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/workflows/ci.yml b/.github/workflows/ci.yml index 3f294347a..4169661c6 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -102,7 +102,7 @@ jobs: mypy freqtrade scripts - name: Slack Notification - uses: homoluctus/slatify@v1.8.0 + uses: lazy-actions/slatify@v3.0.0 if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} @@ -148,6 +148,7 @@ jobs: - name: Installation - macOS run: | + brew update brew install hdf5 c-blosc python -m pip install --upgrade pip export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH @@ -194,7 +195,7 @@ jobs: mypy freqtrade scripts - name: Slack Notification - uses: homoluctus/slatify@v1.8.0 + uses: lazy-actions/slatify@v3.0.0 if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} @@ -257,7 +258,7 @@ jobs: mypy freqtrade scripts - name: Slack Notification - uses: homoluctus/slatify@v1.8.0 + uses: lazy-actions/slatify@v3.0.0 if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} @@ -288,7 +289,7 @@ jobs: mkdocs build - name: Slack Notification - uses: homoluctus/slatify@v1.8.0 + uses: lazy-actions/slatify@v3.0.0 if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} @@ -300,7 +301,7 @@ jobs: runs-on: ubuntu-20.04 steps: - name: Cleanup previous runs on this branch - uses: rokroskar/workflow-run-cleanup-action@v0.2.2 + uses: rokroskar/workflow-run-cleanup-action@v0.3.2 if: "!startsWith(github.ref, 'refs/tags/') && github.ref != 'refs/heads/stable' && github.repository == 'freqtrade/freqtrade'" env: GITHUB_TOKEN: "${{ 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: homoluctus/slatify@v1.8.0 - if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) + uses: lazy-actions/slatify@v3.0.0 + 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*' @@ -398,7 +408,7 @@ jobs: - name: Slack Notification - uses: homoluctus/slatify@v1.8.0 + uses: lazy-actions/slatify@v3.0.0 if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) with: type: ${{ job.status }} diff --git a/Dockerfile b/Dockerfile index 4b399174b..128d0e19c 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,14 +1,23 @@ -FROM python:3.9.2-slim-buster as base +FROM python:3.9.4-slim-buster as base # Setup env ENV LANG C.UTF-8 ENV LC_ALL C.UTF-8 ENV PYTHONDONTWRITEBYTECODE 1 ENV PYTHONFAULTHANDLER 1 -ENV PATH=/root/.local/bin:$PATH +ENV PATH=/home/ftuser/.local/bin:$PATH +ENV FT_APP_ENV="docker" # Prepare environment -RUN mkdir /freqtrade +RUN mkdir /freqtrade \ + && apt update \ + && apt install -y sudo \ + && apt-get clean \ + && useradd -u 1000 -G sudo -U -m ftuser \ + && chown ftuser:ftuser /freqtrade \ + # Allow sudoers + && echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers + WORKDIR /freqtrade # Install dependencies @@ -24,7 +33,8 @@ RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib* ENV LD_LIBRARY_PATH /usr/local/lib # Install dependencies -COPY requirements.txt requirements-hyperopt.txt /freqtrade/ +COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/ +USER ftuser RUN pip install --user --no-cache-dir numpy \ && pip install --user --no-cache-dir -r requirements-hyperopt.txt @@ -33,13 +43,13 @@ FROM base as runtime-image COPY --from=python-deps /usr/local/lib /usr/local/lib ENV LD_LIBRARY_PATH /usr/local/lib -COPY --from=python-deps /root/.local /root/.local - - +COPY --from=python-deps --chown=ftuser:ftuser /home/ftuser/.local /home/ftuser/.local +USER ftuser # Install and execute -COPY . /freqtrade/ -RUN pip install -e . --no-cache-dir \ +COPY --chown=ftuser:ftuser . /freqtrade/ + +RUN pip install -e . --user --no-cache-dir \ && mkdir /freqtrade/user_data/ \ && freqtrade install-ui diff --git a/Dockerfile.armhf b/Dockerfile.armhf index f938ec457..2b3bca042 100644 --- a/Dockerfile.armhf +++ b/Dockerfile.armhf @@ -1,19 +1,24 @@ -FROM --platform=linux/arm/v7 python:3.7.9-slim-buster as base +FROM --platform=linux/arm/v7 python:3.7.10-slim-buster as base # Setup env ENV LANG C.UTF-8 ENV LC_ALL C.UTF-8 ENV PYTHONDONTWRITEBYTECODE 1 ENV PYTHONFAULTHANDLER 1 -ENV PATH=/root/.local/bin:$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 @@ -37,11 +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 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..916f9cf17 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Freqtrade +# ![freqtrade](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) diff --git a/config_full.json.example b/config_full.json.example index 9a613c0a1..973afe2c8 100644 --- a/config_full.json.example +++ b/config_full.json.example @@ -50,6 +50,7 @@ "sell": "limit", "emergencysell": "market", "forcesell": "market", + "forcebuy": "market", "stoploss": "market", "stoploss_on_exchange": false, "stoploss_on_exchange_interval": 60 @@ -112,7 +113,7 @@ "password": "", "ccxt_config": {"enableRateLimit": true}, "ccxt_async_config": { - "enableRateLimit": false, + "enableRateLimit": true, "rateLimit": 500, "aiohttp_trust_env": false }, @@ -162,7 +163,9 @@ "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.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 d2237b3e8..c86978b80 100644 --- a/docs/advanced-hyperopt.md +++ b/docs/advanced-hyperopt.md @@ -4,34 +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 hyperop 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 ... -``` - ## 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. @@ -97,3 +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 a14c8f2e4..ee9926f32 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -15,15 +15,16 @@ 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] 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} @@ -37,6 +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). @@ -48,6 +52,9 @@ optional arguments: Enable protections for backtesting.Will slow backtesting down by a considerable amount, but will include configured protections + --dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET + Starting balance, used for backtesting / hyperopt and + dry-runs. --strategy-list STRATEGY_LIST [STRATEGY_LIST ...] Provide a space-separated list of strategies to backtest. Please note that ticker-interval needs to be @@ -91,8 +98,7 @@ Strategy arguments: ## Test your strategy with Backtesting Now you have good Buy and Sell strategies and some historic data, you want to test it against -real data. This is what we call -[backtesting](https://en.wikipedia.org/wiki/Backtesting). +real data. This is what we call [backtesting](https://en.wikipedia.org/wiki/Backtesting). Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHCLV) data from `user_data/data/` by default. If no data is available for the exchange / pair / timeframe combination, backtesting will ask you to download them first using `freqtrade download-data`. @@ -100,6 +106,8 @@ For details on downloading, please refer to the [Data Downloading](data-download The result of backtesting will confirm if your bot has better odds of making a profit than a loss. +All profit calculations include fees, and freqtrade will use the exchange's default fees for the calculation. + !!! Warning "Using dynamic pairlists for backtesting" Using dynamic pairlists is possible, however it relies on the current market conditions - which will not reflect the historic status of the pairlist. Also, when using pairlists other than StaticPairlist, reproducability of backtesting-results cannot be guaranteed. @@ -107,38 +115,56 @@ The result of backtesting will confirm if your bot has better odds of making a p To achieve reproducible results, best generate a pairlist via the [`test-pairlist`](utils.md#test-pairlist) command and use that as static pairlist. -### Run a backtesting against the currencies listed in your config file +### Starting balance -#### With 5 min candle (OHLCV) data (per default) +Backtesting will require a starting balance, which can be provided as `--dry-run-wallet ` or `--starting-balance ` command line argument, or via `dry_run_wallet` configuration setting. +This amount must be higher than `stake_amount`, otherwise the bot will not be able to simulate any trade. + +### Dynamic stake amount + +Backtesting supports [dynamic stake amount](configuration.md#dynamic-stake-amount) by configuring `stake_amount` as `"unlimited"`, which will split the starting balance into `max_open_trades` pieces. +Profits from early trades will result in subsequent higher stake amounts, resulting in compounding of profits over the backtesting period. + +### Example backtesting commands + +With 5 min candle (OHLCV) data (per default) ```bash -freqtrade backtesting +freqtrade backtesting --strategy AwesomeStrategy ``` -#### With 1 min candle (OHLCV) data +Where `--strategy AwesomeStrategy` / `-s AwesomeStrategy` refers to the class name of the strategy, which is within a python file in the `user_data/strategies` directory. + +--- + +With 1 min candle (OHLCV) data ```bash -freqtrade backtesting --timeframe 1m +freqtrade backtesting --strategy AwesomeStrategy --timeframe 1m ``` -#### Using a different on-disk historical candle (OHLCV) data source +--- + +Providing a custom starting balance of 1000 (in stake currency) + +```bash +freqtrade backtesting --strategy AwesomeStrategy --dry-run-wallet 1000 +``` + +--- + +Using a different on-disk historical candle (OHLCV) data source Assume you downloaded the history data from the Bittrex exchange and kept it in the `user_data/data/bittrex-20180101` directory. You can then use this data for backtesting as follows: ```bash -freqtrade --datadir user_data/data/bittrex-20180101 backtesting +freqtrade backtesting --strategy AwesomeStrategy --datadir user_data/data/bittrex-20180101 ``` -#### With a (custom) strategy file +--- -```bash -freqtrade backtesting -s SampleStrategy -``` - -Where `-s SampleStrategy` refers to the class name within the strategy file `sample_strategy.py` found in the `freqtrade/user_data/strategies` directory. - -#### Comparing multiple Strategies +Comparing multiple Strategies ```bash freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --timeframe 5m @@ -146,23 +172,29 @@ freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --timefram Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies. -#### Exporting trades to file +--- + +Exporting trades to file ```bash -freqtrade backtesting --export trades --config config.json --strategy SampleStrategy +freqtrade backtesting --strategy backtesting --export trades --config config.json ``` The exported trades can be used for [further analysis](#further-backtest-result-analysis), or can be used by the plotting script `plot_dataframe.py` in the scripts directory. -#### Exporting trades to file specifying a custom filename +--- + +Exporting trades to file specifying a custom filename ```bash -freqtrade backtesting --export trades --export-filename=backtest_samplestrategy.json +freqtrade backtesting --strategy backtesting --export trades --export-filename=backtest_samplestrategy.json ``` Please also read about the [strategy startup period](strategy-customization.md#strategy-startup-period). -#### Supplying custom fee value +--- + +Supplying custom fee value Sometimes your account has certain fee rebates (fee reductions starting with a certain account size or monthly volume), which are not visible to ccxt. To account for this in backtesting, you can use the `--fee` command line option to supply this value to backtesting. @@ -177,26 +209,26 @@ freqtrade backtesting --fee 0.001 !!! Note Only supply this option (or the corresponding configuration parameter) if you want to experiment with different fee values. By default, Backtesting fetches the default fee from the exchange pair/market info. -#### Running backtest with smaller testset by using timerange +--- -Use the `--timerange` argument to change how much of the testset you want to use. +Running backtest with smaller test-set by using timerange +Use the `--timerange` argument to change how much of the test-set you want to use. -For example, running backtesting with the `--timerange=20190501-` option will use all available data starting with May 1st, 2019 from your inputdata. +For example, running backtesting with the `--timerange=20190501-` option will use all available data starting with May 1st, 2019 from your input data. ```bash freqtrade backtesting --timerange=20190501- ``` -You can also specify particular dates or a range span indexed by start and stop. +You can also specify particular date ranges. The full timerange specification: -- Use tickframes till 2018/01/31: `--timerange=-20180131` -- Use tickframes since 2018/01/31: `--timerange=20180131-` -- Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301` -- Use tickframes between POSIX timestamps 1527595200 1527618600: - `--timerange=1527595200-1527618600` +- Use data until 2018/01/31: `--timerange=-20180131` +- Use data since 2018/01/31: `--timerange=20180131-` +- Use data since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301` +- Use data between POSIX / epoch timestamps 1527595200 1527618600: `--timerange=1527595200-1527618600` ## Understand the backtesting result @@ -248,19 +280,30 @@ A backtesting result will look like that: | Max open trades | 3 | | | | | Total trades | 429 | -| Total Profit % | 152.41% | +| Starting balance | 0.01000000 BTC | +| Final balance | 0.01762792 BTC | +| Absolute profit | 0.00762792 BTC | +| Total profit % | 76.2% | | Trades per day | 3.575 | +| Avg. stake amount | 0.001 BTC | +| Total trade volume | 0.429 BTC | | | | | Best Pair | LSK/BTC 26.26% | | Worst Pair | ZEC/BTC -10.18% | | Best Trade | LSK/BTC 4.25% | | Worst Trade | ZEC/BTC -10.25% | -| Best day | 25.27% | -| Worst day | -30.67% | +| Best day | 0.00076 BTC | +| Worst day | -0.00036 BTC | +| Days win/draw/lose | 12 / 82 / 25 | | Avg. Duration Winners | 4:23:00 | | Avg. Duration Loser | 6:55:00 | | | | -| Max Drawdown | 50.63% | +| Min balance | 0.00945123 BTC | +| Max balance | 0.01846651 BTC | +| Drawdown | 50.63% | +| Drawdown | 0.0015 BTC | +| Drawdown high | 0.0013 BTC | +| Drawdown low | -0.0002 BTC | | Drawdown Start | 2019-02-15 14:10:00 | | Drawdown End | 2019-04-11 18:15:00 | | Market change | -5.88% | @@ -281,9 +324,9 @@ here: 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 earned a total of `0.00762792 BTC` starting with a capital of 0.01 BTC. -The column `avg profit %` shows the average profit for all trades made while the column `cum profit %` sums up all the profits/losses. -The column `tot profit %` shows instead the total profit % in relation to allocated capital (`max_open_trades * stake_amount`). -In the above results we have `max_open_trades=2` and `stake_amount=0.005` in config so `tot_profit %` will be `(76.20/100) * (0.005 * 2) =~ 0.00762792 BTC`. +The column `Avg Profit %` shows the average profit for all trades made while the column `Cum Profit %` sums up all the profits/losses. +The column `Tot Profit %` shows instead the total profit % in relation to the starting balance. +In the above results, we have a starting balance of 0.01 BTC and an absolute profit of 0.00762792 BTC - so the `Tot Profit %` will be `(0.00762792 / 0.01) * 100 ~= 76.2%`. Your strategy performance is influenced by your buy strategy, your sell strategy, and also by the `minimal_roi` and `stop_loss` you have set. @@ -324,19 +367,30 @@ It contains some useful key metrics about performance of your strategy on backte | Max open trades | 3 | | | | | Total trades | 429 | -| Total Profit % | 152.41% | +| Starting balance | 0.01000000 BTC | +| Final balance | 0.01762792 BTC | +| Absolute profit | 0.00762792 BTC | +| Total profit % | 76.2% | | Trades per day | 3.575 | +| Avg. stake amount | 0.001 BTC | +| Total trade volume | 0.429 BTC | | | | | Best Pair | LSK/BTC 26.26% | | Worst Pair | ZEC/BTC -10.18% | | Best Trade | LSK/BTC 4.25% | | Worst Trade | ZEC/BTC -10.25% | -| Best day | 25.27% | -| Worst day | -30.67% | +| Best day | 0.00076 BTC | +| Worst day | -0.00036 BTC | +| Days win/draw/lose | 12 / 82 / 25 | | Avg. Duration Winners | 4:23:00 | | Avg. Duration Loser | 6:55:00 | | | | -| Max Drawdown | 50.63% | +| Min balance | 0.00945123 BTC | +| Max balance | 0.01846651 BTC | +| Drawdown | 50.63% | +| Drawdown | 0.0015 BTC | +| Drawdown high | 0.0013 BTC | +| Drawdown low | -0.0002 BTC | | Drawdown Start | 2019-02-15 14:10:00 | | Drawdown End | 2019-04-11 18:15:00 | | Market change | -5.88% | @@ -347,13 +401,21 @@ It contains some useful key metrics about performance of your strategy on backte - `Backtesting from` / `Backtesting to`: Backtesting range (usually defined with the `--timerange` option). - `Max open trades`: Setting of `max_open_trades` (or `--max-open-trades`) - or number of pairs in the pairlist (whatever is lower). - `Total trades`: Identical to the total trades of the backtest output table. -- `Total Profit %`: Total profit. Aligned to the `TOTAL` row's `Tot Profit %` from the first table. +- `Starting balance`: Start balance - as given by dry-run-wallet (config or command line). +- `Final balance`: Final balance - starting balance + absolute profit. +- `Absolute profit`: Profit made in stake currency. +- `Total profit %`: Total profit. Aligned to the `TOTAL` row's `Tot Profit %` from the first table. Calculated as `(End capital − Starting capital) / Starting capital`. - `Trades per day`: Total trades divided by the backtesting duration in days (this will give you information about how many trades to expect from the strategy). +- `Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount. +- `Total trade volume`: Volume generated on the exchange to reach the above profit. - `Best Pair` / `Worst Pair`: Best and worst performing pair, and it's corresponding `Cum Profit %`. -- `Best Trade` / `Worst Trade`: Biggest winning trade and biggest losing trade +- `Best Trade` / `Worst Trade`: Biggest single winning trade and biggest single losing trade. - `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. -- `Max Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced). +- `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. - `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command). - `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column. @@ -362,6 +424,7 @@ 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 @@ -418,6 +481,5 @@ Detailed output for all strategies one after the other will be available, so mak ## Next step -Great, your strategy is profitable. What if the bot can give your the -optimal parameters to use for your strategy? +Great, your strategy is profitable. What if the bot can give your the optimal parameters to use for your strategy? Your next step is to learn [how to find optimal parameters with Hyperopt](hyperopt.md) diff --git a/docs/bot-basics.md b/docs/bot-basics.md index 13694c316..943af0362 100644 --- a/docs/bot-basics.md +++ b/docs/bot-basics.md @@ -53,6 +53,7 @@ This loop will be repeated again and again until the bot is stopped. * Calls `bot_loop_start()` once. * Calculate indicators (calls `populate_indicators()` once per pair). * Calculate buy / sell signals (calls `populate_buy_trend()` and `populate_sell_trend()` once per pair) +* Confirm trade buy / sell (calls `confirm_trade_entry()` and `confirm_trade_exit()` if implemented in the strategy) * Loops per candle simulating entry and exit points. * Generate backtest report output diff --git a/docs/bot-usage.md b/docs/bot-usage.md index c7fe8634d..b65220722 100644 --- a/docs/bot-usage.md +++ b/docs/bot-usage.md @@ -56,6 +56,7 @@ optional arguments: usage: freqtrade trade [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-s NAME] [--strategy-path PATH] [--db-url PATH] [--sd-notify] [--dry-run] + [--dry-run-wallet DRY_RUN_WALLET] optional arguments: -h, --help show this help message and exit @@ -66,6 +67,9 @@ optional arguments: --sd-notify Notify systemd service manager. --dry-run Enforce dry-run for trading (removes Exchange secrets and simulates trades). + --dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET + Starting balance, used for backtesting / hyperopt and + dry-runs. Common arguments: -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). diff --git a/docs/configuration.md b/docs/configuration.md index 99a5fea04..0ade558f1 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -40,8 +40,8 @@ Mandatory parameters are marked as **Required**, which means that they are requi | Parameter | Description | |------------|-------------| | `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation which can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).
**Datatype:** Positive integer or -1. -| `stake_currency` | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy).
**Datatype:** String -| `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Positive float or `"unlimited"`. +| `stake_currency` | **Required.** Crypto-currency used for trading.
**Datatype:** String +| `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade).
**Datatype:** Positive float or `"unlimited"`. | `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade).
*Defaults to `0.99` 99%).*
**Datatype:** Positive float between `0.1` and `1.0`. | `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade).
*Defaults to `false`.*
**Datatype:** Boolean | `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade).
*Defaults to `0.5`.*
**Datatype:** Float (as ratio) @@ -49,7 +49,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `timeframe` | The timeframe (former ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** String | `fiat_display_currency` | Fiat currency used to show your profits. [More information below](#what-values-can-be-used-for-fiat_display_currency).
**Datatype:** String | `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode.
*Defaults to `true`.*
**Datatype:** Boolean -| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in the Dry Run mode.
*Defaults to `1000`.*
**Datatype:** Float +| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in Dry Run mode.
*Defaults to `1000`.*
**Datatype:** Float | `cancel_open_orders_on_exit` | Cancel open orders when the `/stop` RPC command is issued, `Ctrl+C` is pressed or the bot dies unexpectedly. When set to `true`, this allows you to use `/stop` to cancel unfilled and partially filled orders in the event of a market crash. It does not impact open positions.
*Defaults to `false`.*
**Datatype:** Boolean | `process_only_new_candles` | Enable processing of indicators only when new candles arrive. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy).
*Defaults to `false`.*
**Datatype:** Boolean | `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Dict @@ -58,15 +58,17 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-custom-positive-loss). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** Float | `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 | `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.** Set the bidding price. More information [below](#buy-price-without-orderbook-enabled). +| `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 | `bid_strategy.order_book_top` | Bot will use the top N rate in Order Book Bids to buy. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in [Order Book Bids](#buy-price-with-orderbook-enabled).
*Defaults to `1`.*
**Datatype:** Positive Integer | `bid_strategy. check_depth_of_market.enabled` | Do not buy if the difference of buy orders and sell orders is met in Order Book. [Check market depth](#check-depth-of-market).
*Defaults to `false`.*
**Datatype:** Boolean | `bid_strategy. check_depth_of_market.bids_to_ask_delta` | The difference ratio of buy orders and sell orders found in Order Book. A value below 1 means sell order size is greater, while value greater than 1 means buy order size is higher. [Check market depth](#check-depth-of-market)
*Defaults to `0`.*
**Datatype:** Float (as ratio) | `ask_strategy.price_side` | Select the side of the spread the bot should look at to get the sell rate. [More information below](#sell-price-side).
*Defaults to `ask`.*
**Datatype:** String (either `ask` or `bid`). +| `ask_strategy.bid_last_balance` | Interpolate the selling price. More information [below](#sell-price-without-orderbook-enabled). | `ask_strategy.use_order_book` | Enable selling of open trades using [Order Book Asks](#sell-price-with-orderbook-enabled).
**Datatype:** Boolean | `ask_strategy.order_book_min` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
*Defaults to `1`.*
**Datatype:** Positive Integer | `ask_strategy.order_book_max` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
*Defaults to `1`.*
**Datatype:** Positive Integer @@ -142,8 +144,6 @@ Values set in the configuration file always overwrite values set in the strategy * `process_only_new_candles` * `order_types` * `order_time_in_force` -* `stake_currency` -* `stake_amount` * `unfilledtimeout` * `disable_dataframe_checks` * `protections` @@ -157,6 +157,23 @@ Values set in the configuration file always overwrite values set in the strategy There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#available-balance) as explained below. +#### Minimum trade stake + +The minimum stake amount will depend by exchange and pair, and is usually listed in the exchange support pages. +Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.4$. + +The minimum stake amount to buy this pair is therefore `20 * 0.6 ~= 12`. +This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case. + +To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%). + +With a reserve of 5%, the minimum stake amount would be ~12.6$ (`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. + +!!! Warning + Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange. + #### Available balance By default, the bot assumes that the `complete amount - 1%` is at it's disposal, and when using [dynamic stake amount](#dynamic-stake-amount), it will split the complete balance into `max_open_trades` buckets per trade. @@ -219,11 +236,12 @@ To allow the bot to trade all the available `stake_currency` in your account (mi "tradable_balance_ratio": 0.99, ``` -!!! Note - This configuration will allow increasing / decreasing stakes depending on the performance of the bot (lower stake if bot is loosing, higher stakes if the bot has a winning record, since higher balances are available). +!!! Tip "Compounding profits" + This configuration will allow increasing / decreasing stakes depending on the performance of the bot (lower stake if bot is loosing, higher stakes if the bot has a winning record, since higher balances are available), and will result in profit compounding. !!! Note "When using Dry-Run Mode" - When using `"stake_amount" : "unlimited",` in combination with Dry-Run, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve over time. It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency. + When using `"stake_amount" : "unlimited",` in combination with Dry-Run, Backtesting or Hyperopt, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve over time. + It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency. --8<-- "includes/pricing.md" @@ -278,7 +296,7 @@ For example, if your strategy is using a 1h timeframe, and you only want to buy ### Understand order_types -The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`, `forcesell`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds. +The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`, `forcesell`, `forcebuy`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds. This allows to buy using limit orders, sell using limit-orders, and create stoplosses using market orders. It also allows to set the @@ -290,7 +308,7 @@ the buy order is fulfilled. If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and `stoploss_on_exchange`) need to be present, otherwise the bot will fail to start. -For information on (`emergencysell`,`forcesell`, `stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md) +For information on (`emergencysell`,`forcesell`, `forcebuy`, `stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md) Syntax for Strategy: @@ -299,6 +317,7 @@ order_types = { "buy": "limit", "sell": "limit", "emergencysell": "market", + "forcebuy": "market", "forcesell": "market", "stoploss": "market", "stoploss_on_exchange": False, @@ -314,6 +333,7 @@ Configuration: "buy": "limit", "sell": "limit", "emergencysell": "market", + "forcebuy": "market", "forcesell": "market", "stoploss": "market", "stoploss_on_exchange": false, @@ -415,26 +435,6 @@ This configuration enables binance, as well as rate limiting to avoid bans from Optimal settings for rate limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings. We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step. -#### Advanced Freqtrade Exchange configuration - -Advanced options can be configured using the `_ft_has_params` setting, which will override Defaults and exchange-specific behaviours. - -Available options are listed in the exchange-class as `_ft_has_default`. - -For example, to test the order type `FOK` with Kraken, and modify candle limit to 200 (so you only get 200 candles per API call): - -```json -"exchange": { - "name": "kraken", - "_ft_has_params": { - "order_time_in_force": ["gtc", "fok"], - "ohlcv_candle_limit": 200 - } -``` - -!!! Warning - Please make sure to fully understand the impacts of these settings before modifying them. - ### What values can be used for fiat_display_currency? The `fiat_display_currency` configuration parameter sets the base currency to use for the diff --git a/docs/data-download.md b/docs/data-download.md index 04f444a8b..7a78334d5 100644 --- a/docs/data-download.md +++ b/docs/data-download.md @@ -30,7 +30,7 @@ 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. @@ -48,10 +48,10 @@ 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..9096000c1 100644 --- a/docs/docker_quickstart.md +++ b/docs/docker_quickstart.md @@ -14,7 +14,7 @@ To simplify running freqtrade, please install [`docker-compose`](https://docs.do ## 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 @@ -156,8 +156,8 @@ 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 2e5bdfadd..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. @@ -118,3 +139,23 @@ Whether your exchange returns incomplete candles or not can be checked using [th Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle. However, if it is based on the need for the latest price for your strategy - then this requirement can be acquired using the [data provider](strategy-customization.md#possible-options-for-dataprovider) from within the strategy. + +### Advanced Freqtrade Exchange configuration + +Advanced options can be configured using the `_ft_has_params` setting, which will override Defaults and exchange-specific behavior. + +Available options are listed in the exchange-class as `_ft_has_default`. + +For example, to test the order type `FOK` with Kraken, and modify candle limit to 200 (so you only get 200 candles per API call): + +```json +"exchange": { + "name": "kraken", + "_ft_has_params": { + "order_time_in_force": ["gtc", "fok"], + "ohlcv_candle_limit": 200 + } +``` + +!!! Warning + Please make sure to fully understand the impacts of these settings before modifying them. 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 ec155062f..51905e616 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 +44,10 @@ 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] [-e INT] + [-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] [--random-state INT] [--min-trades INT] @@ -52,8 +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} @@ -67,6 +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 @@ -82,6 +88,9 @@ optional arguments: Enable protections for backtesting.Will slow backtesting down by a considerable amount, but will include configured protections + --dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET + Starting balance, used for backtesting / hyperopt and + dry-runs. -e INT, --epochs INT Specify number of epochs (default: 100). --spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...] Specify which parameters to hyperopt. Space-separated @@ -100,7 +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 @@ -133,47 +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 thee spaces may use, otherwise hyperopt will not work. + `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) @@ -181,31 +163,19 @@ 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 # 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 - -Let assume you want a hyperopt file `AwesomeHyperopt.py`: - -``` bash -freqtrade new-hyperopt --hyperopt AwesomeHyperopt -``` - -This command will create a new hyperopt file from a template, allowing you to get started quickly. - ### 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`. @@ -221,24 +191,46 @@ 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. +```python +from freqtrade.strategy import IntParameter, IStrategy + +class MyAwesomeStrategy(IStrategy): + # If parameter is prefixed with `buy_` or `sell_` then specifying `space` parameter is optional + # and space is inferred from parameter name. + buy_adx_min = IntParameter(0, 100, default=10) + + def populate_buy_trend(self, dataframe: 'DataFrame', metadata: dict) -> 'DataFrame': + dataframe.loc[ + ( + (dataframe['adx'] > self.buy_adx_min.value) + ), 'buy'] = 1 + return dataframe +``` #### 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. +* 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 +```python +class MyAwesomeStrategy(IStrategy): + # There is no strict parameter naming scheme. If you do not use `buy_` or `sell_` prefixes - + # please specify to which space parameter belongs using `space` parameter. Possible values: + # 'buy' or 'sell'. + adx_max = IntParameter(0, 100, default=50, space='sell') -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`. + def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + dataframe.loc[ + ( + (dataframe['adx'] < self.adx_max.value) + ), 'buy'] = 1 + return dataframe +``` ## Solving a Mystery @@ -248,65 +240,51 @@ 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: +We will start by defining hyperoptable parameters: ```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') - ] +class MyAwesomeStrategy(IStrategy): + buy_adx = IntParameter(20, 40, default=30) + buy_rsi = IntParameter(20, 40, default=30) + buy_adx_enabled = CategoricalParameter([True, False]), + buy_rsi_enabled = CategoricalParameter([True, False]), + buy_trigger = CategoricalParameter(['bb_lower', 'macd_cross_signal']), ``` -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. +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. 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) -> 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. @@ -318,6 +296,24 @@ 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. + ## 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. @@ -339,16 +335,14 @@ 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. @@ -362,30 +356,23 @@ 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. @@ -402,40 +389,9 @@ 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: ``` @@ -443,49 +399,38 @@ 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: @@ -495,11 +440,13 @@ 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: @@ -519,23 +466,26 @@ 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: @@ -545,13 +495,16 @@ 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: @@ -572,6 +525,9 @@ 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: @@ -581,11 +537,11 @@ 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: @@ -607,6 +563,49 @@ 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`. + ## 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/images/logo.png b/docs/images/logo.png index c7138e84b..8a7ffdd70 100644 Binary files a/docs/images/logo.png and b/docs/images/logo.png differ diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md index 2653406e7..85d157e75 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. @@ -164,9 +168,32 @@ 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`](#price-filter), 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": { @@ -189,6 +216,13 @@ 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/includes/pricing.md b/docs/includes/pricing.md index d8a72cc58..bdf27eb20 100644 --- a/docs/includes/pricing.md +++ b/docs/includes/pricing.md @@ -103,6 +103,10 @@ A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting When not using orderbook (`ask_strategy.use_order_book=False`), the price at the `ask_strategy.price_side` side (defaults to `"ask"`) from the ticker will be used as the sell price. +When not using orderbook (`ask_strategy.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's below the `last` traded price from the ticker. Otherwise (when the `side` price is above the `last` price), it calculates a rate between `side` and `last` price. + +The `ask_strategy.bid_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the last price and values between those interpolate between `side` and last price. + ### Market order pricing When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection. 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/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 73ae3ad29..4d7082a7f 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,3 +1,3 @@ -mkdocs-material==7.0.3 +mkdocs-material==7.1.2 mdx_truly_sane_lists==1.2 pymdown-extensions==8.1.1 diff --git a/docs/rest-api.md b/docs/rest-api.md index e2b94f080..5c25e9eeb 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -125,12 +125,14 @@ python3 scripts/rest_client.py --config rest_config.json [optional par | `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. +| `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. | `status` | Lists all open trades. | `count` | Displays number of trades used and available. | `locks` | Displays currently locked pairs. +| `delete_lock ` | Deletes (disables) the lock by id. | `profit` | Display a summary of your profit/loss from close trades and some stats about your performance. | `forcesell ` | Instantly sells the given trade (Ignoring `minimum_roi`). | `forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`). @@ -180,7 +182,12 @@ 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. + + :param lock_id: ID for the lock to delete delete_trade Delete trade from the database. @@ -202,10 +209,13 @@ forcesell :param tradeid: Id of the trade (can be received via status command) +locks + Return current 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 . @@ -225,6 +235,9 @@ pair_history performance Return the performance of the different coins. +ping + simple ping + plot_config Return plot configuration if the strategy defines one. @@ -261,6 +274,11 @@ strategy :param strategy: Strategy class name +trade + Return specific trade + + :param trade_id: Specify which trade to get. + trades Return trades history. diff --git a/docs/sandbox-testing.md b/docs/sandbox-testing.md index 9c14412de..5f572eba8 100644 --- a/docs/sandbox-testing.md +++ b/docs/sandbox-testing.md @@ -6,6 +6,10 @@ With some configuration, freqtrade (in combination with ccxt) provides access to This document is an overview to configure Freqtrade to be used with sandboxes. This can be useful to developers and trader alike. +!!! Warning + Sandboxes usually have very low volume, and either a very wide spread, or no orders available at all. + Therefore, sandboxes will usually not do a good job of showing you how a strategy would work in real trading. + ## Exchanges known to have a sandbox / testnet * [binance](https://testnet.binance.vision/) diff --git a/docs/stoploss.md b/docs/stoploss.md index 4a4391655..ae191f639 100644 --- a/docs/stoploss.md +++ b/docs/stoploss.md @@ -55,6 +55,10 @@ This same logic will reapply a stoploss order on the exchange should you cancel `forcesell` is an optional value, which defaults to the same value as `sell` and is used when sending a `/forcesell` command from Telegram or from the Rest API. +### forcebuy + +`forcebuy` is an optional value, which defaults to the same value as `buy` and is used when sending a `/forcebuy` command from Telegram or from the Rest API. + ### emergencysell `emergencysell` is an optional value, which defaults to `market` and is used when creating stop loss on exchange orders fails. diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md index dcd340fd1..96c927965 100644 --- a/docs/strategy-advanced.md +++ b/docs/strategy-advanced.md @@ -11,14 +11,73 @@ If you're just getting started, please be familiar with the methods described in !!! Tip You can get a strategy template containing all below methods by running `freqtrade new-strategy --strategy MyAwesomeStrategy --template advanced` +## Storing information + +Storing information can be accomplished by creating a new dictionary within the strategy class. + +The name of the variable can be chosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables. + +```python +class AwesomeStrategy(IStrategy): + # Create custom dictionary + custom_info = {} + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + # Check if the entry already exists + if not metadata["pair"] in self.custom_info: + # Create empty entry for this pair + self.custom_info[metadata["pair"]] = {} + + if "crosstime" in self.custom_info[metadata["pair"]]: + self.custom_info[metadata["pair"]]["crosstime"] += 1 + else: + self.custom_info[metadata["pair"]]["crosstime"] = 1 +``` + +!!! 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. + +!!! Note + If the data is pair-specific, make sure to use pair as one of the keys in the dictionary. + +*** + +### Storing custom information using DatetimeIndex from `dataframe` + +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 +import talib.abstract as ta +class AwesomeStrategy(IStrategy): + # Create custom dictionary + custom_info = {} + + 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']].set_index('date') + return dataframe +``` + +!!! 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. + +!!! Note + If the data is pair-specific, make sure to use pair as one of the keys in the dictionary. + +See `custom_stoploss` examples below on how to access the saved dataframe columns + ## Custom stoploss -A stoploss can only ever move upwards - so if you set it to an absolute profit of 2%, you can never move it below this price. -Also, the traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss. +The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss. The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object. -The method must return a stoploss value (float / number) with a relative ratio below the current price. -E.g. `current_profit = 0.05` (5% profit) - stoploss returns `0.02` - then you "locked in" a profit of 3% (`0.05 - 0.02 = 0.03`). +The method must return a stoploss value (float / number) as a percentage of the current price. +E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD. + +The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price. To simulate a regular trailing stoploss of 4% (trailing 4% behind the maximum reached price) you would use the following very simple method: @@ -87,9 +146,9 @@ class AwesomeStrategy(IStrategy): current_rate: float, current_profit: float, **kwargs) -> float: # Make sure you have the longest interval first - these conditions are evaluated from top to bottom. - if current_time - timedelta(minutes=120) > trade.open_date: + if current_time - timedelta(minutes=120) > trade.open_date_utc: return -0.05 - elif current_time - timedelta(minutes=60) > trade.open_date: + elif current_time - timedelta(minutes=60) > trade.open_date_utc: return -0.10 return 1 ``` @@ -142,24 +201,32 @@ class AwesomeStrategy(IStrategy): return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss # After reaching the desired offset, allow the stoploss to trail by half the profit - desired_stoploss = current_profit / 2 + desired_stoploss = current_profit / 2 # Use a minimum of 2.5% and a maximum of 5% return max(min(desired_stoploss, 0.05), 0.025) ``` -#### Absolute stoploss +#### Calculating stoploss relative to open price -The below example sets absolute profit levels based on the current profit. +Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price. + +The helper function [`stoploss_from_open()`](strategy-customization.md#stoploss_from_open) can be used to convert from an open price relative stop, to a current price relative stop which can be returned from `custom_stoploss()`. + +#### Stepped stoploss + +Instead of continuously trailing behind the current price, this example sets fixed stoploss price levels based on the current profit. * Use the regular stoploss until 20% profit is reached -* Once profit is > 40%, stoploss will be at 25%, locking in at least 25% of the profit. -* Once profit is > 25% - stoploss will be 15%. -* Once profit is > 20% - stoploss will be set to 7%. +* Once profit is > 20% - set stoploss to 7% above open price. +* 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 +from freqtrade.strategy import stoploss_from_open class AwesomeStrategy(IStrategy): @@ -170,15 +237,66 @@ class AwesomeStrategy(IStrategy): def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: - # Calculate as `-desired_stop_from_open + current_profit` to get the distance between current_profit and initial price + # evaluate highest to lowest, so that highest possible stop is used if current_profit > 0.40: - return (-0.25 + current_profit) - if current_profit > 0.25: - return (-0.15 + current_profit) - if current_profit > 0.20: - return (-0.07 + current_profit) + return stoploss_from_open(0.25, current_profit) + elif current_profit > 0.25: + return stoploss_from_open(0.15, current_profit) + elif current_profit > 0.20: + return stoploss_from_open(0.07, current_profit) + + # 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. + +``` python +from freqtrade.persistence import Trade +from freqtrade.state import RunMode + +class AwesomeStrategy(IStrategy): + + # ... populate_* methods + + 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] + + 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 + + return result +``` --- @@ -199,7 +317,7 @@ It applies a tight timeout for higher priced assets, while allowing more time to The function must return either `True` (cancel order) or `False` (keep order alive). ``` python -from datetime import datetime, timedelta +from datetime import datetime, timedelta, timezone from freqtrade.persistence import Trade class AwesomeStrategy(IStrategy): @@ -213,21 +331,21 @@ class AwesomeStrategy(IStrategy): } def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool: - if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5): + if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5): return True - elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3): + elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3): return True - elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24): + elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24): return True return False def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool: - if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5): + if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5): return True - elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3): + elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3): return True - elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24): + elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24): return True return False ``` diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index fdc95a3c1..256b28990 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -300,38 +300,7 @@ The metadata-dict (available for `populate_buy_trend`, `populate_sell_trend`, `p Currently this is `pair`, which can be accessed using `metadata['pair']` - and will return a pair in the format `XRP/BTC`. The Metadata-dict should not be modified and does not persist information across multiple calls. -Instead, have a look at the section [Storing information](#Storing-information) - -### Storing information - -Storing information can be accomplished by creating a new dictionary within the strategy class. - -The name of the variable can be chosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables. - -```python -class AwesomeStrategy(IStrategy): - # Create custom dictionary - cust_info = {} - - def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - # Check if the entry already exists - if not metadata["pair"] in self.cust_info: - # Create empty entry for this pair - self.cust_info[metadata["pair"]] = {} - - if "crosstime" in self.cust_info[metadata["pair"]]: - self.cust_info[metadata["pair"]]["crosstime"] += 1 - else: - self.cust_info[metadata["pair"]]["crosstime"] = 1 -``` - -!!! 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. - -!!! Note - If the data is pair-specific, make sure to use pair as one of the keys in the dictionary. - -*** +Instead, have a look at the section [Storing information](strategy-advanced.md#Storing-information) ## Additional data (informative_pairs) @@ -399,7 +368,7 @@ if self.dp: ### *current_whitelist()* -Imagine you've developed a strategy that trades the `5m` timeframe using signals generated from a `1d` timeframe on the top 10 volume pairs by volume. +Imagine you've developed a strategy that trades the `5m` timeframe using signals generated from a `1d` timeframe on the top 10 volume pairs by volume. The strategy might look something like this: @@ -418,7 +387,7 @@ This is where calling `self.dp.current_whitelist()` comes in handy. pairs = self.dp.current_whitelist() # Assign tf to each pair so they can be downloaded and cached for strategy. informative_pairs = [(pair, '1d') for pair in pairs] - return informative_pairs + return informative_pairs ``` ### *get_pair_dataframe(pair, timeframe)* @@ -467,6 +436,26 @@ if self.dp: dataframe['best_ask'] = ob['asks'][0][0] ``` +The orderbook structure is aligned with the order structure from [ccxt](https://github.com/ccxt/ccxt/wiki/Manual#order-book-structure), so the result will look as follows: + +``` js +{ + 'bids': [ + [ price, amount ], // [ float, float ] + [ price, amount ], + ... + ], + 'asks': [ + [ price, amount ], + [ price, amount ], + //... + ], + //... +} +``` + +Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using the best bid price. `ob['bids'][0][1]` would look at the amount at this orderbook position. + !!! Warning "Warning about backtesting" The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return uptodate values. @@ -583,7 +572,7 @@ All columns of the informative dataframe will be available on the returning data ``` python 'date', 'open', 'high', 'low', 'close', 'rsi' # from the original dataframe - 'date_1h', 'open_1h', 'high_1h', 'low_1h', 'close_1h', 'rsi_1h' # from the informative dataframe + 'date_1h', 'open_1h', 'high_1h', 'low_1h', 'close_1h', 'rsi_1h' # from the informative dataframe ``` ??? Example "Custom implementation" @@ -618,6 +607,43 @@ All columns of the informative dataframe will be available on the returning data *** +### *stoploss_from_open()* + +Stoploss values returned from `custom_stoploss` must specify a percentage relative to `current_rate`, but sometimes you may want to specify a stoploss relative to the open price instead. `stoploss_from_open()` is a helper function to calculate a stoploss value that can be returned from `custom_stoploss` which will be equivalent to the desired percentage above the open price. + +??? Example "Returning a stoploss relative to the open price from the custom stoploss function" + + Say the open price was $100, and `current_price` is $121 (`current_profit` will be `0.21`). + + If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100. + + + ``` python + + from datetime import datetime + from freqtrade.persistence import Trade + from freqtrade.strategy import IStrategy, stoploss_from_open + + class AwesomeStrategy(IStrategy): + + # ... populate_* methods + + use_custom_stoploss = True + + 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 + if current_profit > 0.10: + return stoploss_from_open(0.07, current_profit) + + return 1 + + ``` + + Full examples can be found in the [Custom stoploss](strategy-advanced.md#custom-stoploss) section of the Documentation. + + ## Additional data (Wallets) The strategy provides access to the `Wallets` object. This contains the current balances on the exchange. @@ -709,7 +735,7 @@ To verify if a pair is currently locked, use `self.is_pair_locked(pair)`. Locked pairs will always be rounded up to the next candle. So assuming a `5m` timeframe, a lock with `until` set to 10:18 will lock the pair until the candle from 10:15-10:20 will be finished. !!! Warning - Locking pairs is not available during backtesting. + Manually locking pairs is not available during backtesting, only locks via Protections are allowed. #### Pair locking example diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md index d4a6fb118..824cb17c7 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) @@ -146,6 +153,7 @@ official commands. You can ask at any moment for help with `/help`. | `/delete ` | Delete a specific trade from the Database. Tries to close open orders. Requires manual handling of this trade on the exchange. | `/count` | Displays number of trades used and available | `/locks` | Show currently locked pairs. +| `/unlock ` | Remove the lock for this pair (or for this lock id). | `/profit` | Display a summary of your profit/loss from close trades and some stats about your performance | `/forcesell ` | Instantly sells the given trade (Ignoring `minimum_roi`). | `/forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`). 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 5b9babccc..9d5347013 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -14,18 +14,18 @@ ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir", "user_dat ARGS_STRATEGY = ["strategy", "strategy_path"] -ARGS_TRADE = ["db_url", "sd_notify", "dry_run"] +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", + "enable_protections", "dry_run_wallet", "strategy_list", "export", "exportfilename"] ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path", "position_stacking", "use_max_market_positions", - "enable_protections", + "enable_protections", "dry_run_wallet", "epochs", "spaces", "print_all", "print_colorized", "print_json", "hyperopt_jobs", "hyperopt_random_state", "hyperopt_min_trades", 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 4704c31c3..46ceafc35 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -110,10 +110,15 @@ AVAILABLE_CLI_OPTIONS = { help='Enforce dry-run for trading (removes Exchange secrets and simulates trades).', action='store_true', ), + "dry_run_wallet": Arg( + '--dry-run-wallet', '--starting-balance', + help='Starting balance, used for backtesting / hyperopt and dry-runs.', + type=float, + ), # 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', @@ -128,7 +133,6 @@ AVAILABLE_CLI_OPTIONS = { "stake_amount": Arg( '--stake-amount', help='Override the value of the `stake_amount` configuration setting.', - type=float, ), # Backtesting "position_stacking": Arg( @@ -191,6 +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', @@ -262,7 +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: ' @@ -345,7 +350,7 @@ 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 diff --git a/freqtrade/commands/hyperopt_commands.py b/freqtrade/commands/hyperopt_commands.py index fd8f737f0..268e3eeef 100755 --- a/freqtrade/commands/hyperopt_commands.py +++ b/freqtrade/commands/hyperopt_commands.py @@ -17,7 +17,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None: """ List hyperopt epochs previously evaluated """ - from freqtrade.optimize.hyperopt import Hyperopt + from freqtrade.optimize.hyperopt_tools import HyperoptTools config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) @@ -47,7 +47,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None: config.get('hyperoptexportfilename')) # Previous evaluations - epochs = Hyperopt.load_previous_results(results_file) + epochs = HyperoptTools.load_previous_results(results_file) total_epochs = len(epochs) epochs = hyperopt_filter_epochs(epochs, filteroptions) @@ -57,18 +57,19 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None: if not export_csv: try: - print(Hyperopt.get_result_table(config, epochs, total_epochs, - not filteroptions['only_best'], print_colorized, 0)) + print(HyperoptTools.get_result_table(config, epochs, total_epochs, + not filteroptions['only_best'], + print_colorized, 0)) except KeyboardInterrupt: print('User interrupted..') if epochs and not no_details: sorted_epochs = sorted(epochs, key=itemgetter('loss')) results = sorted_epochs[0] - Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header) + HyperoptTools.print_epoch_details(results, total_epochs, print_json, no_header) if epochs and export_csv: - Hyperopt.export_csv_file( + HyperoptTools.export_csv_file( config, epochs, total_epochs, not filteroptions['only_best'], export_csv ) @@ -77,7 +78,7 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None: """ Show details of a hyperopt epoch previously evaluated """ - from freqtrade.optimize.hyperopt import Hyperopt + from freqtrade.optimize.hyperopt_tools import HyperoptTools config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) @@ -105,7 +106,7 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None: } # Previous evaluations - epochs = Hyperopt.load_previous_results(results_file) + epochs = HyperoptTools.load_previous_results(results_file) total_epochs = len(epochs) epochs = hyperopt_filter_epochs(epochs, filteroptions) @@ -124,8 +125,8 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None: if epochs: val = epochs[n] - Hyperopt.print_epoch_details(val, total_epochs, print_json, no_header, - header_str="Epoch details") + HyperoptTools.print_epoch_details(val, total_epochs, print_json, no_header, + header_str="Epoch details") def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List: 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/commands/optimize_commands.py b/freqtrade/commands/optimize_commands.py index 7411ca9c6..6323bc2b1 100644 --- a/freqtrade/commands/optimize_commands.py +++ b/freqtrade/commands/optimize_commands.py @@ -3,7 +3,8 @@ from typing import Any, Dict from freqtrade import constants from freqtrade.configuration import setup_utils_configuration -from freqtrade.exceptions import DependencyException, OperationalException +from freqtrade.exceptions import OperationalException +from freqtrade.misc import round_coin_value from freqtrade.state import RunMode @@ -22,11 +23,13 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[ RunMode.BACKTEST: 'backtesting', RunMode.HYPEROPT: 'hyperoptimization', } - if (method in no_unlimited_runmodes.keys() and - config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT): - raise DependencyException( - f'The value of `stake_amount` cannot be set as "{constants.UNLIMITED_STAKE_AMOUNT}" ' - f'for {no_unlimited_runmodes[method]}') + if method in no_unlimited_runmodes.keys(): + if (config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT + and config['stake_amount'] > config['dry_run_wallet']): + wallet = round_coin_value(config['dry_run_wallet'], config['stake_currency']) + stake = round_coin_value(config['stake_amount'], config['stake_currency']) + raise OperationalException(f"Starting balance ({wallet}) " + f"is smaller than stake_amount {stake}.") return config 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 187b2e3c7..31e38d572 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -47,6 +47,8 @@ def validate_config_schema(conf: Dict[str, Any]) -> Dict[str, Any]: conf_schema = deepcopy(constants.CONF_SCHEMA) if conf.get('runmode', RunMode.OTHER) in (RunMode.DRY_RUN, RunMode.LIVE): conf_schema['required'] = constants.SCHEMA_TRADE_REQUIRED + elif conf.get('runmode', RunMode.OTHER) in (RunMode.BACKTEST, RunMode.HYPEROPT): + conf_schema['required'] = constants.SCHEMA_BACKTEST_REQUIRED else: conf_schema['required'] = constants.SCHEMA_MINIMAL_REQUIRED try: @@ -72,6 +74,7 @@ def validate_config_consistency(conf: Dict[str, Any]) -> None: # validating trailing stoploss _validate_trailing_stoploss(conf) + _validate_price_config(conf) _validate_edge(conf) _validate_whitelist(conf) _validate_protections(conf) @@ -93,6 +96,19 @@ def _validate_unlimited_amount(conf: Dict[str, Any]) -> None: raise OperationalException("`max_open_trades` and `stake_amount` cannot both be unlimited.") +def _validate_price_config(conf: Dict[str, Any]) -> None: + """ + When using market orders, price sides must be using the "other" side of the price + """ + if (conf.get('order_types', {}).get('buy') == 'market' + and conf.get('bid_strategy', {}).get('price_side') != 'ask'): + raise OperationalException('Market buy orders require bid_strategy.price_side = "ask".') + + if (conf.get('order_types', {}).get('sell') == 'market' + and conf.get('ask_strategy', {}).get('price_side') != 'bid'): + raise OperationalException('Market sell orders require ask_strategy.price_side = "bid".') + + def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None: if conf.get('stoploss') == 0.0: @@ -133,11 +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 7bf3e6bf2..cc11f97c2 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 @@ -214,9 +214,6 @@ class Configuration: self._args_to_config( config, argname='enable_protections', logstring='Parameter --enable-protections detected, enabling Protections. ...') - # Setting max_open_trades to infinite if -1 - if config.get('max_open_trades') == -1: - config['max_open_trades'] = float('inf') if 'use_max_market_positions' in self.args and not self.args["use_max_market_positions"]: config.update({'use_max_market_positions': False}) @@ -228,11 +225,23 @@ class Configuration: 'overriding max_open_trades to: %s ...', config.get('max_open_trades')) elif config['runmode'] in NON_UTIL_MODES: logger.info('Using max_open_trades: %s ...', config.get('max_open_trades')) + # Setting max_open_trades to infinite if -1 + if config.get('max_open_trades') == -1: + config['max_open_trades'] = float('inf') + + if self.args.get('stake_amount', None): + # Convert explicitly to float to support CLI argument for both unlimited and value + try: + self.args['stake_amount'] = float(self.args['stake_amount']) + except ValueError: + pass self._args_to_config(config, argname='stake_amount', logstring='Parameter --stake-amount detected, ' 'overriding stake_amount to: {} ...') - + self._args_to_config(config, argname='dry_run_wallet', + logstring='Parameter --dry-run-wallet detected, ' + 'overriding dry_run_wallet to: {} ...') self._args_to_config(config, argname='fee', logstring='Parameter --fee detected, ' 'setting fee to: {} ...') @@ -436,6 +445,7 @@ class Configuration: """ if "pairs" in config: + config['exchange']['pair_whitelist'] = config['pairs'] return if "pairs_file" in self.args and self.args["pairs_file"]: @@ -445,9 +455,8 @@ 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']: @@ -457,7 +466,6 @@ 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 32bbd02a0..6072e296c 100644 --- a/freqtrade/configuration/timerange.py +++ b/freqtrade/configuration/timerange.py @@ -7,6 +7,8 @@ from typing import Optional import arrow +from freqtrade.exceptions import OperationalException + logger = logging.getLogger(__name__) @@ -103,5 +105,8 @@ class TimeRange: stop = int(stops) // 1000 else: stop = int(stops) + if start > stop > 0: + raise OperationalException( + f'Start date is after stop date for timerange "{text}"') return TimeRange(stype[0], stype[1], start, stop) - raise Exception('Incorrect syntax for timerange "%s"' % text) + raise OperationalException(f'Incorrect syntax for timerange "{text}"') diff --git a/freqtrade/constants.py b/freqtrade/constants.py index a0d401a13..5b95ccced 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -26,7 +26,7 @@ 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 @@ -165,12 +165,18 @@ CONF_SCHEMA = { 'type': 'object', 'properties': { 'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'ask'}, + 'bid_last_balance': { + 'type': 'number', + 'minimum': 0, + 'maximum': 1, + 'exclusiveMaximum': False, + }, 'use_order_book': {'type': 'boolean'}, 'order_book_min': {'type': 'integer', 'minimum': 1}, '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'} } }, @@ -179,6 +185,8 @@ CONF_SCHEMA = { 'properties': { 'buy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, 'sell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, + 'forcesell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, + 'forcebuy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, 'emergencysell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, 'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES}, 'stoploss_on_exchange': {'type': 'boolean'}, @@ -238,14 +246,24 @@ 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' + }, } } }, @@ -376,6 +394,16 @@ SCHEMA_TRADE_REQUIRED = [ 'dataformat_trades', ] +SCHEMA_BACKTEST_REQUIRED = [ + 'exchange', + 'max_open_trades', + 'stake_currency', + 'stake_amount', + 'dry_run_wallet', + 'dataformat_ohlcv', + 'dataformat_trades', +] + SCHEMA_MINIMAL_REQUIRED = [ 'exchange', 'dry_run', diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index 8e851a8e8..c98477f4e 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -10,7 +10,7 @@ import pandas as pd from freqtrade.constants import LAST_BT_RESULT_FN from freqtrade.misc import json_load -from freqtrade.persistence import Trade, init_db +from freqtrade.persistence import LocalTrade, Trade, init_db logger = logging.getLogger(__name__) @@ -224,7 +224,7 @@ def evaluate_result_multi(results: pd.DataFrame, timeframe: str, return df_final[df_final['open_trades'] > max_open_trades] -def trade_list_to_dataframe(trades: List[Trade]) -> pd.DataFrame: +def trade_list_to_dataframe(trades: List[LocalTrade]) -> pd.DataFrame: """ Convert list of Trade objects to pandas Dataframe :param trades: List of trade objects @@ -360,13 +360,14 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date', value_col: str = 'profit_ratio' - ) -> Tuple[float, pd.Timestamp, pd.Timestamp]: + ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]: """ Calculate max drawdown and the corresponding close dates :param trades: DataFrame containing trades (requires columns close_date and profit_ratio) :param date_col: Column in DataFrame to use for dates (defaults to 'close_date') :param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio') - :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time + :return: Tuple (float, highdate, lowdate, highvalue, lowvalue) with absolute max drawdown, + high and low time and high and low value. :raise: ValueError if trade-dataframe was found empty. """ if len(trades) == 0: @@ -382,13 +383,17 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date' raise ValueError("No losing trade, therefore no drawdown.") high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col] low_date = profit_results.loc[idxmin, date_col] - return abs(min(max_drawdown_df['drawdown'])), high_date, low_date + high_val = max_drawdown_df.loc[max_drawdown_df.iloc[:idxmin] + ['high_value'].idxmax(), 'cumulative'] + low_val = max_drawdown_df.loc[idxmin, 'cumulative'] + return abs(min(max_drawdown_df['drawdown'])), high_date, low_date, high_val, low_val -def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]: +def calculate_csum(trades: pd.DataFrame, starting_balance: float = 0) -> Tuple[float, float]: """ Calculate min/max cumsum of trades, to show if the wallet/stake amount ratio is sane :param trades: DataFrame containing trades (requires columns close_date and profit_percent) + :param starting_balance: Add starting balance to results, to show the wallets high / low points :return: Tuple (float, float) with cumsum of profit_abs :raise: ValueError if trade-dataframe was found empty. """ @@ -397,7 +402,7 @@ def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]: csum_df = pd.DataFrame() csum_df['sum'] = trades['profit_abs'].cumsum() - csum_min = csum_df['sum'].min() - csum_max = csum_df['sum'].max() + csum_min = csum_df['sum'].min() + starting_balance + csum_max = csum_df['sum'].max() + starting_balance return csum_min, csum_max diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py index d4053abaa..c9d4ef19f 100644 --- a/freqtrade/data/converter.py +++ b/freqtrade/data/converter.py @@ -110,22 +110,35 @@ 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, :] diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index a035b7c3b..b4dea0743 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -170,6 +170,6 @@ 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.") diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py index ff86e522e..d1f76c21f 100644 --- a/freqtrade/edge/edge_positioning.py +++ b/freqtrade/edge/edge_positioning.py @@ -84,9 +84,8 @@ class Edge: self.fee = self.exchange.get_fee(symbol=expand_pairlist( self.config['exchange']['pair_whitelist'], list(self.exchange.markets))[0]) - def calculate(self) -> bool: - pairs = expand_pairlist(self.config['exchange']['pair_whitelist'], - list(self.exchange.markets)) + def calculate(self, pairs: List[str]) -> bool: + heartbeat = self.edge_config.get('process_throttle_secs') if (self._last_updated > 0) and ( diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py index 15ba7b9f6..889bb49c2 100644 --- a/freqtrade/exchange/__init__.py +++ b/freqtrade/exchange/__init__.py @@ -8,10 +8,11 @@ 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.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 617cd6c26..ed7918b36 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 @@ -62,6 +64,7 @@ class Exchange: "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 +85,9 @@ 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] = {} @@ -147,6 +153,9 @@ class Exchange: """ Destructor - clean up async stuff """ + self.close() + + def close(self): logger.debug("Exchange object destroyed, closing async loop") if self._api_async and inspect.iscoroutinefunction(self._api_async.close): asyncio.get_event_loop().run_until_complete(self._api_async.close()) @@ -308,8 +317,8 @@ class Exchange: self._markets = self._api.load_markets() self._load_async_markets() self._last_markets_refresh = arrow.utcnow().int_timestamp - except ccxt.BaseError as e: - logger.warning('Unable to initialize markets. Reason: %s', e) + except ccxt.BaseError: + logger.exception('Unable to initialize markets.') def reload_markets(self) -> None: """Reload markets both sync and async if refresh interval has passed """ @@ -528,19 +537,21 @@ class Exchange: return None # reserve some percent defined in config (5% default) + stoploss - amount_reserve_percent = 1.0 - self._config.get('amount_reserve_percent', + amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent', DEFAULT_AMOUNT_RESERVE_PERCENT) - amount_reserve_percent += 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(amount_reserve_percent, 0.5) + amount_reserve_percent = max(min(amount_reserve_percent, 1.5), 1) # The value returned should satisfy both limits: for amount (base currency) and # for cost (quote, stake currency), so max() is used here. # See also #2575 at github. - return max(min_stake_amounts) / amount_reserve_percent + 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 = { @@ -614,7 +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() @@ -627,7 +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() @@ -658,8 +669,6 @@ class Exchange: @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() @@ -671,8 +680,6 @@ class Exchange: @retrier def get_balances(self) -> dict: - if self._config['dry_run']: - return {} try: balances = self._api.fetch_balance() @@ -692,9 +699,19 @@ 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. ' @@ -803,7 +820,7 @@ 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)) @@ -955,7 +972,7 @@ 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: @@ -987,7 +1004,7 @@ 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 @@ -1053,7 +1070,8 @@ class Exchange: :param order: Order dict as returned from fetch_order() :return: True if order has been cancelled without being filled, False otherwise. """ - return order.get('status') in ('closed', 'canceled') and order.get('filled') == 0.0 + return (order.get('status') in ('closed', 'canceled', 'cancelled') + and order.get('filled') == 0.0) @retrier def cancel_order(self, order_id: str, pair: str) -> Dict: @@ -1153,14 +1171,20 @@ 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: @@ -1170,7 +1194,8 @@ 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 +1253,8 @@ class Exchange: def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1, price: float = 1, taker_or_maker: str = 'maker') -> float: try: + if self._config['dry_run'] and self._config.get('fee', None) is not None: + return self._config['fee'] # validate that markets are loaded before trying to get fee if self._api.markets is None or len(self._api.markets) == 0: self._api.load_markets() @@ -1300,14 +1327,6 @@ 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) @@ -1328,7 +1347,36 @@ 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..fdfd5a674 100644 --- a/freqtrade/exchange/ftx.py +++ b/freqtrade/exchange/ftx.py @@ -53,7 +53,7 @@ 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 +63,11 @@ 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 diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py index 724b11189..786f1b592 100644 --- a/freqtrade/exchange/kraken.py +++ b/freqtrade/exchange/kraken.py @@ -92,7 +92,7 @@ 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 2f64f3dac..ad55b38f8 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -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: @@ -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) @@ -425,14 +423,15 @@ 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") ticker = self.exchange.fetch_ticker(pair) ticker_rate = ticker[bid_strategy['price_side']] if ticker['last'] and ticker_rate > ticker['last']: - balance = self.config['bid_strategy']['ask_last_balance'] + balance = bid_strategy['ask_last_balance'] ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate) used_rate = ticker_rate @@ -479,19 +478,17 @@ class FreqtradeBot(LoggingMixin): 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 @@ -520,7 +517,8 @@ class FreqtradeBot(LoggingMixin): logger.info(f"Bids to asks delta for {pair} does not satisfy condition.") return False - def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None) -> bool: + def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None, + forcebuy: bool = False) -> bool: """ Executes a limit buy for the given pair :param pair: pair for which we want to create a LIMIT_BUY @@ -548,6 +546,10 @@ class FreqtradeBot(LoggingMixin): amount = stake_amount / buy_limit_requested order_type = self.strategy.order_types['buy'] + if forcebuy: + # Forcebuy can define a different ordertype + order_type = self.strategy.order_types.get('forcebuy', order_type) + 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): @@ -616,8 +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() @@ -632,7 +634,7 @@ class FreqtradeBot(LoggingMixin): """ msg = { 'trade_id': trade.id, - 'type': RPCMessageType.BUY_NOTIFICATION, + 'type': RPCMessageType.BUY, 'exchange': self.exchange.name.capitalize(), 'pair': trade.pair, 'limit': trade.open_rate, @@ -656,7 +658,7 @@ class FreqtradeBot(LoggingMixin): 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, @@ -673,6 +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 # @@ -740,7 +757,13 @@ class FreqtradeBot(LoggingMixin): logger.warning("Sell Price at location from orderbook could not be determined.") raise PricingError from e else: - rate = self.exchange.fetch_ticker(pair)[ask_strategy['price_side']] + ticker = self.exchange.fetch_ticker(pair) + ticker_rate = ticker[ask_strategy['price_side']] + if ticker['last'] and ticker_rate < ticker['last']: + balance = ask_strategy.get('bid_last_balance', 0.0) + ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last']) + rate = ticker_rate + if rate is None: raise PricingError(f"Sell-Rate for {pair} was empty.") self._sell_rate_cache[pair] = rate @@ -932,7 +955,7 @@ class FreqtradeBot(LoggingMixin): Check and execute sell """ should_sell = self.strategy.should_sell( - trade, sell_rate, datetime.utcnow(), buy, sell, + trade, sell_rate, datetime.now(timezone.utc), buy, sell, force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0 ) @@ -1018,13 +1041,13 @@ class FreqtradeBot(LoggingMixin): was_trade_fully_canceled = False # Cancelled orders may have the status of 'canceled' or 'closed' - if order['status'] not in ('canceled', 'closed'): + if order['status'] not in ('cancelled', 'canceled', 'closed'): 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. # Simply bailing here is the only safe way - as this order will then be # handled in the next iteration. - if corder.get('status') not in ('canceled', 'closed'): + if corder.get('status') not in ('cancelled', 'canceled', 'closed'): logger.warning(f"Order {trade.open_order_id} for {trade.pair} not cancelled.") return False else: @@ -1194,7 +1217,7 @@ class FreqtradeBot(LoggingMixin): # 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 self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc), @@ -1204,19 +1227,20 @@ 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. """ 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, @@ -1225,6 +1249,7 @@ 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, @@ -1259,7 +1284,7 @@ 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, @@ -1336,9 +1361,15 @@ 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, diff --git a/freqtrade/misc.py b/freqtrade/misc.py index 7bbc24056..6508363d6 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -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) diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 25ec3299d..a1d4a2578 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -17,17 +17,18 @@ from freqtrade.data import history from freqtrade.data.btanalysis import trade_list_to_dataframe from freqtrade.data.converter import trim_dataframe from freqtrade.data.dataprovider import DataProvider -from freqtrade.exceptions import OperationalException +from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds from freqtrade.mixins import LoggingMixin from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results, store_backtest_stats) -from freqtrade.persistence import PairLocks, Trade +from freqtrade.persistence import LocalTrade, PairLocks, Trade from freqtrade.plugins.pairlistmanager import PairListManager from freqtrade.plugins.protectionmanager import ProtectionManager from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper +from freqtrade.wallets import Wallets logger = logging.getLogger(__name__) @@ -114,6 +115,8 @@ class Backtesting: 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 @@ -124,7 +127,7 @@ class Backtesting: PairLocks.use_db = True Trade.use_db = True - def _set_strategy(self, strategy): + def _set_strategy(self, strategy: IStrategy): """ Load strategy into backtesting """ @@ -171,10 +174,8 @@ class Backtesting: PairLocks.use_db = False PairLocks.timeframe = self.config['timeframe'] Trade.use_db = False - if enable_protections: - # Reset persisted data - used for protections only - PairLocks.reset_locks() - Trade.reset_trades() + PairLocks.reset_locks() + Trade.reset_trades() def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]: """ @@ -203,10 +204,10 @@ class Backtesting: # Convert from Pandas to list for performance reasons # (Looping Pandas is slow.) - data[pair] = [x for x in df_analyzed.itertuples(index=False, name=None)] + data[pair] = df_analyzed.values.tolist() return data - def _get_close_rate(self, sell_row: Tuple, trade: Trade, sell: SellCheckTuple, + def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: SellCheckTuple, trade_dur: int) -> float: """ Get close rate for backtesting result @@ -238,7 +239,7 @@ 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... @@ -246,24 +247,67 @@ class Backtesting: else: return sell_row[OPEN_IDX] - def _get_sell_trade_entry(self, trade: Trade, sell_row: Tuple) -> Optional[Trade]: + def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]: - sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], sell_row[DATE_IDX], - sell_row[BUY_IDX], sell_row[SELL_IDX], + sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], # type: ignore + sell_row[DATE_IDX], sell_row[BUY_IDX], sell_row[SELL_IDX], low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX]) + if sell.sell_flag: - trade_dur = int((sell_row[DATE_IDX] - trade.open_date).total_seconds() // 60) + trade.close_date = sell_row[DATE_IDX] + trade.sell_reason = sell.sell_type.value + 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) - trade.close_date = sell_row[DATE_IDX] - trade.sell_reason = sell.sell_type + # Confirm trade exit: + time_in_force = self.strategy.order_time_in_force['sell'] + if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)( + 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): + return None + trade.close(closerate, show_msg=False) return trade return None - def handle_left_open(self, open_trades: Dict[str, List[Trade]], - data: Dict[str, List[Tuple]]) -> List[Trade]: + def _enter_trade(self, pair: str, row: List, max_open_trades: int, + open_trade_count: int) -> Optional[LocalTrade]: + try: + stake_amount = self.wallets.get_trade_stake_amount( + pair, max_open_trades - open_trade_count, None) + except DependencyException: + return None + min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) + + order_type = self.strategy.order_types['buy'] + time_in_force = self.strategy.order_time_in_force['sell'] + # 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): + return None + + if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount): + # Enter trade + trade = LocalTrade( + pair=pair, + open_rate=row[OPEN_IDX], + open_date=row[DATE_IDX], + stake_amount=stake_amount, + amount=round(stake_amount / row[OPEN_IDX], 8), + fee_open=self.fee, + fee_close=self.fee, + is_open=True, + exchange='backtesting', + ) + return trade + return None + + def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]], + data: Dict[str, List[Tuple]]) -> List[LocalTrade]: """ Handling of left open trades at the end of backtesting """ @@ -274,13 +318,16 @@ class Backtesting: sell_row = data[pair][-1] trade.close_date = sell_row[DATE_IDX] - trade.sell_reason = SellType.FORCE_SELL + trade.sell_reason = SellType.FORCE_SELL.value trade.close(sell_row[OPEN_IDX], show_msg=False) - trade.is_open = True - trades.append(trade) + LocalTrade.close_bt_trade(trade) + # Deepcopy object to have wallets update correctly + trade1 = deepcopy(trade) + trade1.is_open = True + trades.append(trade1) return trades - def backtest(self, processed: Dict, stake_amount: float, + 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: @@ -292,7 +339,6 @@ class Backtesting: Avoid extensive logging in this method and functions it calls. :param processed: a processed dictionary with format {pair, data} - :param stake_amount: amount to use for each trade :param start_date: backtesting timerange start datetime :param end_date: backtesting timerange end datetime :param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited @@ -300,11 +346,7 @@ class Backtesting: :param enable_protections: Should protections be enabled? :return: DataFrame with trades (results of backtesting) """ - logger.debug(f"Run backtest, stake_amount: {stake_amount}, " - f"start_date: {start_date}, end_date: {end_date}, " - f"max_open_trades: {max_open_trades}, position_stacking: {position_stacking}" - ) - trades: List[Trade] = [] + trades: List[LocalTrade] = [] self.prepare_backtest(enable_protections) # Use dict of lists with data for performance @@ -315,7 +357,7 @@ class Backtesting: indexes: Dict = {} tmp = start_date + timedelta(minutes=self.timeframe_min) - open_trades: Dict[str, List] = defaultdict(list) + open_trades: Dict[str, List[LocalTrade]] = defaultdict(list) open_trade_count = 0 # Loop timerange and get candle for each pair at that point in time @@ -346,28 +388,18 @@ class Backtesting: and tmp != end_date and row[BUY_IDX] == 1 and row[SELL_IDX] != 1 and not PairLocks.is_pair_locked(pair, row[DATE_IDX])): - # Enter trade - trade = Trade( - pair=pair, - open_rate=row[OPEN_IDX], - open_date=row[DATE_IDX], - stake_amount=stake_amount, - amount=round(stake_amount / row[OPEN_IDX], 8), - fee_open=self.fee, - fee_close=self.fee, - is_open=True, - ) - # TODO: hacky workaround to avoid opening > max_open_trades - # This emulates previous behaviour - not sure if this is correct - # Prevents buying if the trade-slot was freed in this candle - open_trade_count_start += 1 - open_trade_count += 1 - # logger.debug(f"{pair} - Backtesting emulates creation of new trade: {trade}.") - open_trades[pair].append(trade) - Trade.trades.append(trade) + trade = self._enter_trade(pair, row, max_open_trades, open_trade_count_start) + if trade: + # TODO: hacky workaround to avoid opening > max_open_trades + # This emulates previous behaviour - not sure if this is correct + # Prevents buying if the trade-slot was freed in this candle + open_trade_count_start += 1 + open_trade_count += 1 + # logger.debug(f"{pair} - Emulate creation of new trade: {trade}.") + open_trades[pair].append(trade) + LocalTrade.add_bt_trade(trade) for trade in open_trades[pair]: - # since indexes has been incremented before, we need to go one step back to # also check the buying candle for sell conditions. trade_entry = self._get_sell_trade_entry(trade, row) # Sell occured @@ -375,6 +407,8 @@ class Backtesting: # logger.debug(f"{pair} - Backtesting sell {trade}") open_trade_count -= 1 open_trades[pair].remove(trade) + + LocalTrade.close_bt_trade(trade) trades.append(trade_entry) if enable_protections: self.protections.stop_per_pair(pair, row[DATE_IDX]) @@ -384,6 +418,7 @@ class Backtesting: tmp += timedelta(minutes=self.timeframe_min) trades += self.handle_left_open(open_trades, data=data) + self.wallets.update() return trade_list_to_dataframe(trades) @@ -408,7 +443,8 @@ class Backtesting: # Trim startup period from analyzed dataframe for pair, df in preprocessed.items(): - preprocessed[pair] = trim_dataframe(df, timerange) + preprocessed[pair] = trim_dataframe(df, timerange, + startup_candles=self.required_startup) min_date, max_date = history.get_timerange(preprocessed) logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' @@ -417,7 +453,6 @@ class Backtesting: # Execute backtest and store results results = self.backtest( processed=preprocessed, - stake_amount=self.config['stake_amount'], start_date=min_date.datetime, end_date=max_date.datetime, max_open_trades=max_open_trades, @@ -428,7 +463,8 @@ class Backtesting: self.all_results[self.strategy.get_strategy_name()] = { 'results': results, 'config': self.strategy.config, - 'locks': PairLocks.locks, + 'locks': PairLocks.get_all_locks(), + 'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']), 'backtest_start_time': int(backtest_start_time.timestamp()), 'backtest_end_time': int(backtest_end_time.timestamp()), } 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 eee0f13b3..d6003cf86 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -4,36 +4,32 @@ This module contains the hyperopt logic """ -import io import locale import logging import random import warnings -from collections import OrderedDict from datetime import datetime from math import ceil from operator import itemgetter from pathlib import Path -from pprint import pformat from typing import Any, Dict, List, Optional import progressbar -import rapidjson -import tabulate 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, isna, json_normalize +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.history import get_timerange -from freqtrade.exceptions import OperationalException -from freqtrade.misc import file_dump_json, plural, round_dict +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.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver from freqtrade.strategy import IStrategy @@ -66,19 +62,26 @@ class Hyperopt: hyperopt = Hyperopt(config) hyperopt.start() """ + custom_hyperopt: IHyperOpt def __init__(self, config: Dict[str, Any]) -> None: self.config = config self.backtesting = Backtesting(self.config) - self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) + if not self.config.get('hyperopt'): + self.custom_hyperopt = HyperOptAuto(self.config) + else: + self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) + 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'hyperopt_results_{time_now}.pickle') + 'hyperopt_results' / + f'strategy_{strategy}_hyperopt_results_{time_now}.pickle') self.data_pickle_file = (self.config['user_data_dir'] / 'hyperopt_results' / 'hyperopt_tickerdata.pkl') self.total_epochs = config.get('epochs', 0) @@ -166,15 +169,6 @@ class Hyperopt: file_dump_json(latest_filename, {'latest_hyperopt': str(self.results_file.name)}, log=False) - @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) - return data - def _get_params_details(self, params: Dict) -> Dict: """ Return the params for each space @@ -197,102 +191,16 @@ class Hyperopt: return result - @staticmethod - def print_epoch_details(results, total_epochs: int, print_json: bool, - no_header: bool = False, header_str: str = None) -> None: - """ - Display details of the hyperopt result - """ - params = results.get('params_details', {}) - - # Default header string - if header_str is None: - header_str = "Best result" - - if not no_header: - explanation_str = Hyperopt._format_explanation_string(results, total_epochs) - print(f"\n{header_str}:\n\n{explanation_str}\n") - - if print_json: - result_dict: Dict = {} - for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']: - Hyperopt._params_update_for_json(result_dict, params, s) - print(rapidjson.dumps(result_dict, default=str, number_mode=rapidjson.NM_NATIVE)) - - else: - Hyperopt._params_pretty_print(params, 'buy', "Buy hyperspace params:") - Hyperopt._params_pretty_print(params, 'sell', "Sell hyperspace params:") - Hyperopt._params_pretty_print(params, 'roi', "ROI table:") - Hyperopt._params_pretty_print(params, 'stoploss', "Stoploss:") - Hyperopt._params_pretty_print(params, 'trailing', "Trailing stop:") - - @staticmethod - def _params_update_for_json(result_dict, params, space: str) -> None: - if space in params: - space_params = Hyperopt._space_params(params, space) - if space in ['buy', 'sell']: - result_dict.setdefault('params', {}).update(space_params) - 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) - - # Convert keys in min_roi dict to strings because - # rapidjson cannot dump dicts with integer keys... - # OrderedDict is used to keep the numeric order of the items - # in the dict. - result_dict['minimal_roi'] = OrderedDict( - (str(k), v) for k, v in space_params.items() - ) - else: # 'stoploss', 'trailing' - result_dict.update(space_params) - - @staticmethod - def _params_pretty_print(params, space: str, header: str) -> None: - if space in params: - space_params = Hyperopt._space_params(params, space, 5) - params_result = f"\n# {header}\n" - if space == 'stoploss': - params_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) - minimal_roi_result = rapidjson.dumps( - OrderedDict( - (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}" - elif space == 'trailing': - - for k, v in space_params.items(): - params_result += f'{k} = {v}\n' - - else: - params_result += f"{space}_params = {pformat(space_params, indent=4)}" - params_result = params_result.replace("}", "\n}").replace("{", "{\n ") - - params_result = params_result.replace("\n", "\n ") - print(params_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 - - @staticmethod - def is_best_loss(results, current_best_loss: float) -> bool: - return results['loss'] < current_best_loss - def print_results(self, results) -> None: """ Log results if it is better than any previous evaluation + TODO: this should be moved to HyperoptTools too """ is_best = results['is_best'] if self.print_all or is_best: print( - self.get_result_table( + HyperoptTools.get_result_table( self.config, results, self.total_epochs, self.print_all, self.print_colorized, self.hyperopt_table_header @@ -300,164 +208,6 @@ class Hyperopt: ) self.hyperopt_table_header = 2 - @staticmethod - def _format_explanation_string(results, total_epochs) -> str: - return (("*" if results['is_initial_point'] else " ") + - f"{results['current_epoch']:5d}/{total_epochs}: " + - f"{results['results_explanation']} " + - f"Objective: {results['loss']:.5f}") - - @staticmethod - def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool, - print_colorized: bool, remove_header: int) -> str: - """ - Log result table - """ - if not results: - return '' - - tabulate.PRESERVE_WHITESPACE = True - - trials = json_normalize(results, max_level=1) - trials['Best'] = '' - if 'results_metrics.winsdrawslosses' not in trials.columns: - # Ensure compatibility with older versions of hyperopt results - trials['results_metrics.winsdrawslosses'] = 'N/A' - - 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'] - trials['is_profit'] = False - trials.loc[trials['is_initial_point'], 'Best'] = '* ' - trials.loc[trials['is_best'], 'Best'] = 'Best' - 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) - - 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, ' ') - ) - trials['Avg duration'] = trials['Avg duration'].apply( - lambda x: '{:,.1f} m'.format(x).rjust(7, ' ') 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, ' ') - ) - - 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'])), - axis=1 - ) - trials = trials.drop(columns=['Total profit']) - - if print_colorized: - for i in range(len(trials)): - if trials.loc[i]['is_profit']: - for j in range(len(trials.loc[i])-3): - trials.iat[i, j] = "{}{}{}".format(Fore.GREEN, - str(trials.loc[i][j]), Fore.RESET) - if trials.loc[i]['is_best'] and highlight_best: - for j in range(len(trials.loc[i])-3): - trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT, - str(trials.loc[i][j]), Style.RESET_ALL) - - trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit']) - if remove_header > 0: - table = tabulate.tabulate( - trials.to_dict(orient='list'), tablefmt='orgtbl', - headers='keys', stralign="right" - ) - - table = table.split("\n", remove_header)[remove_header] - elif remove_header < 0: - table = tabulate.tabulate( - trials.to_dict(orient='list'), tablefmt='psql', - headers='keys', stralign="right" - ) - table = "\n".join(table.split("\n")[0:remove_header]) - else: - table = tabulate.tabulate( - trials.to_dict(orient='list'), tablefmt='psql', - headers='keys', stralign="right" - ) - return table - - @staticmethod - def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool, - csv_file: str) -> None: - """ - Log result to csv-file - """ - if not results: - return - - # Verification for overwrite - if Path(csv_file).is_file(): - logger.error(f"CSV file already exists: {csv_file}") - return - - try: - io.open(csv_file, 'w+').close() - except IOError: - logger.error(f"Failed to create CSV file: {csv_file}") - return - - trials = json_normalize(results, max_level=1) - trials['Best'] = '' - trials['Stake currency'] = config['stake_currency'] - - base_metrics = ['Best', 'current_epoch', 'results_metrics.trade_count', - 'results_metrics.avg_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] - - base_columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Total profit', 'Stake currency', - 'Profit', 'Avg duration', 'Objective', 'is_initial_point', 'is_best'] - param_columns = list(results[0]['params_dict'].keys()) - trials.columns = base_columns + param_columns - - trials['is_profit'] = False - trials.loc[trials['is_initial_point'], 'Best'] = '*' - trials.loc[trials['is_best'], 'Best'] = 'Best' - trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best' - trials.loc[trials['Total profit'] > 0, 'is_profit'] = True - trials['Epoch'] = trials['Epoch'].astype(str) - trials['Trades'] = trials['Trades'].astype(str) - - trials['Total profit'] = trials['Total profit'].apply( - lambda x: '{:,.8f}'.format(x) if x != 0.0 else "" - ) - trials['Profit'] = trials['Profit'].apply( - lambda x: '{:,.2f}'.format(x) if not isna(x) else "" - ) - trials['Avg profit'] = trials['Avg profit'].apply( - lambda x: '{:,.2f}%'.format(x) if not isna(x) else "" - ) - trials['Avg duration'] = trials['Avg duration'].apply( - lambda x: '{:,.1f} m'.format(x) if not isna(x) else "" - ) - trials['Objective'] = trials['Objective'].apply( - lambda x: '{:,.5f}'.format(x) if x != 100000 else "" - ) - - trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit']) - trials.to_csv(csv_file, index=False, header=True, mode='w', encoding='UTF-8') - logger.info(f"CSV file created: {csv_file}") - def has_space(self, space: str) -> bool: """ Tell if the space value is contained in the configuration @@ -537,7 +287,6 @@ class Hyperopt: backtesting_results = self.backtesting.backtest( processed=processed, - stake_amount=self.config['stake_amount'], start_date=min_date.datetime, end_date=max_date.datetime, max_open_trades=self.max_open_trades, @@ -622,22 +371,6 @@ class Hyperopt: return parallel(delayed( wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked) - @staticmethod - def load_previous_results(results_file: Path) -> List: - """ - Load data for epochs from the file if we have one - """ - epochs: List = [] - if results_file.is_file() and results_file.stat().st_size > 0: - epochs = Hyperopt._read_results(results_file) - # Detection of some old format, without 'is_best' field saved - if epochs[0].get('is_best') is None: - raise OperationalException( - "The file with Hyperopt results is incompatible with this version " - "of Freqtrade and cannot be loaded.") - logger.info(f"Loaded {len(epochs)} previous evaluations from disk.") - return epochs - def _set_random_state(self, random_state: Optional[int]) -> int: return random_state or random.randint(1, 2**16 - 1) @@ -651,7 +384,8 @@ class Hyperopt: # Trim startup period from analyzed dataframe for pair, df in preprocessed.items(): - preprocessed[pair] = trim_dataframe(df, timerange) + preprocessed[pair] = trim_dataframe(df, timerange, + startup_candles=self.backtesting.required_startup) min_date, max_date = get_timerange(preprocessed) logger.info(f'Hyperopting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} ' @@ -661,7 +395,10 @@ class Hyperopt: dump(preprocessed, self.data_pickle_file) # We don't need exchange instance anymore while running hyperopt - self.backtesting.exchange = None # type: ignore + self.backtesting.exchange.close() + self.backtesting.exchange._api = None # type: ignore + 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 @@ -727,7 +464,7 @@ class Hyperopt: logger.debug(f"Optimizer epoch evaluated: {val}") - is_best = self.is_best_loss(val, self.current_best_loss) + is_best = HyperoptTools.is_best_loss(val, self.current_best_loss) # This value is assigned here and not in the optimization method # to keep proper order in the list of results. That's because # evaluations can take different time. Here they are aligned in the @@ -755,7 +492,7 @@ class Hyperopt: if self.epochs: sorted_epochs = sorted(self.epochs, key=itemgetter('loss')) best_epoch = sorted_epochs[0] - self.print_epoch_details(best_epoch, self.total_epochs, self.print_json) + HyperoptTools.print_epoch_details(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 b8c44ed59..889854cad 100644 --- a/freqtrade/optimize/hyperopt_interface.py +++ b/freqtrade/optimize/hyperopt_interface.py @@ -7,11 +7,13 @@ 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 logger = logging.getLogger(__name__) @@ -30,10 +32,11 @@ 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 + strategy: IStrategy def __init__(self, config: dict) -> None: self.config = config @@ -42,36 +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. @@ -86,8 +84,7 @@ class IHyperOpt(ABC): return roi_table - @staticmethod - def roi_space() -> List[Dimension]: + def roi_space(self) -> List[Dimension]: """ Create a ROI space. @@ -95,7 +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. """ @@ -107,7 +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: @@ -117,7 +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 = { @@ -143,7 +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'], @@ -152,19 +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. @@ -172,11 +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. """ @@ -188,8 +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. @@ -204,14 +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 new file mode 100644 index 000000000..d4c347f80 --- /dev/null +++ b/freqtrade/optimize/hyperopt_tools.py @@ -0,0 +1,294 @@ + +import io +import logging +from collections import OrderedDict +from pathlib import Path +from pprint import pformat +from typing import 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 + + +logger = logging.getLogger(__name__) + + +class HyperoptTools(): + + @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) + return data + + @staticmethod + def load_previous_results(results_file: Path) -> List: + """ + Load data for epochs from the file if we have one + """ + epochs: List = [] + if results_file.is_file() and results_file.stat().st_size > 0: + 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( + "The file with HyperoptTools results is incompatible with this version " + "of Freqtrade and cannot be loaded.") + logger.info(f"Loaded {len(epochs)} previous evaluations from disk.") + return epochs + + @staticmethod + def print_epoch_details(results, total_epochs: int, print_json: bool, + no_header: bool = False, header_str: str = None) -> None: + """ + Display details of the hyperopt result + """ + params = results.get('params_details', {}) + + # Default header string + if header_str is None: + header_str = "Best result" + + if not no_header: + explanation_str = HyperoptTools._format_explanation_string(results, total_epochs) + print(f"\n{header_str}:\n\n{explanation_str}\n") + + if print_json: + result_dict: Dict = {} + for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']: + HyperoptTools._params_update_for_json(result_dict, params, s) + 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, 'roi', "ROI table:") + HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:") + HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:") + + @staticmethod + def _params_update_for_json(result_dict, params, space: str) -> None: + if space in params: + space_params = HyperoptTools._space_params(params, space) + if space in ['buy', 'sell']: + result_dict.setdefault('params', {}).update(space_params) + 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) + + # Convert keys in min_roi dict to strings because + # rapidjson cannot dump dicts with integer keys... + # OrderedDict is used to keep the numeric order of the items + # in the dict. + result_dict['minimal_roi'] = OrderedDict( + (str(k), v) for k, v in space_params.items() + ) + else: # 'stoploss', 'trailing' + result_dict.update(space_params) + + @staticmethod + def _params_pretty_print(params, space: str, header: str) -> None: + if space in params: + space_params = HyperoptTools._space_params(params, space, 5) + params_result = f"\n# {header}\n" + if space == 'stoploss': + params_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) + minimal_roi_result = rapidjson.dumps( + OrderedDict( + (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}" + elif space == 'trailing': + + for k, v in space_params.items(): + params_result += f'{k} = {v}\n' + + else: + params_result += f"{space}_params = {pformat(space_params, indent=4)}" + params_result = params_result.replace("}", "\n}").replace("{", "{\n ") + + params_result = params_result.replace("\n", "\n ") + print(params_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 + + @staticmethod + def is_best_loss(results, current_best_loss: float) -> bool: + return results['loss'] < current_best_loss + + @staticmethod + def _format_explanation_string(results, total_epochs) -> str: + return (("*" if results['is_initial_point'] else " ") + + f"{results['current_epoch']:5d}/{total_epochs}: " + + f"{results['results_explanation']} " + + f"Objective: {results['loss']:.5f}") + + @staticmethod + def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool, + print_colorized: bool, remove_header: int) -> str: + """ + Log result table + """ + if not results: + return '' + + tabulate.PRESERVE_WHITESPACE = True + + trials = json_normalize(results, max_level=1) + trials['Best'] = '' + if 'results_metrics.winsdrawslosses' not in trials.columns: + # Ensure compatibility with older versions of hyperopt results + trials['results_metrics.winsdrawslosses'] = 'N/A' + + 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'] + trials['is_profit'] = False + trials.loc[trials['is_initial_point'], 'Best'] = '* ' + trials.loc[trials['is_best'], 'Best'] = 'Best' + 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) + + 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, ' ') + ) + trials['Avg duration'] = trials['Avg duration'].apply( + lambda x: '{:,.1f} m'.format(x).rjust(7, ' ') 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, ' ') + ) + + 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'])), + axis=1 + ) + trials = trials.drop(columns=['Total profit']) + + if print_colorized: + for i in range(len(trials)): + if trials.loc[i]['is_profit']: + for j in range(len(trials.loc[i])-3): + trials.iat[i, j] = "{}{}{}".format(Fore.GREEN, + str(trials.loc[i][j]), Fore.RESET) + if trials.loc[i]['is_best'] and highlight_best: + for j in range(len(trials.loc[i])-3): + trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT, + str(trials.loc[i][j]), Style.RESET_ALL) + + trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit']) + if remove_header > 0: + table = tabulate.tabulate( + trials.to_dict(orient='list'), tablefmt='orgtbl', + headers='keys', stralign="right" + ) + + table = table.split("\n", remove_header)[remove_header] + elif remove_header < 0: + table = tabulate.tabulate( + trials.to_dict(orient='list'), tablefmt='psql', + headers='keys', stralign="right" + ) + table = "\n".join(table.split("\n")[0:remove_header]) + else: + table = tabulate.tabulate( + trials.to_dict(orient='list'), tablefmt='psql', + headers='keys', stralign="right" + ) + return table + + @staticmethod + def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool, + csv_file: str) -> None: + """ + Log result to csv-file + """ + if not results: + return + + # Verification for overwrite + if Path(csv_file).is_file(): + logger.error(f"CSV file already exists: {csv_file}") + return + + try: + io.open(csv_file, 'w+').close() + except IOError: + logger.error(f"Failed to create CSV file: {csv_file}") + return + + trials = json_normalize(results, max_level=1) + 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'] + param_metrics = [("params_dict."+param) for param in results[0]['params_dict'].keys()] + trials = trials[base_metrics + param_metrics] + + base_columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Median profit', 'Total profit', + 'Stake currency', 'Profit', 'Avg duration', 'Objective', + 'is_initial_point', 'is_best'] + param_columns = list(results[0]['params_dict'].keys()) + trials.columns = base_columns + param_columns + + trials['is_profit'] = False + trials.loc[trials['is_initial_point'], 'Best'] = '*' + trials.loc[trials['is_best'], 'Best'] = 'Best' + trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best' + trials.loc[trials['Total profit'] > 0, 'is_profit'] = True + trials['Epoch'] = trials['Epoch'].astype(str) + trials['Trades'] = trials['Trades'].astype(str) + + trials['Total profit'] = trials['Total profit'].apply( + lambda x: '{:,.8f}'.format(x) if x != 0.0 else "" + ) + trials['Profit'] = trials['Profit'].apply( + lambda x: '{:,.2f}'.format(x) if not isna(x) else "" + ) + trials['Avg profit'] = trials['Avg profit'].apply( + lambda x: '{:,.2f}%'.format(x) if not isna(x) else "" + ) + trials['Avg duration'] = trials['Avg duration'].apply( + lambda x: '{:,.1f} m'.format(x) if not isna(x) else "" + ) + trials['Objective'] = trials['Objective'].apply( + lambda x: '{:,.5f}'.format(x) if x != 100000 else "" + ) + + trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit']) + trials.to_csv(csv_file, index=False, header=True, mode='w', encoding='UTF-8') + logger.info(f"CSV file created: {csv_file}") diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 88b2028ba..a80dc5d31 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -8,7 +8,7 @@ from numpy import int64 from pandas import DataFrame from tabulate import tabulate -from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN +from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change, calculate_max_drawdown) from freqtrade.misc import decimals_per_coin, file_dump_json, round_coin_value @@ -56,12 +56,13 @@ def _get_line_header(first_column: str, stake_currency: str) -> List[str]: 'Wins', 'Draws', 'Losses'] -def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: str) -> Dict: +def _generate_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict: """ Generate one result dict, with "first_column" as key. """ profit_sum = result['profit_ratio'].sum() - profit_total = profit_sum / max_open_trades + # (end-capital - starting capital) / starting capital + profit_total = result['profit_abs'].sum() / starting_balance return { 'key': first_column, @@ -88,13 +89,13 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: } -def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_trades: int, +def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_balance: int, results: DataFrame, skip_nan: bool = False) -> List[Dict]: """ Generates and returns a list for the given backtest data and the results dataframe :param data: Dict of containing data that was used during backtesting. :param stake_currency: stake-currency - used to correctly name headers - :param max_open_trades: Maximum allowed open trades + :param starting_balance: Starting balance :param results: Dataframe containing the backtest results :param skip_nan: Print "left open" open trades :return: List of Dicts containing the metrics per pair @@ -107,10 +108,13 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_t if skip_nan and result['profit_abs'].isnull().all(): continue - tabular_data.append(_generate_result_line(result, max_open_trades, pair)) + 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, max_open_trades, 'TOTAL')) + tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL')) return tabular_data @@ -132,7 +136,7 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List tabular_data.append( { - 'sell_reason': reason.value, + 'sell_reason': reason, 'trades': count, 'wins': len(result[result['profit_abs'] > 0]), 'draws': len(result[result['profit_abs'] == 0]), @@ -159,7 +163,7 @@ def generate_strategy_metrics(all_results: Dict) -> List[Dict]: tabular_data = [] for strategy, results in all_results.items(): tabular_data.append(_generate_result_line( - results['results'], results['config']['max_open_trades'], strategy) + results['results'], results['config']['dry_run_wallet'], strategy) ) return tabular_data @@ -195,13 +199,18 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: return { 'backtest_best_day': 0, 'backtest_worst_day': 0, + 'backtest_best_day_abs': 0, + 'backtest_worst_day_abs': 0, 'winning_days': 0, 'draw_days': 0, 'losing_days': 0, 'winner_holding_avg': timedelta(), 'loser_holding_avg': timedelta(), } - daily_profit = results.resample('1d', on='close_date')['profit_ratio'].sum() + 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) + worst_rel = min(daily_profit_rel) + best_rel = max(daily_profit_rel) worst = min(daily_profit) best = max(daily_profit) winning_days = sum(daily_profit > 0) @@ -212,8 +221,10 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: losing_trades = results.loc[results['profit_ratio'] < 0] return { - 'backtest_best_day': best, - 'backtest_worst_day': worst, + 'backtest_best_day': best_rel, + 'backtest_worst_day': worst_rel, + 'backtest_best_day_abs': best, + 'backtest_worst_day_abs': worst, 'winning_days': winning_days, 'draw_days': draw_days, 'losing_days': losing_days, @@ -246,15 +257,16 @@ def generate_backtest_stats(btdata: Dict[str, 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, - max_open_trades=max_open_trades, + 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, - max_open_trades=max_open_trades, + starting_balance=starting_balance, results=results.loc[results['is_open']], skip_nan=True) daily_stats = generate_daily_stats(results) @@ -275,8 +287,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], '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_ratio'].sum() / max_open_trades, + '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, @@ -292,6 +306,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], '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), @@ -316,17 +334,23 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], result['strategy'][strategy] = strat_stats try: - max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown( + 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) + csum_min, csum_max = calculate_csum(results, starting_balance) strat_stats.update({ 'csum_min': csum_min, 'csum_max': csum_max @@ -335,6 +359,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], 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), @@ -431,8 +458,19 @@ def text_table_add_metrics(strat_results: Dict) -> str: ('Max open trades', strat_results['max_open_trades']), ('', ''), # Empty line to improve readability ('Total trades', strat_results['total_trades']), - ('Total Profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"), + ('Starting balance', round_coin_value(strat_results['starting_balance'], + strat_results['stake_currency'])), + ('Final balance', round_coin_value(strat_results['final_balance'], + 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)}%"), ('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)}%"), @@ -442,20 +480,28 @@ def text_table_add_metrics(strat_results: Dict) -> str: ('Worst trade', f"{worst_trade['pair']} " f"{round(worst_trade['profit_ratio'] * 100, 2)}%"), - ('Best day', f"{round(strat_results['backtest_best_day'] * 100, 2)}%"), - ('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"), + ('Best day', round_coin_value(strat_results['backtest_best_day_abs'], + strat_results['stake_currency'])), + ('Worst day', round_coin_value(strat_results['backtest_worst_day_abs'], + strat_results['stake_currency'])), ('Days win/draw/lose', f"{strat_results['winning_days']} / " 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']}"), ('', ''), # Empty line to improve readability - ('Abs Profit Min', round_coin_value(strat_results['csum_min'], - strat_results['stake_currency'])), - ('Abs Profit Max', round_coin_value(strat_results['csum_max'], - strat_results['stake_currency'])), + ('Min balance', round_coin_value(strat_results['csum_min'], + strat_results['stake_currency'])), + ('Max balance', round_coin_value(strat_results['csum_max'], + strat_results['stake_currency'])), - ('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), + ('Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), + ('Drawdown', round_coin_value(strat_results['max_drawdown_abs'], + strat_results['stake_currency'])), + ('Drawdown high', round_coin_value(strat_results['max_drawdown_high'], + 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)), ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"), @@ -463,7 +509,17 @@ def text_table_add_metrics(strat_results: Dict) -> str: return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl") else: - return '' + start_balance = round_coin_value(strat_results['starting_balance'], + strat_results['stake_currency']) + stake_amount = round_coin_value( + strat_results['stake_amount'], strat_results['stake_currency'] + ) if strat_results['stake_amount'] != UNLIMITED_STAKE_AMOUNT else 'unlimited' + + message = ("No trades made. " + f"Your starting balance was {start_balance}, " + f"and your stake was {stake_amount}." + ) + return message def show_backtest_results(config: Dict, backtest_stats: Dict): 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/__init__.py b/freqtrade/persistence/__init__.py index 35f2bc406..d1fcac0ba 100644 --- a/freqtrade/persistence/__init__.py +++ b/freqtrade/persistence/__init__.py @@ -1,4 +1,5 @@ # flake8: noqa: F401 -from freqtrade.persistence.models import Order, Trade, clean_dry_run_db, cleanup_db, init_db +from freqtrade.persistence.models import (LocalTrade, Order, Trade, clean_dry_run_db, cleanup_db, + init_db) from freqtrade.persistence.pairlock_middleware import PairLocks diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py index ed976c2a9..961363b0e 100644 --- a/freqtrade/persistence/migrations.py +++ b/freqtrade/persistence/migrations.py @@ -141,7 +141,7 @@ def check_migrate(engine, decl_base, previous_tables) -> None: inspector = inspect(engine) cols = inspector.get_columns('trades') - if 'orders' not in previous_tables: + if 'orders' not in previous_tables and 'trades' in previous_tables: logger.info('Moving open orders to Orders table.') migrate_open_orders_to_trades(engine) else: diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py index dff59819c..e7fd488c7 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: @@ -163,8 +159,8 @@ 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]): @@ -199,67 +195,69 @@ class Order(_DECL_BASE): return Order.query.filter(Order.ft_is_open.is_(True)).all() -class Trade(_DECL_BASE): +class LocalTrade(): """ Trade database model. - Also handles updating and querying trades + Used in backtesting - must be aligned to Trade model! + """ - __tablename__ = 'trades' - - use_db: bool = True + use_db: bool = False # Trades container for backtesting - trades: List['Trade'] = [] + trades: List['LocalTrade'] = [] + trades_open: List['LocalTrade'] = [] + total_profit: float = 0 - id = Column(Integer, primary_key=True) + id: int = 0 - orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan") + orders: List[Order] = [] - exchange = Column(String, nullable=False) - pair = Column(String, 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_close = Column(Float, nullable=False, default=0.0) - fee_close_cost = Column(Float, nullable=True) - fee_close_currency = Column(String, nullable=True) - open_rate = Column(Float) - open_rate_requested = Column(Float) + exchange: str = '' + pair: str = '' + is_open: bool = True + fee_open: float = 0.0 + fee_open_cost: Optional[float] = None + fee_open_currency: str = '' + fee_close: float = 0.0 + fee_close_cost: Optional[float] = None + fee_close_currency: str = '' + open_rate: float = 0.0 + open_rate_requested: Optional[float] = None # open_trade_value - calculated via _calc_open_trade_value - open_trade_value = Column(Float) - close_rate = Column(Float) - close_rate_requested = Column(Float) - close_profit = Column(Float) - close_profit_abs = Column(Float) - stake_amount = Column(Float, nullable=False) - amount = Column(Float) - amount_requested = Column(Float) - open_date = Column(DateTime, nullable=False, default=datetime.utcnow) - close_date = Column(DateTime) - open_order_id = Column(String) + open_trade_value: float = 0.0 + close_rate: Optional[float] = None + close_rate_requested: Optional[float] = None + close_profit: Optional[float] = None + close_profit_abs: Optional[float] = None + stake_amount: float = 0.0 + amount: float = 0.0 + amount_requested: Optional[float] = None + open_date: datetime + close_date: Optional[datetime] = None + open_order_id: Optional[str] = None # absolute value of the stop loss - stop_loss = Column(Float, nullable=True, default=0.0) + stop_loss: float = 0.0 # percentage value of the stop loss - stop_loss_pct = Column(Float, nullable=True) + stop_loss_pct: float = 0.0 # absolute value of the initial stop loss - initial_stop_loss = Column(Float, nullable=True, default=0.0) + initial_stop_loss: float = 0.0 # percentage value of the initial stop loss - initial_stop_loss_pct = Column(Float, nullable=True) + initial_stop_loss_pct: float = 0.0 # stoploss order id which is on exchange - stoploss_order_id = Column(String, nullable=True, index=True) + stoploss_order_id: Optional[str] = None # last update time of the stoploss order on exchange - stoploss_last_update = Column(DateTime, nullable=True) + stoploss_last_update: Optional[datetime] = None # absolute value of the highest reached price - max_rate = Column(Float, nullable=True, default=0.0) + max_rate: float = 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) - timeframe = Column(Integer, nullable=True) + min_rate: float = 0.0 + sell_reason: str = '' + sell_order_status: str = '' + strategy: str = '' + timeframe: Optional[int] = None def __init__(self, **kwargs): - super().__init__(**kwargs) + for key in kwargs: + setattr(self, key, kwargs[key]) self.recalc_open_trade_value() def __repr__(self): @@ -268,6 +266,14 @@ class Trade(_DECL_BASE): return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, ' f'open_rate={self.open_rate:.8f}, open_since={open_since})') + @property + def open_date_utc(self): + return self.open_date.replace(tzinfo=timezone.utc) + + @property + def close_date_utc(self): + return self.close_date.replace(tzinfo=timezone.utc) + def to_json(self) -> Dict[str, Any]: return { 'trade_id': self.id, @@ -287,15 +293,12 @@ class Trade(_DECL_BASE): '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( @@ -306,9 +309,9 @@ class Trade(_DECL_BASE): 'close_profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None, 'close_profit_abs': self.close_profit_abs, # Deprecated - 'trade_duration_s': (int((self.close_date - self.open_date).total_seconds()) + 'trade_duration_s': (int((self.close_date_utc - self.open_date_utc).total_seconds()) if self.close_date else None), - 'trade_duration': (int((self.close_date - self.open_date).total_seconds() // 60) + 'trade_duration': (int((self.close_date_utc - self.open_date_utc).total_seconds() // 60) if self.close_date else None), 'profit_ratio': self.close_profit, @@ -341,8 +344,9 @@ class Trade(_DECL_BASE): """ Resets all trades. Only active for backtesting mode. """ - if not Trade.use_db: - Trade.trades = [] + LocalTrade.trades = [] + LocalTrade.trades_open = [] + LocalTrade.total_profit = 0 def adjust_min_max_rates(self, current_price: float) -> None: """ @@ -410,8 +414,8 @@ class Trade(_DECL_BASE): if order_type in ('market', 'limit') and order['side'] == 'buy': # Update open rate and actual amount - self.open_rate = Decimal(safe_value_fallback(order, 'average', 'price')) - self.amount = Decimal(safe_value_fallback(order, 'filled', 'amount')) + self.open_rate = float(safe_value_fallback(order, 'average', 'price')) + self.amount = float(safe_value_fallback(order, 'filled', 'amount')) self.recalc_open_trade_value() if self.is_open: logger.info(f'{order_type.upper()}_BUY has been fulfilled for {self}.') @@ -425,7 +429,7 @@ class Trade(_DECL_BASE): self.close_rate_requested = self.stop_loss if self.is_open: logger.info(f'{order_type.upper()} is hit for {self}.') - self.close(order['average']) + self.close(safe_value_fallback(order, 'average', 'price')) else: raise ValueError(f'Unknown order type: {order_type}') cleanup_db() @@ -435,7 +439,7 @@ class Trade(_DECL_BASE): Sets close_rate to the given rate, calculates total profit and marks trade as closed """ - self.close_rate = Decimal(rate) + self.close_rate = rate self.close_profit = self.calc_profit_ratio() self.close_profit_abs = self.calc_profit() self.close_date = self.close_date or datetime.utcnow() @@ -480,14 +484,6 @@ class Trade(_DECL_BASE): def update_order(self, order: Dict) -> None: Order.update_orders(self.orders, order) - def delete(self) -> None: - - for order in self.orders: - Order.session.delete(order) - - Trade.session.delete(self) - Trade.session.flush() - def _calc_open_trade_value(self) -> float: """ Calculate the open_rate including open_fee. @@ -517,7 +513,7 @@ class Trade(_DECL_BASE): if rate is None and not self.close_rate: return 0.0 - sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate) + sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate) # type: ignore fees = sell_trade * Decimal(fee or self.fee_close) return float(sell_trade - fees) @@ -551,6 +547,8 @@ class Trade(_DECL_BASE): 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}") @@ -589,7 +587,7 @@ class Trade(_DECL_BASE): @staticmethod def get_trades_proxy(*, pair: str = None, is_open: bool = None, open_date: datetime = None, close_date: datetime = None, - ) -> List['Trade']: + ) -> List['LocalTrade']: """ Helper function to query Trades. Returns a List of trades, filtered on the parameters given. @@ -598,30 +596,40 @@ class Trade(_DECL_BASE): :return: unsorted List[Trade] """ - if Trade.use_db: - trade_filter = [] - if pair: - trade_filter.append(Trade.pair == pair) - if open_date: - trade_filter.append(Trade.open_date > open_date) - if close_date: - trade_filter.append(Trade.close_date > close_date) - if is_open is not None: - trade_filter.append(Trade.is_open.is_(is_open)) - return Trade.get_trades(trade_filter).all() + + # Offline mode - without database + if is_open is not None: + if is_open: + sel_trades = LocalTrade.trades_open + else: + sel_trades = LocalTrade.trades + else: - # Offline mode - without database - sel_trades = [trade for trade in Trade.trades] - if pair: - sel_trades = [trade for trade in sel_trades if trade.pair == pair] - if open_date: - sel_trades = [trade for trade in sel_trades if trade.open_date > open_date] - if close_date: - sel_trades = [trade for trade in sel_trades if trade.close_date - and trade.close_date > close_date] - if is_open is not None: - sel_trades = [trade for trade in sel_trades if trade.is_open == is_open] - return sel_trades + # Not used during backtesting, but might be used by a strategy + sel_trades = list(LocalTrade.trades + LocalTrade.trades_open) + + if pair: + sel_trades = [trade for trade in sel_trades if trade.pair == pair] + if open_date: + sel_trades = [trade for trade in sel_trades if trade.open_date > open_date] + if close_date: + sel_trades = [trade for trade in sel_trades if trade.close_date + and trade.close_date > close_date] + + return sel_trades + + @staticmethod + def close_bt_trade(trade): + LocalTrade.trades_open.remove(trade) + LocalTrade.trades.append(trade) + LocalTrade.total_profit += trade.close_profit_abs + + @staticmethod + def add_bt_trade(trade): + if trade.is_open: + LocalTrade.trades_open.append(trade) + else: + LocalTrade.trades.append(trade) @staticmethod def get_open_trades() -> List[Any]: @@ -663,9 +671,12 @@ class Trade(_DECL_BASE): Calculates total invested amount in open trades in stake currency """ - total_open_stake_amount = Trade.session.query(func.sum(Trade.stake_amount))\ - .filter(Trade.is_open.is_(True))\ - .scalar() + 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 Trade.get_trades_proxy(is_open=True)) return total_open_stake_amount or 0 @staticmethod @@ -673,7 +684,7 @@ class Trade(_DECL_BASE): """ Returns List of dicts containing all Trades, including profit and trade count """ - pair_rates = Trade.session.query( + pair_rates = Trade.query.with_entities( Trade.pair, func.sum(Trade.close_profit).label('profit_sum'), func.count(Trade.pair).label('count') @@ -696,7 +707,7 @@ class Trade(_DECL_BASE): Get best pair with closed trade. :returns: Tuple containing (pair, profit_sum) """ - best_pair = Trade.session.query( + 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) \ @@ -723,6 +734,108 @@ class Trade(_DECL_BASE): logger.info(f"New stoploss: {trade.stop_loss}.") +class Trade(_DECL_BASE, LocalTrade): + """ + Trade database model. + Also handles updating and querying trades + + Note: Fields must be aligned with LocalTrade class + """ + __tablename__ = 'trades' + + use_db: bool = True + + id = Column(Integer, primary_key=True) + + orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan") + + exchange = Column(String, nullable=False) + pair = Column(String, 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_close = Column(Float, nullable=False, default=0.0) + fee_close_cost = Column(Float, nullable=True) + fee_close_currency = Column(String, nullable=True) + open_rate = Column(Float) + open_rate_requested = Column(Float) + # open_trade_value - calculated via _calc_open_trade_value + open_trade_value = Column(Float) + close_rate = Column(Float) + close_rate_requested = Column(Float) + close_profit = Column(Float) + close_profit_abs = Column(Float) + stake_amount = Column(Float, nullable=False) + amount = Column(Float) + amount_requested = Column(Float) + open_date = Column(DateTime, nullable=False, default=datetime.utcnow) + close_date = Column(DateTime) + open_order_id = Column(String) + # absolute value of the stop loss + stop_loss = Column(Float, nullable=True, default=0.0) + # percentage value of the stop loss + stop_loss_pct = Column(Float, nullable=True) + # absolute value of the initial stop loss + initial_stop_loss = Column(Float, nullable=True, default=0.0) + # 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) + # 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) + timeframe = Column(Integer, nullable=True) + + def __init__(self, **kwargs): + super().__init__(**kwargs) + self.recalc_open_trade_value() + + def delete(self) -> None: + + for order in self.orders: + Order.query.session.delete(order) + + 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. + 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. + + :return: unsorted List[Trade] + """ + if Trade.use_db: + trade_filter = [] + if pair: + trade_filter.append(Trade.pair == pair) + if open_date: + trade_filter.append(Trade.open_date > open_date) + if close_date: + trade_filter.append(Trade.close_date > close_date) + if is_open is not None: + trade_filter.append(Trade.is_open.is_(is_open)) + return Trade.get_trades(trade_filter).all() + else: + return LocalTrade.get_trades_proxy( + pair=pair, is_open=is_open, + open_date=open_date, + close_date=close_date + ) + + class PairLock(_DECL_BASE): """ Pair Locks database model. @@ -765,6 +878,7 @@ class PairLock(_DECL_BASE): def to_json(self) -> Dict[str, Any]: return { + 'id': self.id, 'pair': self.pair, 'lock_time': self.lock_time.strftime(DATETIME_PRINT_FORMAT), 'lock_timestamp': int(self.lock_time.replace(tzinfo=timezone.utc).timestamp() * 1000), diff --git a/freqtrade/persistence/pairlock_middleware.py b/freqtrade/persistence/pairlock_middleware.py index 8644146d8..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: @@ -123,3 +123,11 @@ class PairLocks(): now = datetime.now(timezone.utc) return len(PairLocks.get_pair_locks(pair, now)) > 0 or PairLocks.is_global_lock(now) + + @staticmethod + def get_all_locks() -> List[PairLock]: + + if PairLocks.use_db: + return PairLock.query.all() + else: + return PairLocks.locks diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py index 4325e537e..682c2b018 100644 --- a/freqtrade/plot/plotting.py +++ b/freqtrade/plot/plotting.py @@ -145,7 +145,7 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame, Add scatter points indicating max drawdown """ try: - max_drawdown, highdate, lowdate = calculate_max_drawdown(trades) + max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades) drawdown = go.Scatter( x=[highdate, lowdate], diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py index 184feff9e..c4a9c3e40 100644 --- a/freqtrade/plugins/pairlist/IPairList.py +++ b/freqtrade/plugins/pairlist/IPairList.py @@ -85,7 +85,7 @@ class IPairList(LoggingMixin, ABC): 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..73a9436fa 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: """ diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py index 6558f196f..a0579b196 100644 --- a/freqtrade/plugins/pairlist/PriceFilter.py +++ b/freqtrade/plugins/pairlist/PriceFilter.py @@ -64,7 +64,7 @@ class PriceFilter(IPairList): :param ticker: ticker dict as returned from ccxt.load_markets() :return: True if the pair can stay, false if it should be removed """ - if ticker['last'] is None or ticker['last'] == 0: + if ticker.get('last', None) is None or ticker.get('last') == 0: self.log_once(f"Removed {pair} from whitelist, because " "ticker['last'] is empty (Usually no trade in the last 24h).", logger.info) diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py index c5ced48c9..13d30fc47 100644 --- a/freqtrade/plugins/pairlist/StaticPairList.py +++ b/freqtrade/plugins/pairlist/StaticPairList.py @@ -46,7 +46,7 @@ class StaticPairList(IPairList): """ 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..400b1577d --- /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.load_markets() + :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..e85fb1805 100644 --- a/freqtrade/plugins/pairlist/VolumePairList.py +++ b/freqtrade/plugins/pairlist/VolumePairList.py @@ -67,7 +67,7 @@ class VolumePairList(IPairList): """ 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 diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py index db51a9c77..6565e92c1 100644 --- a/freqtrade/plugins/pairlist/rangestabilityfilter.py +++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py @@ -28,7 +28,7 @@ class RangeStabilityFilter(IPairList): self._min_rate_of_change = pairlistconfig.get('min_rate_of_change', 0.01) self._refresh_period = pairlistconfig.get('refresh_period', 1440) - self._pair_cache: TTLCache = TTLCache(maxsize=100, ttl=self._refresh_period) + self._pair_cache: TTLCache = TTLCache(maxsize=1000, ttl=self._refresh_period) if self._days < 1: raise OperationalException("RangeStabilityFilter requires lookback_days to be >= 1") @@ -87,8 +87,9 @@ class RangeStabilityFilter(IPairList): :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/protections/cooldown_period.py b/freqtrade/plugins/protections/cooldown_period.py index 2d7d7b4c7..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 @@ -44,7 +40,8 @@ class CooldownPeriod(IProtection): trades = Trade.get_trades_proxy(pair=pair, is_open=False, close_date=look_back_until) if trades: # Get latest trade - trade = sorted(trades, key=lambda t: t.close_date)[-1] + # Ignore type error as we know we only get closed trades. + trade = sorted(trades, key=lambda t: t.close_date)[-1] # type: ignore self.log_once(f"Cooldown for {pair} for {self.stop_duration_str}.", logger.info) until = self.calculate_lock_end([trade], self._stop_duration) diff --git a/freqtrade/plugins/protections/iprotection.py b/freqtrade/plugins/protections/iprotection.py index 684bf6cd3..d034beefc 100644 --- a/freqtrade/plugins/protections/iprotection.py +++ b/freqtrade/plugins/protections/iprotection.py @@ -7,7 +7,7 @@ from typing import Any, Dict, List, Optional, Tuple from freqtrade.exchange import timeframe_to_minutes from freqtrade.misc import plural from freqtrade.mixins import LoggingMixin -from freqtrade.persistence import Trade +from freqtrade.persistence import LocalTrade logger = logging.getLogger(__name__) @@ -93,11 +93,11 @@ class IProtection(LoggingMixin, ABC): """ @staticmethod - def calculate_lock_end(trades: List[Trade], stop_minutes: int) -> datetime: + def calculate_lock_end(trades: List[LocalTrade], stop_minutes: int) -> datetime: """ Get lock end time """ - max_date: datetime = max([trade.close_date for trade in trades]) + max_date: datetime = max([trade.close_date for trade in trades if trade.close_date]) # comming from Database, tzinfo is not set. if max_date.tzinfo is None: max_date = max_date.replace(tzinfo=timezone.utc) diff --git a/freqtrade/plugins/protections/low_profit_pairs.py b/freqtrade/plugins/protections/low_profit_pairs.py index 9d5ed35b4..7822ce73c 100644 --- a/freqtrade/plugins/protections/low_profit_pairs.py +++ b/freqtrade/plugins/protections/low_profit_pairs.py @@ -53,7 +53,7 @@ class LowProfitPairs(IProtection): # Not enough trades in the relevant period return False, None, None - profit = sum(trade.close_profit for trade in trades) + profit = sum(trade.close_profit for trade in trades if trade.close_profit) if profit < self._required_profit: self.log_once( f"Trading for {pair} stopped due to {profit:.2f} < {self._required_profit} " diff --git a/freqtrade/plugins/protections/max_drawdown_protection.py b/freqtrade/plugins/protections/max_drawdown_protection.py index d54e6699b..67e204039 100644 --- a/freqtrade/plugins/protections/max_drawdown_protection.py +++ b/freqtrade/plugins/protections/max_drawdown_protection.py @@ -55,13 +55,13 @@ class MaxDrawdown(IProtection): # Drawdown is always positive try: - drawdown, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit') + drawdown, _, _, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit') except ValueError: return False, None, None 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/plugins/protections/stoploss_guard.py b/freqtrade/plugins/protections/stoploss_guard.py index 5a9b9ddd0..635c0be04 100644 --- a/freqtrade/plugins/protections/stoploss_guard.py +++ b/freqtrade/plugins/protections/stoploss_guard.py @@ -56,7 +56,7 @@ class StoplossGuard(IProtection): trades = [trade for trade in trades1 if (str(trade.sell_reason) in ( SellType.TRAILING_STOP_LOSS.value, SellType.STOP_LOSS.value, SellType.STOPLOSS_ON_EXCHANGE.value) - and trade.close_profit < 0)] + and trade.close_profit and trade.close_profit < 0)] if len(trades) < self._trade_limit: return False, None, None 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 2738e5368..12bee1cf2 100644 --- a/freqtrade/rpc/api_server/api_schemas.py +++ b/freqtrade/rpc/api_server/api_schemas.py @@ -62,14 +62,12 @@ class PerformanceEntry(BaseModel): class Profit(BaseModel): profit_closed_coin: float - profit_closed_percent: float profit_closed_percent_mean: float profit_closed_ratio_mean: float profit_closed_percent_sum: float profit_closed_ratio_sum: float profit_closed_fiat: float profit_all_coin: float - profit_all_percent: float profit_all_percent_mean: float profit_all_ratio_mean: float profit_all_percent_sum: float @@ -153,13 +151,11 @@ 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] @@ -170,6 +166,7 @@ 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] @@ -192,7 +189,6 @@ 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 @@ -210,6 +206,7 @@ class ForceBuyResponse(BaseModel): class LockModel(BaseModel): + id: int active: bool lock_end_time: str lock_end_timestamp: int @@ -224,6 +221,11 @@ class Locks(BaseModel): locks: List[LockModel] +class DeleteLockRequest(BaseModel): + pair: Optional[str] + lockid: Optional[int] + + class Logs(BaseModel): log_count: int logs: List[List] diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index 90e3a612f..ebfafc290 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -11,13 +11,13 @@ from freqtrade.data.history import get_datahandler from freqtrade.exceptions import OperationalException from freqtrade.rpc import RPC from freqtrade.rpc.api_server.api_schemas import (AvailablePairs, Balances, BlacklistPayload, - BlacklistResponse, Count, Daily, DeleteTrade, - ForceBuyPayload, ForceBuyResponse, - ForceSellPayload, Locks, Logs, OpenTradeSchema, - PairHistory, PerformanceEntry, Ping, PlotConfig, - Profit, ResultMsg, ShowConfig, Stats, StatusMsg, - StrategyListResponse, StrategyResponse, - TradeResponse, Version, WhitelistResponse) + BlacklistResponse, Count, Daily, + DeleteLockRequest, DeleteTrade, ForceBuyPayload, + ForceBuyResponse, ForceSellPayload, Locks, Logs, + OpenTradeSchema, PairHistory, PerformanceEntry, + Ping, PlotConfig, Profit, ResultMsg, ShowConfig, + Stats, StatusMsg, StrategyListResponse, + StrategyResponse, Version, WhitelistResponse) from freqtrade.rpc.api_server.deps import get_config, get_rpc, get_rpc_optional from freqtrade.rpc.rpc import RPCException @@ -82,11 +82,21 @@ def status(rpc: RPC = Depends(get_rpc)): return [] -@router.get('/trades', response_model=TradeResponse, tags=['info', 'trading']) +# 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 = 0, rpc: RPC = Depends(get_rpc)): return rpc._rpc_trade_history(limit) +@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']) def trades_delete(tradeid: int, rpc: RPC = Depends(get_rpc)): return rpc._rpc_delete(tradeid) @@ -136,11 +146,21 @@ def whitelist(rpc: RPC = Depends(get_rpc)): return rpc._rpc_whitelist() -@router.get('/locks', response_model=Locks, tags=['info']) +@router.get('/locks', response_model=Locks, tags=['info', 'locks']) def locks(rpc: RPC = Depends(get_rpc)): return rpc._rpc_locks() +@router.delete('/locks/{lockid}', response_model=Locks, tags=['info', 'locks']) +def delete_lock(lockid: int, rpc: RPC = Depends(get_rpc)): + return rpc._rpc_delete_lock(lockid=lockid) + + +@router.post('/locks/delete', response_model=Locks, tags=['info', 'locks']) +def delete_lock_pair(payload: DeleteLockRequest, rpc: RPC = Depends(get_rpc)): + return rpc._rpc_delete_lock(lockid=payload.lockid, pair=payload.pair) + + @router.get('/logs', response_model=Logs, tags=['info']) def logs(limit: Optional[int] = None, rpc: RPC = Depends(get_rpc)): return rpc._rpc_get_logs(limit) diff --git a/freqtrade/rpc/api_server/uvicorn_threaded.py b/freqtrade/rpc/api_server/uvicorn_threaded.py index 1554a8e52..2f72cb74c 100644 --- a/freqtrade/rpc/api_server/uvicorn_threaded.py +++ b/freqtrade/rpc/api_server/uvicorn_threaded.py @@ -8,12 +8,33 @@ import uvicorn class UvicornServer(uvicorn.Server): """ Multithreaded server - as found in https://github.com/encode/uvicorn/issues/742 + + Removed install_signal_handlers() override based on changes from this commit: + https://github.com/encode/uvicorn/commit/ce2ef45a9109df8eae038c0ec323eb63d644cbc6 + + Cannot rely on asyncio.get_event_loop() to create new event loop because of this check: + https://github.com/python/cpython/blob/4d7f11e05731f67fd2c07ec2972c6cb9861d52be/Lib/asyncio/events.py#L638 + + Fix by overriding run() and forcing creation of new event loop if uvloop is available """ - def install_signal_handlers(self): + + def run(self, sockets=None): + import asyncio + """ - In the parent implementation, this starts the thread, therefore we must patch it away here. + Parent implementation calls self.config.setup_event_loop(), + but we need to create uvloop event loop manually """ - pass + try: + import uvloop # noqa + except ImportError: # pragma: no cover + from uvicorn.loops.asyncio import asyncio_setup + asyncio_setup() + else: + asyncio.set_event_loop(uvloop.new_event_loop()) + + loop = asyncio.get_event_loop() + loop.run_until_complete(self.serve(sockets=sockets)) @contextlib.contextmanager def run_in_thread(self): 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..380070deb 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -4,9 +4,9 @@ e.g BTC to USD """ import logging -import time -from typing import Dict, List +from typing import Dict +from cachetools.ttl import TTLCache from pycoingecko import CoinGeckoAPI from freqtrade.constants import SUPPORTED_FIAT @@ -15,51 +15,6 @@ 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. @@ -84,7 +39,9 @@ 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: @@ -118,49 +75,31 @@ 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 diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 7549c38be..e5c0dffba 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -3,7 +3,7 @@ This module contains class to define a RPC communications """ import logging from abc import abstractmethod -from datetime import date, datetime, timedelta +from datetime import date, datetime, timedelta, timezone from enum import Enum from math import isnan from typing import Any, Dict, List, Optional, Tuple, Union @@ -20,6 +20,7 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.loggers import bufferHandler from freqtrade.misc import shorten_date from freqtrade.persistence import PairLocks, Trade +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 @@ -30,13 +31,15 @@ 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 @@ -166,12 +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) + + # 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) @@ -190,6 +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), @@ -288,9 +304,10 @@ class RPC: """ Returns the X last trades """ if limit > 0: trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( - Trade.id.desc()).limit(limit) + Trade.close_date.desc()).limit(limit) else: - trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by(Trade.id.desc()).all() + trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( + Trade.close_date.desc()).all() output = [trade.to_json() for trade in trades] @@ -401,14 +418,12 @@ class RPC: num = float(len(durations) or 1) return { 'profit_closed_coin': profit_closed_coin_sum, - 'profit_closed_percent': round(profit_closed_ratio_mean * 100, 2), # DEPRECATED 'profit_closed_percent_mean': round(profit_closed_ratio_mean * 100, 2), 'profit_closed_ratio_mean': profit_closed_ratio_mean, 'profit_closed_percent_sum': round(profit_closed_ratio_sum * 100, 2), 'profit_closed_ratio_sum': profit_closed_ratio_sum, 'profit_closed_fiat': profit_closed_fiat, 'profit_all_coin': profit_all_coin_sum, - 'profit_all_percent': round(profit_all_ratio_mean * 100, 2), # DEPRECATED 'profit_all_percent_mean': round(profit_all_ratio_mean * 100, 2), 'profit_all_ratio_mean': profit_all_ratio_mean, 'profit_all_percent_sum': round(profit_all_ratio_sum * 100, 2), @@ -432,7 +447,7 @@ 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.') @@ -548,7 +563,7 @@ 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 +576,7 @@ 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}.'} @@ -594,7 +609,7 @@ class RPC: pair, self._freqtrade.get_free_open_trades()) # execute buy - if self._freqtrade.execute_buy(pair, stakeamount, price): + if self._freqtrade.execute_buy(pair, stakeamount, price, forcebuy=True): trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first() return trade else: @@ -663,7 +678,7 @@ class RPC: } def _rpc_locks(self) -> Dict[str, Any]: - """ Returns the current locks""" + """ Returns the current locks """ locks = PairLocks.get_pair_locks(None) return { @@ -671,6 +686,25 @@ class RPC: 'locks': [lock.to_json() for lock in locks] } + def _rpc_delete_lock(self, lockid: Optional[int] = None, + pair: Optional[str] = None) -> Dict[str, Any]: + """ Delete specific lock(s) """ + locks = [] + + if pair: + locks = PairLocks.get_pair_locks(pair) + if lockid: + locks = PairLock.query.filter(PairLock.id == lockid).all() + + for lock in locks: + lock.active = False + lock.lock_end_time = datetime.now(timezone.utc) + + # session is always the same + PairLock.query.session.flush() + + return self._rpc_locks() + def _rpc_whitelist(self) -> Dict: """ Returns the currently active whitelist""" res = {'method': self._freqtrade.pairlists.name_list, 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 9d05ae142..ffe7a7ceb 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -6,6 +6,7 @@ This module manage Telegram communication import json import logging from datetime import timedelta +from html import escape from itertools import chain from typing import Any, Callable, Dict, List, Union @@ -144,6 +145,7 @@ class Telegram(RPCHandler): CommandHandler('daily', self._daily), CommandHandler('count', self._count), CommandHandler('locks', self._locks), + CommandHandler(['unlock', 'delete_locks'], self._delete_locks), CommandHandler(['reload_config', 'reload_conf'], self._reload_config), CommandHandler(['show_config', 'show_conf'], self._show_config), CommandHandler('stopbuy', self._stopbuy), @@ -157,10 +159,10 @@ 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', @@ -174,6 +176,53 @@ 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 """ @@ -184,65 +233,31 @@ 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']}\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}. Reason: {reason}.".format(**msg)) + "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'] in (RPCMessageType.BUY_FILL, RPCMessageType.SELL_FILL): + msg['message_side'] = 'Buy' if msg['type'] == RPCMessageType.BUY_FILL else 'Sell' - msg['emoji'] = self._get_sell_emoji(msg) + message = ("\N{LARGE CIRCLE} *{exchange}:* " + "Buy order for {pair} (#{trade_id}) filled for {open_rate}.".format(**msg)) - message = ("{emoji} *{exchange}:* Selling {pair}\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) + elif msg['type'] == RPCMessageType.SELL: + message = self._format_sell_msg(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}. 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: @@ -290,6 +305,7 @@ 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}", @@ -339,8 +355,17 @@ class Telegram(RPCHandler): statlist, head = self._rpc._rpc_status_table( self._config['stake_currency'], self._config.get('fiat_display_currency', '')) - message = tabulate(statlist, headers=head, tablefmt='simple') - self._send_msg(f"
{message}
", parse_mode=ParseMode.HTML) + 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], + headers=head, + tablefmt='simple') + self._send_msg(f"
{message}
", parse_mode=ParseMode.HTML) except RPCException as e: self._send_msg(str(e)) @@ -633,13 +658,13 @@ class Telegram(RPCHandler): nrecent ) trades_tab = tabulate( - [[arrow.get(trade['open_date']).humanize(), - trade['pair'], + [[arrow.get(trade['close_date']).humanize(), + trade['pair'] + " (#" + str(trade['trade_id']) + ")", f"{(100 * trade['close_profit']):.2f}% ({trade['close_profit_abs']})"] for trade in trades['trades']], headers=[ - 'Open Date', - 'Pair', + 'Close Date', + 'Pair (ID)', f'Profit ({stake_cur})', ], tablefmt='simple') @@ -682,14 +707,18 @@ 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{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)) @@ -719,19 +748,35 @@ class Telegram(RPCHandler): Handler for /locks. Returns the currently active locks """ - try: - locks = self._rpc._rpc_locks() - message = tabulate([[ - lock['pair'], - lock['lock_end_time'], - lock['reason']] for lock in locks['locks']], - headers=['Pair', 'Until', 'Reason'], - tablefmt='simple') - message = "
{}
".format(message) - logger.debug(message) - self._send_msg(message, parse_mode=ParseMode.HTML) - except RPCException as e: - self._send_msg(str(e)) + 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) + + @authorized_only + def _delete_locks(self, update: Update, context: CallbackContext) -> None: + """ + Handler for /delete_locks. + Returns the currently active locks + """ + arg = context.args[0] if context.args and len(context.args) > 0 else None + lockid = None + pair = None + if arg: + try: + lockid = int(arg) + except ValueError: + pair = arg + + self._rpc._rpc_delete_lock(lockid=lockid, pair=pair) + self._locks(update, context) @authorized_only def _whitelist(self, update: Update, context: CallbackContext) -> None: @@ -850,6 +895,7 @@ class Telegram(RPCHandler): "Avg. holding durationsfor buys and sells.`\n" "*/count:* `Show number of active trades compared to allowed number of trades`\n" "*/locks:* `Show currently locked pairs`\n" + "*/unlock :* `Unlock this Pair (or this lock id if it's numeric)`\n" "*/balance:* `Show account balance per currency`\n" "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n" "*/reload_config:* `Reload configuration file` \n" 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 662156ae9..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 +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..16b576a73 --- /dev/null +++ b/freqtrade/strategy/hyper.py @@ -0,0 +1,271 @@ +""" +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, Iterator, Optional, Sequence, Tuple, Union + + +with suppress(ImportError): + from skopt.space import Integer, Real, Categorical + from freqtrade.optimize.space import SKDecimal + +from freqtrade.exceptions import OperationalException + + +logger = logging.getLogger(__name__) + + +class BaseParameter(ABC): + """ + Defines a parameter that can be optimized by hyperopt. + """ + category: Optional[str] + default: Any + value: Any + + 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) + + +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, *args, **kwargs): + """ + Initialize hyperoptable strategy mixin. + """ + self._load_params(getattr(self, 'buy_params', None)) + self._load_params(getattr(self, 'sell_params', None)) + + 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.') + 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 (category and 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 is None or category == attr.category or + (attr_name.startswith(category + '_') and attr.category is None)): + yield attr_name, attr + + def _load_params(self, params: dict) -> None: + """ + Set optimizeable parameter values. + :param params: Dictionary with new parameter values. + """ + if not params: + return + for attr_name, attr in self.enumerate_parameters(): + if 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.') diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 8a0b27e96..54c7f2353 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -18,6 +18,7 @@ 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 @@ -59,7 +60,7 @@ class SellCheckTuple(NamedTuple): sell_type: SellType -class IStrategy(ABC): +class IStrategy(ABC, HyperStrategyMixin): """ Interface for freqtrade strategies Defines the mandatory structure must follow any custom strategies @@ -140,6 +141,7 @@ 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: @@ -649,7 +651,7 @@ class IStrategy(ABC): :return: True if bot should sell at current rate """ # Check if time matches and current rate is above threshold - trade_dur = int((current_time.timestamp() - trade.open_date.timestamp()) // 60) + trade_dur = int((current_time.timestamp() - trade.open_date_utc.timestamp()) // 60) _, roi = self.min_roi_reached_entry(trade_dur) if roi is None: return False diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py index d7b1327d9..22b6f0be5 100644 --- a/freqtrade/strategy/strategy_helper.py +++ b/freqtrade/strategy/strategy_helper.py @@ -56,3 +56,30 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, dataframe = dataframe.ffill() return dataframe + + +def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float: + """ + + Given the current profit, and a desired stop loss value relative to the open price, + return a stop loss value that is relative to the current price, and which can be + returned from `custom_stoploss`. + + The requested stop can be positive for a stop above the open price, or negative for + a stop below the open price. The return value is always >= 0. + + Returns 0 if the resulting stop price would be above the current price. + + :param open_relative_stop: Desired stop loss percentage relative to open price + :param current_profit: The current profit percentage + :return: Positive stop loss value relative to current price + """ + + # formula is undefined for current_profit -1, return maximum value + if current_profit == -1: + return 1 + + stoploss = 1-((1+open_relative_stop)/(1+current_profit)) + + # negative stoploss values indicate the requested stop price is higher than the current price + return max(stoploss, 0.0) diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2 index 226bf1a81..42f088f9f 100644 --- a/freqtrade/templates/base_config.json.j2 +++ b/freqtrade/templates/base_config.json.j2 @@ -54,15 +54,15 @@ "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_hyperopt.py.j2 b/freqtrade/templates/base_hyperopt.py.j2 index 2bdfdba16..58b3f209d 100644 --- a/freqtrade/templates/base_hyperopt.py.j2 +++ b/freqtrade/templates/base_hyperopt.py.j2 @@ -39,6 +39,15 @@ class {{ hyperopt }}(IHyperOpt): https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py. """ + @staticmethod + def indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching buy strategy parameters. + """ + return [ + {{ buy_space | indent(12) }} + ] + @staticmethod def buy_strategy_generator(params: Dict[str, Any]) -> Callable: """ @@ -79,12 +88,12 @@ class {{ hyperopt }}(IHyperOpt): return populate_buy_trend @staticmethod - def indicator_space() -> List[Dimension]: + def sell_indicator_space() -> List[Dimension]: """ - Define your Hyperopt space for searching buy strategy parameters. + Define your Hyperopt space for searching sell strategy parameters. """ return [ - {{ buy_space | indent(12) }} + {{ sell_space | indent(12) }} ] @staticmethod @@ -133,4 +142,4 @@ class {{ hyperopt }}(IHyperOpt): """ return [ {{ sell_space | indent(12) }} - ] \ No newline at end of file + ] diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2 index dd6b773e1..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 @@ -26,8 +28,9 @@ class {{ strategy }}(IStrategy): You must keep: - the lib in the section "Do not remove these libs" - - the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend, - populate_sell_trend, hyperopt_space, buy_strategy_generator + - the methods: populate_indicators, populate_buy_trend, populate_sell_trend + You should keep: + - timeframe, minimal_roi, stoploss, trailing_* """ # Strategy interface version - allow new iterations of the strategy interface. # Check the documentation or the Sample strategy to get the latest version. diff --git a/freqtrade/templates/sample_hyperopt.py b/freqtrade/templates/sample_hyperopt.py index 10743e911..ed1af7718 100644 --- a/freqtrade/templates/sample_hyperopt.py +++ b/freqtrade/templates/sample_hyperopt.py @@ -45,6 +45,23 @@ class SampleHyperOpt(IHyperOpt): https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py. """ + @staticmethod + def indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching buy strategy parameters. + """ + return [ + Integer(10, 25, name='mfi-value'), + Integer(15, 45, name='fastd-value'), + Integer(20, 50, name='adx-value'), + Integer(20, 40, name='rsi-value'), + Categorical([True, False], name='mfi-enabled'), + Categorical([True, False], name='fastd-enabled'), + Categorical([True, False], name='adx-enabled'), + Categorical([True, False], name='rsi-enabled'), + Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger') + ] + @staticmethod def buy_strategy_generator(params: Dict[str, Any]) -> Callable: """ @@ -92,20 +109,22 @@ class SampleHyperOpt(IHyperOpt): return populate_buy_trend @staticmethod - def indicator_space() -> List[Dimension]: + def sell_indicator_space() -> List[Dimension]: """ - Define your Hyperopt space for searching buy strategy parameters. + Define your Hyperopt space for searching sell strategy parameters. """ return [ - Integer(10, 25, name='mfi-value'), - Integer(15, 45, name='fastd-value'), - Integer(20, 50, name='adx-value'), - Integer(20, 40, name='rsi-value'), - Categorical([True, False], name='mfi-enabled'), - Categorical([True, False], name='fastd-enabled'), - Categorical([True, False], name='adx-enabled'), - Categorical([True, False], name='rsi-enabled'), - Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger') + Integer(75, 100, name='sell-mfi-value'), + Integer(50, 100, name='sell-fastd-value'), + Integer(50, 100, name='sell-adx-value'), + Integer(60, 100, name='sell-rsi-value'), + Categorical([True, False], name='sell-mfi-enabled'), + Categorical([True, False], name='sell-fastd-enabled'), + Categorical([True, False], name='sell-adx-enabled'), + Categorical([True, False], name='sell-rsi-enabled'), + Categorical(['sell-bb_upper', + 'sell-macd_cross_signal', + 'sell-sar_reversal'], name='sell-trigger') ] @staticmethod @@ -153,56 +172,3 @@ class SampleHyperOpt(IHyperOpt): return dataframe return populate_sell_trend - - @staticmethod - def sell_indicator_space() -> List[Dimension]: - """ - Define your Hyperopt space for searching sell strategy parameters. - """ - return [ - Integer(75, 100, name='sell-mfi-value'), - Integer(50, 100, name='sell-fastd-value'), - Integer(50, 100, name='sell-adx-value'), - Integer(60, 100, name='sell-rsi-value'), - Categorical([True, False], name='sell-mfi-enabled'), - Categorical([True, False], name='sell-fastd-enabled'), - Categorical([True, False], name='sell-adx-enabled'), - Categorical([True, False], name='sell-rsi-enabled'), - Categorical(['sell-bb_upper', - 'sell-macd_cross_signal', - 'sell-sar_reversal'], name='sell-trigger') - ] - - def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - """ - Based on TA indicators. Should be a copy of same method from strategy. - Must align to populate_indicators in this file. - Only used when --spaces does not include buy space. - """ - dataframe.loc[ - ( - (dataframe['close'] < dataframe['bb_lowerband']) & - (dataframe['mfi'] < 16) & - (dataframe['adx'] > 25) & - (dataframe['rsi'] < 21) - ), - 'buy'] = 1 - - return dataframe - - def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - """ - Based on TA indicators. Should be a copy of same method from strategy. - Must align to populate_indicators in this file. - Only used when --spaces does not include sell space. - """ - dataframe.loc[ - ( - (qtpylib.crossed_above( - dataframe['macdsignal'], dataframe['macd'] - )) & - (dataframe['fastd'] > 54) - ), - 'sell'] = 1 - - return dataframe diff --git a/freqtrade/templates/sample_hyperopt_advanced.py b/freqtrade/templates/sample_hyperopt_advanced.py index 52e397466..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 @@ -60,6 +60,23 @@ class AdvancedSampleHyperOpt(IHyperOpt): dataframe['sar'] = ta.SAR(dataframe) return dataframe + @staticmethod + def indicator_space() -> List[Dimension]: + """ + Define your Hyperopt space for searching buy strategy parameters. + """ + return [ + Integer(10, 25, name='mfi-value'), + Integer(15, 45, name='fastd-value'), + Integer(20, 50, name='adx-value'), + Integer(20, 40, name='rsi-value'), + Categorical([True, False], name='mfi-enabled'), + Categorical([True, False], name='fastd-enabled'), + Categorical([True, False], name='adx-enabled'), + Categorical([True, False], name='rsi-enabled'), + Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger') + ] + @staticmethod def buy_strategy_generator(params: Dict[str, Any]) -> Callable: """ @@ -106,20 +123,22 @@ class AdvancedSampleHyperOpt(IHyperOpt): return populate_buy_trend @staticmethod - def indicator_space() -> List[Dimension]: + def sell_indicator_space() -> List[Dimension]: """ - Define your Hyperopt space for searching strategy parameters + Define your Hyperopt space for searching sell strategy parameters. """ return [ - Integer(10, 25, name='mfi-value'), - Integer(15, 45, name='fastd-value'), - Integer(20, 50, name='adx-value'), - Integer(20, 40, name='rsi-value'), - Categorical([True, False], name='mfi-enabled'), - Categorical([True, False], name='fastd-enabled'), - Categorical([True, False], name='adx-enabled'), - Categorical([True, False], name='rsi-enabled'), - Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger') + Integer(75, 100, name='sell-mfi-value'), + Integer(50, 100, name='sell-fastd-value'), + Integer(50, 100, name='sell-adx-value'), + Integer(60, 100, name='sell-rsi-value'), + Categorical([True, False], name='sell-mfi-enabled'), + Categorical([True, False], name='sell-fastd-enabled'), + Categorical([True, False], name='sell-adx-enabled'), + Categorical([True, False], name='sell-rsi-enabled'), + Categorical(['sell-bb_upper', + 'sell-macd_cross_signal', + 'sell-sar_reversal'], name='sell-trigger') ] @staticmethod @@ -168,25 +187,6 @@ class AdvancedSampleHyperOpt(IHyperOpt): return populate_sell_trend - @staticmethod - def sell_indicator_space() -> List[Dimension]: - """ - Define your Hyperopt space for searching sell strategy parameters - """ - return [ - Integer(75, 100, name='sell-mfi-value'), - Integer(50, 100, name='sell-fastd-value'), - Integer(50, 100, name='sell-adx-value'), - Integer(60, 100, name='sell-rsi-value'), - Categorical([True, False], name='sell-mfi-enabled'), - Categorical([True, False], name='sell-fastd-enabled'), - Categorical([True, False], name='sell-adx-enabled'), - Categorical([True, False], name='sell-rsi-enabled'), - Categorical(['sell-bb_upper', - 'sell-macd_cross_signal', - 'sell-sar_reversal'], name='sell-trigger') - ] - @staticmethod def generate_roi_table(params: Dict) -> Dict[int, float]: """ @@ -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 @@ -256,51 +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'), ] - - def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - """ - Based on TA indicators. - Can be a copy of the corresponding method from the strategy, - or will be loaded from the strategy. - Must align to populate_indicators used (either from this File, or from the strategy) - Only used when --spaces does not include buy - """ - dataframe.loc[ - ( - (dataframe['close'] < dataframe['bb_lowerband']) & - (dataframe['mfi'] < 16) & - (dataframe['adx'] > 25) & - (dataframe['rsi'] < 21) - ), - 'buy'] = 1 - - return dataframe - - def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - """ - Based on TA indicators. - Can be a copy of the corresponding method from the strategy, - or will be loaded from the strategy. - Must align to populate_indicators used (either from this File, or from the strategy) - Only used when --spaces does not include sell - """ - dataframe.loc[ - ( - (qtpylib.crossed_above( - dataframe['macdsignal'], dataframe['macd'] - )) & - (dataframe['fastd'] > 54) - ), - 'sell'] = 1 - return dataframe diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index db1ba48b8..a51b30f3f 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -1,11 +1,13 @@ # 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 import pandas as pd # noqa from pandas import DataFrame -from freqtrade.strategy.interface import IStrategy +from freqtrade.strategy import IStrategy +from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter # -------------------------------- # Add your lib to import here @@ -27,8 +29,9 @@ class SampleStrategy(IStrategy): You must keep: - the lib in the section "Do not remove these libs" - - the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend, - populate_sell_trend, hyperopt_space, buy_strategy_generator + - the methods: populate_indicators, populate_buy_trend, populate_sell_trend + You should keep: + - timeframe, minimal_roi, stoploss, trailing_* """ # Strategy interface version - allow new iterations of the strategy interface. # Check the documentation or the Sample strategy to get the latest version. @@ -52,7 +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. @@ -339,7 +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 @@ -357,7 +365,8 @@ class SampleStrategy(IStrategy): """ 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/wallets.py b/freqtrade/wallets.py index d7dcfd487..f4432e932 100644 --- a/freqtrade/wallets.py +++ b/freqtrade/wallets.py @@ -10,7 +10,8 @@ import arrow from freqtrade.constants import UNLIMITED_STAKE_AMOUNT from freqtrade.exceptions import DependencyException from freqtrade.exchange import Exchange -from freqtrade.persistence import Trade +from freqtrade.persistence import LocalTrade, Trade +from freqtrade.state import RunMode logger = logging.getLogger(__name__) @@ -26,8 +27,9 @@ class Wallet(NamedTuple): class Wallets: - def __init__(self, config: dict, exchange: Exchange) -> None: + def __init__(self, config: dict, exchange: Exchange, log: bool = True) -> None: self._config = config + self._log = log self._exchange = exchange self._wallets: Dict[str, Wallet] = {} self.start_cap = config['dry_run_wallet'] @@ -64,9 +66,15 @@ class Wallets: """ # Recreate _wallets to reset closed trade balances _wallets = {} - closed_trades = Trade.get_trades(Trade.is_open.is_(False)).all() - open_trades = Trade.get_trades(Trade.is_open.is_(True)).all() - tot_profit = sum([trade.calc_profit() for trade in closed_trades]) + open_trades = Trade.get_trades_proxy(is_open=True) + # If not backtesting... + # TODO: potentially remove the ._log workaround to determine backtest mode. + if self._log: + closed_trades = Trade.get_trades_proxy(is_open=False) + tot_profit = sum( + [trade.close_profit_abs for trade in closed_trades if trade.close_profit_abs]) + else: + tot_profit = LocalTrade.total_profit tot_in_trades = sum([trade.stake_amount for trade in open_trades]) current_stake = self.start_cap + tot_profit - tot_in_trades @@ -111,11 +119,12 @@ class Wallets: :param require_update: Allow skipping an update if balances were recently refreshed """ if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().int_timestamp)): - if self._config['dry_run']: - self._update_dry() - else: + if (not self._config['dry_run'] or self._config.get('runmode') == RunMode.LIVE): self._update_live() - logger.info('Wallets synced.') + else: + self._update_dry() + if self._log: + logger.info('Wallets synced.') self._last_wallet_refresh = arrow.utcnow().int_timestamp def get_all_balances(self) -> Dict[str, Any]: @@ -154,6 +163,7 @@ class Wallets: 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() diff --git a/requirements-dev.txt b/requirements-dev.txt index 6ca1a4d9c..5e96e2cc2 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -3,17 +3,17 @@ -r requirements-plot.txt -r requirements-hyperopt.txt -coveralls==3.0.0 -flake8==3.8.4 +coveralls==3.0.1 +flake8==3.9.1 flake8-type-annotations==0.1.0 flake8-tidy-imports==4.2.1 mypy==0.812 -pytest==6.2.2 -pytest-asyncio==0.14.0 +pytest==6.2.3 +pytest-asyncio==0.15.0 pytest-cov==2.11.1 pytest-mock==3.5.1 pytest-random-order==1.0.4 -isort==5.7.0 +isort==5.8.0 # Convert jupyter notebooks to markdown documents nbconvert==6.0.7 diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt index 8cdb6fd28..9eb490f83 100644 --- a/requirements-hyperopt.txt +++ b/requirements-hyperopt.txt @@ -2,7 +2,7 @@ -r requirements.txt # Required for hyperopt -scipy==1.6.1 +scipy==1.6.2 scikit-learn==0.24.1 scikit-optimize==0.8.1 filelock==3.0.12 diff --git a/requirements.txt b/requirements.txt index ed5d24be1..a89eb2383 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,21 +1,22 @@ -numpy==1.20.1 -pandas==1.2.2 +numpy==1.20.2 +pandas==1.2.4 -ccxt==1.42.47 +ccxt==1.48.22 # Pin cryptography for now due to rust build errors with piwheels -cryptography==3.4.6 -aiohttp==3.7.4 -SQLAlchemy==1.3.23 -python-telegram-bot==13.3 -arrow==1.0.2 +cryptography==3.4.7 +aiohttp==3.7.4.post0 +SQLAlchemy==1.4.9 +python-telegram-bot==13.4.1 +arrow==1.0.3 cachetools==4.2.1 requests==2.25.1 -urllib3==1.26.3 +urllib3==1.26.4 wrapt==1.12.1 jsonschema==3.2.0 TA-Lib==0.4.19 +technical==1.2.2 tabulate==0.8.9 -pycoingecko==1.4.0 +pycoingecko==1.4.1 jinja2==2.11.3 tables==3.6.1 blosc==1.10.2 @@ -39,4 +40,4 @@ aiofiles==0.6.0 colorama==0.4.4 # Building config files interactively questionary==1.9.0 -prompt-toolkit==3.0.16 +prompt-toolkit==3.0.18 diff --git a/scripts/rest_client.py b/scripts/rest_client.py index b6e66cfa4..40b338ce8 100755 --- a/scripts/rest_client.py +++ b/scripts/rest_client.py @@ -118,8 +118,16 @@ class FtRestClient(): """ return self._get("locks") + def delete_lock(self, lock_id): + """Delete (disable) lock from the database. + + :param lock_id: ID for the lock to delete + :return: json object + """ + 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 """ @@ -174,10 +182,20 @@ class FtRestClient(): """ return self._get("show_config") + def ping(self): + """simple ping""" + configstatus = self.show_config() + if not configstatus: + return {"status": "not_running"} + elif configstatus['state'] == "running": + return {"status": "pong"} + else: + return {"status": "not_running"} + 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) @@ -190,6 +208,14 @@ class FtRestClient(): """ return self._get("trades", params={"limit": limit} if limit else 0) + 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. Tries to close open orders. Requires manual handling of this asset on the exchange. 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/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 c81909025..d86bced5d 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 = [ @@ -706,7 +706,7 @@ def test_download_data_timerange(mocker, caplog, markets): start_download_data(get_args(args)) assert dl_mock.call_count == 1 # 20days ago - days_ago = arrow.get(arrow.utcnow().shift(days=-20).date()).int_timestamp + days_ago = arrow.get(arrow.now().shift(days=-20).date()).int_timestamp assert dl_mock.call_args_list[0][1]['timerange'].startts == days_ago dl_mock.reset_mock() @@ -920,7 +920,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys): def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): mocker.patch( - 'freqtrade.optimize.hyperopt.Hyperopt.load_previous_results', + 'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results', MagicMock(return_value=hyperopt_results) ) @@ -1145,14 +1145,14 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): captured = capsys.readouterr() log_has("CSV file created: test_file.csv", caplog) f = Path("test_file.csv") - assert 'Best,1,2,-1.25%,-0.00125625,,-2.51,"3,930.0 m",0.43662' in f.read_text() + 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.Hyperopt.load_previous_results', + 'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results', MagicMock(return_value=hyperopt_results) ) 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 61899dd53..788586134 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -6,7 +6,7 @@ from copy import deepcopy from datetime import datetime from functools import reduce from pathlib import Path -from unittest.mock import MagicMock, PropertyMock +from unittest.mock import MagicMock, Mock, PropertyMock import arrow import numpy as np @@ -19,7 +19,7 @@ from freqtrade.data.converter import ohlcv_to_dataframe from freqtrade.edge import Edge, PairInfo from freqtrade.exchange import Exchange from freqtrade.freqtradebot import FreqtradeBot -from freqtrade.persistence import Trade, init_db +from freqtrade.persistence import LocalTrade, Trade, init_db from freqtrade.resolvers import ExchangeResolver from freqtrade.worker import Worker from tests.conftest_trades import (mock_trade_1, mock_trade_2, mock_trade_3, mock_trade_4, @@ -64,6 +64,14 @@ def get_args(args): return Arguments(args).get_parsed_arg() +# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines +def get_mock_coro(return_value): + async def mock_coro(*args, **kwargs): + return return_value + + return Mock(wraps=mock_coro) + + def patched_configuration_load_config_file(mocker, config) -> None: mocker.patch( 'freqtrade.configuration.configuration.load_config_file', @@ -71,7 +79,7 @@ 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()) @@ -90,7 +98,7 @@ 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 @@ -183,28 +191,37 @@ def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None: freqtrade.exchange.refresh_latest_ohlcv = lambda p: None -def create_mock_trades(fee): +def create_mock_trades(fee, use_db: bool = True): """ Create some fake trades ... """ + def add_trade(trade): + if use_db: + Trade.query.session.add(trade) + else: + LocalTrade.add_bt_trade(trade) + # Simulate dry_run entries trade = mock_trade_1(fee) - Trade.session.add(trade) + add_trade(trade) trade = mock_trade_2(fee) - Trade.session.add(trade) + add_trade(trade) trade = mock_trade_3(fee) - Trade.session.add(trade) + add_trade(trade) trade = mock_trade_4(fee) - Trade.session.add(trade) + add_trade(trade) trade = mock_trade_5(fee) - Trade.session.add(trade) + add_trade(trade) trade = mock_trade_6(fee) - Trade.session.add(trade) + add_trade(trade) + + if use_db: + Trade.query.session.flush() @pytest.fixture(autouse=True) @@ -255,6 +272,7 @@ def get_default_conf(testdatadir): "20": 0.02, "0": 0.04 }, + "dry_run_wallet": 1000, "stoploss": -0.10, "unfilledtimeout": { "buy": 10, @@ -275,7 +293,7 @@ def get_default_conf(testdatadir): "order_book_max": 1 }, "exchange": { - "name": "bittrex", + "name": "binance", "enabled": True, "key": "key", "secret": "secret", @@ -296,7 +314,8 @@ def get_default_conf(testdatadir): "telegram": { "enabled": True, "token": "token", - "chat_id": "0" + "chat_id": "0", + "notification_settings": {}, }, "datadir": str(testdatadir), "initial_state": "running", @@ -1729,7 +1748,7 @@ def import_fails() -> None: realimport = builtins.__import__ def mockedimport(name, *args, **kwargs): - if name in ["filelock", 'systemd.journal']: + if name in ["filelock", 'systemd.journal', 'uvloop']: raise ImportError(f"No module named '{name}'") return realimport(name, *args, **kwargs) @@ -1747,7 +1766,7 @@ 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, @@ -1766,7 +1785,7 @@ def hyperopt_results(): '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': {'trade_count': 2, 'avg_profit': -1.254995, 'total_profit': -0.00125625, 'profit': -2.50999, 'duration': 3930.0}, # noqa: E501 + 'results_metrics': {'trade_count': 2, 'avg_profit': -1.254995, 'median_profit': -1.2222, 'total_profit': -0.00125625, 'profit': -2.50999, 'duration': 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, @@ -1781,7 +1800,7 @@ def hyperopt_results(): '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': {'trade_count': 1, 'avg_profit': 0.12357, 'total_profit': 6.185e-05, 'profit': 0.12357, 'duration': 1200.0}, # noqa: E501 + 'results_metrics': {'trade_count': 1, 'avg_profit': 0.12357, 'median_profit': -1.2222, 'total_profit': 6.185e-05, 'profit': 0.12357, 'duration': 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, @@ -1791,7 +1810,7 @@ def hyperopt_results(): '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': {'trade_count': 621, 'avg_profit': -0.43883302093397747, 'total_profit': -0.13639474, 'profit': -272.515306, 'duration': 1691.207729468599}, # noqa: E501 + 'results_metrics': {'trade_count': 621, 'avg_profit': -0.43883302093397747, 'median_profit': -1.2222, 'total_profit': -0.13639474, 'profit': -272.515306, 'duration': 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, @@ -1801,14 +1820,14 @@ def hyperopt_results(): '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': {'trade_count': 0, 'avg_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None}, # noqa: E501 + 'results_metrics': {'trade_count': 0, 'avg_profit': None, 'median_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None}, # 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': {'trade_count': 14, 'avg_profit': -0.3539515, 'total_profit': -0.002480140000000001, 'profit': -4.955321, 'duration': 3402.8571428571427}, # noqa: E501 + 'results_metrics': {'trade_count': 14, 'avg_profit': -0.3539515, 'median_profit': -1.2222, 'total_profit': -0.002480140000000001, 'profit': -4.955321, 'duration': 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, @@ -1818,7 +1837,7 @@ def hyperopt_results(): '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': {'trade_count': 39, 'avg_profit': -0.21400679487179478, 'total_profit': -0.0041773, 'profit': -8.346264999999997, 'duration': 636.9230769230769}, # noqa: E501 + 'results_metrics': {'trade_count': 39, 'avg_profit': -0.21400679487179478, 'median_profit': -1.2222, 'total_profit': -0.0041773, 'profit': -8.346264999999997, 'duration': 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, @@ -1830,7 +1849,7 @@ def hyperopt_results(): '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': {'trade_count': 318, 'avg_profit': -0.39833954716981146, 'total_profit': -0.06339929, 'profit': -126.67197600000004, 'duration': 3140.377358490566}, # noqa: E501 + 'results_metrics': {'trade_count': 318, 'avg_profit': -0.39833954716981146, 'median_profit': -1.2222, 'total_profit': -0.06339929, 'profit': -126.67197600000004, 'duration': 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, @@ -1840,7 +1859,7 @@ def hyperopt_results(): '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': {'trade_count': 1, 'avg_profit': 0.0, 'total_profit': 0.0, 'profit': 0.0, 'duration': 5340.0}, # noqa: E501 + 'results_metrics': {'trade_count': 1, 'avg_profit': 0.0, 'median_profit': 0.0, 'total_profit': 0.0, 'profit': 0.0, 'duration': 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, @@ -1850,7 +1869,7 @@ def hyperopt_results(): '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': {'trade_count': 229, 'avg_profit': -0.38433433624454144, 'total_profit': -0.044050070000000004, 'profit': -88.01256299999999, 'duration': 6505.676855895196}, # noqa: E501 + 'results_metrics': {'trade_count': 229, 'avg_profit': -0.38433433624454144, 'median_profit': -1.2222, 'total_profit': -0.044050070000000004, 'profit': -88.01256299999999, 'duration': 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, @@ -1860,7 +1879,7 @@ def hyperopt_results(): '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': {'trade_count': 4, 'avg_profit': 0.1080385, 'total_profit': 0.00021629, 'profit': 0.432154, 'duration': 2850.0}, # noqa: E501 + 'results_metrics': {'trade_count': 4, 'avg_profit': 0.1080385, 'median_profit': -1.2222, 'total_profit': 0.00021629, 'profit': 0.432154, 'duration': 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, @@ -1870,7 +1889,7 @@ def hyperopt_results(): '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 - 'results_metrics': {'trade_count': 117, 'avg_profit': -1.2698609145299145, 'total_profit': -0.07436117, 'profit': -148.573727, 'duration': 4282.5641025641025}, # noqa: E501 + 'results_metrics': {'trade_count': 117, 'avg_profit': -1.2698609145299145, 'median_profit': -1.2222, 'total_profit': -0.07436117, 'profit': -148.573727, 'duration': 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, @@ -1880,7 +1899,7 @@ def hyperopt_results(): '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': {'trade_count': 0, 'avg_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None}, # noqa: E501 + 'results_metrics': {'trade_count': 0, 'avg_profit': None, 'median_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None}, # 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, diff --git a/tests/conftest_trades.py b/tests/conftest_trades.py index fa9910b8d..b92b51144 100644 --- a/tests/conftest_trades.py +++ b/tests/conftest_trades.py @@ -28,8 +28,10 @@ def mock_trade_1(fee): amount_requested=123.0, fee_open=fee.return_value, fee_close=fee.return_value, + 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, @@ -81,14 +83,15 @@ def mock_trade_2(fee): open_rate=0.123, close_rate=0.128, close_profit=0.005, - exchange='bittrex', + close_profit_abs=0.000584127, + exchange='binance', is_open=False, open_order_id='dry_run_sell_12345', strategy='DefaultStrategy', timeframe=5, sell_reason='sell_signal', open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20), - close_date=datetime.now(tz=timezone.utc), + close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=2), ) o = Order.parse_from_ccxt_object(mock_order_2(), 'ETC/BTC', 'buy') trade.orders.append(o) @@ -140,7 +143,8 @@ def mock_trade_3(fee): open_rate=0.05, close_rate=0.06, close_profit=0.01, - exchange='bittrex', + close_profit_abs=0.000155, + exchange='binance', is_open=False, strategy='DefaultStrategy', timeframe=5, @@ -180,8 +184,10 @@ def mock_trade_4(fee): amount_requested=124.0, fee_open=fee.return_value, fee_close=fee.return_value, + 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, @@ -230,10 +236,13 @@ def mock_trade_5(fee): amount_requested=124.0, fee_open=fee.return_value, fee_close=fee.return_value, + 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) @@ -279,12 +288,15 @@ def mock_trade_6(fee): stake_amount=0.001, amount=2.0, amount_requested=2.0, + open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=5), fee_open=fee.return_value, 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 3c4687745..e42c13e18 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -274,15 +274,17 @@ def test_create_cum_profit1(testdatadir): def test_calculate_max_drawdown(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) - drawdown, h, low = calculate_max_drawdown(bt_data) + drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(bt_data) assert isinstance(drawdown, float) assert pytest.approx(drawdown) == 0.21142322 - assert isinstance(h, Timestamp) - assert isinstance(low, Timestamp) - assert h == Timestamp('2018-01-24 14:25:00', tz='UTC') - assert low == Timestamp('2018-01-30 04:45:00', tz='UTC') + assert isinstance(hdate, Timestamp) + assert isinstance(lowdate, Timestamp) + assert isinstance(hval, float) + assert isinstance(lval, float) + assert hdate == Timestamp('2018-01-24 14:25:00', tz='UTC') + assert lowdate == Timestamp('2018-01-30 04:45:00', tz='UTC') with pytest.raises(ValueError, match='Trade dataframe empty.'): - drawdown, h, low = calculate_max_drawdown(DataFrame()) + drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(DataFrame()) def test_calculate_csum(testdatadir): @@ -294,6 +296,10 @@ def test_calculate_csum(testdatadir): assert isinstance(csum_max, float) assert csum_min < 0.01 assert csum_max > 0.02 + csum_min1, csum_max1 = calculate_csum(bt_data, 5) + + assert csum_min1 == csum_min + 5 + assert csum_max1 == csum_max + 5 with pytest.raises(ValueError, match='Trade dataframe empty.'): csum_min, csum_max = calculate_csum(DataFrame()) @@ -310,13 +316,16 @@ def test_calculate_max_drawdown2(): # sort by profit and reset index df = df.sort_values('profit').reset_index(drop=True) df1 = df.copy() - drawdown, h, low = calculate_max_drawdown(df, date_col='open_date', value_col='profit') + drawdown, hdate, ldate, hval, lval = calculate_max_drawdown( + df, date_col='open_date', value_col='profit') # Ensure df has not been altered. assert df.equals(df1) assert isinstance(drawdown, float) # High must be before low - assert h < low + assert hdate < ldate + # High value must be higher than low value + assert hval > lval assert drawdown == 0.091755 df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_date']) 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..6b33fa7f2 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) diff --git a/tests/edge/test_edge.py b/tests/edge/test_edge.py index c30bce6a4..5142dd985 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 @@ -337,7 +337,7 @@ def test_edge_process_no_trades(mocker, edge_conf, caplog): mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', 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 trades found.", caplog) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 03cb30d62..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', + }, } @@ -44,6 +49,7 @@ EXCHANGES = { def exchange_conf(): config = get_default_conf((Path(__file__).parent / "testdata").resolve()) config['exchange']['pair_whitelist'] = [] + config['dry_run'] = False return config @@ -99,14 +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 75db2de26..27f4d0db9 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -1,6 +1,7 @@ import copy import logging from datetime import datetime, timedelta, timezone +from math import isclose from random import randint from unittest.mock import MagicMock, Mock, PropertyMock, patch @@ -18,21 +19,13 @@ from freqtrade.exchange.exchange import (market_is_active, timeframe_to_minutes, timeframe_to_next_date, timeframe_to_prev_date, timeframe_to_seconds) from freqtrade.resolvers.exchange_resolver import ExchangeResolver -from tests.conftest import get_patched_exchange, log_has, log_has_re +from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re # Make sure to always keep one exchange here which is NOT subclassed!! EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx'] -# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines -def get_mock_coro(return_value): - async def mock_coro(*args, **kwargs): - return return_value - - return Mock(wraps=mock_coro) - - def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name, fun, mock_ccxt_fun, retries=API_RETRY_COUNT + 1, **kwargs): @@ -378,7 +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 result == 2 / 0.9 + assert isclose(result, 2 * (1+0.05) / (1-abs(stoploss))) # min amount is set markets["ETH/BTC"]["limits"] = { @@ -390,7 +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 result == 2 * 2 / 0.9 + assert isclose(result, 2 * 2 * (1+0.05) / (1-abs(stoploss))) # min amount and cost are set (cost is minimal) markets["ETH/BTC"]["limits"] = { @@ -402,7 +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 result == max(2, 2 * 2) / 0.9 + 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"] = { @@ -414,7 +407,14 @@ 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 result == max(8, 2 * 2) / 0.9 + 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) * 1.5) + + # Really big stoploss + result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1) + assert isclose(result, max(8, 2 * 2) * 1.5) def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None: @@ -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) / 0.9, 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): @@ -498,7 +501,7 @@ def test__load_markets(default_conf, mocker, caplog): mocker.patch('freqtrade.exchange.Exchange._load_async_markets') mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency') Exchange(default_conf) - assert log_has('Unable to initialize markets. Reason: SomeError', caplog) + assert log_has('Unable to initialize markets.', caplog) expected_return = {'ETH/BTC': 'available'} api_mock = MagicMock() @@ -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"] @@ -1245,14 +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() @@ -1276,13 +1271,6 @@ def test_get_balance_prod(default_conf, mocker, exchange_name): 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 +1322,16 @@ 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 +1654,9 @@ 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 @@ -2276,12 +2277,20 @@ def test_get_fee(default_conf, mocker, exchange_name): 'cost': 0.05 }) exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) + exchange._config.pop('fee', None) assert exchange.get_fee('ETH/BTC') == 0.025 + assert api_mock.calculate_fee.call_count == 1 ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name, 'get_fee', 'calculate_fee', symbol="ETH/BTC") + api_mock.calculate_fee.reset_mock() + exchange._config['fee'] = 0.001 + + assert exchange.get_fee('ETH/BTC') == 0.001 + assert api_mock.calculate_fee.call_count == 0 + def test_stoploss_order_unsupported_exchange(default_conf, mocker): exchange = get_patched_exchange(mocker, default_conf, id='bittrex') diff --git a/tests/exchange/test_ftx.py b/tests/exchange/test_ftx.py index 17cfb26fa..494d86e56 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): diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py index df6f22e01..5c789ec1e 100644 --- a/tests/optimize/conftest.py +++ b/tests/optimize/conftest.py @@ -14,6 +14,7 @@ from tests.conftest import patch_exchange def hyperopt_conf(default_conf): hyperconf = deepcopy(default_conf) hyperconf.update({ + 'datadir': Path(default_conf['datadir']), 'hyperopt': 'DefaultHyperOpt', 'hyperopt_loss': 'ShortTradeDurHyperOptLoss', 'hyperopt_path': str(Path(__file__).parent / 'hyperopts'), @@ -21,6 +22,7 @@ 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 daf7c2053..3655b941d 100644 --- a/tests/optimize/test_backtest_detail.py +++ b/tests/optimize/test_backtest_detail.py @@ -1,6 +1,5 @@ # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, C0330, unused-argument import logging -from unittest.mock import MagicMock import pytest @@ -269,7 +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], @@ -489,7 +488,8 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset default_conf["ask_strategy"] = {"use_sell_signal": data.use_sell_signal} - mocker.patch("freqtrade.exchange.Exchange.get_fee", MagicMock(return_value=0.0)) + mocker.patch("freqtrade.exchange.Exchange.get_fee", return_value=0.0) + mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) frame = _build_backtest_dataframe(data.data) backtesting = Backtesting(default_conf) @@ -503,7 +503,6 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: min_date, max_date = get_timerange({pair: frame}) results = backtesting.backtest( processed=data_processed, - stake_amount=default_conf['stake_amount'], start_date=min_date, end_date=max_date, max_open_trades=10, @@ -514,6 +513,6 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: for c, trade in enumerate(data.trades): res = results.iloc[c] - assert res.sell_reason == trade.sell_reason + assert res.sell_reason == trade.sell_reason.value assert res.open_date == _get_frame_time_from_offset(trade.open_tick) assert res.close_date == _get_frame_time_from_offset(trade.close_tick) diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index c8d4338af..4bbfe8a78 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -9,7 +9,6 @@ import pandas as pd import pytest from arrow import Arrow -from freqtrade import constants from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting from freqtrade.configuration import TimeRange from freqtrade.data import history @@ -19,6 +18,7 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history import get_timerange from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.optimize.backtesting import Backtesting +from freqtrade.persistence import LocalTrade from freqtrade.resolvers import StrategyResolver from freqtrade.state import RunMode from freqtrade.strategy.interface import SellType @@ -90,7 +90,6 @@ def simple_backtest(config, contour, mocker, testdatadir) -> None: assert isinstance(processed, dict) results = backtesting.backtest( processed=processed, - stake_amount=config['stake_amount'], start_date=min_date, end_date=max_date, max_open_trades=1, @@ -111,7 +110,6 @@ def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'): min_date, max_date = get_timerange(processed) return { 'processed': processed, - 'stake_amount': conf['stake_amount'], 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 10, @@ -233,8 +231,7 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) -> assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog) -def test_setup_optimize_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None: - default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT +def test_setup_optimize_configuration_stake_amount(mocker, default_conf, caplog) -> None: patched_configuration_load_config_file(mocker, default_conf) @@ -242,9 +239,21 @@ def test_setup_optimize_configuration_unlimited_stake_amount(mocker, default_con 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', + '--stake-amount', '1', + '--starting-balance', '2' ] - with pytest.raises(DependencyException, match=r'.`stake_amount`.*'): + conf = setup_optimize_configuration(get_args(args), RunMode.BACKTEST) + assert isinstance(conf, dict) + + args = [ + 'backtesting', + '--config', 'config.json', + '--strategy', 'DefaultStrategy', + '--stake-amount', '1', + '--starting-balance', '0.5' + ] + with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"): setup_optimize_configuration(get_args(args), RunMode.BACKTEST) @@ -448,9 +457,48 @@ 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: + 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' + backtesting = Backtesting(default_conf) + pair = 'UNITTEST/BTC' + row = [ + pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0), + 1, # Sell + 0.001, # Open + 0.0011, # Close + 0, # Sell + 0.00099, # Low + 0.0012, # High + ] + trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) + assert isinstance(trade, LocalTrade) + assert trade.stake_amount == 495 + + trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=2) + assert trade is 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) + assert trade is None + + # Stake-amount too high! + 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) + assert trade is None + + def test_backtest_one(default_conf, fee, mocker, testdatadir) -> 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) backtesting = Backtesting(default_conf) pair = 'UNITTEST/BTC' @@ -461,7 +509,6 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: min_date, max_date = get_timerange(processed) results = backtesting.backtest( processed=processed, - stake_amount=default_conf['stake_amount'], start_date=min_date, end_date=max_date, max_open_trades=10, @@ -486,7 +533,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: 'trade_duration': [235, 40], 'profit_ratio': [0.0, 0.0], 'profit_abs': [0.0, 0.0], - 'sell_reason': [SellType.ROI, SellType.ROI], + 'sell_reason': [SellType.ROI.value, SellType.ROI.value], 'initial_stop_loss_abs': [0.0940005, 0.09272236], 'initial_stop_loss_ratio': [-0.1, -0.1], 'stop_loss_abs': [0.0940005, 0.09272236], @@ -512,6 +559,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> 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) backtesting = Backtesting(default_conf) @@ -523,7 +571,6 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None min_date, max_date = get_timerange(processed) results = backtesting.backtest( processed=processed, - stake_amount=default_conf['stake_amount'], start_date=min_date, end_date=max_date, max_open_trades=1, @@ -558,6 +605,7 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad default_conf['enable_protections'] = True mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) + mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) tests = [ ['sine', 9], ['raise', 10], @@ -589,6 +637,7 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir, default_conf['protections'] = protections default_conf['enable_protections'] = True + mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) # While buy-signals are unrealistic, running backtesting # over and over again should not cause different results @@ -626,6 +675,7 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir): def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir): + mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC', datadir=testdatadir) @@ -658,6 +708,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0) return dataframe + mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) patch_exchange(mocker) @@ -678,7 +729,6 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) min_date, max_date = get_timerange(processed) backtest_conf = { 'processed': processed, - 'stake_amount': default_conf['stake_amount'], 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 3, @@ -694,7 +744,6 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) backtest_conf = { 'processed': processed, - 'stake_amount': default_conf['stake_amount'], 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 1, @@ -822,6 +871,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat '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] @@ -838,6 +888,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat '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] diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 68eb3d6f7..59bc4aefb 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -12,11 +12,13 @@ import pytest from arrow import Arrow from filelock import Timeout -from freqtrade import constants from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt from freqtrade.data.history import load_data -from freqtrade.exceptions import DependencyException, OperationalException +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.space import SKDecimal from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver from freqtrade.state import RunMode from tests.conftest import (get_args, log_has, log_has_re, patch_exchange, @@ -130,8 +132,7 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo assert log_has('Parameter --print-all detected ...', caplog) -def test_setup_hyperopt_configuration_unlimited_stake_amount(mocker, default_conf) -> None: - default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT +def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None: patched_configuration_load_config_file(mocker, default_conf) @@ -139,9 +140,20 @@ def test_setup_hyperopt_configuration_unlimited_stake_amount(mocker, default_con 'hyperopt', '--config', 'config.json', '--hyperopt', 'DefaultHyperOpt', + '--stake-amount', '1', + '--starting-balance', '2' ] + conf = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT) + assert isinstance(conf, dict) - with pytest.raises(DependencyException, match=r'.`stake_amount`.*'): + args = [ + 'hyperopt', + '--config', 'config.json', + '--strategy', 'DefaultStrategy', + '--stake-amount', '1', + '--starting-balance', '0.5' + ] + with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"): setup_optimize_configuration(get_args(args), RunMode.HYPEROPT) @@ -327,9 +339,9 @@ def test_save_results_saves_epochs(mocker, hyperopt, testdatadir, caplog) -> Non def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> None: epochs = create_results(mocker, hyperopt, testdatadir) - mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs) + mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs) results_file = testdatadir / 'optimize' / 'ut_results.pickle' - hyperopt_epochs = hyperopt._read_results(results_file) + 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() @@ -337,7 +349,7 @@ def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> N def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None: epochs = create_results(mocker, hyperopt, testdatadir) - mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs) + 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 @@ -345,16 +357,16 @@ def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None: results_file = testdatadir / 'optimize' / 'ut_results.pickle' - hyperopt_epochs = hyperopt.load_previous_results(results_file) + hyperopt_epochs = HyperoptTools.load_previous_results(results_file) assert hyperopt_epochs == epochs mock_load.assert_called_once() del epochs[0]['is_best'] - mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs) + mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs) with pytest.raises(OperationalException): - hyperopt.load_previous_results(results_file) + HyperoptTools.load_previous_results(results_file) def test_roi_table_generation(hyperopt) -> None: @@ -444,7 +456,7 @@ def test_format_results(hyperopt): 'is_initial_point': True, } - result = hyperopt._format_explanation_string(results, 1) + 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 %') @@ -458,7 +470,7 @@ def test_format_results(hyperopt): df = pd.DataFrame.from_records(trades, columns=labels) results_metrics = hyperopt._calculate_results_metrics(df) results['total_profit'] = results_metrics['total_profit'] - result = hyperopt._format_explanation_string(results, 1) + result = HyperoptTools._format_explanation_string(results, 1) assert result.find('Total profit 1.00000000 EUR') @@ -1067,7 +1079,7 @@ def test_print_epoch_details(capsys): 'is_best': True } - Hyperopt.print_epoch_details(test_result, 5, False, no_header=True) + HyperoptTools.print_epoch_details(test_result, 5, False, no_header=True) captured = capsys.readouterr() assert '# Trailing stop:' in captured.out # re.match(r"Pairs for .*", captured.out) @@ -1079,3 +1091,34 @@ 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) -> None: + (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) + + 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] diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index 51a78c7cc..8119c732b 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -48,7 +48,7 @@ def test_text_table_bt_results(): ) pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC', - max_open_trades=2, results=results) + starting_balance=4, results=results) assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str @@ -73,11 +73,13 @@ def test_generate_backtest_stats(default_conf, testdatadir): "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': default_conf, 'locks': [], + 'final_balance': 1000.02, 'backtest_start_time': Arrow.utcnow().int_timestamp, 'backtest_end_time': Arrow.utcnow().int_timestamp, } @@ -100,6 +102,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): # Above sample had no loosing trade assert strat_stats['max_drawdown'] == 0.0 + # Retry with losing trade results = {'DefStrat': { 'results': pd.DataFrame( {"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"], @@ -116,18 +119,31 @@ def test_generate_backtest_stats(default_conf, testdatadir): "open_rate": [0.002543, 0.003003, 0.003089, 0.003214], "close_rate": [0.002546, 0.003014, 0.0032903, 0.003217], "trade_duration": [123, 34, 31, 14], - "open_at_end": [False, False, False, True], - "sell_reason": [SellType.ROI, SellType.STOP_LOSS, - SellType.ROI, SellType.FORCE_SELL] + "is_open": [False, False, False, True], + "stake_amount": [0.01, 0.01, 0.01, 0.01], + "sell_reason": [SellType.ROI, SellType.ROI, + SellType.STOP_LOSS, SellType.FORCE_SELL] }), - 'config': default_conf} + 'config': default_conf, + 'locks': [], + 'final_balance': 1000.02, + 'backtest_start_time': Arrow.utcnow().int_timestamp, + 'backtest_end_time': Arrow.utcnow().int_timestamp, + } } - assert strat_stats['max_drawdown'] == 0.0 - assert strat_stats['drawdown_start'] == datetime(1970, 1, 1, tzinfo=timezone.utc) - assert strat_stats['drawdown_end'] == datetime(1970, 1, 1, tzinfo=timezone.utc) - assert strat_stats['drawdown_end_ts'] == 0 - assert strat_stats['drawdown_start_ts'] == 0 + stats = generate_backtest_stats(btdata, results, min_date, max_date) + assert isinstance(stats, dict) + assert 'strategy' in stats + assert 'DefStrat' in stats['strategy'] + assert 'strategy_comparison' in stats + 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_end_ts'] == 1510699380000 + assert strat_stats['drawdown_start_ts'] == 1510697400000 assert strat_stats['pairlist'] == ['UNITTEST/BTC'] # Test storing stats @@ -189,7 +205,7 @@ def test_generate_pair_metrics(): ) pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC', - max_open_trades=2, results=results) + starting_balance=2, results=results) assert isinstance(pair_results, list) assert len(pair_results) == 2 assert pair_results[-1]['key'] == 'TOTAL' @@ -265,7 +281,7 @@ def test_generate_sell_reason_stats(): 'wins': [2, 0, 0], 'draws': [0, 0, 0], 'losses': [0, 0, 1], - 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] + 'sell_reason': [SellType.ROI.value, SellType.ROI.value, SellType.STOP_LOSS.value] } ) @@ -291,6 +307,7 @@ def test_generate_sell_reason_stats(): def test_text_table_strategy(default_conf): default_conf['max_open_trades'] = 2 + default_conf['dry_run_wallet'] = 3 results = {} results['TestStrategy1'] = {'results': pd.DataFrame( { @@ -323,9 +340,9 @@ def test_text_table_strategy(default_conf): '|---------------+--------+----------------+----------------+------------------+' '----------------+----------------+--------+---------+----------|\n' '| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |' - ' 30.00 | 0:17:00 | 3 | 0 | 0 |\n' + ' 36.67 | 0:17:00 | 3 | 0 | 0 |\n' '| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |' - ' 45.00 | 0:20:00 | 3 | 0 | 0 |' + ' 43.33 | 0:20:00 | 3 | 0 | 0 |' ) strategy_results = generate_strategy_metrics(all_results=results) diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index 67cd96f5b..bf225271f 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -407,6 +407,10 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf): {"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 +418,15 @@ 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)) @@ -487,6 +494,8 @@ 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: diff --git a/tests/plugins/test_pairlocks.py b/tests/plugins/test_pairlocks.py index dfcbff0ed..fce3a8cd1 100644 --- a/tests/plugins/test_pairlocks.py +++ b/tests/plugins/test_pairlocks.py @@ -73,9 +73,13 @@ def test_PairLocks(use_db): assert PairLocks.is_pair_locked('XRP/USDT', lock_time + timedelta(minutes=-50)) if use_db: - assert len(PairLock.query.all()) > 0 + locks = PairLocks.get_all_locks() + locks_db = PairLock.query.all() + assert len(locks) == len(locks_db) + assert len(locks_db) > 0 else: # Nothing was pushed to the database + assert len(PairLocks.get_all_locks()) > 0 assert len(PairLock.query.all()) == 0 # Reset use-db variable PairLocks.reset_locks() 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..2d43addff 100644 --- a/tests/rpc/test_fiat_convert.py +++ b/tests/rpc/test_fiat_convert.py @@ -1,44 +1,15 @@ # pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors, # pragma pylint: disable=protected-access, C0103 -import time 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 @@ -47,28 +18,6 @@ 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() @@ -95,8 +44,8 @@ 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 +53,17 @@ 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): diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py index 60d9950aa..6d31e7635 100644 --- a/tests/rpc/test_rpc.py +++ b/tests/rpc/test_rpc.py @@ -1,7 +1,7 @@ # pragma pylint: disable=missing-docstring, C0103 # pragma pylint: disable=invalid-sequence-index, invalid-name, too-many-arguments -from datetime import datetime +from datetime import datetime, timedelta, timezone from unittest.mock import ANY, MagicMock, PropertyMock import pytest @@ -10,6 +10,7 @@ from numpy import isnan from freqtrade.edge import PairInfo from freqtrade.exceptions import ExchangeError, InvalidOrderException, TemporaryError from freqtrade.persistence import Trade +from freqtrade.persistence.pairlock_middleware import PairLocks from freqtrade.rpc import RPC, RPCException from freqtrade.rpc.fiat_convert import CryptoToFiatConverter from freqtrade.state import State @@ -52,7 +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, @@ -72,7 +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, @@ -91,6 +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, @@ -106,7 +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', @@ -119,7 +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, @@ -139,7 +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, @@ -158,6 +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, @@ -173,7 +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', } @@ -412,10 +411,10 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee, stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency) assert prec_satoshi(stats['profit_closed_coin'], 6.217e-05) - assert prec_satoshi(stats['profit_closed_percent'], 6.2) + assert prec_satoshi(stats['profit_closed_percent_mean'], 6.2) assert prec_satoshi(stats['profit_closed_fiat'], 0.93255) assert prec_satoshi(stats['profit_all_coin'], 5.802e-05) - assert prec_satoshi(stats['profit_all_percent'], 2.89) + assert prec_satoshi(stats['profit_all_percent_mean'], 2.89) assert prec_satoshi(stats['profit_all_fiat'], 0.8703) assert stats['trade_count'] == 2 assert stats['first_trade_date'] == 'just now' @@ -481,10 +480,10 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee, stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency) assert prec_satoshi(stats['profit_closed_coin'], 0) - assert prec_satoshi(stats['profit_closed_percent'], 0) + assert prec_satoshi(stats['profit_closed_percent_mean'], 0) assert prec_satoshi(stats['profit_closed_fiat'], 0) assert prec_satoshi(stats['profit_all_coin'], 0) - assert prec_satoshi(stats['profit_all_percent'], 0) + assert prec_satoshi(stats['profit_all_percent_mean'], 0) assert prec_satoshi(stats['profit_all_fiat'], 0) assert stats['trade_count'] == 1 assert stats['first_trade_date'] == 'just now' @@ -570,6 +569,8 @@ 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', @@ -911,6 +912,24 @@ def test_rpcforcebuy_disabled(mocker, default_conf) -> None: rpc._rpc_forcebuy(pair, None) +@pytest.mark.usefixtures("init_persistence") +def test_rpc_delete_lock(mocker, default_conf): + freqtradebot = get_patched_freqtradebot(mocker, default_conf) + rpc = RPC(freqtradebot) + pair = 'ETH/BTC' + + PairLocks.lock_pair(pair, datetime.now(timezone.utc) + timedelta(minutes=4)) + PairLocks.lock_pair(pair, datetime.now(timezone.utc) + timedelta(minutes=5)) + PairLocks.lock_pair(pair, datetime.now(timezone.utc) + timedelta(minutes=10)) + locks = rpc._rpc_locks() + assert locks['lock_count'] == 3 + locks1 = rpc._rpc_delete_lock(lockid=locks['locks'][0]['id']) + assert locks1['lock_count'] == 2 + + locks2 = rpc._rpc_delete_lock(pair=pair) + assert locks2['lock_count'] == 0 + + def test_rpc_whitelist(mocker, default_conf) -> None: mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock()) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index d7d69d0ae..6505629eb 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -23,8 +23,8 @@ from freqtrade.rpc.api_server import ApiServer from freqtrade.rpc.api_server.api_auth import create_token, get_user_from_token from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer from freqtrade.state import RunMode, State -from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, log_has_re, - patch_get_signal) +from tests.conftest import (create_mock_trades, get_mock_coro, get_patched_freqtradebot, log_has, + log_has_re, patch_get_signal) BASE_URI = "/api/v1" @@ -230,7 +230,7 @@ def test_api__init__(default_conf, mocker): assert apiserver._config == default_conf -def test_api_UvicornServer(default_conf, mocker): +def test_api_UvicornServer(mocker): thread_mock = mocker.patch('freqtrade.rpc.api_server.uvicorn_threaded.threading.Thread') s = UvicornServer(uvicorn.Config(MagicMock(), port=8080, host='127.0.0.1')) assert thread_mock.call_count == 0 @@ -248,6 +248,38 @@ def test_api_UvicornServer(default_conf, mocker): assert s.should_exit is True +def test_api_UvicornServer_run(mocker): + serve_mock = mocker.patch('freqtrade.rpc.api_server.uvicorn_threaded.UvicornServer.serve', + get_mock_coro(None)) + s = UvicornServer(uvicorn.Config(MagicMock(), port=8080, host='127.0.0.1')) + assert serve_mock.call_count == 0 + + s.install_signal_handlers() + # Original implementation starts a thread - make sure that's not the case + assert serve_mock.call_count == 0 + + # Fake started to avoid sleeping forever + s.started = True + s.run() + assert serve_mock.call_count == 1 + + +def test_api_UvicornServer_run_no_uvloop(mocker, import_fails): + serve_mock = mocker.patch('freqtrade.rpc.api_server.uvicorn_threaded.UvicornServer.serve', + get_mock_coro(None)) + s = UvicornServer(uvicorn.Config(MagicMock(), port=8080, host='127.0.0.1')) + assert serve_mock.call_count == 0 + + s.install_signal_handlers() + # Original implementation starts a thread - make sure that's not the case + assert serve_mock.call_count == 0 + + # Fake started to avoid sleeping forever + s.started = True + s.run() + assert serve_mock.call_count == 1 + + def test_api_run(default_conf, mocker, caplog): default_conf.update({"api_server": {"enabled": True, "listen_ip_address": "127.0.0.1", @@ -384,10 +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') @@ -418,6 +450,16 @@ def test_api_locks(botclient): assert 'randreason' in (rc.json()['locks'][0]['reason'], rc.json()['locks'][1]['reason']) assert 'deadbeef' in (rc.json()['locks'][0]['reason'], rc.json()['locks'][1]['reason']) + # Test deletions + rc = client_delete(client, f"{BASE_URI}/locks/1") + assert_response(rc) + assert rc.json()['lock_count'] == 1 + + rc = client_post(client, f"{BASE_URI}/locks/delete", + data='{"pair": "XRP/BTC"}') + assert_response(rc) + assert rc.json()['lock_count'] == 0 + def test_api_show_config(botclient, mocker): ftbot, client = botclient @@ -426,7 +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 @@ -468,7 +510,7 @@ def test_api_trades(botclient, mocker, fee, markets): assert rc.json()['trades_count'] == 0 create_mock_trades(fee) - Trade.session.flush() + Trade.query.session.flush() rc = client_get(client, f"{BASE_URI}/trades") assert_response(rc) @@ -480,6 +522,26 @@ def test_api_trades(botclient, mocker, fee, markets): assert rc.json()['trades_count'] == 1 +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): ftbot, client = botclient patch_get_signal(ftbot, (True, False)) @@ -496,7 +558,7 @@ 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' @@ -570,7 +632,7 @@ 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( @@ -585,50 +647,33 @@ 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': 6.2, - '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_percent': 6.2, - '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, } @@ -680,7 +725,7 @@ def test_api_performance(botclient, mocker, ticker, fee): ) trade.close_profit = trade.calc_profit_ratio() - Trade.session.add(trade) + Trade.query.session.add(trade) trade = Trade( pair='XRP/ETH', @@ -695,8 +740,8 @@ 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.query.session.add(trade) + Trade.query.session.flush() rc = client_get(client, f"{BASE_URI}/performance") assert_response(rc) @@ -713,83 +758,75 @@ 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, - 'current_rate': 1.099e-05, + 'close_rate_requested': ANY, 'fee_close': 0.0025, 'fee_close_cost': None, 'fee_close_currency': None, 'fee_open': 0.0025, 'fee_open_cost': None, 'fee_open_currency': None, - 'open_date': ANY, '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"))) @@ -797,7 +834,7 @@ 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']) @@ -879,7 +916,7 @@ 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", @@ -902,11 +939,9 @@ 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', @@ -927,6 +962,7 @@ 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, @@ -943,7 +979,7 @@ def test_api_forcebuy(botclient, mocker, fee): 'sell_order_status': None, 'strategy': 'DefaultStrategy', 'timeframe': 5, - 'exchange': 'bittrex', + 'exchange': 'binance', } @@ -1111,7 +1147,11 @@ 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 922aa2de8..d72ba36ad 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -92,7 +92,8 @@ def test_telegram_init(default_conf, mocker, caplog) -> None: message_str = ("rpc.telegram is listening for following commands: [['status'], ['profit'], " "['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], ['trades'], " "['delete'], ['performance'], ['stats'], ['daily'], ['count'], ['locks'], " - "['reload_config', 'reload_conf'], ['show_config', 'show_conf'], ['stopbuy'], " + "['unlock', 'delete_locks'], ['reload_config', 'reload_conf'], " + "['show_config', 'show_conf'], ['stopbuy'], " "['whitelist'], ['blacklist'], ['logs'], ['edge'], ['help'], ['version']" "]") @@ -176,9 +177,7 @@ 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, @@ -684,12 +683,12 @@ 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, @@ -704,6 +703,7 @@ 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 @@ -744,13 +744,13 @@ 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, @@ -765,6 +765,7 @@ 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 @@ -795,13 +796,13 @@ 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, @@ -816,6 +817,7 @@ 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 @@ -981,6 +983,16 @@ def test_telegram_lock_handle(default_conf, update, ticker, fee, mocker) -> None assert 'deadbeef' in msg_mock.call_args_list[0][0][0] assert 'randreason' in msg_mock.call_args_list[0][0][0] + context = MagicMock() + context.args = ['XRP/BTC'] + msg_mock.reset_mock() + telegram._delete_locks(update=update, context=context) + + assert 'ETH/BTC' in msg_mock.call_args_list[0][0][0] + assert 'randreason' in msg_mock.call_args_list[0][0][0] + assert 'XRP/BTC' not in msg_mock.call_args_list[0][0][0] + assert 'deadbeef' not in msg_mock.call_args_list[0][0][0] + def test_whitelist_static(default_conf, update, mocker) -> None: @@ -1117,8 +1129,10 @@ def test_telegram_trades(mocker, update, default_conf, fee): msg_mock.call_count == 1 assert "2 recent trades:" in msg_mock.call_args_list[0][0][0] assert "Profit (" in msg_mock.call_args_list[0][0][0] - assert "Open Date" in msg_mock.call_args_list[0][0][0] + assert "Close Date" in msg_mock.call_args_list[0][0][0] assert "
" in msg_mock.call_args_list[0][0][0]
+    assert bool(re.search(r"just now[ ]*XRP\/BTC \(#3\)  1.00% \(",
+                msg_mock.call_args_list[0][0][0]))
 
 
 def test_telegram_delete_trade(mocker, update, default_conf, fee):
@@ -1167,7 +1181,7 @@ 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]
 
@@ -1176,7 +1190,7 @@ 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]
 
@@ -1184,8 +1198,9 @@ 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,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY,
+        'trade_id': 1,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 1.099e-05,
         'order_type': 'limit',
@@ -1201,7 +1216,7 @@ 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\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' \
@@ -1228,13 +1243,34 @@ 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,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY_CANCEL,
+        'trade_id': 1,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'reason': CANCEL_REASON['TIMEOUT']
     })
-    assert (msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Bittrex:* '
-            'Cancelling open buy Order for ETH/BTC. Reason: cancelled due to timeout.')
+    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:
@@ -1244,7 +1280,8 @@ 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',
         'gain': 'loss',
@@ -1262,7 +1299,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'close_date': arrow.utcnow(),
     })
     assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
+        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
             '*Amount:* `1333.33333333`\n'
             '*Open Rate:* `0.00007500`\n'
             '*Current Rate:* `0.00003201`\n'
@@ -1273,7 +1310,8 @@ 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',
         'gain': 'loss',
@@ -1290,7 +1328,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'close_date': arrow.utcnow(),
     })
     assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
+        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
             '*Amount:* `1333.33333333`\n'
             '*Open Rate:* `0.00007500`\n'
             '*Current Rate:* `0.00003201`\n'
@@ -1309,24 +1347,27 @@ 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. '
-            '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. 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
 
@@ -1335,7 +1376,7 @@ 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`'
@@ -1344,7 +1385,7 @@ 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`'
@@ -1353,7 +1394,7 @@ 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`'
@@ -1372,8 +1413,9 @@ 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,
-        'exchange': 'Bittrex',
+        'type': RPCMessageType.BUY,
+        'trade_id': 1,
+        'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 1.099e-05,
         'order_type': 'limit',
@@ -1385,7 +1427,7 @@ 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\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'
@@ -1397,7 +1439,8 @@ 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',
         'gain': 'loss',
@@ -1414,7 +1457,7 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
         'open_date': arrow.utcnow().shift(hours=-2, minutes=-35, seconds=-3),
         'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
+    assert msg_mock.call_args[0][0] == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
                                         '*Amount:* `1333.33333333`\n'
                                         '*Open Rate:* `0.00007500`\n'
                                         '*Current Rate:* `0.00003201`\n'
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_interface.py b/tests/strategy/test_interface.py
index f158a1518..78fa368e4 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)
@@ -552,3 +554,69 @@ 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)
+
+    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.enumerate_parameters('sell')]
diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py
index 252288e2e..3b84fc254 100644
--- a/tests/strategy/test_strategy_helpers.py
+++ b/tests/strategy/test_strategy_helpers.py
@@ -1,8 +1,10 @@
+from math import isclose
+
 import numpy as np
 import pandas as pd
 import pytest
 
-from freqtrade.strategy import merge_informative_pair, timeframe_to_minutes
+from freqtrade.strategy import merge_informative_pair, stoploss_from_open, timeframe_to_minutes
 
 
 def generate_test_data(timeframe: str, size: int):
@@ -95,3 +97,38 @@ def test_merge_informative_pair_lower():
 
     with pytest.raises(ValueError, match=r"Tried to merge a faster timeframe .*"):
         merge_informative_pair(data, informative, '1h', '15m', ffill=True)
+
+
+def test_stoploss_from_open():
+    open_price_ranges = [
+        [0.01, 1.00, 30],
+        [1, 100, 30],
+        [100, 10000, 30],
+    ]
+    current_profit_range = [-0.99, 2, 30]
+    desired_stop_range = [-0.50, 0.50, 30]
+
+    for open_range in open_price_ranges:
+        for open_price in np.linspace(*open_range):
+            for desired_stop in np.linspace(*desired_stop_range):
+
+                # -1 is not a valid current_profit, should return 1
+                assert stoploss_from_open(desired_stop, -1) == 1
+
+                for current_profit in np.linspace(*current_profit_range):
+                    current_price = open_price * (1 + current_profit)
+                    expected_stop_price = open_price * (1 + desired_stop)
+
+                    stoploss = stoploss_from_open(desired_stop, current_profit)
+
+                    assert stoploss >= 0
+                    assert stoploss <= 1
+
+                    stop_price = current_price * (1 - stoploss)
+
+                    # there is no correct answer if the expected stop price is above
+                    # the current price
+                    if expected_stop_price > current_price:
+                        assert stoploss == 0
+                    else:
+                        assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
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 94c3e24f6..b2c883108 100644
--- a/tests/test_configuration.py
+++ b/tests/test_configuration.py
@@ -430,7 +430,8 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
         '--enable-position-stacking',
         '--disable-max-market-positions',
         '--timerange', ':100',
-        '--export', '/bar/foo'
+        '--export', '/bar/foo',
+        '--stake-amount', 'unlimited'
     ]
 
     args = Arguments(arglist).get_parsed_arg()
@@ -463,6 +464,8 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
 
     assert 'export' in config
     assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog)
+    assert 'stake_amount' in config
+    assert config['stake_amount'] == 'unlimited'
 
 
 def test_setup_configuration_with_stratlist(mocker, default_conf, caplog) -> None:
@@ -562,7 +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()
 
@@ -787,6 +790,38 @@ def test_validate_max_open_trades(default_conf):
         validate_config_consistency(default_conf)
 
 
+def test_validate_price_side(default_conf):
+    default_conf['order_types'] = {
+        "buy": "limit",
+        "sell": "limit",
+        "stoploss": "limit",
+        "stoploss_on_exchange": False,
+    }
+    # Default should pass
+    validate_config_consistency(default_conf)
+
+    conf = deepcopy(default_conf)
+    conf['order_types']['buy'] = 'market'
+    with pytest.raises(OperationalException,
+                       match='Market buy orders require bid_strategy.price_side = "ask".'):
+        validate_config_consistency(conf)
+
+    conf = deepcopy(default_conf)
+    conf['order_types']['sell'] = 'market'
+    with pytest.raises(OperationalException,
+                       match='Market sell orders require ask_strategy.price_side = "bid".'):
+        validate_config_consistency(conf)
+
+    # Validate inversed case
+    conf = deepcopy(default_conf)
+    conf['order_types']['sell'] = 'market'
+    conf['order_types']['buy'] = 'market'
+    conf['ask_strategy']['price_side'] = 'bid'
+    conf['bid_strategy']['price_side'] = 'ask'
+
+    validate_config_consistency(conf)
+
+
 def test_validate_tsl(default_conf):
     default_conf['stoploss'] = 0.0
     with pytest.raises(OperationalException, match='The config stoploss needs to be different '
@@ -825,22 +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,
@@ -983,6 +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'
 
 
@@ -1019,37 +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()
@@ -1062,7 +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 3bd2f5607..44791f928 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -94,6 +94,7 @@ def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
         'stoploss': 'limit',
         'stoploss_on_exchange': True,
     }
+    conf['bid_strategy']['price_side'] = 'ask'
 
     freqtrade = FreqtradeBot(conf)
     assert freqtrade.strategy.order_types['stoploss_on_exchange']
@@ -128,6 +129,7 @@ def test_order_dict_live(default_conf, mocker, caplog) -> None:
         'stoploss': 'limit',
         'stoploss_on_exchange': True,
     }
+    conf['bid_strategy']['price_side'] = 'ask'
 
     freqtrade = FreqtradeBot(conf)
     assert not log_has_re(".*stoploss_on_exchange .* dry-run", caplog)
@@ -205,65 +207,6 @@ def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_b
                                                          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
-
-
 def test_edge_called_in_process(mocker, edge_conf) -> None:
     patch_RPCManager(mocker)
     patch_edge(mocker)
@@ -419,7 +362,7 @@ 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)
@@ -678,12 +621,13 @@ 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
     )
 
 
@@ -766,7 +710,7 @@ 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,
@@ -774,9 +718,9 @@ 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,
@@ -784,7 +728,7 @@ 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
@@ -837,17 +781,17 @@ def test_process_informative_pairs_added(default_conf, ticker, mocker) -> None:
     ('ask', 4, 5, None, 0.5, 4),  # last not available - uses ask
     ('ask', 4, 5, None, 1, 4),  # last not available - uses ask
     ('ask', 4, 5, None, 0, 4),  # last not available - uses ask
-    ('bid', 10, 20, 10, 0.0, 20),  # Full bid side
-    ('bid', 10, 20, 10, 1.0, 10),  # Full last side
-    ('bid', 10, 20, 10, 0.5, 15),  # Between bid and last
-    ('bid', 10, 20, 10, 0.7, 13),  # Between bid and last
-    ('bid', 10, 20, 10, 0.3, 17),  # Between bid and last
-    ('bid', 4, 5, 10, 1.0, 5),  # last bigger than bid
-    ('bid', 4, 5, 10, 0.5, 5),  # last bigger than bid
-    ('bid', 10, 20, None, 0.5, 20),  # last not available - uses bid
-    ('bid', 4, 5, None, 0.5, 5),  # last not available - uses bid
-    ('bid', 4, 5, None, 1, 5),  # last not available - uses bid
-    ('bid', 4, 5, None, 0, 5),  # last not available - uses bid
+    ('bid', 21, 20, 10, 0.0, 20),  # Full bid side
+    ('bid', 21, 20, 10, 1.0, 10),  # Full last side
+    ('bid', 21, 20, 10, 0.5, 15),  # Between bid and last
+    ('bid', 21, 20, 10, 0.7, 13),  # Between bid and last
+    ('bid', 21, 20, 10, 0.3, 17),  # Between bid and last
+    ('bid', 6, 5, 10, 1.0, 5),  # last bigger than bid
+    ('bid', 6, 5, 10, 0.5, 5),  # last bigger than bid
+    ('bid', 21, 20, None, 0.5, 20),  # last not available - uses bid
+    ('bid', 6, 5, None, 0.5, 5),  # last not available - uses bid
+    ('bid', 6, 5, None, 1, 5),  # last not available - uses bid
+    ('bid', 6, 5, None, 0, 5),  # last not available - uses bid
 ])
 def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
                       last, last_ab, expected) -> None:
@@ -856,7 +800,7 @@ def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
     default_conf['bid_strategy']['price_side'] = side
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={'ask': ask, 'last': last, 'bid': bid}))
+                 return_value={'ask': ask, 'last': last, 'bid': bid})
 
     assert freqtrade.get_buy_rate('ETH/BTC', True) == expected
     assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
@@ -1025,7 +969,7 @@ 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
@@ -1057,6 +1001,9 @@ 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)
@@ -1081,7 +1028,7 @@ 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
@@ -1094,7 +1041,7 @@ 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
@@ -1120,14 +1067,14 @@ 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
@@ -1139,9 +1086,9 @@ 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
 
@@ -1151,7 +1098,7 @@ 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
 
@@ -1171,6 +1118,9 @@ 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()),
     )
@@ -1205,6 +1155,9 @@ 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()),
     )
@@ -1250,6 +1203,9 @@ 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)
@@ -1287,6 +1243,9 @@ 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),
     )
@@ -1327,7 +1286,7 @@ 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
@@ -1342,8 +1301,8 @@ 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
@@ -1390,6 +1349,9 @@ 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),
     )
@@ -1425,9 +1387,9 @@ 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', 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)
 
@@ -1436,8 +1398,8 @@ 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)
@@ -1459,6 +1421,9 @@ 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),
     )
@@ -1499,7 +1464,7 @@ 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
@@ -1513,8 +1478,8 @@ 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
@@ -1745,6 +1710,7 @@ 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)
@@ -1777,7 +1743,6 @@ 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(
@@ -1803,7 +1768,6 @@ 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(
@@ -1866,7 +1830,6 @@ 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()
@@ -2108,7 +2071,7 @@ 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()
@@ -2159,7 +2122,7 @@ 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
@@ -2189,7 +2152,7 @@ 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()
@@ -2216,7 +2179,7 @@ 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()
@@ -2243,9 +2206,10 @@ def test_check_handle_timedout_sell_usercustom(default_conf, ticker, limit_sell_
 
     open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
     open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    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
@@ -2290,9 +2254,10 @@ def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old,
 
     open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
     open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    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
@@ -2323,7 +2288,7 @@ 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()
@@ -2349,13 +2314,13 @@ 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
@@ -2382,7 +2347,7 @@ 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()
@@ -2390,7 +2355,7 @@ 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
@@ -2422,7 +2387,7 @@ 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()
@@ -2430,7 +2395,7 @@ 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
@@ -2459,7 +2424,7 @@ 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, "
@@ -2482,7 +2447,6 @@ 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'
     limit_buy_order['filled'] = 0.0
@@ -2516,7 +2480,6 @@ 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'
@@ -2545,7 +2508,6 @@ 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'
     limit_buy_order['filled'] = 0.0
@@ -2662,8 +2624,8 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> N
     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,
@@ -2678,6 +2640,7 @@ 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
 
 
@@ -2711,9 +2674,9 @@ def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker)
     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,
@@ -2728,6 +2691,7 @@ 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
 
 
@@ -2768,9 +2732,9 @@ def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fe
     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,
@@ -2785,7 +2749,7 @@ 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
 
 
@@ -2794,7 +2758,7 @@ def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee, c
     mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
                  side_effect=InvalidOrderException())
     mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=300))
-    sellmock = MagicMock()
+    sellmock = MagicMock(return_value={'id': '12345555'})
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -2808,7 +2772,6 @@ 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
@@ -2870,7 +2833,7 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticke
     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,
@@ -2938,7 +2901,10 @@ 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,
@@ -2972,12 +2938,12 @@ def test_execute_sell_market_order(default_conf, ticker, fee,
     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,
@@ -2992,6 +2958,7 @@ 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
 
@@ -3960,7 +3927,7 @@ 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
 
@@ -4108,22 +4075,33 @@ def test_order_book_ask_strategy(default_conf, limit_buy_order_open, limit_buy_o
     assert log_has('Sell Price at location 1 from orderbook could not be determined.', caplog)
 
 
-@pytest.mark.parametrize('side,ask,bid,expected', [
-    ('bid', 10.0, 11.0, 11.0),
-    ('bid', 10.0, 11.2, 11.2),
-    ('bid', 10.0, 11.0, 11.0),
-    ('bid', 9.8, 11.0, 11.0),
-    ('bid', 0.0001, 0.002, 0.002),
-    ('ask', 10.0, 11.0, 10.0),
-    ('ask', 10.11, 11.2, 10.11),
-    ('ask', 0.001, 0.002, 0.001),
-    ('ask', 0.006, 1.0, 0.006),
+@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', [
+    ('bid', 12.0, 11.0, 11.5, 0.0, 11.0),  # full bid side
+    ('bid', 12.0, 11.0, 11.5, 1.0, 11.5),  # full last side
+    ('bid', 12.0, 11.0, 11.5, 0.5, 11.25),  # between bid and lat
+    ('bid', 12.0, 11.2, 10.5, 0.0, 11.2),  # Last smaller than bid
+    ('bid', 12.0, 11.2, 10.5, 1.0, 11.2),  # Last smaller than bid - uses bid
+    ('bid', 12.0, 11.2, 10.5, 0.5, 11.2),  # Last smaller than bid - uses bid
+    ('bid', 0.003, 0.002, 0.005, 0.0, 0.002),
+    ('ask', 12.0, 11.0, 12.5, 0.0, 12.0),  # full ask side
+    ('ask', 12.0, 11.0, 12.5, 1.0, 12.5),  # full last side
+    ('ask', 12.0, 11.0, 12.5, 0.5, 12.25),  # between bid and lat
+    ('ask', 12.2, 11.2, 10.5, 0.0, 12.2),  # Last smaller than ask
+    ('ask', 12.0, 11.0, 10.5, 1.0, 12.0),  # Last smaller than ask - uses ask
+    ('ask', 12.0, 11.2, 10.5, 0.5, 12.0),  # Last smaller than ask - uses ask
+    ('ask', 10.0, 11.0, 11.0, 0.0, 10.0),
+    ('ask', 10.11, 11.2, 11.0, 0.0, 10.11),
+    ('ask', 0.001, 0.002, 11.0, 0.0, 0.001),
+    ('ask', 0.006, 1.0, 11.0, 0.0, 0.006),
 ])
-def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask, expected) -> None:
+def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask,
+                       last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
 
     default_conf['ask_strategy']['price_side'] = side
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'ask': ask, 'bid': bid})
+    default_conf['ask_strategy']['bid_last_balance'] = last_ab
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 return_value={'ask': ask, 'bid': bid, 'last': last})
     pair = "ETH/BTC"
 
     # Test regular mode
@@ -4182,7 +4160,7 @@ def test_get_sell_rate_exception(default_conf, mocker, caplog):
     default_conf['ask_strategy']['price_side'] = 'ask'
     pair = "ETH/BTC"
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 return_value={'ask': None, 'bid': 0.12})
+                 return_value={'ask': None, 'bid': 0.12, 'last': None})
     ft = get_patched_freqtradebot(mocker, default_conf)
     with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
         ft.get_sell_rate(pair, True)
@@ -4191,7 +4169,7 @@ def test_get_sell_rate_exception(default_conf, mocker, caplog):
     assert ft.get_sell_rate(pair, True) == 0.12
     # Reverse sides
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 return_value={'ask': 0.13, 'bid': None})
+                 return_value={'ask': 0.13, 'bid': None, 'last': None})
     with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
         ft.get_sell_rate(pair, True)
 
@@ -4405,9 +4383,9 @@ 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..1c60faa7b 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -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)
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 d0d29f142..dad0e275e 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -1,5 +1,8 @@
 # pragma pylint: disable=missing-docstring, C0103
 import logging
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from types import FunctionType
 from unittest.mock import MagicMock
 
 import arrow
@@ -8,25 +11,26 @@ from sqlalchemy import create_engine
 
 from freqtrade import constants
 from freqtrade.exceptions import DependencyException, OperationalException
-from freqtrade.persistence import Order, Trade, clean_dry_run_db, init_db
+from freqtrade.persistence import LocalTrade, Order, Trade, clean_dry_run_db, init_db
 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, mocker):
+def test_init_custom_db_url(default_conf, tmpdir):
     # Update path to a value other than default, but still in-memory
-    default_conf.update({'db_url': 'sqlite:///tmp/freqtrade2_test.sqlite'})
-    create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock())
+    filename = f"{tmpdir}/freqtrade2_test.sqlite"
+    assert not Path(filename).is_file()
+
+    default_conf.update({'db_url': f'sqlite:///{filename}'})
 
     init_db(default_conf['db_url'], default_conf['dry_run'])
-    assert create_engine_mock.call_count == 1
-    assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tmp/freqtrade2_test.sqlite'
+    assert Path(filename).is_file()
 
 
 def test_init_invalid_db_url(default_conf):
@@ -47,19 +51,20 @@ def test_init_prod_db(default_conf, mocker):
     assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tradesv3.sqlite'
 
 
-def test_init_dryrun_db(default_conf, mocker):
-    default_conf.update({'dry_run': True})
-    default_conf.update({'db_url': constants.DEFAULT_DB_DRYRUN_URL})
-
-    create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock())
+def test_init_dryrun_db(default_conf, tmpdir):
+    filename = f"{tmpdir}/freqtrade2_prod.sqlite"
+    assert not Path(filename).is_file()
+    default_conf.update({
+        'dry_run': True,
+        'db_url': f'sqlite:///{filename}'
+    })
 
     init_db(default_conf['db_url'], default_conf['dry_run'])
-    assert create_engine_mock.call_count == 1
-    assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tradesv3.dryrun.sqlite'
+    assert Path(filename).is_file()
 
 
 @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.
 
@@ -97,7 +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
@@ -137,7 +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'
@@ -172,7 +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'
@@ -200,7 +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
@@ -228,7 +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'
@@ -245,7 +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
@@ -269,7 +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'):
@@ -285,7 +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
@@ -306,7 +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
@@ -331,7 +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
@@ -365,7 +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
@@ -383,6 +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):
@@ -395,10 +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',
@@ -407,10 +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(
@@ -420,10 +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
@@ -458,7 +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,
@@ -467,7 +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,
@@ -495,7 +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
@@ -689,7 +697,7 @@ 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,
     )
@@ -741,7 +749,7 @@ 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,
     )
 
@@ -785,7 +793,7 @@ 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()
@@ -794,11 +802,9 @@ 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,
@@ -838,7 +844,7 @@ def test_to_json(default_conf, fee):
                       'max_rate': None,
                       'strategy': None,
                       'timeframe': None,
-                      'exchange': 'bittrex',
+                      'exchange': 'binance',
                       }
 
     # Simulate dry_run entries
@@ -853,17 +859,15 @@ 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,
@@ -905,7 +909,7 @@ def test_to_json(default_conf, fee):
                       'sell_order_status': None,
                       'strategy': None,
                       'timeframe': None,
-                      'exchange': 'bittrex',
+                      'exchange': 'binance',
                       }
 
 
@@ -918,7 +922,7 @@ 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,
     )
@@ -928,7 +932,7 @@ 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)
@@ -977,7 +981,7 @@ 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,
     )
@@ -1016,7 +1020,7 @@ 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,
     )
@@ -1039,14 +1043,45 @@ def test_fee_updated(fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_total_open_trades_stakes(fee):
+@pytest.mark.parametrize('use_db', [True, False])
+def test_total_open_trades_stakes(fee, use_db):
 
+    Trade.use_db = use_db
+    Trade.reset_trades()
     res = Trade.total_open_trades_stakes()
     assert res == 0
-    create_mock_trades(fee)
+    create_mock_trades(fee, use_db)
     res = Trade.total_open_trades_stakes()
     assert res == 0.004
 
+    Trade.use_db = True
+
+
+@pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('use_db', [True, False])
+def test_get_trades_proxy(fee, use_db):
+    Trade.use_db = use_db
+    Trade.reset_trades()
+    create_mock_trades(fee, use_db)
+    trades = Trade.get_trades_proxy()
+    assert len(trades) == 6
+
+    assert isinstance(trades[0], Trade)
+
+    trades = Trade.get_trades_proxy(is_open=True)
+    assert len(trades) == 4
+    assert trades[0].is_open
+    trades = Trade.get_trades_proxy(is_open=False)
+
+    assert len(trades) == 2
+    assert not trades[0].is_open
+
+    opendate = datetime.now(tz=timezone.utc) - timedelta(minutes=15)
+
+    assert len(Trade.get_trades_proxy(open_date=opendate)) == 3
+
+    Trade.use_db = True
+
 
 @pytest.mark.usefixtures("init_persistence")
 def test_get_overall_performance(fee):
@@ -1172,3 +1207,25 @@ def test_select_order(fee):
     assert order.ft_order_side == 'stoploss'
     order = trades[4].select_order('sell', False)
     assert order is None
+
+
+def test_Trade_object_idem():
+
+    assert issubclass(Trade, LocalTrade)
+
+    trade = vars(Trade)
+    localtrade = vars(LocalTrade)
+
+    # 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')):
+            assert item in localtrade
+
+    # Fails if only a column is added without corresponding parent field
+    for item in localtrade:
+        if (not item.startswith('__')
+                and item not in ('trades', 'trades_open', 'total_profit')
+                and type(getattr(LocalTrade, item)) not in (property, FunctionType)):
+            assert item in trade
diff --git a/tests/test_timerange.py b/tests/test_timerange.py
index 5c35535f0..dcdaad09d 100644
--- a/tests/test_timerange.py
+++ b/tests/test_timerange.py
@@ -3,6 +3,7 @@ import arrow
 import pytest
 
 from freqtrade.configuration import TimeRange
+from freqtrade.exceptions import OperationalException
 
 
 def test_parse_timerange_incorrect():
@@ -27,9 +28,13 @@ def test_parse_timerange_incorrect():
     timerange = TimeRange.parse_timerange('-1231006505000')
     assert TimeRange(None, 'date', 0, 1231006505) == timerange
 
-    with pytest.raises(Exception, match=r'Incorrect syntax.*'):
+    with pytest.raises(OperationalException, match=r'Incorrect syntax.*'):
         TimeRange.parse_timerange('-')
 
+    with pytest.raises(OperationalException,
+                       match=r'Start date is after stop date for timerange.*'):
+        TimeRange.parse_timerange('20100523-20100522')
+
 
 def test_subtract_start():
     x = TimeRange('date', 'date', 1274486400, 1438214400)
diff --git a/tests/test_wallets.py b/tests/test_wallets.py
index b7aead0c4..562957790 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 +111,55 @@ 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', freqtrade.get_free_open_trades())
+
+
+@pytest.mark.parametrize("balance_ratio,result1", [
+                        (1, 50),
+                        (0.99, 49.5),
+                        (0.50, 25),
+])
+def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, result1,
+                                                 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', 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/USDT', result)
+
+    result = freqtrade.wallets.get_trade_stake_amount('LTC/USDDT', 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/USDT', freqtrade.get_free_open_trades())
+    assert result == 0
+
+    # set max_open_trades = None, so do not trade
+    freqtrade.config['max_open_trades'] = 0
+    result = freqtrade.wallets.get_trade_stake_amount('NEO/USDT', freqtrade.get_free_open_trades())
+    assert result == 0