvalidOrderException("")) + + co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555) + assert co['amount'] == 555 + assert co == {'fee': {}, 'status': 'canceled', 'amount': 555, 'info': {}} + + with pytest.raises(InvalidOrderException): + mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', + side_effect=InvalidOrderException("Did not find order")) + mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', + side_effect=InvalidOrderException("Did not find order")) + exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) + exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=123) + + @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_fetch_order(default_conf, mocker, exchange_name): default_conf['dry_run'] = True diff --git a/tests/exchange/test_ftx.py b/tests/exchange/test_ftx.py index 17cfb26fa..63d99acdf 100644 --- a/tests/exchange/test_ftx.py +++ b/tests/exchange/test_ftx.py @@ -39,8 +39,9 @@ def test_stoploss_order_ftx(default_conf, mocker): assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell' assert api_mock.create_order.call_args_list[0][1]['amount'] == 1 - assert api_mock.create_order.call_args_list[0][1]['price'] == 190 assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params'] + assert 'stopPrice' in api_mock.create_order.call_args_list[0][1]['params'] + assert api_mock.create_order.call_args_list[0][1]['params']['stopPrice'] == 190 assert api_mock.create_order.call_count == 1 @@ -55,8 +56,8 @@ def test_stoploss_order_ftx(default_conf, mocker): assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell' assert api_mock.create_order.call_args_list[0][1]['amount'] == 1 - assert api_mock.create_order.call_args_list[0][1]['price'] == 220 assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params'] + assert api_mock.create_order.call_args_list[0][1]['params']['stopPrice'] == 220 api_mock.create_order.reset_mock() order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, @@ -69,9 +70,9 @@ def test_stoploss_order_ftx(default_conf, mocker): assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell' assert api_mock.create_order.call_args_list[0][1]['amount'] == 1 - assert api_mock.create_order.call_args_list[0][1]['price'] == 220 assert 'orderPrice' in api_mock.create_order.call_args_list[0][1]['params'] assert api_mock.create_order.call_args_list[0][1]['params']['orderPrice'] == 217.8 + assert api_mock.create_order.call_args_list[0][1]['params']['stopPrice'] == 220 # test exception handling with pytest.raises(DependencyException): @@ -156,3 +157,26 @@ def test_fetch_stoploss_order(default_conf, mocker): 'fetch_stoploss_order', 'fetch_orders', retries=API_FETCH_ORDER_RETRY_COUNT + 1, order_id='_', pair='TKN/BTC') + + +def test_get_order_id(mocker, default_conf): + exchange = get_patched_exchange(mocker, default_conf, id='ftx') + order = { + 'type': STOPLOSS_ORDERTYPE, + 'price': 1500, + 'id': '1111', + 'info': { + 'orderId': '1234' + } + } + assert exchange.get_order_id_conditional(order) == '1234' + + order = { + 'type': 'limit', + 'price': 1500, + 'id': '1111', + 'info': { + 'orderId': '1234' + } + } + assert exchange.get_order_id_conditional(order) == '1111' diff --git a/tests/exchange/test_kraken.py b/tests/exchange/test_kraken.py index 97f428e2f..ed22cde92 100644 --- a/tests/exchange/test_kraken.py +++ b/tests/exchange/test_kraken.py @@ -90,6 +90,7 @@ def test_get_balances_prod(default_conf, mocker): '3ST': balance_item.copy(), '4ST': balance_item.copy(), 'EUR': balance_item.copy(), + 'timestamp': 123123 }) kraken_open_orders = [{'symbol': '1ST/EUR', 'type': 'limit', @@ -138,7 +139,7 @@ def test_get_balances_prod(default_conf, mocker): default_conf['dry_run'] = False exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken") balances = exchange.get_balances() - assert len(balances) == 5 + assert len(balances) == 6 assert balances['1ST']['free'] == 9.0 assert balances['1ST']['total'] == 10.0 diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py index df6f22e01..11b4674f3 100644 --- a/tests/optimize/conftest.py +++ b/tests/optimize/conftest.py @@ -6,6 +6,7 @@ import pandas as pd import pytest from freqtrade.optimize.hyperopt import Hyperopt +from freqtrade.state import RunMode from freqtrade.strategy.interface import SellType from tests.conftest import patch_exchange @@ -14,6 +15,8 @@ from tests.conftest import patch_exchange def hyperopt_conf(default_conf): hyperconf = deepcopy(default_conf) hyperconf.update({ + 'datadir': Path(default_conf['datadir']), + 'runmode': RunMode.HYPEROPT, 'hyperopt': 'DefaultHyperOpt', 'hyperopt_loss': 'ShortTradeDurHyperOptLoss', 'hyperopt_path': str(Path(__file__).parent / 'hyperopts'), @@ -21,6 +24,7 @@ def hyperopt_conf(default_conf): 'timerange': None, 'spaces': ['default'], 'hyperopt_jobs': 1, + 'hyperopt_min_trades': 1, }) return hyperconf diff --git a/tests/optimize/test_backtest_detail.py b/tests/optimize/test_backtest_detail.py index 0ba6f4a7f..c35a083ec 100644 --- a/tests/optimize/test_backtest_detail.py +++ b/tests/optimize/test_backtest_detail.py @@ -185,7 +185,7 @@ tc11 = BTContainer(data=[ [0, 5000, 5050, 4950, 5000, 6172, 1, 0], [1, 5000, 5050, 4950, 5100, 6172, 0, 0], [2, 5100, 5251, 5100, 5100, 6172, 0, 0], - [3, 4850, 5050, 4650, 4750, 6172, 0, 0], + [3, 5000, 5150, 4650, 4750, 6172, 0, 0], [4, 4750, 4950, 4350, 4750, 6172, 0, 0]], stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True, trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05, @@ -268,7 +268,7 @@ tc16 = BTContainer(data=[ # Test 17: Buy, hold for 120 mins, then forcesell using roi=-1 # Causes negative profit even though sell-reason is ROI. # stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration) -# Uses open as sell-rate (special case) - since the roi-time is a multiple of the ticker interval. +# Uses open as sell-rate (special case) - since the roi-time is a multiple of the timeframe. tc17 = BTContainer(data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], @@ -440,6 +440,23 @@ tc27 = BTContainer(data=[ trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=4)] ) +# Test 28: trailing_stop should raise so candle 3 causes a stoploss +# Same case than tc11 - but candle 3 "gaps down" - the stoploss will be above the candle, +# therefore "open" will be used +# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2 +tc28 = BTContainer(data=[ + # D O H L C V B S + [0, 5000, 5050, 4950, 5000, 6172, 1, 0], + [1, 5000, 5050, 4950, 5100, 6172, 0, 0], + [2, 5100, 5251, 5100, 5100, 6172, 0, 0], + [3, 4850, 5050, 4650, 4750, 6172, 0, 0], + [4, 4750, 4950, 4350, 4750, 6172, 0, 0]], + stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.03, trailing_stop=True, + trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05, + trailing_stop_positive=0.03, + trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)] +) + TESTS = [ tc0, tc1, @@ -469,6 +486,7 @@ TESTS = [ tc25, tc26, tc27, + tc28, ] @@ -493,6 +511,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: patch_exchange(mocker) frame = _build_backtest_dataframe(data.data) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.advise_buy = lambda a, m: frame backtesting.strategy.advise_sell = lambda a, m: frame caplog.set_level(logging.DEBUG) @@ -501,13 +520,14 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: # Dummy data as we mock the analyze functions data_processed = {pair: frame.copy()} min_date, max_date = get_timerange({pair: frame}) - results = backtesting.backtest( + result = backtesting.backtest( processed=data_processed, start_date=min_date, end_date=max_date, max_open_trades=10, ) + results = result['results'] assert len(results) == len(data.trades) assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3) diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index 4bbfe8a78..632d458ce 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -83,6 +83,7 @@ def simple_backtest(config, contour, mocker, testdatadir) -> None: patch_exchange(mocker) config['timeframe'] = '1m' backtesting = Backtesting(config) + backtesting._set_strategy(backtesting.strategylist[0]) data = load_data_test(contour, testdatadir) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) @@ -106,6 +107,7 @@ def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'): data = trim_dictlist(data, -201) patch_exchange(mocker) backtesting = Backtesting(conf) + backtesting._set_strategy(backtesting.strategylist[0]) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) return { @@ -285,6 +287,7 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None: patch_exchange(mocker) get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5)) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) assert backtesting.config == default_conf assert backtesting.timeframe == '5m' assert callable(backtesting.strategy.ohlcvdata_to_dataframe) @@ -315,11 +318,13 @@ def test_data_with_fee(default_conf, mocker, testdatadir) -> None: fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5)) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) assert backtesting.fee == 0.1234 assert fee_mock.call_count == 0 default_conf['fee'] = 0.0 backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) assert backtesting.fee == 0.0 assert fee_mock.call_count == 0 @@ -330,6 +335,7 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None: data = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange, fill_up_missing=True) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) assert len(processed['UNITTEST/BTC']) == 102 @@ -361,12 +367,13 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None: default_conf['timerange'] = '-1510694220' backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.bot_loop_start = MagicMock() backtesting.start() # check the logs, that will contain the backtest result exists = [ 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:59:00 (0 days)..' + 'up to 2017-11-14 22:59:00 (0 days).' ] for line in exists: assert log_has(line, caplog) @@ -393,6 +400,7 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) -> default_conf['timerange'] = '20180101-20180102' backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) with pytest.raises(OperationalException, match='No data found. Terminating.'): backtesting.start() @@ -457,13 +465,15 @@ def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, ti Backtesting(default_conf) -def test_backtest__enter_trade(default_conf, fee, mocker, testdatadir) -> None: +def test_backtest__enter_trade(default_conf, fee, mocker) -> None: default_conf['ask_strategy']['use_sell_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) default_conf['stake_amount'] = 'unlimited' + default_conf['max_open_trades'] = 2 backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) pair = 'UNITTEST/BTC' row = [ pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0), @@ -474,24 +484,30 @@ def test_backtest__enter_trade(default_conf, fee, mocker, testdatadir) -> None: 0.00099, # Low 0.0012, # High ] - trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) + trade = backtesting._enter_trade(pair, row=row) assert isinstance(trade, LocalTrade) assert trade.stake_amount == 495 - trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=2) + # Fake 2 trades, so there's not enough amount for the next trade left. + LocalTrade.trades_open.append(trade) + LocalTrade.trades_open.append(trade) + trade = backtesting._enter_trade(pair, row=row) assert trade is None + LocalTrade.trades_open.pop() + trade = backtesting._enter_trade(pair, row=row) + assert trade is not None # Stake-amount too high! mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0) - trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) + trade = backtesting._enter_trade(pair, row=row) assert trade is None - # Stake-amount too high! + # Stake-amount throwing error mocker.patch("freqtrade.wallets.Wallets.get_trade_stake_amount", side_effect=DependencyException) - trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) + trade = backtesting._enter_trade(pair, row=row) assert trade is None @@ -501,19 +517,21 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) pair = 'UNITTEST/BTC' timerange = TimeRange('date', None, 1517227800, 0) data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'], timerange=timerange) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) - results = backtesting.backtest( + result = backtesting.backtest( processed=processed, start_date=min_date, end_date=max_date, max_open_trades=10, position_stacking=False, ) + results = result['results'] assert not results.empty assert len(results) == 2 @@ -562,6 +580,7 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) # Run a backtesting for an exiting 1min timeframe timerange = TimeRange.parse_timerange('1510688220-1510700340') @@ -576,13 +595,14 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None max_open_trades=1, position_stacking=False, ) - assert not results.empty - assert len(results) == 1 + assert not results['results'].empty + assert len(results['results']) == 1 def test_processed(default_conf, mocker, testdatadir) -> None: patch_exchange(mocker) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) dict_of_tickerrows = load_data_test('raise', testdatadir) dataframes = backtesting.strategy.ohlcvdata_to_dataframe(dict_of_tickerrows) @@ -616,7 +636,7 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad # While buy-signals are unrealistic, running backtesting # over and over again should not cause different results for [contour, numres] in tests: - assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == numres + assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres @pytest.mark.parametrize('protections,contour,expected', [ @@ -641,7 +661,7 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir, mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) # While buy-signals are unrealistic, running backtesting # over and over again should not cause different results - assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == expected + assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == expected def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir): @@ -653,10 +673,11 @@ def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir): backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.advise_buy = fun # Override backtesting.strategy.advise_sell = fun # Override - results = backtesting.backtest(**backtest_conf) - assert results.empty + result = backtesting.backtest(**backtest_conf) + assert result['results'].empty def test_backtest_only_sell(mocker, default_conf, testdatadir): @@ -668,10 +689,11 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir): backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir) backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.advise_buy = fun # Override backtesting.strategy.advise_sell = fun # Override - results = backtesting.backtest(**backtest_conf) - assert results.empty + result = backtesting.backtest(**backtest_conf) + assert result['results'].empty def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir): @@ -681,12 +703,14 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir): pair='UNITTEST/BTC', datadir=testdatadir) default_conf['timeframe'] = '1m' backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.advise_buy = _trend_alternate # Override backtesting.strategy.advise_sell = _trend_alternate # Override - results = backtesting.backtest(**backtest_conf) + result = backtesting.backtest(**backtest_conf) # 200 candles in backtest data # won't buy on first (shifted by 1) # 100 buys signals + results = result['results'] assert len(results) == 100 # One trade was force-closed at the end assert len(results.loc[results['is_open']]) == 0 @@ -722,6 +746,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) default_conf['timeframe'] = '5m' backtesting = Backtesting(default_conf) + backtesting._set_strategy(backtesting.strategylist[0]) backtesting.strategy.advise_buy = _trend_alternate_hold # Override backtesting.strategy.advise_sell = _trend_alternate_hold # Override @@ -738,9 +763,9 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) results = backtesting.backtest(**backtest_conf) # Make sure we have parallel trades - assert len(evaluate_result_multi(results, '5m', 2)) > 0 + assert len(evaluate_result_multi(results['results'], '5m', 2)) > 0 # make sure we don't have trades with more than configured max_open_trades - assert len(evaluate_result_multi(results, '5m', 3)) == 0 + assert len(evaluate_result_multi(results['results'], '5m', 3)) == 0 backtest_conf = { 'processed': processed, @@ -750,7 +775,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) 'position_stacking': False, } results = backtesting.backtest(**backtest_conf) - assert len(evaluate_result_multi(results, '5m', 1)) == 0 + assert len(evaluate_result_multi(results['results'], '5m', 1)) == 0 def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): @@ -782,9 +807,9 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Parameter --enable-position-stacking detected ...' ] @@ -795,8 +820,20 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): @pytest.mark.filterwarnings("ignore:deprecated") def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): + default_conf['ask_strategy'].update({ + "use_sell_signal": True, + "sell_profit_only": False, + "sell_profit_offset": 0.0, + "ignore_roi_if_buy_signal": False, + }) patch_exchange(mocker) - backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS)) + backtestmock = MagicMock(return_value={ + 'results': pd.DataFrame(columns=BT_DATA_COLUMNS), + 'config': default_conf, + 'locks': [], + 'rejected_signals': 20, + 'final_balance': 1000, + }) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock) @@ -810,7 +847,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): text_table_strategy=strattable_mock, generate_pair_metrics=MagicMock(), generate_sell_reason_stats=sell_reason_mock, - generate_strategy_metrics=strat_summary, + generate_strategy_comparison=strat_summary, generate_daily_stats=MagicMock(), ) patched_configuration_load_config_file(mocker, default_conf) @@ -844,9 +881,9 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Parameter --enable-position-stacking detected ...', 'Running backtesting for Strategy DefaultStrategy', 'Running backtesting for Strategy TestStrategyLegacy', @@ -858,41 +895,60 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): @pytest.mark.filterwarnings("ignore:deprecated") def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys): - + default_conf['ask_strategy'].update({ + "use_sell_signal": True, + "sell_profit_only": False, + "sell_profit_offset": 0.0, + "ignore_roi_if_buy_signal": False, + }) patch_exchange(mocker) + result1 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'], + 'profit_ratio': [0.0, 0.0], + 'profit_abs': [0.0, 0.0], + 'open_date': pd.to_datetime(['2018-01-29 18:40:00', + '2018-01-30 03:30:00', ], utc=True + ), + 'close_date': pd.to_datetime(['2018-01-29 20:45:00', + '2018-01-30 05:35:00', ], utc=True), + 'trade_duration': [235, 40], + 'is_open': [False, False], + 'stake_amount': [0.01, 0.01], + 'open_rate': [0.104445, 0.10302485], + 'close_rate': [0.104969, 0.103541], + 'sell_reason': [SellType.ROI, SellType.ROI] + }) + result2 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'], + 'profit_ratio': [0.03, 0.01, 0.1], + 'profit_abs': [0.01, 0.02, 0.2], + 'open_date': pd.to_datetime(['2018-01-29 18:40:00', + '2018-01-30 03:30:00', + '2018-01-30 05:30:00'], utc=True + ), + 'close_date': pd.to_datetime(['2018-01-29 20:45:00', + '2018-01-30 05:35:00', + '2018-01-30 08:30:00'], utc=True), + 'trade_duration': [47, 40, 20], + 'is_open': [False, False, False], + 'stake_amount': [0.01, 0.01, 0.01], + 'open_rate': [0.104445, 0.10302485, 0.122541], + 'close_rate': [0.104969, 0.103541, 0.123541], + 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] + }) backtestmock = MagicMock(side_effect=[ - pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'], - 'profit_ratio': [0.0, 0.0], - 'profit_abs': [0.0, 0.0], - 'open_date': pd.to_datetime(['2018-01-29 18:40:00', - '2018-01-30 03:30:00', ], utc=True - ), - 'close_date': pd.to_datetime(['2018-01-29 20:45:00', - '2018-01-30 05:35:00', ], utc=True), - 'trade_duration': [235, 40], - 'is_open': [False, False], - 'stake_amount': [0.01, 0.01], - 'open_rate': [0.104445, 0.10302485], - 'close_rate': [0.104969, 0.103541], - 'sell_reason': [SellType.ROI, SellType.ROI] - }), - pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'], - 'profit_ratio': [0.03, 0.01, 0.1], - 'profit_abs': [0.01, 0.02, 0.2], - 'open_date': pd.to_datetime(['2018-01-29 18:40:00', - '2018-01-30 03:30:00', - '2018-01-30 05:30:00'], utc=True - ), - 'close_date': pd.to_datetime(['2018-01-29 20:45:00', - '2018-01-30 05:35:00', - '2018-01-30 08:30:00'], utc=True), - 'trade_duration': [47, 40, 20], - 'is_open': [False, False, False], - 'stake_amount': [0.01, 0.01, 0.01], - 'open_rate': [0.104445, 0.10302485, 0.122541], - 'close_rate': [0.104969, 0.103541, 0.123541], - 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] - }), + { + 'results': result1, + 'config': default_conf, + 'locks': [], + 'rejected_signals': 20, + 'final_balance': 1000, + }, + { + 'results': result2, + 'config': default_conf, + 'locks': [], + 'rejected_signals': 20, + 'final_balance': 1000, + } ]) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) @@ -923,9 +979,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Backtesting with data from 2017-11-14 21:17:00 ' - 'up to 2017-11-14 22:58:00 (0 days)..', + 'up to 2017-11-14 22:58:00 (0 days).', 'Parameter --enable-position-stacking detected ...', 'Running backtesting for Strategy DefaultStrategy', 'Running backtesting for Strategy TestStrategyLegacy', diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 193d997db..d7eb8bf67 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -5,7 +5,7 @@ import re from datetime import datetime from pathlib import Path from typing import Dict, List -from unittest.mock import MagicMock +from unittest.mock import ANY, MagicMock import pandas as pd import pytest @@ -16,9 +16,14 @@ from freqtrade.commands.optimize_commands import setup_optimize_configuration, s from freqtrade.data.history import load_data from freqtrade.exceptions import OperationalException from freqtrade.optimize.hyperopt import Hyperopt +from freqtrade.optimize.hyperopt_auto import HyperOptAuto from freqtrade.optimize.hyperopt_tools import HyperoptTools +from freqtrade.optimize.optimize_reports import generate_strategy_stats +from freqtrade.optimize.space import SKDecimal from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver from freqtrade.state import RunMode +from freqtrade.strategy.hyper import IntParameter +from freqtrade.strategy.interface import SellType from tests.conftest import (get_args, log_has, log_has_re, patch_exchange, patched_configuration_load_config_file) @@ -26,23 +31,7 @@ from .hyperopts.default_hyperopt import DefaultHyperOpt # Functions for recurrent object patching -def create_results(mocker, hyperopt, testdatadir) -> List[Dict]: - """ - When creating results, mock the hyperopt so that *by default* - - we don't create any pickle'd files in the filesystem - - we might have a pickle'd file so make sure that we return - false when looking for it - """ - hyperopt.results_file = testdatadir / 'optimize/ut_results.pickle' - - mocker.patch.object(Path, "is_file", MagicMock(return_value=False)) - stat_mock = MagicMock() - stat_mock.st_size = 1 - mocker.patch.object(Path, "stat", MagicMock(return_value=stat_mock)) - - mocker.patch.object(Path, "unlink", MagicMock(return_value=True)) - mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None) - mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') +def create_results() -> List[Dict]: return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}] @@ -316,54 +305,49 @@ def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None: assert caplog.record_tuples == [] -def test_save_results_saves_epochs(mocker, hyperopt, testdatadir, caplog) -> None: - epochs = create_results(mocker, hyperopt, testdatadir) - mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None) - mock_dump_json = mocker.patch('freqtrade.optimize.hyperopt.file_dump_json', return_value=None) - results_file = testdatadir / 'optimize' / 'ut_results.pickle' +def test_save_results_saves_epochs(mocker, hyperopt, tmpdir, caplog) -> None: + # Test writing to temp dir and reading again + epochs = create_results() + hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt') caplog.set_level(logging.DEBUG) - hyperopt.epochs = epochs - hyperopt._save_results() - assert log_has(f"1 epoch saved to '{results_file}'.", caplog) - mock_dump.assert_called_once() - mock_dump_json.assert_called_once() + for epoch in epochs: + hyperopt._save_result(epoch) + assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog) - hyperopt.epochs = epochs + epochs - hyperopt._save_results() - assert log_has(f"2 epochs saved to '{results_file}'.", caplog) + hyperopt._save_result(epochs[0]) + assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog) + + hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file) + assert len(hyperopt_epochs) == 2 -def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> None: - epochs = create_results(mocker, hyperopt, testdatadir) - mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs) - results_file = testdatadir / 'optimize' / 'ut_results.pickle' - hyperopt_epochs = HyperoptTools._read_results(results_file) - assert log_has(f"Reading epochs from '{results_file}'", caplog) - assert hyperopt_epochs == epochs - mock_load.assert_called_once() +def test_load_previous_results(testdatadir, caplog) -> None: - -def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None: - epochs = create_results(mocker, hyperopt, testdatadir) - mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs) - mocker.patch.object(Path, 'is_file', MagicMock(return_value=True)) - statmock = MagicMock() - statmock.st_size = 5 - # mocker.patch.object(Path, 'stat', MagicMock(return_value=statmock)) - - results_file = testdatadir / 'optimize' / 'ut_results.pickle' + results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle' hyperopt_epochs = HyperoptTools.load_previous_results(results_file) - assert hyperopt_epochs == epochs - mock_load.assert_called_once() + assert len(hyperopt_epochs) == 5 + assert log_has_re(r"Reading pickled epochs from .*", caplog) - del epochs[0]['is_best'] - mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs) + caplog.clear() - with pytest.raises(OperationalException): + # Modern version + results_file = testdatadir / 'strategy_SampleStrategy.fthypt' + + hyperopt_epochs = HyperoptTools.load_previous_results(results_file) + + assert len(hyperopt_epochs) == 5 + assert log_has_re(r"Reading epochs from .*", caplog) + + +def test_load_previous_results2(mocker, testdatadir, caplog) -> None: + mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle', + return_value=[{'asdf': '222'}]) + results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle' + with pytest.raises(OperationalException, match=r"The file .* incompatible.*"): HyperoptTools.load_previous_results(results_file) @@ -381,7 +365,8 @@ def test_roi_table_generation(hyperopt) -> None: def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', @@ -420,9 +405,9 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: out, err = capsys.readouterr() assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out - assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + # Should be called for historical candle data + assert dumper.call_count == 1 + assert dumper2.call_count == 1 assert hasattr(hyperopt.backtesting.strategy, "advise_sell") assert hasattr(hyperopt.backtesting.strategy, "advise_buy") assert hasattr(hyperopt, "max_open_trades") @@ -430,18 +415,42 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: assert hasattr(hyperopt, "position_stacking") -def test_format_results(hyperopt): - # Test with BTC as stake_currency - trades = [ - ('ETH/BTC', 2, 2, 123), - ('LTC/BTC', 1, 1, 123), - ('XPR/BTC', -1, -2, -246) - ] - labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] - df = pd.DataFrame.from_records(trades, columns=labels) - results_metrics = hyperopt._calculate_results_metrics(df) - results_explanation = hyperopt._format_results_explanation_string(results_metrics) - total_profit = results_metrics['total_profit'] +def test_hyperopt_format_results(hyperopt): + + bt_result = { + 'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC", + "UNITTEST/BTC", "UNITTEST/BTC"], + "profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780], + "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003], + "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime, + Arrow(2017, 11, 14, 21, 36, 00).datetime, + Arrow(2017, 11, 14, 22, 12, 00).datetime, + Arrow(2017, 11, 14, 22, 44, 00).datetime], + "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime, + Arrow(2017, 11, 14, 22, 10, 00).datetime, + Arrow(2017, 11, 14, 22, 43, 00).datetime, + Arrow(2017, 11, 14, 22, 58, 00).datetime], + "open_rate": [0.002543, 0.003003, 0.003089, 0.003214], + "close_rate": [0.002546, 0.003014, 0.003103, 0.003217], + "trade_duration": [123, 34, 31, 14], + "is_open": [False, False, False, True], + "stake_amount": [0.01, 0.01, 0.01, 0.01], + "sell_reason": [SellType.ROI, SellType.STOP_LOSS, + SellType.ROI, SellType.FORCE_SELL] + }), + 'config': hyperopt.config, + 'locks': [], + 'final_balance': 0.02, + 'rejected_signals': 2, + 'backtest_start_time': 1619718665, + 'backtest_end_time': 1619718665, + } + results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result, + Arrow(2017, 11, 14, 19, 32, 00), + Arrow(2017, 12, 14, 19, 32, 00), market_change=0) + + results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC') + total_profit = results_metrics['profit_total_abs'] results = { 'loss': 0.0, @@ -455,21 +464,9 @@ def test_format_results(hyperopt): } result = HyperoptTools._format_explanation_string(results, 1) - assert result.find(' 66.67%') - assert result.find('Total profit 1.00000000 BTC') - assert result.find('2.0000Σ %') - - # Test with EUR as stake_currency - trades = [ - ('ETH/EUR', 2, 2, 123), - ('LTC/EUR', 1, 1, 123), - ('XPR/EUR', -1, -2, -246) - ] - df = pd.DataFrame.from_records(trades, columns=labels) - results_metrics = hyperopt._calculate_results_metrics(df) - results['total_profit'] = results_metrics['total_profit'] - result = HyperoptTools._format_explanation_string(results, 1) - assert result.find('Total profit 1.00000000 EUR') + assert ' 0.71%' in result + assert 'Total profit 0.00003100 BTC' in result + assert '0:50:00 min' in result @pytest.mark.parametrize("spaces, expected_results", [ @@ -500,10 +497,10 @@ def test_format_results(hyperopt): (['default', 'buy'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}), ]) -def test_has_space(hyperopt, spaces, expected_results): +def test_has_space(hyperopt_conf, spaces, expected_results): for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']: - hyperopt.config.update({'spaces': spaces}) - assert hyperopt.has_space(s) == expected_results[s] + hyperopt_conf.update({'spaces': spaces}) + assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s] def test_populate_indicators(hyperopt, testdatadir) -> None: @@ -574,22 +571,39 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'hyperopt_min_trades': 1, }) - trades = [ - ('TRX/BTC', 0.023117, 0.000233, 100) - ] - labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] - backtest_result = pd.DataFrame.from_records(trades, columns=labels) + backtest_result = { + 'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC", + "UNITTEST/BTC", "UNITTEST/BTC"], + "profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780], + "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003], + "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime, + Arrow(2017, 11, 14, 21, 36, 00).datetime, + Arrow(2017, 11, 14, 22, 12, 00).datetime, + Arrow(2017, 11, 14, 22, 44, 00).datetime], + "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime, + Arrow(2017, 11, 14, 22, 10, 00).datetime, + Arrow(2017, 11, 14, 22, 43, 00).datetime, + Arrow(2017, 11, 14, 22, 58, 00).datetime], + "open_rate": [0.002543, 0.003003, 0.003089, 0.003214], + "close_rate": [0.002546, 0.003014, 0.003103, 0.003217], + "trade_duration": [123, 34, 31, 14], + "is_open": [False, False, False, True], + "stake_amount": [0.01, 0.01, 0.01, 0.01], + "sell_reason": [SellType.ROI, SellType.STOP_LOSS, + SellType.ROI, SellType.FORCE_SELL] + }), + 'config': hyperopt_conf, + 'locks': [], + 'rejected_signals': 20, + 'final_balance': 1000, + } - mocker.patch( - 'freqtrade.optimize.hyperopt.Backtesting.backtest', - MagicMock(return_value=backtest_result) - ) - mocker.patch( - 'freqtrade.optimize.hyperopt.get_timerange', - MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13))) - ) + mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result) + mocker.patch('freqtrade.optimize.hyperopt.get_timerange', + return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13))) patch_exchange(mocker) - mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock()) + mocker.patch.object(Path, 'open') + mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None}) optimizer_param = { 'adx-value': 0, @@ -623,11 +637,11 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'trailing_only_offset_is_reached': False, } response_expected = { - 'loss': 1.9840569076926293, - 'results_explanation': (' 1 trades. 1/0/0 Wins/Draws/Losses. ' - 'Avg profit 2.31%. Median profit 2.31%. Total profit ' - '0.00023300 BTC ( 2.31\N{GREEK CAPITAL LETTER SIGMA}%). ' - 'Avg duration 100.0 min.' + 'loss': 1.9147239021396234, + 'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. ' + 'Avg profit 0.77%. Median profit 0.71%. Total profit ' + '0.00003100 BTC ( 0.00\N{GREEK CAPITAL LETTER SIGMA}%). ' + 'Avg duration 0:50:00 min.' ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8'), 'params_details': {'buy': {'adx-enabled': False, 'adx-value': 0, @@ -638,10 +652,10 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'rsi-enabled': False, 'rsi-value': 0, 'trigger': 'macd_cross_signal'}, - 'roi': {0: 0.12000000000000001, - 20.0: 0.02, - 50.0: 0.01, - 110.0: 0}, + 'roi': {"0": 0.12000000000000001, + "20.0": 0.02, + "50.0": 0.01, + "110.0": 0}, 'sell': {'sell-adx-enabled': False, 'sell-adx-value': 0, 'sell-fastd-enabled': True, @@ -657,21 +671,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'trailing_stop_positive': 0.02, 'trailing_stop_positive_offset': 0.07}}, 'params_dict': optimizer_param, - 'results_metrics': {'avg_profit': 2.3117, - 'draws': 0, - 'duration': 100.0, - 'losses': 0, - 'winsdrawslosses': ' 1 0 0', - 'median_profit': 2.3117, - 'profit': 2.3117, - 'total_profit': 0.000233, - 'trade_count': 1, - 'wins': 1}, - 'total_profit': 0.00023300 + 'params_not_optimized': {'buy': {}, 'sell': {}}, + 'results_metrics': ANY, + 'total_profit': 3.1e-08 } hyperopt = Hyperopt(hyperopt_conf) - hyperopt.dimensions = hyperopt.hyperopt_space() + hyperopt.min_date = Arrow(2017, 12, 10) + hyperopt.max_date = Arrow(2017, 12, 13) + hyperopt.init_spaces() + hyperopt.dimensions = hyperopt.dimensions generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values())) assert generate_optimizer_value == response_expected @@ -688,7 +697,8 @@ def test_clean_hyperopt(mocker, hyperopt_conf, caplog): def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', @@ -739,13 +749,14 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None: ':{},"stoploss":null,"trailing_stop":null}' ) assert result_str in out # noqa: E501 - assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + # Should be called for historical candle data + assert dumper.call_count == 1 + assert dumper2.call_count == 1 def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -787,13 +798,14 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None: out, err = capsys.readouterr() assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501 - assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + # Should be called for historical candle data + assert dumper.call_count == 1 + assert dumper2.call_count == 1 def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -834,13 +846,14 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: out, err = capsys.readouterr() assert '{"minimal_roi":{},"stoploss":null}' in out - assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + + assert dumper.call_count == 1 + assert dumper2.call_count == 1 def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -882,9 +895,9 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non out, err = capsys.readouterr() assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out - assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + assert dumper.call_count == 1 + assert dumper2.call_count == 1 + assert hasattr(hyperopt.backtesting.strategy, "advise_sell") assert hasattr(hyperopt.backtesting.strategy, "advise_buy") assert hasattr(hyperopt, "max_open_trades") @@ -920,7 +933,8 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None: def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -963,8 +977,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: out, err = capsys.readouterr() assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + assert dumper.call_count == 1 + assert dumper2.call_count == 1 assert hasattr(hyperopt.backtesting.strategy, "advise_sell") assert hasattr(hyperopt.backtesting.strategy, "advise_buy") assert hasattr(hyperopt, "max_open_trades") @@ -973,7 +987,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None: def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None: - dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock()) + dumper = mocker.patch('freqtrade.optimize.hyperopt.dump') + dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result') mocker.patch('freqtrade.optimize.hyperopt.file_dump_json') mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data', MagicMock(return_value=(MagicMock(), None))) @@ -1016,8 +1031,8 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None: out, err = capsys.readouterr() assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out assert dumper.called - # Should be called twice, once for historical candle data, once to save evaluations - assert dumper.call_count == 2 + assert dumper.call_count == 1 + assert dumper2.call_count == 1 assert hasattr(hyperopt.backtesting.strategy, "advise_sell") assert hasattr(hyperopt.backtesting.strategy, "advise_buy") assert hasattr(hyperopt, "max_open_trades") @@ -1089,3 +1104,58 @@ def test_print_epoch_details(capsys): assert '# ROI table:' in captured.out assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE) assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE) + + +def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None: + patch_exchange(mocker) + mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) + (Path(tmpdir) / 'hyperopt_results').mkdir(parents=True) + # No hyperopt needed + del hyperopt_conf['hyperopt'] + hyperopt_conf.update({ + 'strategy': 'HyperoptableStrategy', + 'user_data_dir': Path(tmpdir), + }) + hyperopt = Hyperopt(hyperopt_conf) + assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto) + assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter) + + assert hyperopt.backtesting.strategy.buy_rsi.in_space is True + assert hyperopt.backtesting.strategy.buy_rsi.value == 35 + buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range + assert isinstance(buy_rsi_range, range) + # Range from 0 - 50 (inclusive) + assert len(list(buy_rsi_range)) == 51 + + hyperopt.start() + + +def test_SKDecimal(): + space = SKDecimal(1, 2, decimals=2) + assert 1.5 in space + assert 2.5 not in space + assert space.low == 100 + assert space.high == 200 + + assert space.inverse_transform([200]) == [2.0] + assert space.inverse_transform([100]) == [1.0] + assert space.inverse_transform([150, 160]) == [1.5, 1.6] + + assert space.transform([1.5]) == [150] + assert space.transform([2.0]) == [200] + assert space.transform([1.0]) == [100] + assert space.transform([1.5, 1.6]) == [150, 160] + + +def test___pprint(): + params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'} + non_params = {'buy_notoptimied': 55} + + x = HyperoptTools._pprint(params, non_params) + assert x == """{ + "buy_std": 1.2, + "buy_rsi": 31, + "buy_enable": True, + "buy_what": "asdf", + "buy_notoptimied": 55, # value loaded from strategy +}""" diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index 8119c732b..f9dac3397 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -1,5 +1,6 @@ +import datetime import re -from datetime import datetime, timedelta, timezone +from datetime import timedelta from pathlib import Path import pandas as pd @@ -7,14 +8,15 @@ import pytest from arrow import Arrow from freqtrade.configuration import TimeRange -from freqtrade.constants import LAST_BT_RESULT_FN +from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN from freqtrade.data import history from freqtrade.data.btanalysis import get_latest_backtest_filename, load_backtest_data from freqtrade.edge import PairInfo from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats, generate_edge_table, generate_pair_metrics, generate_sell_reason_stats, - generate_strategy_metrics, store_backtest_stats, + generate_strategy_comparison, + generate_trading_stats, store_backtest_stats, text_table_bt_results, text_table_sell_reason, text_table_strategy) from freqtrade.resolvers.strategy_resolver import StrategyResolver @@ -26,25 +28,22 @@ def test_text_table_bt_results(): results = pd.DataFrame( { - 'pair': ['ETH/BTC', 'ETH/BTC'], - 'profit_ratio': [0.1, 0.2], - 'profit_abs': [0.2, 0.4], - 'trade_duration': [10, 30], - 'wins': [2, 0], - 'draws': [0, 0], - 'losses': [0, 0] + 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], + 'profit_ratio': [0.1, 0.2, -0.05], + 'profit_abs': [0.2, 0.4, -0.1], + 'trade_duration': [10, 30, 20], } ) result_str = ( - '| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |' - ' Tot Profit % | Avg Duration | Wins | Draws | Losses |\n' - '|---------+--------+----------------+----------------+------------------+' - '----------------+----------------+--------+---------+----------|\n' - '| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 |' - ' 15.00 | 0:20:00 | 2 | 0 | 0 |\n' - '| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 |' - ' 15.00 | 0:20:00 | 2 | 0 | 0 |' + '| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |' + ' Avg Duration | Win Draw Loss Win% |\n' + '|---------+--------+----------------+----------------+------------------+----------------+' + '----------------+-------------------------|\n' + '| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |' + ' 0:20:00 | 2 0 1 66.7 |\n' + '| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |' + ' 0:20:00 | 2 0 1 66.7 |' ) pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC', @@ -80,6 +79,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): 'config': default_conf, 'locks': [], 'final_balance': 1000.02, + 'rejected_signals': 20, 'backtest_start_time': Arrow.utcnow().int_timestamp, 'backtest_end_time': Arrow.utcnow().int_timestamp, } @@ -96,8 +96,8 @@ def test_generate_backtest_stats(default_conf, testdatadir): assert 'DefStrat' in stats['strategy'] assert 'strategy_comparison' in stats strat_stats = stats['strategy']['DefStrat'] - assert strat_stats['backtest_start'] == min_date.datetime - assert strat_stats['backtest_end'] == max_date.datetime + assert strat_stats['backtest_start'] == min_date.strftime(DATETIME_PRINT_FORMAT) + assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT) assert strat_stats['total_trades'] == len(results['DefStrat']['results']) # Above sample had no loosing trade assert strat_stats['max_drawdown'] == 0.0 @@ -127,6 +127,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): 'config': default_conf, 'locks': [], 'final_balance': 1000.02, + 'rejected_signals': 20, 'backtest_start_time': Arrow.utcnow().int_timestamp, 'backtest_end_time': Arrow.utcnow().int_timestamp, } @@ -140,8 +141,8 @@ def test_generate_backtest_stats(default_conf, testdatadir): strat_stats = stats['strategy']['DefStrat'] assert strat_stats['max_drawdown'] == 0.013803 - assert strat_stats['drawdown_start'] == datetime(2017, 11, 14, 22, 10, tzinfo=timezone.utc) - assert strat_stats['drawdown_end'] == datetime(2017, 11, 14, 22, 43, tzinfo=timezone.utc) + assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00' + assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00' assert strat_stats['drawdown_end_ts'] == 1510699380000 assert strat_stats['drawdown_start_ts'] == 1510697400000 assert strat_stats['pairlist'] == ['UNITTEST/BTC'] @@ -226,8 +227,6 @@ def test_generate_daily_stats(testdatadir): assert res['winning_days'] == 14 assert res['draw_days'] == 4 assert res['losing_days'] == 3 - assert res['winner_holding_avg'] == timedelta(seconds=1440) - assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420) # Select empty dataframe! res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :]) @@ -238,6 +237,23 @@ def test_generate_daily_stats(testdatadir): assert res['losing_days'] == 0 +def test_generate_trading_stats(testdatadir): + filename = testdatadir / "backtest-result_new.json" + bt_data = load_backtest_data(filename) + res = generate_trading_stats(bt_data) + assert isinstance(res, dict) + assert res['winner_holding_avg'] == timedelta(seconds=1440) + assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420) + assert 'wins' in res + assert 'losses' in res + assert 'draws' in res + + # Select empty dataframe! + res = generate_trading_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :]) + assert res['wins'] == 0 + assert res['losses'] == 0 + + def test_text_table_sell_reason(): results = pd.DataFrame( @@ -254,14 +270,14 @@ def test_text_table_sell_reason(): ) result_str = ( - '| Sell Reason | Sells | Wins | Draws | Losses |' - ' Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |\n' - '|---------------+---------+--------+---------+----------+' - '----------------+----------------+------------------+----------------|\n' - '| roi | 2 | 2 | 0 | 0 |' - ' 15 | 30 | 0.6 | 15 |\n' - '| stop_loss | 1 | 0 | 0 | 1 |' - ' -10 | -10 | -0.2 | -5 |' + '| Sell Reason | Sells | Win Draws Loss Win% | Avg Profit % | Cum Profit % |' + ' Tot Profit BTC | Tot Profit % |\n' + '|---------------+---------+--------------------------+----------------+----------------+' + '------------------+----------------|\n' + '| roi | 2 | 2 0 0 100 | 15 | 30 |' + ' 0.6 | 15 |\n' + '| stop_loss | 1 | 0 0 1 0 | -10 | -10 |' + ' -0.2 | -5 |' ) sell_reason_stats = generate_sell_reason_stats(max_open_trades=2, @@ -309,9 +325,12 @@ def test_text_table_strategy(default_conf): default_conf['max_open_trades'] = 2 default_conf['dry_run_wallet'] = 3 results = {} + date = datetime.datetime(year=2020, month=1, day=1, hour=12, minute=30) + delta = datetime.timedelta(days=1) results['TestStrategy1'] = {'results': pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], + 'close_date': [date, date + delta, date + delta * 2], 'profit_ratio': [0.1, 0.2, 0.3], 'profit_abs': [0.2, 0.4, 0.5], 'trade_duration': [10, 30, 10], @@ -324,6 +343,7 @@ def test_text_table_strategy(default_conf): results['TestStrategy2'] = {'results': pd.DataFrame( { 'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'], + 'close_date': [date, date + delta, date + delta * 2], 'profit_ratio': [0.4, 0.2, 0.3], 'profit_abs': [0.4, 0.4, 0.5], 'trade_duration': [15, 30, 15], @@ -335,18 +355,17 @@ def test_text_table_strategy(default_conf): ), 'config': default_conf} result_str = ( - '| Strategy | Buys | Avg Profit % | Cum Profit % | Tot' - ' Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |\n' + '| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |' + ' Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |\n' '|---------------+--------+----------------+----------------+------------------+' - '----------------+----------------+--------+---------+----------|\n' + '----------------+----------------+-------------------------+-----------------------|\n' '| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |' - ' 36.67 | 0:17:00 | 3 | 0 | 0 |\n' + ' 36.67 | 0:17:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |\n' '| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |' - ' 43.33 | 0:20:00 | 3 | 0 | 0 |' + ' 43.33 | 0:20:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |' ) - strategy_results = generate_strategy_metrics(all_results=results) - + strategy_results = generate_strategy_comparison(all_results=results) assert text_table_strategy(strategy_results, 'BTC') == result_str diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index 67cd96f5b..5e2274ce3 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -1,15 +1,17 @@ # pragma pylint: disable=missing-docstring,C0103,protected-access +import time from unittest.mock import MagicMock, PropertyMock import pytest from freqtrade.constants import AVAILABLE_PAIRLISTS from freqtrade.exceptions import OperationalException +from freqtrade.persistence import Trade from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.plugins.pairlistmanager import PairListManager from freqtrade.resolvers import PairListResolver -from tests.conftest import get_patched_freqtradebot, log_has, log_has_re +from tests.conftest import get_patched_exchange, get_patched_freqtradebot, log_has, log_has_re @pytest.fixture(scope="function") @@ -260,6 +262,8 @@ def test_refresh_pairlist_dynamic_2(mocker, shitcoinmarkets, tickers, whitelist_ freqtrade.pairlists.refresh_pairlist() assert whitelist == freqtrade.pairlists.whitelist + # Delay to allow 0 TTL cache to expire... + time.sleep(1) whitelist = ['FUEL/BTC', 'ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC'] tickers_dict['FUEL/BTC']['quoteVolume'] = 10000.0 freqtrade.pairlists.refresh_pairlist() @@ -403,10 +407,17 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf): ([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"}, {"method": "PriceFilter", "low_price_ratio": 0.02}], "USDT", ['ETH/USDT', 'NANO/USDT']), + ([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"}, + {"method": "PriceFilter", "max_value": 0.000001}], + "USDT", ['NANO/USDT']), ([{"method": "StaticPairList"}, {"method": "RangeStabilityFilter", "lookback_days": 10, "min_rate_of_change": 0.01, "refresh_period": 1440}], "BTC", ['ETH/BTC', 'TKN/BTC', 'HOT/BTC']), + ([{"method": "StaticPairList"}, + {"method": "VolatilityFilter", "lookback_days": 3, + "min_volatility": 0.002, "max_volatility": 0.004, "refresh_period": 1440}], + "BTC", ['ETH/BTC', 'TKN/BTC']) ]) def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, tickers, ohlcv_history, pairlists, base_currency, @@ -414,12 +425,15 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t whitelist_conf['pairlists'] = pairlists whitelist_conf['stake_currency'] = base_currency + ohlcv_history_high_vola = ohlcv_history.copy() + ohlcv_history_high_vola.loc[ohlcv_history_high_vola.index == 1, 'close'] = 0.00090 + ohlcv_data = { ('ETH/BTC', '1d'): ohlcv_history, ('TKN/BTC', '1d'): ohlcv_history, ('LTC/BTC', '1d'): ohlcv_history, ('XRP/BTC', '1d'): ohlcv_history, - ('HOT/BTC', '1d'): ohlcv_history, + ('HOT/BTC', '1d'): ohlcv_history_high_vola, } mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) @@ -478,6 +492,8 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t r'because last price < .*%$', caplog) or log_has_re(r'^Removed .* from whitelist, ' r'because last price > .*%$', caplog) or + log_has_re(r'^Removed .* from whitelist, ' + r'because min value change of .*', caplog) or log_has_re(r"^Removed .* from whitelist, because ticker\['last'\] " r"is empty.*", caplog)) if pairlist['method'] == 'VolumePairList': @@ -487,6 +503,8 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t assert log_has(logmsg, caplog) else: assert not log_has(logmsg, caplog) + if pairlist["method"] == 'VolatilityFilter': + assert log_has_re(r'^Removed .* from whitelist, because volatility.*$', caplog) def test_PrecisionFilter_error(mocker, whitelist_conf) -> None: @@ -500,6 +518,18 @@ def test_PrecisionFilter_error(mocker, whitelist_conf) -> None: PairListManager(MagicMock, whitelist_conf) +def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None: + whitelist_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PerformanceFilter"}] + if hasattr(Trade, 'query'): + del Trade.query + mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) + exchange = get_patched_exchange(mocker, whitelist_conf) + pm = PairListManager(exchange, whitelist_conf) + pm.refresh_pairlist() + + assert log_has("PerformanceFilter is not available in this mode.", caplog) + + def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None: default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10}] @@ -595,17 +625,14 @@ def test_volumepairlist_caching(mocker, markets, whitelist_conf, tickers): get_tickers=tickers ) freqtrade = get_patched_freqtradebot(mocker, whitelist_conf) - assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh == 0 + assert len(freqtrade.pairlists._pairlist_handlers[0]._pair_cache) == 0 assert tickers.call_count == 0 freqtrade.pairlists.refresh_pairlist() assert tickers.call_count == 1 - assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh != 0 - lrf = freqtrade.pairlists._pairlist_handlers[0]._last_refresh + assert len(freqtrade.pairlists._pairlist_handlers[0]._pair_cache) == 1 freqtrade.pairlists.refresh_pairlist() assert tickers.call_count == 1 - # Time should not be updated. - assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh == lrf def test_agefilter_min_days_listed_too_small(mocker, default_conf, markets, tickers): @@ -778,6 +805,10 @@ def test_spreadfilter_invalid_data(mocker, default_conf, markets, tickers, caplo "[{'PriceFilter': 'PriceFilter - Filtering pairs priced below 0.00002000.'}]", None ), + ({"method": "PriceFilter", "max_value": 0.00002000}, + "[{'PriceFilter': 'PriceFilter - Filtering pairs priced Value above 0.00002000.'}]", + None + ), ({"method": "PriceFilter"}, "[{'PriceFilter': 'PriceFilter - No price filters configured.'}]", None @@ -794,6 +825,10 @@ def test_spreadfilter_invalid_data(mocker, default_conf, markets, tickers, caplo None, "PriceFilter requires max_price to be >= 0" ), # OperationalException expected + ({"method": "PriceFilter", "max_value": -1.00010000}, + None, + "PriceFilter requires max_value to be >= 0" + ), # OperationalException expected ({"method": "RangeStabilityFilter", "lookback_days": 10, "min_rate_of_change": 0.01}, "[{'RangeStabilityFilter': 'RangeStabilityFilter - Filtering pairs with rate of change below " "0.01 over the last days.'}]", diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py index 2e42c1be4..a39301145 100644 --- a/tests/plugins/test_protections.py +++ b/tests/plugins/test_protections.py @@ -27,7 +27,7 @@ def generate_mock_trade(pair: str, fee: float, is_open: bool, open_rate=open_rate, is_open=is_open, amount=0.01 / open_rate, - exchange='bittrex', + exchange='binance', ) trade.recalc_open_trade_value() if not is_open: @@ -91,7 +91,7 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=200, min_ago_close=30, )) @@ -100,12 +100,12 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) caplog.clear() # This trade does not count, as it's closed too long ago - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'BCH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=250, min_ago_close=100, )) - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=240, min_ago_close=30, )) @@ -114,7 +114,7 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'LTC/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=180, min_ago_close=30, )) @@ -148,7 +148,7 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair assert not log_has_re(message, caplog) caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=200, min_ago_close=30, profit_rate=0.9, )) @@ -158,12 +158,12 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair assert not log_has_re(message, caplog) caplog.clear() # This trade does not count, as it's closed too long ago - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=250, min_ago_close=100, profit_rate=0.9, )) # Trade does not count for per pair stop as it's the wrong pair. - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=240, min_ago_close=30, profit_rate=0.9, )) @@ -178,7 +178,7 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair caplog.clear() # 2nd Trade that counts with correct pair - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=180, min_ago_close=30, profit_rate=0.9, )) @@ -203,7 +203,7 @@ def test_CooldownPeriod(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=200, min_ago_close=30, )) @@ -213,7 +213,7 @@ def test_CooldownPeriod(mocker, default_conf, fee, caplog): assert PairLocks.is_pair_locked('XRP/BTC') assert not PairLocks.is_global_lock() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'ETH/BTC', fee.return_value, False, sell_reason=SellType.ROI.value, min_ago_open=205, min_ago_close=35, )) @@ -242,7 +242,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=800, min_ago_close=450, profit_rate=0.9, )) @@ -253,7 +253,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog): assert not PairLocks.is_pair_locked('XRP/BTC') assert not PairLocks.is_global_lock() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=200, min_ago_close=120, profit_rate=0.9, )) @@ -265,14 +265,14 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog): assert not PairLocks.is_global_lock() # Add positive trade - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value, min_ago_open=20, min_ago_close=10, profit_rate=1.15, )) assert not freqtrade.protections.stop_per_pair('XRP/BTC') assert not PairLocks.is_pair_locked('XRP/BTC') - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=110, min_ago_close=20, profit_rate=0.8, )) @@ -300,15 +300,15 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog): assert not freqtrade.protections.stop_per_pair('XRP/BTC') caplog.clear() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=1000, min_ago_close=900, profit_rate=1.1, )) - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=1000, min_ago_close=900, profit_rate=1.1, )) - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'NEO/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=1000, min_ago_close=900, profit_rate=1.1, )) @@ -316,7 +316,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog): assert not freqtrade.protections.global_stop() assert not freqtrade.protections.stop_per_pair('XRP/BTC') - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=500, min_ago_close=400, profit_rate=0.9, )) @@ -326,7 +326,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog): assert not PairLocks.is_pair_locked('XRP/BTC') assert not PairLocks.is_global_lock() - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value, min_ago_open=1200, min_ago_close=1100, profit_rate=0.5, )) @@ -339,7 +339,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog): assert not log_has_re(message, caplog) # Winning trade ... (should not lock, does not change drawdown!) - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value, min_ago_open=320, min_ago_close=410, profit_rate=1.5, )) @@ -349,7 +349,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog): caplog.clear() # Add additional negative trade, causing a loss of > 15% - Trade.session.add(generate_mock_trade( + Trade.query.session.add(generate_mock_trade( 'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value, min_ago_open=20, min_ago_close=10, profit_rate=0.8, )) diff --git a/tests/rpc/test_fiat_convert.py b/tests/rpc/test_fiat_convert.py index ed21bc516..5174f9416 100644 --- a/tests/rpc/test_fiat_convert.py +++ b/tests/rpc/test_fiat_convert.py @@ -1,44 +1,16 @@ # pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors, # pragma pylint: disable=protected-access, C0103 -import time +import datetime from unittest.mock import MagicMock import pytest from requests.exceptions import RequestException -from freqtrade.rpc.fiat_convert import CryptoFiat, CryptoToFiatConverter +from freqtrade.rpc.fiat_convert import CryptoToFiatConverter from tests.conftest import log_has, log_has_re -def test_pair_convertion_object(): - pair_convertion = CryptoFiat( - crypto_symbol='btc', - fiat_symbol='usd', - price=12345.0 - ) - - # Check the cache duration is 6 hours - assert pair_convertion.CACHE_DURATION == 6 * 60 * 60 - - # Check a regular usage - assert pair_convertion.crypto_symbol == 'btc' - assert pair_convertion.fiat_symbol == 'usd' - assert pair_convertion.price == 12345.0 - assert pair_convertion.is_expired() is False - - # Update the expiration time (- 2 hours) and check the behavior - pair_convertion._expiration = time.time() - 2 * 60 * 60 - assert pair_convertion.is_expired() is True - - # Check set price behaviour - time_reference = time.time() + pair_convertion.CACHE_DURATION - pair_convertion.set_price(price=30000.123) - assert pair_convertion.is_expired() is False - assert pair_convertion._expiration >= time_reference - assert pair_convertion.price == 30000.123 - - def test_fiat_convert_is_supported(mocker): fiat_convert = CryptoToFiatConverter() assert fiat_convert._is_supported_fiat(fiat='USD') is True @@ -47,31 +19,15 @@ def test_fiat_convert_is_supported(mocker): assert fiat_convert._is_supported_fiat(fiat='ABC') is False -def test_fiat_convert_add_pair(mocker): - - fiat_convert = CryptoToFiatConverter() - - pair_len = len(fiat_convert._pairs) - assert pair_len == 0 - - fiat_convert._add_pair(crypto_symbol='btc', fiat_symbol='usd', price=12345.0) - pair_len = len(fiat_convert._pairs) - assert pair_len == 1 - assert fiat_convert._pairs[0].crypto_symbol == 'btc' - assert fiat_convert._pairs[0].fiat_symbol == 'usd' - assert fiat_convert._pairs[0].price == 12345.0 - - fiat_convert._add_pair(crypto_symbol='btc', fiat_symbol='Eur', price=13000.2) - pair_len = len(fiat_convert._pairs) - assert pair_len == 2 - assert fiat_convert._pairs[1].crypto_symbol == 'btc' - assert fiat_convert._pairs[1].fiat_symbol == 'eur' - assert fiat_convert._pairs[1].price == 13000.2 - - def test_fiat_convert_find_price(mocker): fiat_convert = CryptoToFiatConverter() + fiat_convert._cryptomap = {} + fiat_convert._backoff = 0 + mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._load_cryptomap', + return_value=None) + assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='EUR') == 0.0 + with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'): fiat_convert._find_price(crypto_symbol='BTC', fiat_symbol='ABC') @@ -95,8 +51,8 @@ def test_fiat_convert_unsupported_crypto(mocker, caplog): def test_fiat_convert_get_price(mocker): - mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price', - return_value=28000.0) + find_price = mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price', + return_value=28000.0) fiat_convert = CryptoToFiatConverter() @@ -104,26 +60,17 @@ def test_fiat_convert_get_price(mocker): fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='US Dollar') # Check the value return by the method - pair_len = len(fiat_convert._pairs) + pair_len = len(fiat_convert._pair_price) assert pair_len == 0 assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 28000.0 - assert fiat_convert._pairs[0].crypto_symbol == 'btc' - assert fiat_convert._pairs[0].fiat_symbol == 'usd' - assert fiat_convert._pairs[0].price == 28000.0 - assert fiat_convert._pairs[0]._expiration != 0 - assert len(fiat_convert._pairs) == 1 + assert fiat_convert._pair_price['btc/usd'] == 28000.0 + assert len(fiat_convert._pair_price) == 1 + assert find_price.call_count == 1 # Verify the cached is used - fiat_convert._pairs[0].price = 9867.543 - expiration = fiat_convert._pairs[0]._expiration + fiat_convert._pair_price['btc/usd'] = 9867.543 assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 9867.543 - assert fiat_convert._pairs[0]._expiration == expiration - - # Verify the cache expiration - expiration = time.time() - 2 * 60 * 60 - fiat_convert._pairs[0]._expiration = expiration - assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 28000.0 - assert fiat_convert._pairs[0]._expiration is not expiration + assert find_price.call_count == 1 def test_fiat_convert_same_currencies(mocker): @@ -175,6 +122,28 @@ def test_fiat_convert_without_network(mocker): CryptoToFiatConverter._coingekko = cmc_temp +def test_fiat_too_many_requests_response(mocker, caplog): + # Because CryptoToFiatConverter is a Singleton we reset the listings + req_exception = "429 Too Many Requests" + listmock = MagicMock(return_value="{}", side_effect=RequestException(req_exception)) + mocker.patch.multiple( + 'freqtrade.rpc.fiat_convert.CoinGeckoAPI', + get_coins_list=listmock, + ) + # with pytest.raises(RequestEsxception): + fiat_convert = CryptoToFiatConverter() + fiat_convert._cryptomap = {} + fiat_convert._load_cryptomap() + + length_cryptomap = len(fiat_convert._cryptomap) + assert length_cryptomap == 0 + assert fiat_convert._backoff > datetime.datetime.now().timestamp() + assert log_has( + 'Too many requests for Coingecko API, backing off and trying again later.', + caplog + ) + + def test_fiat_invalid_response(mocker, caplog): # Because CryptoToFiatConverter is a Singleton we reset the listings listmock = MagicMock(return_value="{'novalidjson':DEADBEEFf}") diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py index b11470711..b005fb105 100644 --- a/tests/rpc/test_rpc.py +++ b/tests/rpc/test_rpc.py @@ -53,7 +53,6 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'pair': 'ETH/BTC', 'base_currency': 'BTC', 'open_date': ANY, - 'open_date_hum': ANY, 'open_timestamp': ANY, 'is_open': ANY, 'fee_open': ANY, @@ -73,7 +72,6 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'timeframe': 5, 'open_order_id': ANY, 'close_date': None, - 'close_date_hum': None, 'close_timestamp': None, 'open_rate': 1.098e-05, 'close_rate': None, @@ -92,6 +90,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'profit_ratio': -0.00408133, 'profit_pct': -0.41, 'profit_abs': -4.09e-06, + 'profit_fiat': ANY, 'stop_loss_abs': 9.882e-06, 'stop_loss_pct': -10.0, 'stop_loss_ratio': -0.1, @@ -107,7 +106,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'stoploss_entry_dist': -0.00010475, 'stoploss_entry_dist_ratio': -0.10448878, 'open_order': None, - 'exchange': 'bittrex', + 'exchange': 'binance', } mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate', @@ -120,7 +119,6 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'pair': 'ETH/BTC', 'base_currency': 'BTC', 'open_date': ANY, - 'open_date_hum': ANY, 'open_timestamp': ANY, 'is_open': ANY, 'fee_open': ANY, @@ -140,7 +138,6 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'timeframe': ANY, 'open_order_id': ANY, 'close_date': None, - 'close_date_hum': None, 'close_timestamp': None, 'open_rate': 1.098e-05, 'close_rate': None, @@ -159,6 +156,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'profit_ratio': ANY, 'profit_pct': ANY, 'profit_abs': ANY, + 'profit_fiat': ANY, 'stop_loss_abs': 9.882e-06, 'stop_loss_pct': -10.0, 'stop_loss_ratio': -0.1, @@ -174,7 +172,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'stoploss_entry_dist': -0.00010475, 'stoploss_entry_dist_ratio': -0.10448878, 'open_order': None, - 'exchange': 'bittrex', + 'exchange': 'binance', } @@ -201,28 +199,31 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None: freqtradebot.enter_positions() - result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') + result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') assert "Since" in headers assert "Pair" in headers assert 'instantly' == result[0][2] assert 'ETH/BTC' in result[0][1] assert '-0.41%' == result[0][3] + assert isnan(fiat_profit_sum) # Test with fiatconvert rpc._fiat_converter = CryptoToFiatConverter() - result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') + result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') assert "Since" in headers assert "Pair" in headers assert 'instantly' == result[0][2] assert 'ETH/BTC' in result[0][1] assert '-0.41% (-0.06)' == result[0][3] + assert '-0.06' == f'{fiat_profit_sum:.2f}' mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate', MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available"))) - result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') + result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD') assert 'instantly' == result[0][2] assert 'ETH/BTC' in result[0][1] assert 'nan%' == result[0][3] + assert isnan(fiat_profit_sum) def test_rpc_daily_profit(default_conf, update, ticker, fee, @@ -571,6 +572,8 @@ def test_rpc_balance_handle(default_conf, mocker, tickers): result = rpc._rpc_balance(default_conf['stake_currency'], default_conf['fiat_display_currency']) assert prec_satoshi(result['total'], 12.309096315) assert prec_satoshi(result['value'], 184636.44472997) + assert tickers.call_count == 1 + assert tickers.call_args_list[0][1]['cached'] is True assert 'USD' == result['symbol'] assert result['currencies'] == [ {'currency': 'BTC', diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 5a0a04943..1a66b2e81 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -416,10 +416,10 @@ def test_api_count(botclient, mocker, ticker, fee, markets): assert rc.json()["max"] == 1 # Create some test data - ftbot.enter_positions() + create_mock_trades(fee) rc = client_get(client, f"{BASE_URI}/count") assert_response(rc) - assert rc.json()["current"] == 1 + assert rc.json()["current"] == 4 assert rc.json()["max"] == 1 ftbot.config['max_open_trades'] = float('inf') @@ -468,7 +468,7 @@ def test_api_show_config(botclient, mocker): rc = client_get(client, f"{BASE_URI}/show_config") assert_response(rc) assert 'dry_run' in rc.json() - assert rc.json()['exchange'] == 'bittrex' + assert rc.json()['exchange'] == 'binance' assert rc.json()['timeframe'] == '5m' assert rc.json()['timeframe_ms'] == 300000 assert rc.json()['timeframe_min'] == 5 @@ -506,20 +506,43 @@ def test_api_trades(botclient, mocker, fee, markets): ) rc = client_get(client, f"{BASE_URI}/trades") assert_response(rc) - assert len(rc.json()) == 2 + assert len(rc.json()) == 3 assert rc.json()['trades_count'] == 0 + assert rc.json()['total_trades'] == 0 create_mock_trades(fee) - Trade.session.flush() + Trade.query.session.flush() rc = client_get(client, f"{BASE_URI}/trades") assert_response(rc) assert len(rc.json()['trades']) == 2 assert rc.json()['trades_count'] == 2 + assert rc.json()['total_trades'] == 2 rc = client_get(client, f"{BASE_URI}/trades?limit=1") assert_response(rc) assert len(rc.json()['trades']) == 1 assert rc.json()['trades_count'] == 1 + assert rc.json()['total_trades'] == 2 + + +def test_api_trade_single(botclient, mocker, fee, ticker, markets): + ftbot, client = botclient + patch_get_signal(ftbot, (True, False)) + mocker.patch.multiple( + 'freqtrade.exchange.Exchange', + markets=PropertyMock(return_value=markets), + fetch_ticker=ticker, + ) + rc = client_get(client, f"{BASE_URI}/trade/3") + assert_response(rc, 404) + assert rc.json()['detail'] == 'Trade not found.' + + create_mock_trades(fee) + Trade.query.session.flush() + + rc = client_get(client, f"{BASE_URI}/trade/3") + assert_response(rc) + assert rc.json()['trade_id'] == 3 def test_api_delete_trade(botclient, mocker, fee, markets): @@ -538,7 +561,7 @@ def test_api_delete_trade(botclient, mocker, fee, markets): assert_response(rc, 502) create_mock_trades(fee) - Trade.session.flush() + Trade.query.session.flush() ftbot.strategy.order_types['stoploss_on_exchange'] = True trades = Trade.query.all() trades[1].stoploss_order_id = '1234' @@ -612,7 +635,7 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets): @pytest.mark.usefixtures("init_persistence") -def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, limit_sell_order): +def test_api_profit(botclient, mocker, ticker, fee, markets): ftbot, client = botclient patch_get_signal(ftbot, (True, False)) mocker.patch.multiple( @@ -627,48 +650,33 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, li assert_response(rc, 200) assert rc.json()['trade_count'] == 0 - ftbot.enter_positions() - trade = Trade.query.first() - + create_mock_trades(fee) # Simulate fulfilled LIMIT_BUY order for trade - trade.update(limit_buy_order) - rc = client_get(client, f"{BASE_URI}/profit") - assert_response(rc, 200) - # One open trade - assert rc.json()['trade_count'] == 1 - assert rc.json()['best_pair'] == '' - assert rc.json()['best_rate'] == 0 - - trade = Trade.query.first() - trade.update(limit_sell_order) - - trade.close_date = datetime.utcnow() - trade.is_open = False rc = client_get(client, f"{BASE_URI}/profit") assert_response(rc) assert rc.json() == {'avg_duration': ANY, - 'best_pair': 'ETH/BTC', - 'best_rate': 6.2, - 'first_trade_date': 'just now', + 'best_pair': 'XRP/BTC', + 'best_rate': 1.0, + 'first_trade_date': ANY, 'first_trade_timestamp': ANY, - 'latest_trade_date': 'just now', + 'latest_trade_date': '5 minutes ago', 'latest_trade_timestamp': ANY, - 'profit_all_coin': 6.217e-05, - 'profit_all_fiat': 0.76748865, - 'profit_all_percent_mean': 6.2, - 'profit_all_ratio_mean': 0.06201058, - 'profit_all_percent_sum': 6.2, - 'profit_all_ratio_sum': 0.06201058, - 'profit_closed_coin': 6.217e-05, - 'profit_closed_fiat': 0.76748865, - 'profit_closed_ratio_mean': 0.06201058, - 'profit_closed_percent_mean': 6.2, - 'profit_closed_ratio_sum': 0.06201058, - 'profit_closed_percent_sum': 6.2, - 'trade_count': 1, - 'closed_trade_count': 1, - 'winning_trades': 1, + 'profit_all_coin': -44.0631579, + 'profit_all_fiat': -543959.6842755, + 'profit_all_percent_mean': -66.41, + 'profit_all_ratio_mean': -0.6641100666666667, + 'profit_all_percent_sum': -398.47, + 'profit_all_ratio_sum': -3.9846604, + 'profit_closed_coin': 0.00073913, + 'profit_closed_fiat': 9.124559849999999, + 'profit_closed_ratio_mean': 0.0075, + 'profit_closed_percent_mean': 0.75, + 'profit_closed_ratio_sum': 0.015, + 'profit_closed_percent_sum': 1.5, + 'trade_count': 6, + 'closed_trade_count': 2, + 'winning_trades': 2, 'losing_trades': 0, } @@ -702,7 +710,7 @@ def test_api_stats(botclient, mocker, ticker, fee, markets,): assert 'draws' in rc.json()['durations'] -def test_api_performance(botclient, mocker, ticker, fee): +def test_api_performance(botclient, fee): ftbot, client = botclient patch_get_signal(ftbot, (True, False)) @@ -720,7 +728,8 @@ def test_api_performance(botclient, mocker, ticker, fee): ) trade.close_profit = trade.calc_profit_ratio() - Trade.session.add(trade) + trade.close_profit_abs = trade.calc_profit() + Trade.query.session.add(trade) trade = Trade( pair='XRP/ETH', @@ -735,14 +744,16 @@ def test_api_performance(botclient, mocker, ticker, fee): close_rate=0.391 ) trade.close_profit = trade.calc_profit_ratio() - Trade.session.add(trade) - Trade.session.flush() + trade.close_profit_abs = trade.calc_profit() + + Trade.query.session.add(trade) + Trade.query.session.flush() rc = client_get(client, f"{BASE_URI}/performance") assert_response(rc) assert len(rc.json()) == 2 - assert rc.json() == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61}, - {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57}] + assert rc.json() == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61, 'profit_abs': 0.01872279}, + {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57, 'profit_abs': -0.1150375}] def test_api_status(botclient, mocker, ticker, fee, markets): @@ -753,63 +764,57 @@ def test_api_status(botclient, mocker, ticker, fee, markets): get_balances=MagicMock(return_value=ticker), fetch_ticker=ticker, get_fee=fee, - markets=PropertyMock(return_value=markets) + markets=PropertyMock(return_value=markets), + fetch_order=MagicMock(return_value={}), ) rc = client_get(client, f"{BASE_URI}/status") assert_response(rc, 200) assert rc.json() == [] - - ftbot.enter_positions() - trades = Trade.get_open_trades() - trades[0].open_order_id = None - ftbot.exit_positions(trades) - Trade.session.flush() + create_mock_trades(fee) rc = client_get(client, f"{BASE_URI}/status") assert_response(rc) - assert len(rc.json()) == 1 - assert rc.json() == [{ - 'amount': 91.07468123, - 'amount_requested': 91.07468123, - 'base_currency': 'BTC', + assert len(rc.json()) == 4 + assert rc.json()[0] == { + 'amount': 123.0, + 'amount_requested': 123.0, 'close_date': None, - 'close_date_hum': None, 'close_timestamp': None, 'close_profit': None, 'close_profit_pct': None, 'close_profit_abs': None, 'close_rate': None, - 'current_profit': -0.00408133, - 'current_profit_pct': -0.41, - 'current_profit_abs': -4.09e-06, - 'profit_ratio': -0.00408133, - 'profit_pct': -0.41, - 'profit_abs': -4.09e-06, + 'current_profit': ANY, + 'current_profit_pct': ANY, + 'current_profit_abs': ANY, + 'profit_ratio': ANY, + 'profit_pct': ANY, + 'profit_abs': ANY, + 'profit_fiat': ANY, 'current_rate': 1.099e-05, 'open_date': ANY, - 'open_date_hum': 'just now', 'open_timestamp': ANY, 'open_order': None, - 'open_rate': 1.098e-05, + 'open_rate': 0.123, 'pair': 'ETH/BTC', 'stake_amount': 0.001, - 'stop_loss_abs': 9.882e-06, - 'stop_loss_pct': -10.0, - 'stop_loss_ratio': -0.1, + 'stop_loss_abs': ANY, + 'stop_loss_pct': ANY, + 'stop_loss_ratio': ANY, 'stoploss_order_id': None, 'stoploss_last_update': ANY, 'stoploss_last_update_timestamp': ANY, - 'initial_stop_loss_abs': 9.882e-06, - 'initial_stop_loss_pct': -10.0, - 'initial_stop_loss_ratio': -0.1, - 'stoploss_current_dist': -1.1080000000000002e-06, - 'stoploss_current_dist_ratio': -0.10081893, - 'stoploss_current_dist_pct': -10.08, - 'stoploss_entry_dist': -0.00010475, - 'stoploss_entry_dist_ratio': -0.10448878, + 'initial_stop_loss_abs': 0.0, + 'initial_stop_loss_pct': ANY, + 'initial_stop_loss_ratio': ANY, + 'stoploss_current_dist': ANY, + 'stoploss_current_dist_ratio': ANY, + 'stoploss_current_dist_pct': ANY, + 'stoploss_entry_dist': ANY, + 'stoploss_entry_dist_ratio': ANY, 'trade_id': 1, - 'close_rate_requested': None, + 'close_rate_requested': ANY, 'fee_close': 0.0025, 'fee_close_cost': None, 'fee_close_currency': None, @@ -817,17 +822,17 @@ def test_api_status(botclient, mocker, ticker, fee, markets): 'fee_open_cost': None, 'fee_open_currency': None, 'is_open': True, - 'max_rate': 1.099e-05, - 'min_rate': 1.098e-05, - 'open_order_id': None, - 'open_rate_requested': 1.098e-05, - 'open_trade_value': 0.0010025, + 'max_rate': ANY, + 'min_rate': ANY, + 'open_order_id': 'dry_run_buy_12345', + 'open_rate_requested': ANY, + 'open_trade_value': 15.1668225, 'sell_reason': None, 'sell_order_status': None, 'strategy': 'DefaultStrategy', 'timeframe': 5, - 'exchange': 'bittrex', - }] + 'exchange': 'binance', + } mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate', MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available"))) @@ -835,7 +840,7 @@ def test_api_status(botclient, mocker, ticker, fee, markets): rc = client_get(client, f"{BASE_URI}/status") assert_response(rc) resp_values = rc.json() - assert len(resp_values) == 1 + assert len(resp_values) == 4 assert isnan(resp_values[0]['profit_abs']) @@ -917,7 +922,7 @@ def test_api_forcebuy(botclient, mocker, fee): pair='ETH/ETH', amount=1, amount_requested=1, - exchange='bittrex', + exchange='binance', stake_amount=1, open_rate=0.245441, open_order_id="123456", @@ -940,11 +945,9 @@ def test_api_forcebuy(botclient, mocker, fee): 'amount_requested': 1, 'trade_id': 22, 'close_date': None, - 'close_date_hum': None, 'close_timestamp': None, 'close_rate': 0.265441, 'open_date': ANY, - 'open_date_hum': 'just now', 'open_timestamp': ANY, 'open_rate': 0.245441, 'pair': 'ETH/ETH', @@ -965,6 +968,7 @@ def test_api_forcebuy(botclient, mocker, fee): 'profit_ratio': None, 'profit_pct': None, 'profit_abs': None, + 'profit_fiat': None, 'fee_close': 0.0025, 'fee_close_cost': None, 'fee_close_currency': None, @@ -981,7 +985,7 @@ def test_api_forcebuy(botclient, mocker, fee): 'sell_order_status': None, 'strategy': 'DefaultStrategy', 'timeframe': 5, - 'exchange': 'bittrex', + 'exchange': 'binance', } @@ -1141,6 +1145,14 @@ def test_api_plot_config(botclient): assert_response(rc) assert rc.json() == ftbot.strategy.plot_config assert isinstance(rc.json()['main_plot'], dict) + assert isinstance(rc.json()['subplots'], dict) + + ftbot.strategy.plot_config = {'main_plot': {'sma': {}}} + rc = client_get(client, f"{BASE_URI}/plot_config") + assert_response(rc) + + assert isinstance(rc.json()['main_plot'], dict) + assert isinstance(rc.json()['subplots'], dict) def test_api_strategies(botclient): @@ -1149,7 +1161,11 @@ def test_api_strategies(botclient): rc = client_get(client, f"{BASE_URI}/strategies") assert_response(rc) - assert rc.json() == {'strategies': ['DefaultStrategy', 'TestStrategyLegacy']} + assert rc.json() == {'strategies': [ + 'DefaultStrategy', + 'HyperoptableStrategy', + 'TestStrategyLegacy' + ]} def test_api_strategy(botclient): diff --git a/tests/rpc/test_rpc_manager.py b/tests/rpc/test_rpc_manager.py index 3068e9764..69a757fcf 100644 --- a/tests/rpc/test_rpc_manager.py +++ b/tests/rpc/test_rpc_manager.py @@ -71,7 +71,7 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None: freqtradebot = get_patched_freqtradebot(mocker, default_conf) rpc_manager = RPCManager(freqtradebot) rpc_manager.send_msg({ - 'type': RPCMessageType.STATUS_NOTIFICATION, + 'type': RPCMessageType.STATUS, 'status': 'test' }) @@ -86,7 +86,7 @@ def test_send_msg_telegram_enabled(mocker, default_conf, caplog) -> None: freqtradebot = get_patched_freqtradebot(mocker, default_conf) rpc_manager = RPCManager(freqtradebot) rpc_manager.send_msg({ - 'type': RPCMessageType.STATUS_NOTIFICATION, + 'type': RPCMessageType.STATUS, 'status': 'test' }) @@ -124,7 +124,7 @@ def test_send_msg_webhook_CustomMessagetype(mocker, default_conf, caplog) -> Non rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf)) assert 'webhook' in [mod.name for mod in rpc_manager.registered_modules] - rpc_manager.send_msg({'type': RPCMessageType.STARTUP_NOTIFICATION, + rpc_manager.send_msg({'type': RPCMessageType.STARTUP, 'status': 'TestMessage'}) assert log_has( "Message type 'startup' not implemented by handler webhook.", @@ -140,7 +140,7 @@ def test_startupmessages_telegram_enabled(mocker, default_conf, caplog) -> None: rpc_manager.startup_messages(default_conf, freqtradebot.pairlists, freqtradebot.protections) assert telegram_mock.call_count == 3 - assert "*Exchange:* `bittrex`" in telegram_mock.call_args_list[1][0][0]['status'] + assert "*Exchange:* `binance`" in telegram_mock.call_args_list[1][0][0]['status'] telegram_mock.reset_mock() default_conf['dry_run'] = True diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py index 6e818ff8d..e640f2dff 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -186,9 +186,7 @@ def test_telegram_status(default_conf, update, mocker) -> None: 'pair': 'ETH/BTC', 'base_currency': 'BTC', 'open_date': arrow.utcnow(), - 'open_date_hum': arrow.utcnow().humanize, 'close_date': None, - 'close_date_hum': None, 'open_rate': 1.099e-05, 'close_rate': None, 'current_rate': 1.098e-05, @@ -694,12 +692,12 @@ def test_telegram_forcesell_handle(default_conf, update, ticker, fee, context.args = ["1"] telegram._forcesell(update=update, context=context) - assert msg_mock.call_count == 3 + assert msg_mock.call_count == 4 last_msg = msg_mock.call_args_list[-1][0][0] assert { - 'type': RPCMessageType.SELL_NOTIFICATION, + 'type': RPCMessageType.SELL, 'trade_id': 1, - 'exchange': 'Bittrex', + 'exchange': 'Binance', 'pair': 'ETH/BTC', 'gain': 'profit', 'limit': 1.173e-05, @@ -714,6 +712,7 @@ def test_telegram_forcesell_handle(default_conf, update, ticker, fee, 'sell_reason': SellType.FORCE_SELL.value, 'open_date': ANY, 'close_date': ANY, + 'close_rate': ANY, } == last_msg @@ -754,13 +753,13 @@ def test_telegram_forcesell_down_handle(default_conf, update, ticker, fee, context.args = ["1"] telegram._forcesell(update=update, context=context) - assert msg_mock.call_count == 3 + assert msg_mock.call_count == 4 last_msg = msg_mock.call_args_list[-1][0][0] assert { - 'type': RPCMessageType.SELL_NOTIFICATION, + 'type': RPCMessageType.SELL, 'trade_id': 1, - 'exchange': 'Bittrex', + 'exchange': 'Binance', 'pair': 'ETH/BTC', 'gain': 'loss', 'limit': 1.043e-05, @@ -775,6 +774,7 @@ def test_telegram_forcesell_down_handle(default_conf, update, ticker, fee, 'sell_reason': SellType.FORCE_SELL.value, 'open_date': ANY, 'close_date': ANY, + 'close_rate': ANY, } == last_msg @@ -805,13 +805,13 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None context.args = ["all"] telegram._forcesell(update=update, context=context) - # Called for each trade 3 times - assert msg_mock.call_count == 8 - msg = msg_mock.call_args_list[1][0][0] + # Called for each trade 4 times + assert msg_mock.call_count == 12 + msg = msg_mock.call_args_list[2][0][0] assert { - 'type': RPCMessageType.SELL_NOTIFICATION, + 'type': RPCMessageType.SELL, 'trade_id': 1, - 'exchange': 'Bittrex', + 'exchange': 'Binance', 'pair': 'ETH/BTC', 'gain': 'loss', 'limit': 1.099e-05, @@ -826,6 +826,7 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None 'sell_reason': SellType.FORCE_SELL.value, 'open_date': ANY, 'close_date': ANY, + 'close_rate': ANY, } == msg @@ -964,7 +965,7 @@ def test_performance_handle(default_conf, update, ticker, fee, telegram._performance(update=update, context=MagicMock()) assert msg_mock.call_count == 1 assert 'Performance' in msg_mock.call_args_list[0][0][0] - assert 'ETH/BTC\t6.20% (1)' in msg_mock.call_args_list[0][0][0] + assert 'ETH/BTC\t0.00006217 BTC (6.20%) (1)' in msg_mock.call_args_list[0][0][0] def test_count_handle(default_conf, update, ticker, fee, mocker) -> None: @@ -1004,6 +1005,11 @@ def test_telegram_lock_handle(default_conf, update, ticker, fee, mocker) -> None ) telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf) patch_get_signal(freqtradebot, (True, False)) + telegram._locks(update=update, context=MagicMock()) + assert msg_mock.call_count == 1 + assert 'No active locks.' in msg_mock.call_args_list[0][0][0] + + msg_mock.reset_mock() PairLocks.lock_pair('ETH/BTC', arrow.utcnow().shift(minutes=4).datetime, 'randreason') PairLocks.lock_pair('XRP/BTC', arrow.utcnow().shift(minutes=20).datetime, 'deadbeef') @@ -1137,6 +1143,15 @@ def test_edge_enabled(edge_conf, update, mocker) -> None: assert 'Edge only validated following pairs:\n
' in msg_mock.call_args_list[0][0][0]
     assert 'Pair      Winrate    Expectancy    Stoploss' in msg_mock.call_args_list[0][0][0]
 
+    msg_mock.reset_mock()
+
+    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
+        return_value={}))
+    telegram._edge(update=update, context=MagicMock())
+    assert msg_mock.call_count == 1
+    assert 'Edge only validated following pairs:' in msg_mock.call_args_list[0][0][0]
+    assert 'Winrate' not in msg_mock.call_args_list[0][0][0]
+
 
 def test_telegram_trades(mocker, update, default_conf, fee):
 
@@ -1216,7 +1231,7 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
     telegram._show_config(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
-    assert '*Exchange:* `bittrex`' in msg_mock.call_args_list[0][0][0]
+    assert '*Exchange:* `binance`' in msg_mock.call_args_list[0][0][0]
     assert '*Strategy:* `DefaultStrategy`' in msg_mock.call_args_list[0][0][0]
     assert '*Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
 
@@ -1225,7 +1240,7 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
     telegram._show_config(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
-    assert '*Exchange:* `bittrex`' in msg_mock.call_args_list[0][0][0]
+    assert '*Exchange:* `binance`' in msg_mock.call_args_list[0][0][0]
     assert '*Strategy:* `DefaultStrategy`' in msg_mock.call_args_list[0][0][0]
     assert '*Initial Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
 
@@ -1233,9 +1248,9 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
 def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
 
     msg = {
-        'type': RPCMessageType.BUY_NOTIFICATION,
+        'type': RPCMessageType.BUY,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 1.099e-05,
         'order_type': 'limit',
@@ -1251,7 +1266,7 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
 
     telegram.send_msg(msg)
     assert msg_mock.call_args[0][0] \
-        == '\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC (#1)\n' \
+        == '\N{LARGE BLUE CIRCLE} *Binance:* Buying ETH/BTC (#1)\n' \
            '*Amount:* `1333.33333333`\n' \
            '*Open Rate:* `0.00001099`\n' \
            '*Current Rate:* `0.00001099`\n' \
@@ -1278,17 +1293,36 @@ def test_send_msg_buy_cancel_notification(default_conf, mocker) -> None:
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.BUY_CANCEL_NOTIFICATION,
+        'type': RPCMessageType.BUY_CANCEL,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'reason': CANCEL_REASON['TIMEOUT']
     })
-    assert (msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Bittrex:* '
+    assert (msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Binance:* '
             'Cancelling open buy Order for ETH/BTC (#1). '
             'Reason: cancelled due to timeout.')
 
 
+def test_send_msg_buy_fill_notification(default_conf, mocker) -> None:
+
+    default_conf['telegram']['notification_settings']['buy_fill'] = 'on'
+    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    telegram.send_msg({
+        'type': RPCMessageType.BUY_FILL,
+        'trade_id': 1,
+        'exchange': 'Binance',
+        'pair': 'ETH/USDT',
+        'open_rate': 200,
+        'stake_amount': 100,
+        'amount': 0.5,
+        'open_date': arrow.utcnow().datetime
+    })
+    assert (msg_mock.call_args[0][0] == '\N{LARGE CIRCLE} *Binance:* '
+            'Buy order for ETH/USDT (#1) filled for 200.')
+
+
 def test_send_msg_sell_notification(default_conf, mocker) -> None:
 
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
@@ -1296,7 +1330,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
     old_convamount = telegram._rpc._fiat_converter.convert_amount
     telegram._rpc._fiat_converter.convert_amount = lambda a, b, c: -24.812
     telegram.send_msg({
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
@@ -1326,7 +1360,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
 
     msg_mock.reset_mock()
     telegram.send_msg({
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
@@ -1363,36 +1397,65 @@ def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
     old_convamount = telegram._rpc._fiat_converter.convert_amount
     telegram._rpc._fiat_converter.convert_amount = lambda a, b, c: -24.812
     telegram.send_msg({
-        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+        'type': RPCMessageType.SELL_CANCEL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
         'reason': 'Cancelled on exchange'
     })
     assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH (#1).'
-            ' Reason: Cancelled on exchange')
+        == ('\N{WARNING SIGN} *Binance:* Cancelling open sell Order for KEY/ETH (#1).'
+            ' Reason: Cancelled on exchange.')
 
     msg_mock.reset_mock()
     telegram.send_msg({
-        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+        'type': RPCMessageType.SELL_CANCEL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
         'reason': 'timeout'
     })
     assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH (#1).'
-            ' Reason: timeout')
+        == ('\N{WARNING SIGN} *Binance:* Cancelling open sell Order for KEY/ETH (#1).'
+            ' Reason: timeout.')
     # Reset singleton function to avoid random breaks
     telegram._rpc._fiat_converter.convert_amount = old_convamount
 
 
+def test_send_msg_sell_fill_notification(default_conf, mocker) -> None:
+
+    default_conf['telegram']['notification_settings']['sell_fill'] = 'on'
+    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    telegram.send_msg({
+        'type': RPCMessageType.SELL_FILL,
+        'trade_id': 1,
+        'exchange': 'Binance',
+        'pair': 'ETH/USDT',
+        'gain': 'loss',
+        'limit': 3.201e-05,
+        'amount': 0.1,
+        'order_type': 'market',
+        'open_rate': 500,
+        'close_rate': 550,
+        'current_rate': 3.201e-05,
+        'profit_amount': -0.05746268,
+        'profit_ratio': -0.57405275,
+        'stake_currency': 'ETH',
+        'fiat_currency': 'USD',
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(hours=-1),
+        'close_date': arrow.utcnow(),
+    })
+    assert msg_mock.call_args[0][0] \
+        == ('\N{LARGE CIRCLE} *Binance:* Sell order for ETH/USDT (#1) filled for 550.')
+
+
 def test_send_msg_status_notification(default_conf, mocker) -> None:
 
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
     telegram.send_msg({
-        'type': RPCMessageType.STATUS_NOTIFICATION,
+        'type': RPCMessageType.STATUS,
         'status': 'running'
     })
     assert msg_mock.call_args[0][0] == '*Status:* `running`'
@@ -1401,7 +1464,7 @@ def test_send_msg_status_notification(default_conf, mocker) -> None:
 def test_warning_notification(default_conf, mocker) -> None:
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
     telegram.send_msg({
-        'type': RPCMessageType.WARNING_NOTIFICATION,
+        'type': RPCMessageType.WARNING,
         'status': 'message'
     })
     assert msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Warning:* `message`'
@@ -1410,7 +1473,7 @@ def test_warning_notification(default_conf, mocker) -> None:
 def test_startup_notification(default_conf, mocker) -> None:
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
     telegram.send_msg({
-        'type': RPCMessageType.STARTUP_NOTIFICATION,
+        'type': RPCMessageType.STARTUP,
         'status': '*Custom:* `Hello World`'
     })
     assert msg_mock.call_args[0][0] == '*Custom:* `Hello World`'
@@ -1429,9 +1492,9 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.BUY_NOTIFICATION,
+        'type': RPCMessageType.BUY,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 1.099e-05,
         'order_type': 'limit',
@@ -1443,7 +1506,7 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
         'amount': 1333.3333333333335,
         'open_date': arrow.utcnow().shift(hours=-1)
     })
-    assert msg_mock.call_args[0][0] == ('\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC (#1)\n'
+    assert msg_mock.call_args[0][0] == ('\N{LARGE BLUE CIRCLE} *Binance:* Buying ETH/BTC (#1)\n'
                                         '*Amount:* `1333.33333333`\n'
                                         '*Open Rate:* `0.00001099`\n'
                                         '*Current Rate:* `0.00001099`\n'
@@ -1455,7 +1518,7 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
diff --git a/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py
index 5361cd947..0560f8d53 100644
--- a/tests/rpc/test_rpc_webhook.py
+++ b/tests/rpc/test_rpc_webhook.py
@@ -25,6 +25,11 @@ def get_webhook_dict() -> dict:
             "value2": "limit {limit:8f}",
             "value3": "{stake_amount:8f} {stake_currency}"
         },
+        "webhookbuyfill": {
+            "value1": "Buy Order for {pair} filled",
+            "value2": "at {open_rate:8f}",
+            "value3": "{stake_amount:8f} {stake_currency}"
+        },
         "webhooksell": {
             "value1": "Selling {pair}",
             "value2": "limit {limit:8f}",
@@ -35,6 +40,11 @@ def get_webhook_dict() -> dict:
             "value2": "limit {limit:8f}",
             "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
+        "webhooksellfill": {
+            "value1": "Sell Order for {pair} filled",
+            "value2": "at {close_rate:8f}",
+            "value3": ""
+        },
         "webhookstatus": {
             "value1": "Status: {status}",
             "value2": "",
@@ -49,7 +59,7 @@ def test__init__(mocker, default_conf):
     assert webhook._config == default_conf
 
 
-def test_send_msg(default_conf, mocker):
+def test_send_msg_webhook(default_conf, mocker):
     default_conf["webhook"] = get_webhook_dict()
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
@@ -58,8 +68,8 @@ def test_send_msg(default_conf, mocker):
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     msg = {
-        'type': RPCMessageType.BUY_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 0.005,
         'stake_amount': 0.8,
@@ -76,11 +86,11 @@ def test_send_msg(default_conf, mocker):
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhookbuy"]["value3"].format(**msg))
     # Test buy cancel
-    msg_mock = MagicMock()
-    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
+    msg_mock.reset_mock()
+
     msg = {
-        'type': RPCMessageType.BUY_CANCEL_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY_CANCEL,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 0.005,
         'stake_amount': 0.8,
@@ -96,12 +106,32 @@ def test_send_msg(default_conf, mocker):
             default_conf["webhook"]["webhookbuycancel"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhookbuycancel"]["value3"].format(**msg))
-    # Test sell
-    msg_mock = MagicMock()
-    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
+    # Test buy fill
+    msg_mock.reset_mock()
+
     msg = {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY_FILL,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'open_rate': 0.005,
+        'stake_amount': 0.8,
+        'stake_amount_fiat': 500,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'EUR'
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhookbuyfill"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhookbuyfill"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhookbuyfill"]["value3"].format(**msg))
+    # Test sell
+    msg_mock.reset_mock()
+    msg = {
+        'type': RPCMessageType.SELL,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': "profit",
         'limit': 0.005,
@@ -123,11 +153,10 @@ def test_send_msg(default_conf, mocker):
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhooksell"]["value3"].format(**msg))
     # Test sell cancel
-    msg_mock = MagicMock()
-    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
+    msg_mock.reset_mock()
     msg = {
-        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.SELL_CANCEL,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': "profit",
         'limit': 0.005,
@@ -148,9 +177,35 @@ def test_send_msg(default_conf, mocker):
             default_conf["webhook"]["webhooksellcancel"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhooksellcancel"]["value3"].format(**msg))
-    for msgtype in [RPCMessageType.STATUS_NOTIFICATION,
-                    RPCMessageType.WARNING_NOTIFICATION,
-                    RPCMessageType.STARTUP_NOTIFICATION]:
+    # Test Sell fill
+    msg_mock.reset_mock()
+    msg = {
+        'type': RPCMessageType.SELL_FILL,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'gain': "profit",
+        'close_rate': 0.005,
+        'amount': 0.8,
+        'order_type': 'limit',
+        'open_rate': 0.004,
+        'current_rate': 0.005,
+        'profit_amount': 0.001,
+        'profit_ratio': 0.20,
+        'stake_currency': 'BTC',
+        'sell_reason': SellType.STOP_LOSS.value
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhooksellfill"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhooksellfill"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhooksellfill"]["value3"].format(**msg))
+
+    for msgtype in [RPCMessageType.STATUS,
+                    RPCMessageType.WARNING,
+                    RPCMessageType.STARTUP]:
         # Test notification
         msg = {
             'type': msgtype,
@@ -173,8 +228,8 @@ def test_exception_send_msg(default_conf, mocker, caplog):
     del default_conf["webhook"]["webhookbuy"]
 
     webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
-    webhook.send_msg({'type': RPCMessageType.BUY_NOTIFICATION})
-    assert log_has(f"Message type '{RPCMessageType.BUY_NOTIFICATION}' not configured for webhooks",
+    webhook.send_msg({'type': RPCMessageType.BUY})
+    assert log_has(f"Message type '{RPCMessageType.BUY}' not configured for webhooks",
                    caplog)
 
     default_conf["webhook"] = get_webhook_dict()
@@ -183,8 +238,8 @@ def test_exception_send_msg(default_conf, mocker, caplog):
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
     msg = {
-        'type': RPCMessageType.BUY_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 0.005,
         'order_type': 'limit',
diff --git a/tests/strategy/strats/default_strategy.py b/tests/strategy/strats/default_strategy.py
index 98842ff7c..7171b93ae 100644
--- a/tests/strategy/strats/default_strategy.py
+++ b/tests/strategy/strats/default_strategy.py
@@ -28,7 +28,7 @@ class DefaultStrategy(IStrategy):
     # Optimal stoploss designed for the strategy
     stoploss = -0.10
 
-    # Optimal ticker interval for the strategy
+    # Optimal timeframe for the strategy
     timeframe = '5m'
 
     # Optional order type mapping
diff --git a/tests/strategy/strats/hyperoptable_strategy.py b/tests/strategy/strats/hyperoptable_strategy.py
new file mode 100644
index 000000000..cc4734e13
--- /dev/null
+++ b/tests/strategy/strats/hyperoptable_strategy.py
@@ -0,0 +1,173 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, RealParameter
+
+
+class HyperoptableStrategy(IStrategy):
+    """
+    Default Strategy provided by freqtrade bot.
+    Please do not modify this strategy, it's  intended for internal use only.
+    Please look at the SampleStrategy in the user_data/strategy directory
+    or strategy repository https://github.com/freqtrade/freqtrade-strategies
+    for samples and inspiration.
+    """
+    INTERFACE_VERSION = 2
+
+    # Minimal ROI designed for the strategy
+    minimal_roi = {
+        "40": 0.0,
+        "30": 0.01,
+        "20": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy
+    stoploss = -0.10
+
+    # Optimal ticker interval for the strategy
+    timeframe = '5m'
+
+    # Optional order type mapping
+    order_types = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False
+    }
+
+    # Number of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 20
+
+    # Optional time in force for orders
+    order_time_in_force = {
+        'buy': 'gtc',
+        'sell': 'gtc',
+    }
+
+    buy_params = {
+        'buy_rsi': 35,
+        # Intentionally not specified, so "default" is tested
+        # 'buy_plusdi': 0.4
+    }
+
+    sell_params = {
+        'sell_rsi': 74,
+        'sell_minusdi': 0.4
+    }
+
+    buy_rsi = IntParameter([0, 50], default=30, space='buy')
+    buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
+    sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
+    sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
+                                    load=False)
+
+    def informative_pairs(self):
+        """
+        Define additional, informative pair/interval combinations to be cached from the exchange.
+        These pair/interval combinations are non-tradeable, unless they are part
+        of the whitelist as well.
+        For more information, please consult the documentation
+        :return: List of tuples in the format (pair, interval)
+            Sample: return [("ETH/USDT", "5m"),
+                            ("BTC/USDT", "15m"),
+                            ]
+        """
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Adds several different TA indicators to the given DataFrame
+
+        Performance Note: For the best performance be frugal on the number of indicators
+        you are using. Let uncomment only the indicator you are using in your strategies
+        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
+        :param dataframe: Dataframe with data from the exchange
+        :param metadata: Additional information, like the currently traded pair
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+
+        # Momentum Indicator
+        # ------------------------------------
+
+        # ADX
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # MACD
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        dataframe['macdhist'] = macd['macdhist']
+
+        # Minus Directional Indicator / Movement
+        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
+
+        # Plus Directional Indicator / Movement
+        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
+
+        # RSI
+        dataframe['rsi'] = ta.RSI(dataframe)
+
+        # Stoch fast
+        stoch_fast = ta.STOCHF(dataframe)
+        dataframe['fastd'] = stoch_fast['fastd']
+        dataframe['fastk'] = stoch_fast['fastk']
+
+        # Bollinger bands
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+        dataframe['bb_lowerband'] = bollinger['lower']
+        dataframe['bb_middleband'] = bollinger['mid']
+        dataframe['bb_upperband'] = bollinger['upper']
+
+        # EMA - Exponential Moving Average
+        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (dataframe['rsi'] < self.buy_rsi.value) &
+                (dataframe['fastd'] < 35) &
+                (dataframe['adx'] > 30) &
+                (dataframe['plus_di'] > self.buy_plusdi.value)
+            ) |
+            (
+                (dataframe['adx'] > 65) &
+                (dataframe['plus_di'] > self.buy_plusdi.value)
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (
+                    (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
+                    (qtpylib.crossed_above(dataframe['fastd'], 70))
+                ) &
+                (dataframe['adx'] > 10) &
+                (dataframe['minus_di'] > 0)
+            ) |
+            (
+                (dataframe['adx'] > 70) &
+                (dataframe['minus_di'] > self.sell_minusdi.value)
+            ),
+            'sell'] = 1
+        return dataframe
diff --git a/tests/strategy/strats/legacy_strategy.py b/tests/strategy/strats/legacy_strategy.py
index 1e7bb5e1e..9ef00b110 100644
--- a/tests/strategy/strats/legacy_strategy.py
+++ b/tests/strategy/strats/legacy_strategy.py
@@ -31,7 +31,7 @@ class TestStrategyLegacy(IStrategy):
     # This attribute will be overridden if the config file contains "stoploss"
     stoploss = -0.10
 
-    # Optimal ticker interval for the strategy
+    # Optimal timeframe for the strategy
     # Keep the legacy value here to test compatibility
     ticker_interval = '5m'
 
diff --git a/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py
index ec7b3c33d..92ac9f63a 100644
--- a/tests/strategy/test_default_strategy.py
+++ b/tests/strategy/test_default_strategy.py
@@ -36,9 +36,11 @@ def test_default_strategy(result, fee):
     )
 
     assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
-                                        rate=20000, time_in_force='gtc') is True
+                                        rate=20000, time_in_force='gtc',
+                                        current_time=datetime.utcnow()) is True
     assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
-                                       rate=20000, time_in_force='gtc', sell_reason='roi') is True
+                                       rate=20000, time_in_force='gtc', sell_reason='roi',
+                                       current_time=datetime.utcnow()) is True
 
     assert strategy.custom_stoploss(pair='ETH/BTC', trade=trade, current_time=datetime.now(),
                                     current_rate=20_000, current_profit=0.05) == strategy.stoploss
diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
index f158a1518..ded396779 100644
--- a/tests/strategy/test_interface.py
+++ b/tests/strategy/test_interface.py
@@ -10,9 +10,11 @@ from pandas import DataFrame
 from freqtrade.configuration import TimeRange
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history import load_data
-from freqtrade.exceptions import StrategyError
+from freqtrade.exceptions import OperationalException, StrategyError
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.resolvers import StrategyResolver
+from freqtrade.strategy.hyper import (BaseParameter, CategoricalParameter, DecimalParameter,
+                                      IntParameter, RealParameter)
 from freqtrade.strategy.interface import SellCheckTuple, SellType
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from tests.conftest import log_has, log_has_re
@@ -217,7 +219,7 @@ def test_min_roi_reached(default_conf, fee) -> None:
             open_date=arrow.utcnow().shift(hours=-1).datetime,
             fee_open=fee.return_value,
             fee_close=fee.return_value,
-            exchange='bittrex',
+            exchange='binance',
             open_rate=1,
         )
 
@@ -256,7 +258,7 @@ def test_min_roi_reached2(default_conf, fee) -> None:
             open_date=arrow.utcnow().shift(hours=-1).datetime,
             fee_open=fee.return_value,
             fee_close=fee.return_value,
-            exchange='bittrex',
+            exchange='binance',
             open_rate=1,
         )
 
@@ -291,7 +293,7 @@ def test_min_roi_reached3(default_conf, fee) -> None:
         open_date=arrow.utcnow().shift(hours=-1).datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
     )
 
@@ -344,7 +346,7 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
         open_date=arrow.utcnow().shift(hours=-1).datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
     )
     trade.adjust_min_max_rates(trade.open_rate)
@@ -380,6 +382,50 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
     strategy.custom_stoploss = original_stopvalue
 
 
+def test_custom_sell(default_conf, fee, caplog) -> None:
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+
+    strategy = StrategyResolver.load_strategy(default_conf)
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.01,
+        amount=1,
+        open_date=arrow.utcnow().shift(hours=-1).datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=1,
+    )
+
+    now = arrow.utcnow().datetime
+    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
+
+    assert res.sell_flag is False
+    assert res.sell_type == SellType.NONE
+
+    strategy.custom_sell = MagicMock(return_value=True)
+    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
+    assert res.sell_flag is True
+    assert res.sell_type == SellType.CUSTOM_SELL
+    assert res.sell_reason == 'custom_sell'
+
+    strategy.custom_sell = MagicMock(return_value='hello world')
+
+    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
+    assert res.sell_type == SellType.CUSTOM_SELL
+    assert res.sell_flag is True
+    assert res.sell_reason == 'hello world'
+
+    caplog.clear()
+    strategy.custom_sell = MagicMock(return_value='h' * 100)
+    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
+    assert res.sell_type == SellType.CUSTOM_SELL
+    assert res.sell_flag is True
+    assert res.sell_reason == 'h' * 64
+    assert log_has_re('Custom sell reason returned from custom_sell is too long.*', caplog)
+
+
 def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
     caplog.set_level(logging.DEBUG)
     ind_mock = MagicMock(side_effect=lambda x, meta: x)
@@ -552,3 +598,77 @@ def test_strategy_safe_wrapper(value):
 
     assert type(ret) == type(value)
     assert ret == value
+
+
+def test_hyperopt_parameters():
+    from skopt.space import Categorical, Integer, Real
+    with pytest.raises(OperationalException, match=r"Name is determined.*"):
+        IntParameter(low=0, high=5, default=1, name='hello')
+
+    with pytest.raises(OperationalException, match=r"IntParameter space must be.*"):
+        IntParameter(low=0, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"RealParameter space must be.*"):
+        RealParameter(low=0, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"DecimalParameter space must be.*"):
+        DecimalParameter(low=0, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"IntParameter space invalid\."):
+        IntParameter([0, 10], high=7, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"RealParameter space invalid\."):
+        RealParameter([0, 10], high=7, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"DecimalParameter space invalid\."):
+        DecimalParameter([0, 10], high=7, default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"CategoricalParameter space must.*"):
+        CategoricalParameter(['aa'], default='aa', space='buy')
+
+    with pytest.raises(TypeError):
+        BaseParameter(opt_range=[0, 1], default=1, space='buy')
+
+    intpar = IntParameter(low=0, high=5, default=1, space='buy')
+    assert intpar.value == 1
+    assert isinstance(intpar.get_space(''), Integer)
+    assert isinstance(intpar.range, range)
+    assert len(list(intpar.range)) == 1
+    # Range contains ONLY the default / value.
+    assert list(intpar.range) == [intpar.value]
+    intpar.in_space = True
+
+    assert len(list(intpar.range)) == 6
+    assert list(intpar.range) == [0, 1, 2, 3, 4, 5]
+
+    fltpar = RealParameter(low=0.0, high=5.5, default=1.0, space='buy')
+    assert isinstance(fltpar.get_space(''), Real)
+    assert fltpar.value == 1
+
+    fltpar = DecimalParameter(low=0.0, high=5.5, default=1.0004, decimals=3, space='buy')
+    assert isinstance(fltpar.get_space(''), Integer)
+    assert fltpar.value == 1
+
+    catpar = CategoricalParameter(['buy_rsi', 'buy_macd', 'buy_none'],
+                                  default='buy_macd', space='buy')
+    assert isinstance(catpar.get_space(''), Categorical)
+    assert catpar.value == 'buy_macd'
+
+
+def test_auto_hyperopt_interface(default_conf):
+    default_conf.update({'strategy': 'HyperoptableStrategy'})
+    PairLocks.timeframe = default_conf['timeframe']
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.buy_rsi.value == strategy.buy_params['buy_rsi']
+    # PlusDI is NOT in the buy-params, so default should be used
+    assert strategy.buy_plusdi.value == 0.5
+    assert strategy.sell_rsi.value == strategy.sell_params['sell_rsi']
+
+    # Parameter is disabled - so value from sell_param dict will NOT be used.
+    assert strategy.sell_minusdi.value == 0.5
+
+    strategy.sell_rsi = IntParameter([0, 10], default=5, space='buy')
+
+    with pytest.raises(OperationalException, match=r"Inconclusive parameter.*"):
+        [x for x in strategy._detect_parameters('sell')]
diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py
index 1c692d2da..965c3d37b 100644
--- a/tests/strategy/test_strategy_loading.py
+++ b/tests/strategy/test_strategy_loading.py
@@ -35,7 +35,7 @@ def test_search_all_strategies_no_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
     assert isinstance(strategies, list)
-    assert len(strategies) == 2
+    assert len(strategies) == 3
     assert isinstance(strategies[0], dict)
 
 
@@ -43,10 +43,10 @@ def test_search_all_strategies_with_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
     assert isinstance(strategies, list)
-    assert len(strategies) == 3
+    assert len(strategies) == 4
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 2
+    assert len([x for x in strategies if x['class'] is not None]) == 3
     assert len([x for x in strategies if x['class'] is None]) == 1
 
 
diff --git a/tests/test_configuration.py b/tests/test_configuration.py
index a0824e65c..b2c883108 100644
--- a/tests/test_configuration.py
+++ b/tests/test_configuration.py
@@ -565,7 +565,7 @@ def test_check_exchange(default_conf, caplog) -> None:
     # Test a 'bad' exchange, which known to have serious problems
     default_conf.get('exchange').update({'name': 'bitmex'})
     with pytest.raises(OperationalException,
-                       match=r"Exchange .* is known to not work with the bot yet.*"):
+                       match=r"Exchange .* will not work with Freqtrade\..*"):
         check_exchange(default_conf)
     caplog.clear()
 
@@ -860,22 +860,6 @@ def test_validate_tsl(default_conf):
         validate_config_consistency(default_conf)
 
 
-def test_validate_edge(edge_conf):
-    edge_conf.update({"pairlist": {
-        "method": "VolumePairList",
-    }})
-
-    with pytest.raises(OperationalException,
-                       match="Edge and VolumePairList are incompatible, "
-                       "Edge will override whatever pairs VolumePairlist selects."):
-        validate_config_consistency(edge_conf)
-
-    edge_conf.update({"pairlist": {
-        "method": "StaticPairList",
-    }})
-    validate_config_consistency(edge_conf)
-
-
 def test_validate_edge2(edge_conf):
     edge_conf.update({"ask_strategy": {
         "use_sell_signal": True,
@@ -1018,6 +1002,7 @@ def test_pairlist_resolving():
     config = configuration.get_config()
 
     assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert config['exchange']['pair_whitelist'] == ['ETH/BTC', 'XRP/BTC']
     assert config['exchange']['name'] == 'binance'
 
 
@@ -1054,37 +1039,30 @@ def test_pairlist_resolving_with_config(mocker, default_conf):
 
 def test_pairlist_resolving_with_config_pl(mocker, default_conf):
     patched_configuration_load_config_file(mocker, default_conf)
-    load_mock = mocker.patch("freqtrade.configuration.configuration.json_load",
-                             MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
-    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
-    mocker.patch.object(Path, "open", MagicMock(return_value=MagicMock()))
 
     arglist = [
         'download-data',
         '--config', 'config.json',
-        '--pairs-file', 'pairs.json',
+        '--pairs-file', 'tests/testdata/pairs.json',
     ]
 
     args = Arguments(arglist).get_parsed_arg()
 
     configuration = Configuration(args)
     config = configuration.get_config()
-
-    assert load_mock.call_count == 1
-    assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert len(config['pairs']) == 23
+    assert 'ETH/BTC' in config['pairs']
+    assert 'XRP/BTC' in config['pairs']
     assert config['exchange']['name'] == default_conf['exchange']['name']
 
 
 def test_pairlist_resolving_with_config_pl_not_exists(mocker, default_conf):
     patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch("freqtrade.configuration.configuration.json_load",
-                 MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
-    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
 
     arglist = [
         'download-data',
         '--config', 'config.json',
-        '--pairs-file', 'pairs.json',
+        '--pairs-file', 'tests/testdata/pairs_doesnotexist.json',
     ]
 
     args = Arguments(arglist).get_parsed_arg()
@@ -1097,7 +1075,7 @@ def test_pairlist_resolving_with_config_pl_not_exists(mocker, default_conf):
 def test_pairlist_resolving_fallback(mocker):
     mocker.patch.object(Path, "exists", MagicMock(return_value=True))
     mocker.patch.object(Path, "open", MagicMock(return_value=MagicMock()))
-    mocker.patch("freqtrade.configuration.configuration.json_load",
+    mocker.patch("freqtrade.configuration.configuration.load_file",
                  MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
     arglist = [
         'download-data',
diff --git a/tests/test_directory_operations.py b/tests/test_directory_operations.py
index a8058c514..a11200526 100644
--- a/tests/test_directory_operations.py
+++ b/tests/test_directory_operations.py
@@ -1,11 +1,12 @@
 # pragma pylint: disable=missing-docstring, protected-access, invalid-name
+import os
 from pathlib import Path
 from unittest.mock import MagicMock
 
 import pytest
 
-from freqtrade.configuration.directory_operations import (copy_sample_files, create_datadir,
-                                                          create_userdata_dir)
+from freqtrade.configuration.directory_operations import (chown_user_directory, copy_sample_files,
+                                                          create_datadir, create_userdata_dir)
 from freqtrade.exceptions import OperationalException
 from tests.conftest import log_has, log_has_re
 
@@ -31,6 +32,24 @@ def test_create_userdata_dir(mocker, default_conf, caplog) -> None:
     assert str(x) == str(Path("/tmp/bar"))
 
 
+def test_create_userdata_dir_and_chown(mocker, tmpdir, caplog) -> None:
+    sp_mock = mocker.patch('subprocess.check_output')
+    path = Path(tmpdir / 'bar')
+    assert not path.is_dir()
+
+    x = create_userdata_dir(str(path), create_dir=True)
+    assert sp_mock.call_count == 0
+    assert log_has(f'Created user-data directory: {path}', caplog)
+    assert isinstance(x, Path)
+    assert path.is_dir()
+    assert (path / 'data').is_dir()
+
+    os.environ['FT_APP_ENV'] = 'docker'
+    chown_user_directory(path / 'data')
+    assert sp_mock.call_count == 1
+    del os.environ['FT_APP_ENV']
+
+
 def test_create_userdata_dir_exists(mocker, default_conf, caplog) -> None:
     mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
     md = mocker.patch.object(Path, 'mkdir', MagicMock())
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index 486c31090..4d9284a2f 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -82,10 +82,6 @@ def test_bot_cleanup(mocker, default_conf, caplog) -> None:
 def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
-    )
     conf = default_conf.copy()
     conf['runmode'] = RunMode.DRY_RUN
     conf['order_types'] = {
@@ -117,10 +113,7 @@ def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
 def test_order_dict_live(default_conf, mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
-    )
+
     conf = default_conf.copy()
     conf['runmode'] = RunMode.LIVE
     conf['order_types'] = {
@@ -153,15 +146,10 @@ def test_order_dict_live(default_conf, mocker, caplog) -> None:
 def test_get_trade_stake_amount(default_conf, ticker, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
-    )
 
     freqtrade = FreqtradeBot(default_conf)
 
-    result = freqtrade.wallets.get_trade_stake_amount(
-        'ETH/BTC', freqtrade.get_free_open_trades())
+    result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
     assert result == default_conf['stake_amount']
 
 
@@ -182,7 +170,6 @@ def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_b
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker,
-        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2),
         buy=MagicMock(return_value=limit_buy_order_open),
         get_fee=fee
     )
@@ -197,73 +184,12 @@ def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_b
 
         if expected[i] is not None:
             limit_buy_order_open['id'] = str(i)
-            result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC',
-                                                              freqtrade.get_free_open_trades())
+            result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
             assert pytest.approx(result) == expected[i]
             freqtrade.execute_buy('ETH/BTC', result)
         else:
             with pytest.raises(DependencyException):
-                freqtrade.wallets.get_trade_stake_amount('ETH/BTC',
-                                                         freqtrade.get_free_open_trades())
-
-
-def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
-        freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.get_free_open_trades())
-
-
-@pytest.mark.parametrize("balance_ratio,result1", [
-                        (1, 0.005),
-                        (0.99, 0.00495),
-                        (0.50, 0.0025),
-                        ])
-def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, result1,
-                                                 limit_buy_order_open, fee, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        buy=MagicMock(return_value=limit_buy_order_open),
-        get_fee=fee
-    )
-
-    conf = deepcopy(default_conf)
-    conf['stake_amount'] = UNLIMITED_STAKE_AMOUNT
-    conf['dry_run_wallet'] = 0.01
-    conf['max_open_trades'] = 2
-    conf['tradable_balance_ratio'] = balance_ratio
-
-    freqtrade = FreqtradeBot(conf)
-    patch_get_signal(freqtrade)
-
-    # no open trades, order amount should be 'balance / max_open_trades'
-    result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.get_free_open_trades())
-    assert result == result1
-
-    # create one trade, order amount should be 'balance / (max_open_trades - num_open_trades)'
-    freqtrade.execute_buy('ETH/BTC', result)
-
-    result = freqtrade.wallets.get_trade_stake_amount('LTC/BTC', freqtrade.get_free_open_trades())
-    assert result == result1
-
-    # create 2 trades, order amount should be None
-    freqtrade.execute_buy('LTC/BTC', result)
-
-    result = freqtrade.wallets.get_trade_stake_amount('XRP/BTC', freqtrade.get_free_open_trades())
-    assert result == 0
-
-    # set max_open_trades = None, so do not trade
-    conf['max_open_trades'] = 0
-    freqtrade = FreqtradeBot(conf)
-    result = freqtrade.wallets.get_trade_stake_amount('NEO/BTC', freqtrade.get_free_open_trades())
-    assert result == 0
+                freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
 
 
 def test_edge_called_in_process(mocker, edge_conf) -> None:
@@ -289,9 +215,9 @@ def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
     freqtrade = FreqtradeBot(edge_conf)
 
     assert freqtrade.wallets.get_trade_stake_amount(
-        'NEO/BTC', freqtrade.get_free_open_trades(), freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.20
+        'NEO/BTC', freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.20
     assert freqtrade.wallets.get_trade_stake_amount(
-        'LTC/BTC', freqtrade.get_free_open_trades(), freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.21
+        'LTC/BTC', freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.21
 
 
 def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf) -> None:
@@ -421,7 +347,7 @@ def test_create_trade(default_conf, ticker, limit_buy_order, fee, mocker) -> Non
     assert trade.stake_amount == 0.001
     assert trade.is_open
     assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
+    assert trade.exchange == 'binance'
 
     # Simulate fulfilled LIMIT_BUY order for trade
     trade.update(limit_buy_order)
@@ -497,7 +423,6 @@ def test_create_trade_limit_reached(default_conf, ticker, limit_buy_order_open,
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker,
         buy=MagicMock(return_value=limit_buy_order_open),
-        get_balance=MagicMock(return_value=default_conf['stake_amount']),
         get_fee=fee,
     )
     default_conf['max_open_trades'] = 0
@@ -507,8 +432,7 @@ def test_create_trade_limit_reached(default_conf, ticker, limit_buy_order_open,
     patch_get_signal(freqtrade)
 
     assert not freqtrade.create_trade('ETH/BTC')
-    assert freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.get_free_open_trades(),
-                                                    freqtrade.edge) == 0
+    assert freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.edge) == 0
 
 
 def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_open, fee,
@@ -586,7 +510,6 @@ def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=20),
         get_fee=fee,
     )
     default_conf['stake_amount'] = 10
@@ -680,12 +603,13 @@ def test_process_trade_creation(default_conf, ticker, limit_buy_order, limit_buy
     assert trade.stake_amount == default_conf['stake_amount']
     assert trade.is_open
     assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
+    assert trade.exchange == 'binance'
     assert trade.open_rate == 0.00001098
     assert trade.amount == 91.07468123
 
     assert log_has(
-        'Buy signal found: about create a new trade with stake_amount: 0.001 ...', caplog
+        'Buy signal found: about create a new trade for ETH/BTC with stake_amount: 0.001 ...',
+        caplog
     )
 
 
@@ -768,7 +692,7 @@ def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
     assert pair not in default_conf['exchange']['pair_whitelist']
 
     # create open trade not in whitelist
-    Trade.session.add(Trade(
+    Trade.query.session.add(Trade(
         pair=pair,
         stake_amount=0.001,
         fee_open=fee.return_value,
@@ -776,9 +700,9 @@ def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
         is_open=True,
         amount=20,
         open_rate=0.01,
-        exchange='bittrex',
+        exchange='binance',
     ))
-    Trade.session.add(Trade(
+    Trade.query.session.add(Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
         fee_open=fee.return_value,
@@ -786,7 +710,7 @@ def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
         is_open=True,
         amount=12,
         open_rate=0.001,
-        exchange='bittrex',
+        exchange='binance',
     ))
 
     assert pair not in freqtrade.active_pair_whitelist
@@ -1027,7 +951,7 @@ def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None
                  return_value=limit_buy_order['amount'])
 
     stoploss = MagicMock(return_value={'id': 13434334})
-    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
 
     freqtrade = FreqtradeBot(default_conf)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
@@ -1059,6 +983,9 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
         buy=MagicMock(return_value={'id': limit_buy_order['id']}),
         sell=MagicMock(return_value={'id': limit_sell_order['id']}),
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         stoploss=stoploss
     )
     freqtrade = FreqtradeBot(default_conf)
@@ -1083,7 +1010,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.stoploss_order_id = 100
 
     hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', hanging_stoploss_order)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', hanging_stoploss_order)
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
     assert trade.stoploss_order_id == 100
@@ -1096,7 +1023,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.stoploss_order_id = 100
 
     canceled_stoploss_order = MagicMock(return_value={'status': 'canceled'})
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', canceled_stoploss_order)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', canceled_stoploss_order)
     stoploss.reset_mock()
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
@@ -1122,14 +1049,14 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
         'average': 2,
         'amount': limit_buy_order['amount'],
     })
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hit)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', stoploss_order_hit)
     assert freqtrade.handle_stoploss_on_exchange(trade) is True
     assert log_has_re(r'STOP_LOSS_LIMIT is hit for Trade\(id=1, .*\)\.', caplog)
     assert trade.stoploss_order_id is None
     assert trade.is_open is False
 
     mocker.patch(
-        'freqtrade.exchange.Exchange.stoploss',
+        'freqtrade.exchange.Binance.stoploss',
         side_effect=ExchangeError()
     )
     trade.is_open = True
@@ -1141,9 +1068,9 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     # It should try to add stoploss order
     trade.stoploss_order_id = 100
     stoploss.reset_mock()
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order',
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order',
                  side_effect=InvalidOrderException())
-    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
     freqtrade.handle_stoploss_on_exchange(trade)
     assert stoploss.call_count == 1
 
@@ -1153,7 +1080,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.is_open = False
     stoploss.reset_mock()
     mocker.patch('freqtrade.exchange.Exchange.fetch_order')
-    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
     assert stoploss.call_count == 0
 
@@ -1173,6 +1100,9 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
         buy=MagicMock(return_value={'id': limit_buy_order['id']}),
         sell=MagicMock(return_value={'id': limit_sell_order['id']}),
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         fetch_stoploss_order=MagicMock(return_value={'status': 'canceled', 'id': 100}),
         stoploss=MagicMock(side_effect=ExchangeError()),
     )
@@ -1207,6 +1137,9 @@ def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
         buy=MagicMock(return_value=limit_buy_order_open),
         sell=sell_mock,
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         fetch_order=MagicMock(return_value={'status': 'canceled'}),
         stoploss=MagicMock(side_effect=InvalidOrderException()),
     )
@@ -1252,6 +1185,9 @@ def test_create_stoploss_order_insufficient_funds(mocker, default_conf, caplog,
         sell=sell_mock,
         get_fee=fee,
         fetch_order=MagicMock(return_value={'status': 'canceled'}),
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         stoploss=MagicMock(side_effect=InsufficientFundsError()),
     )
     patch_get_signal(freqtrade)
@@ -1289,6 +1225,9 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
         buy=MagicMock(return_value={'id': limit_buy_order['id']}),
         sell=MagicMock(return_value={'id': limit_sell_order['id']}),
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         stoploss=stoploss,
         stoploss_adjust=MagicMock(return_value=True),
     )
@@ -1329,7 +1268,7 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
         }
     })
 
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', stoploss_order_hanging)
 
     # stoploss initially at 5%
     assert freqtrade.handle_trade(trade) is False
@@ -1344,8 +1283,8 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
 
     cancel_order_mock = MagicMock()
     stoploss_order_mock = MagicMock(return_value={'id': 13434334})
-    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', cancel_order_mock)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss_order_mock)
+    mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock)
 
     # stoploss should not be updated as the interval is 60 seconds
     assert freqtrade.handle_trade(trade) is False
@@ -1392,6 +1331,9 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
         buy=MagicMock(return_value={'id': limit_buy_order['id']}),
         sell=MagicMock(return_value={'id': limit_sell_order['id']}),
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         stoploss=stoploss,
         stoploss_adjust=MagicMock(return_value=True),
     )
@@ -1427,9 +1369,10 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
             'stopPrice': '0.1'
         }
     }
-    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
+    mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order',
                  side_effect=InvalidOrderException())
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order',
+                 return_value=stoploss_order_hanging)
     freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
     assert log_has_re(r"Could not cancel stoploss order abcd for pair ETH/BTC.*", caplog)
 
@@ -1438,8 +1381,8 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
 
     # Fail creating stoploss order
     caplog.clear()
-    cancel_mock = mocker.patch("freqtrade.exchange.Exchange.cancel_stoploss_order", MagicMock())
-    mocker.patch("freqtrade.exchange.Exchange.stoploss", side_effect=ExchangeError())
+    cancel_mock = mocker.patch("freqtrade.exchange.Binance.cancel_stoploss_order", MagicMock())
+    mocker.patch("freqtrade.exchange.Binance.stoploss", side_effect=ExchangeError())
     freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
     assert cancel_mock.call_count == 1
     assert log_has_re(r"Could not create trailing stoploss order for pair ETH/BTC\..*", caplog)
@@ -1461,6 +1404,9 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
         buy=MagicMock(return_value={'id': limit_buy_order['id']}),
         sell=MagicMock(return_value={'id': limit_sell_order['id']}),
         get_fee=fee,
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
         stoploss=stoploss,
         stoploss_adjust=MagicMock(return_value=True),
     )
@@ -1501,7 +1447,7 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
         }
     })
 
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', stoploss_order_hanging)
 
     assert freqtrade.handle_trade(trade) is False
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
@@ -1515,8 +1461,8 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
 
     cancel_order_mock = MagicMock()
     stoploss_order_mock = MagicMock(return_value={'id': 13434334})
-    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', cancel_order_mock)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss_order_mock)
+    mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock)
 
     # stoploss should not be updated as the interval is 60 seconds
     assert freqtrade.handle_trade(trade) is False
@@ -1747,6 +1693,7 @@ def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> No
         open_rate=0.01,
         open_date=arrow.utcnow().datetime,
         amount=11,
+        exchange="binance",
     )
     assert not freqtrade.update_trade_state(trade, None)
     assert log_has_re(r'Orderid for trade .* is empty.', caplog)
@@ -1779,7 +1726,6 @@ def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_
     # fetch_order should not be called!!
     mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
     patch_exchange(mocker)
-    Trade.session = MagicMock()
     amount = sum(x['amount'] for x in trades_for_order)
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     trade = Trade(
@@ -1805,7 +1751,6 @@ def test_update_trade_state_withorderdict_rounding_fee(default_conf, trades_for_
     # fetch_order should not be called!!
     mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
     patch_exchange(mocker)
-    Trade.session = MagicMock()
     amount = sum(x['amount'] for x in trades_for_order)
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     trade = Trade(
@@ -1868,7 +1813,6 @@ def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_orde
     mocker.patch('freqtrade.wallets.Wallets.update', wallet_mock)
 
     patch_exchange(mocker)
-    Trade.session = MagicMock()
     amount = limit_sell_order["amount"]
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     wallet_mock.reset_mock()
@@ -2016,7 +1960,7 @@ def test_handle_trade_roi(default_conf, ticker, limit_buy_order_open,
     # if ROI is reached we must sell
     patch_get_signal(freqtrade, value=(False, True))
     assert freqtrade.handle_trade(trade)
-    assert log_has("ETH/BTC - Required profit reached. sell_flag=True, sell_type=SellType.ROI",
+    assert log_has("ETH/BTC - Required profit reached. sell_type=SellType.ROI",
                    caplog)
 
 
@@ -2045,7 +1989,7 @@ def test_handle_trade_use_sell_signal(
 
     patch_get_signal(freqtrade, value=(False, True))
     assert freqtrade.handle_trade(trade)
-    assert log_has("ETH/BTC - Sell signal received. sell_flag=True, sell_type=SellType.SELL_SIGNAL",
+    assert log_has("ETH/BTC - Sell signal received. sell_type=SellType.SELL_SIGNAL",
                    caplog)
 
 
@@ -2110,7 +2054,7 @@ def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_or
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     # Ensure default is to return empty (so not mocked yet)
     freqtrade.check_handle_timedout()
@@ -2161,7 +2105,7 @@ def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, op
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     freqtrade.strategy.check_buy_timeout = MagicMock(return_value=False)
     # check it does cancel buy orders over the time limit
@@ -2191,7 +2135,7 @@ def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, o
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
     freqtrade.check_handle_timedout()
@@ -2218,7 +2162,7 @@ def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_ord
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
     freqtrade.check_handle_timedout()
@@ -2248,7 +2192,7 @@ def test_check_handle_timedout_sell_usercustom(default_conf, ticker, limit_sell_
     open_trade.close_profit_abs = 0.001
     open_trade.is_open = False
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
     # Ensure default is false
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
@@ -2296,7 +2240,7 @@ def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old,
     open_trade.close_profit_abs = 0.001
     open_trade.is_open = False
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     freqtrade.strategy.check_sell_timeout = MagicMock(return_value=False)
     # check it does cancel sell orders over the time limit
@@ -2327,7 +2271,7 @@ def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old,
     open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
     open_trade.is_open = False
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     # check it does cancel sell orders over the time limit
     freqtrade.check_handle_timedout()
@@ -2353,13 +2297,13 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
     # note this is for a partially-complete buy order
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
+    assert rpc_mock.call_count == 2
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     assert len(trades) == 1
     assert trades[0].amount == 23.0
@@ -2386,7 +2330,7 @@ def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, cap
 
     open_trade.fee_open = fee()
     open_trade.fee_close = fee()
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
     # cancelling a half-filled order should update the amount to the bought amount
     # and apply fees if necessary.
     freqtrade.check_handle_timedout()
@@ -2394,7 +2338,7 @@ def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, cap
     assert log_has_re(r"Applying fee on amount for Trade.*", caplog)
 
     assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
+    assert rpc_mock.call_count == 2
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     assert len(trades) == 1
     # Verify that trade has been updated
@@ -2426,7 +2370,7 @@ def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade,
 
     open_trade.fee_open = fee()
     open_trade.fee_close = fee()
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
     # cancelling a half-filled order should update the amount to the bought amount
     # and apply fees if necessary.
     freqtrade.check_handle_timedout()
@@ -2434,7 +2378,7 @@ def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade,
     assert log_has_re(r"Could not update trade amount: .*", caplog)
 
     assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
+    assert rpc_mock.call_count == 2
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     assert len(trades) == 1
     # Verify that trade has been updated
@@ -2463,7 +2407,7 @@ def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocke
     )
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session.add(open_trade)
+    Trade.query.session.add(open_trade)
 
     freqtrade.check_handle_timedout()
     assert log_has_re(r"Cannot query order for Trade\(id=1, pair=ETH/BTC, amount=90.99181073, "
@@ -2486,15 +2430,23 @@ def test_handle_cancel_buy(mocker, caplog, default_conf, limit_buy_order) -> Non
     freqtrade = FreqtradeBot(default_conf)
     freqtrade._notify_buy_cancel = MagicMock()
 
-    Trade.session = MagicMock()
     trade = MagicMock()
-    trade.pair = 'LTC/ETH'
+    trade.pair = 'LTC/USDT'
+    trade.open_rate = 200
     limit_buy_order['filled'] = 0.0
     limit_buy_order['status'] = 'open'
     reason = CANCEL_REASON['TIMEOUT']
     assert freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
     assert cancel_order_mock.call_count == 1
 
+    cancel_order_mock.reset_mock()
+    caplog.clear()
+    limit_buy_order['filled'] = 0.01
+    assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert cancel_order_mock.call_count == 0
+    assert log_has_re("Order .* for .* not cancelled, as the filled amount.* unsellable.*", caplog)
+
+    caplog.clear()
     cancel_order_mock.reset_mock()
     limit_buy_order['filled'] = 2
     assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
@@ -2520,7 +2472,6 @@ def test_handle_cancel_buy_exchanges(mocker, caplog, default_conf,
     nofiy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot._notify_buy_cancel')
     freqtrade = FreqtradeBot(default_conf)
 
-    Trade.session = MagicMock()
     reason = CANCEL_REASON['TIMEOUT']
     trade = MagicMock()
     trade.pair = 'LTC/ETH'
@@ -2549,9 +2500,9 @@ def test_handle_cancel_buy_corder_empty(mocker, default_conf, limit_buy_order,
     freqtrade = FreqtradeBot(default_conf)
     freqtrade._notify_buy_cancel = MagicMock()
 
-    Trade.session = MagicMock()
     trade = MagicMock()
-    trade.pair = 'LTC/ETH'
+    trade.pair = 'LTC/USDT'
+    trade.open_rate = 200
     limit_buy_order['filled'] = 0.0
     limit_buy_order['status'] = 'open'
     reason = CANCEL_REASON['TIMEOUT']
@@ -2652,22 +2603,24 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> N
         fetch_ticker=ticker_sell_up
     )
     # Prevented sell ...
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
+                           sell_reason=SellCheckTuple(sell_type=SellType.ROI))
     assert rpc_mock.call_count == 0
     assert freqtrade.strategy.confirm_trade_exit.call_count == 1
 
     # Repatch with true
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
 
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
+                           sell_reason=SellCheckTuple(sell_type=SellType.ROI))
     assert freqtrade.strategy.confirm_trade_exit.call_count == 1
 
     assert rpc_mock.call_count == 1
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
         'trade_id': 1,
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.SELL,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'profit',
         'limit': 1.172e-05,
@@ -2682,6 +2635,7 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> N
         'sell_reason': SellType.ROI.value,
         'open_date': ANY,
         'close_date': ANY,
+        'close_rate': ANY,
     } == last_msg
 
 
@@ -2710,14 +2664,14 @@ def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker)
     )
 
     freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
+                           sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
 
     assert rpc_mock.call_count == 2
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'loss',
         'limit': 1.044e-05,
@@ -2732,6 +2686,7 @@ def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker)
         'sell_reason': SellType.STOP_LOSS.value,
         'open_date': ANY,
         'close_date': ANY,
+        'close_rate': ANY,
     } == last_msg
 
 
@@ -2766,15 +2721,15 @@ def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fe
 
     trade.stop_loss = 0.00001099 * 0.99
     freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
+                           sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
 
     assert rpc_mock.call_count == 2
     last_msg = rpc_mock.call_args_list[-1][0][0]
 
     assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'loss',
         'limit': 1.08801e-05,
@@ -2789,7 +2744,7 @@ def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fe
         'sell_reason': SellType.STOP_LOSS.value,
         'open_date': ANY,
         'close_date': ANY,
-
+        'close_rate': ANY,
     } == last_msg
 
 
@@ -2812,14 +2767,13 @@ def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee, c
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    Trade.session = MagicMock()
     PairLock.session = MagicMock()
 
     freqtrade.config['dry_run'] = False
     trade.stoploss_order_id = "abcd"
 
     freqtrade.execute_sell(trade=trade, limit=1234,
-                           sell_reason=SellType.STOP_LOSS)
+                           sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
     assert sellmock.call_count == 1
     assert log_has('Could not cancel stoploss order abcd', caplog)
 
@@ -2869,12 +2823,12 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticke
     )
 
     freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
-                           sell_reason=SellType.SELL_SIGNAL)
+                           sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
 
     trade = Trade.query.first()
     assert trade
     assert cancel_order.call_count == 1
-    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_count == 3
 
 
 def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf, ticker, fee,
@@ -2942,7 +2896,10 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf, ticker, f
     assert trade.stoploss_order_id is None
     assert trade.is_open is False
     assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
-    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_count == 3
+    assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.BUY
+    assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.BUY_FILL
+    assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.SELL
 
 
 def test_execute_sell_market_order(default_conf, ticker, fee,
@@ -2971,17 +2928,18 @@ def test_execute_sell_market_order(default_conf, ticker, fee,
     )
     freqtrade.config['order_types']['sell'] = 'market'
 
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
+                           sell_reason=SellCheckTuple(sell_type=SellType.ROI))
 
     assert not trade.is_open
     assert trade.close_profit == 0.0620716
 
-    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_count == 3
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
+        'type': RPCMessageType.SELL,
         'trade_id': 1,
-        'exchange': 'Bittrex',
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'profit',
         'limit': 1.172e-05,
@@ -2996,6 +2954,7 @@ def test_execute_sell_market_order(default_conf, ticker, fee,
         'sell_reason': SellType.ROI.value,
         'open_date': ANY,
         'close_date': ANY,
+        'close_rate': ANY,
 
     } == last_msg
 
@@ -3024,8 +2983,9 @@ def test_execute_sell_insufficient_funds_error(default_conf, ticker, fee,
         fetch_ticker=ticker_sell_up
     )
 
+    sell_reason = SellCheckTuple(sell_type=SellType.ROI)
     assert not freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
-                                      sell_reason=SellType.ROI)
+                                      sell_reason=sell_reason)
     assert mock_insuf.call_count == 1
 
 
@@ -3118,7 +3078,7 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, limit_buy_o
     freqtrade = FreqtradeBot(default_conf)
     patch_get_signal(freqtrade)
     freqtrade.strategy.stop_loss_reached = MagicMock(return_value=SellCheckTuple(
-        sell_flag=False, sell_type=SellType.NONE))
+        sell_type=SellType.NONE))
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
@@ -3267,7 +3227,7 @@ def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplo
     )
 
     freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
+                           sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
     trade.close(ticker_sell_down()['bid'])
     assert freqtrade.strategy.is_pair_locked(trade.pair)
 
@@ -3964,7 +3924,7 @@ def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order_open,
     assert trade.stake_amount == 0.001
     assert trade.is_open
     assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
+    assert trade.exchange == 'binance'
 
     assert len(Trade.query.all()) == 1
 
@@ -4420,9 +4380,9 @@ def test_reupdate_buy_order_fees(mocker, default_conf, fee, caplog):
         is_open=True,
         amount=20,
         open_rate=0.01,
-        exchange='bittrex',
+        exchange='binance',
     )
-    Trade.session.add(trade)
+    Trade.query.session.add(trade)
 
     freqtrade.reupdate_buy_order_fees(trade)
     assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
diff --git a/tests/test_integration.py b/tests/test_integration.py
index 8e3bd251a..33b3e1140 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -51,8 +51,8 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
         side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
     # Sell 3rd trade (not called for the first trade)
     should_sell_mock = MagicMock(side_effect=[
-        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
-        SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
+        SellCheckTuple(sell_type=SellType.NONE),
+        SellCheckTuple(sell_type=SellType.SELL_SIGNAL)]
     )
     cancel_order_mock = MagicMock()
     mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
@@ -63,7 +63,7 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
         amount_to_precision=lambda s, x, y: y,
         price_to_precision=lambda s, x, y: y,
         fetch_stoploss_order=stoploss_order_mock,
-        cancel_stoploss_order=cancel_order_mock,
+        cancel_stoploss_order_with_result=cancel_order_mock,
     )
 
     mocker.patch.multiple(
@@ -89,7 +89,6 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
     freqtrade.strategy.confirm_trade_entry.reset_mock()
     assert freqtrade.strategy.confirm_trade_exit.call_count == 0
     wallets_mock.reset_mock()
-    Trade.session = MagicMock()
 
     trades = Trade.query.all()
     # Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
@@ -157,11 +156,11 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
         _notify_sell=MagicMock(),
     )
     should_sell_mock = MagicMock(side_effect=[
-        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
-        SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL),
-        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
-        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
-        SellCheckTuple(sell_flag=None, sell_type=SellType.NONE)]
+        SellCheckTuple(sell_type=SellType.NONE),
+        SellCheckTuple(sell_type=SellType.SELL_SIGNAL),
+        SellCheckTuple(sell_type=SellType.NONE),
+        SellCheckTuple(sell_type=SellType.NONE),
+        SellCheckTuple(sell_type=SellType.NONE)]
     )
     mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
 
@@ -178,8 +177,7 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
 
     trades = Trade.query.all()
     assert len(trades) == 4
-    assert freqtrade.wallets.get_trade_stake_amount(
-        'XRP/BTC', freqtrade.get_free_open_trades()) == result1
+    assert freqtrade.wallets.get_trade_stake_amount('XRP/BTC') == result1
 
     rpc._rpc_forcebuy('TKN/BTC', None)
 
@@ -200,8 +198,7 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
     # One trade sold
     assert len(trades) == 4
     # stake-amount should now be reduced, since one trade was sold at a loss.
-    assert freqtrade.wallets.get_trade_stake_amount(
-        'XRP/BTC', freqtrade.get_free_open_trades()) < result1
+    assert freqtrade.wallets.get_trade_stake_amount('XRP/BTC') < result1
     # Validate that balance of sold trade is not in dry-run balances anymore.
     bals2 = freqtrade.wallets.get_all_balances()
     assert bals != bals2
diff --git a/tests/test_main.py b/tests/test_main.py
index 70632aeaa..d52dcaf79 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -118,7 +118,7 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
 def test_main_operational_exception1(mocker, default_conf, caplog) -> None:
     patch_exchange(mocker)
     mocker.patch(
-        'freqtrade.commands.list_commands.available_exchanges',
+        'freqtrade.commands.list_commands.validate_exchanges',
         MagicMock(side_effect=ValueError('Oh snap!'))
     )
     patched_configuration_load_config_file(mocker, default_conf)
@@ -132,7 +132,7 @@ def test_main_operational_exception1(mocker, default_conf, caplog) -> None:
     assert log_has('Fatal exception!', caplog)
     assert not log_has_re(r'SIGINT.*', caplog)
     mocker.patch(
-        'freqtrade.commands.list_commands.available_exchanges',
+        'freqtrade.commands.list_commands.validate_exchanges',
         MagicMock(side_effect=KeyboardInterrupt)
     )
     with pytest.raises(SystemExit):
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 6a388327c..669f220bb 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -7,7 +7,7 @@ from unittest.mock import MagicMock
 
 import arrow
 import pytest
-from sqlalchemy import create_engine
+from sqlalchemy import create_engine, inspect
 
 from freqtrade import constants
 from freqtrade.exceptions import DependencyException, OperationalException
@@ -18,8 +18,8 @@ from tests.conftest import create_mock_trades, log_has, log_has_re
 def test_init_create_session(default_conf):
     # Check if init create a session
     init_db(default_conf['db_url'], default_conf['dry_run'])
-    assert hasattr(Trade, 'session')
-    assert 'scoped_session' in type(Trade.session).__name__
+    assert hasattr(Trade, '_session')
+    assert 'scoped_session' in type(Trade._session).__name__
 
 
 def test_init_custom_db_url(default_conf, tmpdir):
@@ -64,7 +64,7 @@ def test_init_dryrun_db(default_conf, tmpdir):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
+def test_update_with_binance(limit_buy_order, limit_sell_order, fee, caplog):
     """
     On this test we will buy and sell a crypto currency.
 
@@ -102,7 +102,7 @@ def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
         open_date=arrow.utcnow().datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
     assert trade.open_order_id is None
     assert trade.close_profit is None
@@ -142,7 +142,7 @@ def test_update_market_order(market_buy_order, market_sell_order, fee, caplog):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_date=arrow.utcnow().datetime,
-        exchange='bittrex',
+        exchange='binance',
     )
 
     trade.open_order_id = 'something'
@@ -177,7 +177,7 @@ def test_calc_open_close_trade_price(limit_buy_order, limit_sell_order, fee):
         amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
 
     trade.open_order_id = 'something'
@@ -205,7 +205,7 @@ def test_trade_close(limit_buy_order, limit_sell_order, fee):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_date=arrow.Arrow(2020, 2, 1, 15, 5, 1).datetime,
-        exchange='bittrex',
+        exchange='binance',
     )
     assert trade.close_profit is None
     assert trade.close_date is None
@@ -233,7 +233,7 @@ def test_calc_close_trade_price_exception(limit_buy_order, fee):
         amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
 
     trade.open_order_id = 'something'
@@ -250,7 +250,7 @@ def test_update_open_order(limit_buy_order):
         amount=5,
         fee_open=0.1,
         fee_close=0.1,
-        exchange='bittrex',
+        exchange='binance',
     )
 
     assert trade.open_order_id is None
@@ -274,7 +274,7 @@ def test_update_invalid_order(limit_buy_order):
         open_rate=0.001,
         fee_open=0.1,
         fee_close=0.1,
-        exchange='bittrex',
+        exchange='binance',
     )
     limit_buy_order['type'] = 'invalid'
     with pytest.raises(ValueError, match=r'Unknown order type'):
@@ -290,7 +290,7 @@ def test_calc_open_trade_value(limit_buy_order, fee):
         open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
     trade.open_order_id = 'open_trade'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
@@ -311,7 +311,7 @@ def test_calc_close_trade_price(limit_buy_order, limit_sell_order, fee):
         open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
     trade.open_order_id = 'close_trade'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
@@ -336,7 +336,7 @@ def test_calc_profit(limit_buy_order, limit_sell_order, fee):
         open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
     trade.open_order_id = 'something'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
@@ -370,7 +370,7 @@ def test_calc_profit_ratio(limit_buy_order, limit_sell_order, fee):
         open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
     )
     trade.open_order_id = 'something'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
@@ -388,6 +388,9 @@ def test_calc_profit_ratio(limit_buy_order, limit_sell_order, fee):
     # Test with a custom fee rate on the close trade
     assert trade.calc_profit_ratio(fee=0.003) == 0.06147824
 
+    trade.open_trade_value = 0.0
+    assert trade.calc_profit_ratio(fee=0.003) == 0.0
+
 
 @pytest.mark.usefixtures("init_persistence")
 def test_clean_dry_run_db(default_conf, fee):
@@ -400,10 +403,10 @@ def test_clean_dry_run_db(default_conf, fee):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_rate=0.123,
-        exchange='bittrex',
+        exchange='binance',
         open_order_id='dry_run_buy_12345'
     )
-    Trade.session.add(trade)
+    Trade.query.session.add(trade)
 
     trade = Trade(
         pair='ETC/BTC',
@@ -412,10 +415,10 @@ def test_clean_dry_run_db(default_conf, fee):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_rate=0.123,
-        exchange='bittrex',
+        exchange='binance',
         open_order_id='dry_run_sell_12345'
     )
-    Trade.session.add(trade)
+    Trade.query.session.add(trade)
 
     # Simulate prod entry
     trade = Trade(
@@ -425,10 +428,10 @@ def test_clean_dry_run_db(default_conf, fee):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_rate=0.123,
-        exchange='bittrex',
+        exchange='binance',
         open_order_id='prod_buy_12345'
     )
-    Trade.session.add(trade)
+    Trade.query.session.add(trade)
 
     # We have 3 entries: 2 dry_run, 1 prod
     assert len(Trade.query.filter(Trade.open_order_id.isnot(None)).all()) == 3
@@ -463,7 +466,7 @@ def test_migrate_old(mocker, default_conf, fee):
                                 );"""
     insert_table_old = """INSERT INTO trades (exchange, pair, is_open, open_order_id, fee,
                           open_rate, stake_amount, amount, open_date)
-                          VALUES ('BITTREX', 'BTC_ETC', 1, '123123', {fee},
+                          VALUES ('binance', 'BTC_ETC', 1, '123123', {fee},
                           0.00258580, {stake}, {amount},
                           '2017-11-28 12:44:24.000000')
                           """.format(fee=fee.return_value,
@@ -472,7 +475,7 @@ def test_migrate_old(mocker, default_conf, fee):
                                      )
     insert_table_old2 = """INSERT INTO trades (exchange, pair, is_open, fee,
                           open_rate, close_rate, stake_amount, amount, open_date)
-                          VALUES ('BITTREX', 'BTC_ETC', 0, {fee},
+                          VALUES ('binance', 'BTC_ETC', 0, {fee},
                           0.00258580, 0.00268580, {stake}, {amount},
                           '2017-11-28 12:44:24.000000')
                           """.format(fee=fee.return_value,
@@ -500,7 +503,7 @@ def test_migrate_old(mocker, default_conf, fee):
     assert trade.amount_requested == amount
     assert trade.stake_amount == default_conf.get("stake_amount")
     assert trade.pair == "ETC/BTC"
-    assert trade.exchange == "bittrex"
+    assert trade.exchange == "binance"
     assert trade.max_rate == 0.0
     assert trade.stop_loss == 0.0
     assert trade.initial_stop_loss == 0.0
@@ -624,6 +627,63 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert orders[1].order_id == 'stop_order_id222'
     assert orders[1].ft_order_side == 'stoploss'
 
+    caplog.clear()
+    # Drop latest column
+    engine.execute("alter table orders rename to orders_bak")
+    inspector = inspect(engine)
+
+    for index in inspector.get_indexes('orders_bak'):
+        engine.execute(f"drop index {index['name']}")
+    # Recreate table
+    engine.execute("""
+        CREATE TABLE orders (
+            id INTEGER NOT NULL,
+            ft_trade_id INTEGER,
+            ft_order_side VARCHAR NOT NULL,
+            ft_pair VARCHAR NOT NULL,
+            ft_is_open BOOLEAN NOT NULL,
+            order_id VARCHAR NOT NULL,
+            status VARCHAR,
+            symbol VARCHAR,
+            order_type VARCHAR,
+            side VARCHAR,
+            price FLOAT,
+            amount FLOAT,
+            filled FLOAT,
+            remaining FLOAT,
+            cost FLOAT,
+            order_date DATETIME,
+            order_filled_date DATETIME,
+            order_update_date DATETIME,
+            PRIMARY KEY (id),
+            CONSTRAINT _order_pair_order_id UNIQUE (ft_pair, order_id),
+            FOREIGN KEY(ft_trade_id) REFERENCES trades (id)
+        )
+        """)
+
+    engine.execute("""
+    insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
+        symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
+        order_filled_date, order_update_date)
+        select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
+        symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
+        order_filled_date, order_update_date
+        from orders_bak
+    """)
+
+    # Run init to test migration
+    init_db(default_conf['db_url'], default_conf['dry_run'])
+
+    assert log_has("trying orders_bak1", caplog)
+
+    orders = Order.query.all()
+    assert len(orders) == 2
+    assert orders[0].order_id == 'buy_order'
+    assert orders[0].ft_order_side == 'buy'
+
+    assert orders[1].order_id == 'stop_order_id222'
+    assert orders[1].ft_order_side == 'stoploss'
+
 
 def test_migrate_mid_state(mocker, default_conf, fee, caplog):
     """
@@ -694,7 +754,7 @@ def test_adjust_stop_loss(fee):
         amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
         max_rate=1,
     )
@@ -746,7 +806,7 @@ def test_adjust_min_max_rates(fee):
         amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
     )
 
@@ -771,11 +831,16 @@ def test_adjust_min_max_rates(fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_get_open(fee):
+@pytest.mark.parametrize('use_db', [True, False])
+def test_get_open(fee, use_db):
+    Trade.use_db = use_db
+    Trade.reset_trades()
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, use_db)
     assert len(Trade.get_open_trades()) == 4
 
+    Trade.use_db = True
+
 
 @pytest.mark.usefixtures("init_persistence")
 def test_to_json(default_conf, fee):
@@ -790,7 +855,7 @@ def test_to_json(default_conf, fee):
         fee_close=fee.return_value,
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         open_rate=0.123,
-        exchange='bittrex',
+        exchange='binance',
         open_order_id='dry_run_buy_12345'
     )
     result = trade.to_json()
@@ -799,11 +864,9 @@ def test_to_json(default_conf, fee):
     assert result == {'trade_id': None,
                       'pair': 'ETH/BTC',
                       'is_open': None,
-                      'open_date_hum': '2 hours ago',
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
                       'open_timestamp': int(trade.open_date.timestamp() * 1000),
                       'open_order_id': 'dry_run_buy_12345',
-                      'close_date_hum': None,
                       'close_date': None,
                       'close_timestamp': None,
                       'open_rate': 0.123,
@@ -843,7 +906,7 @@ def test_to_json(default_conf, fee):
                       'max_rate': None,
                       'strategy': None,
                       'timeframe': None,
-                      'exchange': 'bittrex',
+                      'exchange': 'binance',
                       }
 
     # Simulate dry_run entries
@@ -858,17 +921,15 @@ def test_to_json(default_conf, fee):
         close_date=arrow.utcnow().shift(hours=-1).datetime,
         open_rate=0.123,
         close_rate=0.125,
-        exchange='bittrex',
+        exchange='binance',
     )
     result = trade.to_json()
     assert isinstance(result, dict)
 
     assert result == {'trade_id': None,
                       'pair': 'XRP/BTC',
-                      'open_date_hum': '2 hours ago',
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
                       'open_timestamp': int(trade.open_date.timestamp() * 1000),
-                      'close_date_hum': 'an hour ago',
                       'close_date': trade.close_date.strftime("%Y-%m-%d %H:%M:%S"),
                       'close_timestamp': int(trade.close_date.timestamp() * 1000),
                       'open_rate': 0.123,
@@ -910,7 +971,7 @@ def test_to_json(default_conf, fee):
                       'sell_order_status': None,
                       'strategy': None,
                       'timeframe': None,
-                      'exchange': 'bittrex',
+                      'exchange': 'binance',
                       }
 
 
@@ -923,7 +984,7 @@ def test_stoploss_reinitialization(default_conf, fee):
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         amount=10,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
         max_rate=1,
     )
@@ -933,7 +994,7 @@ def test_stoploss_reinitialization(default_conf, fee):
     assert trade.stop_loss_pct == -0.05
     assert trade.initial_stop_loss == 0.95
     assert trade.initial_stop_loss_pct == -0.05
-    Trade.session.add(trade)
+    Trade.query.session.add(trade)
 
     # Lower stoploss
     Trade.stoploss_reinitialization(0.06)
@@ -982,7 +1043,7 @@ def test_update_fee(fee):
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         amount=10,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
         max_rate=1,
     )
@@ -1021,7 +1082,7 @@ def test_fee_updated(fee):
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         amount=10,
         fee_close=fee.return_value,
-        exchange='bittrex',
+        exchange='binance',
         open_rate=1,
         max_rate=1,
     )
@@ -1084,6 +1145,13 @@ def test_get_trades_proxy(fee, use_db):
     Trade.use_db = True
 
 
+def test_get_trades_backtest():
+    Trade.use_db = False
+    with pytest.raises(NotImplementedError, match=r"`Trade.get_trades\(\)` not .*"):
+        Trade.get_trades([])
+    Trade.use_db = True
+
+
 @pytest.mark.usefixtures("init_persistence")
 def test_get_overall_performance(fee):
 
@@ -1217,11 +1285,24 @@ def test_Trade_object_idem():
     trade = vars(Trade)
     localtrade = vars(LocalTrade)
 
+    excludes = (
+        'delete',
+        'session',
+        'query',
+        'open_date',
+        'get_best_pair',
+        'get_overall_performance',
+        'total_open_trades_stakes',
+        'get_sold_trades_without_assigned_fees',
+        'get_open_trades_without_assigned_fees',
+        'get_open_order_trades',
+        'get_trades',
+        )
+
     # Parent (LocalTrade) should have the same attributes
     for item in trade:
         # Exclude private attributes and open_date (as it's not assigned a default)
-        if (not item.startswith('_')
-                and item not in ('delete', 'session', 'query', 'open_date')):
+        if (not item.startswith('_') and item not in excludes):
             assert item in localtrade
 
     # Fails if only a column is added without corresponding parent field
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
index 1752f9b94..a22c8c681 100644
--- a/tests/test_plotting.py
+++ b/tests/test_plotting.py
@@ -331,13 +331,13 @@ def test_generate_profit_graph(testdatadir):
 
     trades = trades[trades['pair'].isin(pairs)]
 
-    fig = generate_profit_graph(pairs, data, trades, timeframe="5m")
+    fig = generate_profit_graph(pairs, data, trades, timeframe="5m", stake_currency='BTC')
     assert isinstance(fig, go.Figure)
 
     assert fig.layout.title.text == "Freqtrade Profit plot"
     assert fig.layout.yaxis.title.text == "Price"
-    assert fig.layout.yaxis2.title.text == "Profit"
-    assert fig.layout.yaxis3.title.text == "Profit"
+    assert fig.layout.yaxis2.title.text == "Profit BTC"
+    assert fig.layout.yaxis3.title.text == "Profit BTC"
 
     figure = fig.layout.figure
     assert len(figure.data) == 5
@@ -356,7 +356,8 @@ def test_generate_profit_graph(testdatadir):
 
     with pytest.raises(OperationalException, match=r"No trades found.*"):
         # Pair cannot be empty - so it's an empty dataframe.
-        generate_profit_graph(pairs, data, trades.loc[trades['pair'].isnull()], timeframe="5m")
+        generate_profit_graph(pairs, data, trades.loc[trades['pair'].isnull()], timeframe="5m",
+                              stake_currency='BTC')
 
 
 def test_start_plot_dataframe(mocker):
diff --git a/tests/test_wallets.py b/tests/test_wallets.py
index b7aead0c4..ff303e2ec 100644
--- a/tests/test_wallets.py
+++ b/tests/test_wallets.py
@@ -1,7 +1,12 @@
 # pragma pylint: disable=missing-docstring
+from copy import deepcopy
 from unittest.mock import MagicMock
 
-from tests.conftest import get_patched_freqtradebot
+import pytest
+
+from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
+from freqtrade.exceptions import DependencyException
+from tests.conftest import get_patched_freqtradebot, patch_wallet
 
 
 def test_sync_wallet_at_boot(mocker, default_conf):
@@ -106,3 +111,62 @@ def test_sync_wallet_missing_data(mocker, default_conf):
     assert freqtrade.wallets._wallets['GAS'].used is None
     assert freqtrade.wallets._wallets['GAS'].total == 0.260739
     assert freqtrade.wallets.get_free('GAS') == 0.260739
+
+
+def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
+    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
+        freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
+
+
+@pytest.mark.parametrize("balance_ratio,result1,result2", [
+                        (1, 50, 66.66666),
+                        (0.99, 49.5, 66.0),
+                        (0.50, 25, 33.3333),
+])
+def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, result1,
+                                                 result2, limit_buy_order_open,
+                                                 fee, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee
+    )
+
+    conf = deepcopy(default_conf)
+    conf['stake_amount'] = UNLIMITED_STAKE_AMOUNT
+    conf['dry_run_wallet'] = 100
+    conf['max_open_trades'] = 2
+    conf['tradable_balance_ratio'] = balance_ratio
+
+    freqtrade = get_patched_freqtradebot(mocker, conf)
+
+    # no open trades, order amount should be 'balance / max_open_trades'
+    result = freqtrade.wallets.get_trade_stake_amount('ETH/USDT')
+    assert result == result1
+
+    # create one trade, order amount should be 'balance / (max_open_trades - num_open_trades)'
+    freqtrade.execute_buy('ETH/USDT', result)
+
+    result = freqtrade.wallets.get_trade_stake_amount('LTC/USDT')
+    assert result == result1
+
+    # create 2 trades, order amount should be None
+    freqtrade.execute_buy('LTC/BTC', result)
+
+    result = freqtrade.wallets.get_trade_stake_amount('XRP/USDT')
+    assert result == 0
+
+    freqtrade.config['max_open_trades'] = 3
+    freqtrade.config['dry_run_wallet'] = 200
+    freqtrade.wallets.start_cap = 200
+    result = freqtrade.wallets.get_trade_stake_amount('XRP/USDT')
+    assert round(result, 4) == round(result2, 4)
+
+    # set max_open_trades = None, so do not trade
+    freqtrade.config['max_open_trades'] = 0
+    result = freqtrade.wallets.get_trade_stake_amount('NEO/USDT')
+    assert result == 0
diff --git a/tests/testdata/hyperopt_results_SampleStrategy.pickle b/tests/testdata/hyperopt_results_SampleStrategy.pickle
new file mode 100644
index 000000000..2231de7bf
Binary files /dev/null and b/tests/testdata/hyperopt_results_SampleStrategy.pickle differ
diff --git a/tests/testdata/strategy_SampleStrategy.fthypt b/tests/testdata/strategy_SampleStrategy.fthypt
new file mode 100644
index 000000000..6dc2b9ab1
--- /dev/null
+++ b/tests/testdata/strategy_SampleStrategy.fthypt
@@ -0,0 +1,5 @@
+{"loss":100000,"params_dict":{"mfi-value":"20","fastd-value":"21","adx-value":"26","rsi-value":"23","mfi-enabled":true,"fastd-enabled":false,"adx-enabled":false,"rsi-enabled":true,"trigger":"sar_reversal","sell-mfi-value":"97","sell-fastd-value":"85","sell-adx-value":"55","sell-rsi-value":"76","sell-mfi-enabled":true,"sell-fastd-enabled":false,"sell-adx-enabled":true,"sell-rsi-enabled":true,"sell-trigger":"sell-bb_upper","roi_t1":"34","roi_t2":"28","roi_t3":"32","roi_p1":0.031,"roi_p2":0.033,"roi_p3":0.146,"stoploss":-0.05},"params_details":{"buy":{"mfi-value":"20","fastd-value":"21","adx-value":"26","rsi-value":"23","mfi-enabled":true,"fastd-enabled":false,"adx-enabled":false,"rsi-enabled":true,"trigger":"sar_reversal"},"sell":{"sell-mfi-value":"97","sell-fastd-value":"85","sell-adx-value":"55","sell-rsi-value":"76","sell-mfi-enabled":true,"sell-fastd-enabled":false,"sell-adx-enabled":true,"sell-rsi-enabled":true,"sell-trigger":"sell-bb_upper"},"roi":"{0: 0.21, 32: 0.064, 60: 0.031, 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