diff --git a/.github/ISSUE_TEMPLATE/question.md b/.github/ISSUE_TEMPLATE/question.md index f87b78f29..fd3d7df93 100644 --- a/.github/ISSUE_TEMPLATE/question.md +++ b/.github/ISSUE_TEMPLATE/question.md @@ -1,5 +1,5 @@ --- -name: BQuestion +name: Question about: Ask a question you could not find an answer in the docs title: '' labels: "Question" diff --git a/.gitignore b/.gitignore index f206fce66..4720ff5cb 100644 --- a/.gitignore +++ b/.gitignore @@ -8,6 +8,7 @@ user_data/* user_data/notebooks/* freqtrade-plot.html freqtrade-profit-plot.html +freqtrade/rpc/api_server/ui/* # Byte-compiled / optimized / DLL files __pycache__/ diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index afa41ed33..c29d6e632 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -12,7 +12,7 @@ Few pointers for contributions: - New features need to contain unit tests, must conform to PEP8 (max-line-length = 100) and should be documented with the introduction PR. - PR's can be declared as `[WIP]` - which signify Work in Progress Pull Requests (which are not finished). -If you are unsure, discuss the feature on our [discord server](https://discord.gg/MA9v74M), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-l9d9iqgl-9cVBIeBkCBa8j6upSmd_NA) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR. +If you are unsure, discuss the feature on our [discord server](https://discord.gg/MA9v74M), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR. ## Getting started diff --git a/Dockerfile b/Dockerfile index 602e6a28c..4b399174b 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM python:3.8.6-slim-buster as base +FROM python:3.9.2-slim-buster as base # Setup env ENV LANG C.UTF-8 @@ -40,7 +40,9 @@ COPY --from=python-deps /root/.local /root/.local # Install and execute COPY . /freqtrade/ RUN pip install -e . --no-cache-dir \ - && mkdir /freqtrade/user_data/ + && mkdir /freqtrade/user_data/ \ + && freqtrade install-ui + ENTRYPOINT ["freqtrade"] # Default to trade mode CMD [ "trade" ] diff --git a/Dockerfile.armhf b/Dockerfile.armhf index b6f2e44e6..f938ec457 100644 --- a/Dockerfile.armhf +++ b/Dockerfile.armhf @@ -41,7 +41,9 @@ COPY --from=python-deps /root/.local /root/.local # Install and execute COPY . /freqtrade/ -RUN pip install -e . --no-cache-dir +RUN pip install -e . --no-cache-dir \ + && freqtrade install-ui + ENTRYPOINT ["freqtrade"] # Default to trade mode CMD [ "trade" ] diff --git a/MANIFEST.in b/MANIFEST.in index 2f59bcc7a..adbcd2e30 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -2,3 +2,5 @@ include LICENSE include README.md recursive-include freqtrade *.py recursive-include freqtrade/templates/ *.j2 *.ipynb +include freqtrade/rpc/api_server/ui/fallback_file.html +include freqtrade/rpc/api_server/ui/favicon.ico diff --git a/README.md b/README.md index db648198f..c3a665c47 100644 --- a/README.md +++ b/README.md @@ -22,12 +22,21 @@ expect. We strongly recommend you to have coding and Python knowledge. Do not hesitate to read the source code and understand the mechanism of this bot. -## Exchange marketplaces supported +## Supported Exchange marketplaces + +Please read the [exchange specific notes](docs/exchanges.md) to learn about eventual, special configurations needed for each exchange. - [X] [Bittrex](https://bittrex.com/) - [X] [Binance](https://www.binance.com/) ([*Note for binance users](docs/exchanges.md#blacklists)) - [X] [Kraken](https://kraken.com/) -- [ ] [113 others to tests](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_ +- [X] [FTX](https://ftx.com) +- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_ + +### Community tested + +Exchanges confirmed working by the community: + +- [X] [Bitvavo](https://bitvavo.com/) ## Documentation @@ -39,7 +48,7 @@ Please find the complete documentation on our [website](https://www.freqtrade.io - [x] **Based on Python 3.7+**: For botting on any operating system - Windows, macOS and Linux. - [x] **Persistence**: Persistence is achieved through sqlite. -- [x] **Dry-run**: Run the bot without playing money. +- [x] **Dry-run**: Run the bot without paying money. - [x] **Backtesting**: Run a simulation of your buy/sell strategy. - [x] **Strategy Optimization by machine learning**: Use machine learning to optimize your buy/sell strategy parameters with real exchange data. - [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/latest/edge/). @@ -138,7 +147,7 @@ For any questions not covered by the documentation or for further information ab Please check out our [discord server](https://discord.gg/MA9v74M). -You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-l9d9iqgl-9cVBIeBkCBa8j6upSmd_NA). +You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). ### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue) @@ -169,7 +178,7 @@ to understand the requirements before sending your pull-requests. Coding is not a necessity to contribute - maybe start with improving our documentation? Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/good%20first%20issue) can be good first contributions, and will help get you familiar with the codebase. -**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/MA9v74M) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-k9o2v5ut-jX8Mc4CwNM8CDc2Dyg96YA). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it. +**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/MA9v74M) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it. **Important:** Always create your PR against the `develop` branch, not `stable`. @@ -191,5 +200,5 @@ To run this bot we recommend you a cloud instance with a minimum of: - [pip](https://pip.pypa.io/en/stable/installing/) - [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) - [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) -- [virtualenv](https://virtualenv.pypa.io/en/stable/installation/) (Recommended) +- [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended) - [Docker](https://www.docker.com/products/docker) (Recommended) diff --git a/build_helpers/publish_docker.sh b/build_helpers/publish_docker.sh index 9bc1aa0a6..d987bcc69 100755 --- a/build_helpers/publish_docker.sh +++ b/build_helpers/publish_docker.sh @@ -51,6 +51,8 @@ fi docker images docker push ${IMAGE_NAME} +docker push ${IMAGE_NAME}:$TAG_PLOT +docker push ${IMAGE_NAME}:$TAG if [ $? -ne 0 ]; then echo "failed pushing repo" return 1 diff --git a/config_binance.json.example b/config_binance.json.example index 83c9748d7..4fa615d6d 100644 --- a/config_binance.json.example +++ b/config_binance.json.example @@ -12,15 +12,15 @@ "sell": 30 }, "bid_strategy": { - "use_order_book": false, "ask_last_balance": 0.0, + "use_order_book": false, "order_book_top": 1, "check_depth_of_market": { "enabled": false, "bids_to_ask_delta": 1 } }, - "ask_strategy":{ + "ask_strategy": { "use_order_book": false, "order_book_min": 1, "order_book_max": 1, diff --git a/docker-compose.yml b/docker-compose.yml index 7094500b4..1f63059f0 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -14,6 +14,11 @@ services: container_name: freqtrade volumes: - "./user_data:/freqtrade/user_data" + # Expose api on port 8080 (localhost only) + # Please read the https://www.freqtrade.io/en/latest/rest-api/ documentation + # before enabling this. + # ports: + # - "127.0.0.1:8080:8080" # Default command used when running `docker compose up` command: > trade diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md index 1ace61769..d2237b3e8 100644 --- a/docs/advanced-hyperopt.md +++ b/docs/advanced-hyperopt.md @@ -40,6 +40,11 @@ For the sample below, you then need to add the command line parameter `--hyperop A sample of this can be found below, which is identical to the Default Hyperopt loss implementation. A full sample can be found in [userdata/hyperopts](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_loss.py). ``` python +from datetime import datetime +from typing import Dict + +from pandas import DataFrame + from freqtrade.optimize.hyperopt import IHyperOptLoss TARGET_TRADES = 600 @@ -54,6 +59,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss): @staticmethod def hyperopt_loss_function(results: DataFrame, trade_count: int, min_date: datetime, max_date: datetime, + config: Dict, processed: Dict[str, DataFrame], *args, **kwargs) -> float: """ Objective function, returns smaller number for better results @@ -63,7 +69,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss): * 0.25: Avoiding trade loss * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above """ - total_profit = results['profit_percent'].sum() + total_profit = results['profit_ratio'].sum() trade_duration = results['trade_duration'].mean() trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8) @@ -77,10 +83,12 @@ Currently, the arguments are: * `results`: DataFrame containing the result The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`): - `pair, profit_percent, profit_abs, open_date, open_rate, open_fee, close_date, close_rate, close_fee, amount, trade_duration, open_at_end, sell_reason` + `pair, profit_ratio, profit_abs, open_date, open_rate, fee_open, close_date, close_rate, fee_close, amount, trade_duration, is_open, sell_reason, stake_amount, min_rate, max_rate, stop_loss_ratio, stop_loss_abs` * `trade_count`: Amount of trades (identical to `len(results)`) -* `min_date`: Start date of the hyperopting TimeFrame -* `min_date`: End date of the hyperopting TimeFrame +* `min_date`: Start date of the timerange used +* `min_date`: End date of the timerange used +* `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space). +* `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting. This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you. diff --git a/docs/backtesting.md b/docs/backtesting.md index 27bfebe37..a14c8f2e4 100644 --- a/docs/backtesting.md +++ b/docs/backtesting.md @@ -5,6 +5,89 @@ This page explains how to validate your strategy performance by using Backtestin Backtesting requires historic data to be available. 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. +## Backtesting command reference + +``` +usage: freqtrade backtesting [-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] + [--eps] [--dmmp] [--enable-protections] + [--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`). + --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. + --stake-amount STAKE_AMOUNT + Override the value of the `stake_amount` configuration + setting. + --fee FLOAT Specify fee ratio. Will be applied twice (on trade + entry and exit). + --eps, --enable-position-stacking + Allow buying the same pair multiple times (position + stacking). + --dmmp, --disable-max-market-positions + Disable applying `max_open_trades` during backtest + (same as setting `max_open_trades` to a very high + number). + --enable-protections, --enableprotections + Enable protections for backtesting.Will slow + backtesting down by a considerable amount, but will + include configured protections + --strategy-list STRATEGY_LIST [STRATEGY_LIST ...] + Provide a space-separated list of strategies to + backtest. Please note that ticker-interval needs to be + set either in config or via command line. When using + this together with `--export trades`, the strategy- + name is injected into the filename (so `backtest- + data.json` becomes `backtest-data- + DefaultStrategy.json` + --export EXPORT Export backtest results, argument are: trades. + Example: `--export=trades` + --export-filename PATH + Save backtest results to the file with this filename. + Requires `--export` to be set as well. Example: + `--export-filename=user_data/backtest_results/backtest + _today.json` + +Common arguments: + -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). + --logfile FILE Log to the file specified. Special values are: + 'syslog', 'journald'. See the documentation for more + details. + -V, --version show program's version number and exit + -c PATH, --config PATH + Specify configuration file (default: + `userdir/config.json` or `config.json` whichever + exists). Multiple --config options may be used. Can be + set to `-` to read config from stdin. + -d PATH, --datadir PATH + Path to directory with historical backtesting data. + --userdir PATH, --user-data-dir PATH + Path to userdata directory. + +Strategy arguments: + -s NAME, --strategy NAME + Specify strategy class name which will be used by the + bot. + --strategy-path PATH Specify additional strategy lookup path. + +``` + ## Test your strategy with Backtesting Now you have good Buy and Sell strategies and some historic data, you want to test it against @@ -20,7 +103,7 @@ The result of backtesting will confirm if your bot has better odds of making a p !!! 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. - Please read the [pairlists documentation](configuration.md#pairlists) for more information. + Please read the [pairlists documentation](plugins.md#pairlists) for more information. To achieve reproducible results, best generate a pairlist via the [`test-pairlist`](utils.md#test-pairlist) command and use that as static pairlist. @@ -262,9 +345,9 @@ 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`) - to clearly see settings for this. +- `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 per stake amount. Aligned to the TOTAL column of the first table. +- `Total Profit %`: Total profit. Aligned to the `TOTAL` row's `Tot Profit %` from the first table. - `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). - `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 diff --git a/docs/bot-basics.md b/docs/bot-basics.md index 86fb18645..30a25d4fc 100644 --- a/docs/bot-basics.md +++ b/docs/bot-basics.md @@ -4,6 +4,7 @@ This page provides you some basic concepts on how Freqtrade works and operates. ## Freqtrade terminology +* Strategy: Your trading strategy, telling the bot what to do. * Trade: Open position. * Open Order: Order which is currently placed on the exchange, and is not yet complete. * Pair: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT). diff --git a/docs/bot-usage.md b/docs/bot-usage.md index 5820b3cc7..c7fe8634d 100644 --- a/docs/bot-usage.md +++ b/docs/bot-usage.md @@ -205,258 +205,6 @@ in production mode. Example command: freqtrade trade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite ``` -## Backtesting commands - -Backtesting also uses the config specified via `-c/--config`. - -``` -usage: freqtrade backtesting [-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] - [--eps] [--dmmp] [--enable-protections] - [--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`). - --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. - --stake-amount STAKE_AMOUNT - Override the value of the `stake_amount` configuration - setting. - --fee FLOAT Specify fee ratio. Will be applied twice (on trade - entry and exit). - --eps, --enable-position-stacking - Allow buying the same pair multiple times (position - stacking). - --dmmp, --disable-max-market-positions - Disable applying `max_open_trades` during backtest - (same as setting `max_open_trades` to a very high - number). - --enable-protections, --enableprotections - Enable protections for backtesting.Will slow - backtesting down by a considerable amount, but will - include configured protections - --strategy-list STRATEGY_LIST [STRATEGY_LIST ...] - Provide a space-separated list of strategies to - backtest. Please note that ticker-interval needs to be - set either in config or via command line. When using - this together with `--export trades`, the strategy- - name is injected into the filename (so `backtest- - data.json` becomes `backtest-data- - DefaultStrategy.json` - --export EXPORT Export backtest results, argument are: trades. - Example: `--export=trades` - --export-filename PATH - Save backtest results to the file with this filename. - Requires `--export` to be set as well. Example: - `--export-filename=user_data/backtest_results/backtest - _today.json` - -Common arguments: - -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). - --logfile FILE Log to the file specified. Special values are: - 'syslog', 'journald'. See the documentation for more - details. - -V, --version show program's version number and exit - -c PATH, --config PATH - Specify configuration file (default: - `userdir/config.json` or `config.json` whichever - exists). Multiple --config options may be used. Can be - set to `-` to read config from stdin. - -d PATH, --datadir PATH - Path to directory with historical backtesting data. - --userdir PATH, --user-data-dir PATH - Path to userdata directory. - -Strategy arguments: - -s NAME, --strategy NAME - Specify strategy class name which will be used by the - bot. - --strategy-path PATH Specify additional strategy lookup path. - -``` - -### Getting historic data for backtesting - -The first time your run Backtesting, you will need to download some historic data first. -This can be accomplished by using `freqtrade download-data`. -Check the corresponding [Data Downloading](data-download.md) section for more details - -## Hyperopt commands - -To optimize your strategy, you can use hyperopt parameter hyperoptimization -to find optimal parameter values for your strategy. - -``` -usage: freqtrade hyperopt [-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] - [--hyperopt NAME] [--hyperopt-path PATH] [--eps] - [--dmmp] [--enable-protections] [-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] - [--hyperopt-loss NAME] - -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`). - --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. - --stake-amount STAKE_AMOUNT - Override the value of the `stake_amount` configuration - setting. - --fee FLOAT Specify fee ratio. Will be applied twice (on trade - entry and exit). - --hyperopt NAME Specify hyperopt class name which will be used by the - bot. - --hyperopt-path PATH Specify additional lookup path for Hyperopt and - Hyperopt Loss functions. - --eps, --enable-position-stacking - Allow buying the same pair multiple times (position - stacking). - --dmmp, --disable-max-market-positions - Disable applying `max_open_trades` during backtest - (same as setting `max_open_trades` to a very high - number). - --enable-protections, --enableprotections - Enable protections for backtesting.Will slow - backtesting down by a considerable amount, but will - include configured protections - -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 - list. - --print-all Print all results, not only the best ones. - --no-color Disable colorization of hyperopt results. May be - useful if you are redirecting output to a file. - --print-json Print output in JSON format. - -j JOBS, --job-workers JOBS - The number of concurrently running jobs for - hyperoptimization (hyperopt worker processes). If -1 - (default), all CPUs are used, for -2, all CPUs but one - are used, etc. If 1 is given, no parallel computing - code is used at all. - --random-state INT Set random state to some positive integer for - 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 - class (IHyperOptLoss). Different functions can - generate completely different results, since the - target for optimization is different. Built-in - Hyperopt-loss-functions are: - ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss, - SharpeHyperOptLoss, SharpeHyperOptLossDaily, - SortinoHyperOptLoss, SortinoHyperOptLossDaily - -Common arguments: - -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). - --logfile FILE Log to the file specified. Special values are: - 'syslog', 'journald'. See the documentation for more - details. - -V, --version show program's version number and exit - -c PATH, --config PATH - Specify configuration file (default: - `userdir/config.json` or `config.json` whichever - exists). Multiple --config options may be used. Can be - set to `-` to read config from stdin. - -d PATH, --datadir PATH - Path to directory with historical backtesting data. - --userdir PATH, --user-data-dir PATH - Path to userdata directory. - -Strategy arguments: - -s NAME, --strategy NAME - Specify strategy class name which will be used by the - bot. - --strategy-path PATH Specify additional strategy lookup path. - -``` - -## Edge commands - -To know your trade expectancy and winrate against historical data, you can use Edge. - -``` -usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] - [--userdir PATH] [-s NAME] [--strategy-path PATH] - [-i TIMEFRAME] [--timerange TIMERANGE] - [--max-open-trades INT] [--stake-amount STAKE_AMOUNT] - [--fee FLOAT] [--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`). - --timerange TIMERANGE - Specify what timerange of data to use. - --max-open-trades INT - Override the value of the `max_open_trades` - configuration setting. - --stake-amount STAKE_AMOUNT - Override the value of the `stake_amount` configuration - setting. - --fee FLOAT Specify fee ratio. Will be applied twice (on trade - entry and exit). - --stoplosses STOPLOSS_RANGE - Defines a range of stoploss values against which edge - will assess the strategy. The format is "min,max,step" - (without any space). Example: - `--stoplosses=-0.01,-0.1,-0.001` - -Common arguments: - -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). - --logfile FILE Log to the file specified. Special values are: - 'syslog', 'journald'. See the documentation for more - details. - -V, --version show program's version number and exit - -c PATH, --config PATH - Specify configuration file (default: - `userdir/config.json` or `config.json` whichever - exists). Multiple --config options may be used. Can be - set to `-` to read config from stdin. - -d PATH, --datadir PATH - Path to directory with historical backtesting data. - --userdir PATH, --user-data-dir PATH - Path to userdata directory. - -Strategy arguments: - -s NAME, --strategy NAME - Specify strategy class name which will be used by the - bot. - --strategy-path PATH Specify additional strategy lookup path. - -``` - -To understand edge and how to read the results, please read the [edge documentation](edge.md). - ## Next step The optimal strategy of the bot will change with time depending of the market trends. The next step is to diff --git a/docs/configuration.md b/docs/configuration.md index 660dd6171..00d2830e4 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -82,17 +82,18 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String -| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Supports regex pairs as `.*/BTC`. Not used by VolumePairList (see [below](#pairlists-and-pairlist-handlers)).
**Datatype:** List -| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting (see [below](#pairlists-and-pairlist-handlers)).
**Datatype:** List +| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Supports regex pairs as `.*/BTC`. Not used by VolumePairList. [More information](plugins.md#pairlists-and-pairlist-handlers).
**Datatype:** List +| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting. [More information](plugins.md#pairlists-and-pairlist-handlers).
**Datatype:** List | `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
**Datatype:** Dict | `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
**Datatype:** Dict | `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
**Datatype:** Dict | `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded.
*Defaults to `60` minutes.*
**Datatype:** Positive Integer | `exchange.skip_pair_validation` | Skip pairlist validation on startup.
*Defaults to `false`
**Datatype:** Boolean +| `exchange.skip_open_order_update` | Skips open order updates on startup should the exchange cause problems. Only relevant in live conditions.
*Defaults to `false`
**Datatype:** Boolean | `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation. | `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now.
*Defaults to `true`.*
**Datatype:** Boolean -| `pairlists` | Define one or more pairlists to be used. [More information below](#pairlists-and-pairlist-handlers).
*Defaults to `StaticPairList`.*
**Datatype:** List of Dicts -| `protections` | Define one or more protections to be used. [More information below](#protections). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** List of Dicts +| `pairlists` | Define one or more pairlists to be used. [More information](plugins.md#pairlists-and-pairlist-handlers).
*Defaults to `StaticPairList`.*
**Datatype:** List of Dicts +| `protections` | Define one or more protections to be used. [More information](plugins.md#protections). [Strategy Override](#parameters-in-the-strategy).
**Datatype:** List of Dicts | `telegram.enabled` | Enable the usage of Telegram.
**Datatype:** Boolean | `telegram.token` | Your Telegram bot token. Only required if `telegram.enabled` is `true`.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `telegram.chat_id` | Your personal Telegram account id. Only required if `telegram.enabled` is `true`.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String @@ -111,12 +112,12 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `bot_name` | Name of the bot. Passed via API to a client - can be shown to distinguish / name bots.
*Defaults to `freqtrade`*
**Datatype:** String | `db_url` | Declares database URL to use. NOTE: This defaults to `sqlite:///tradesv3.dryrun.sqlite` if `dry_run` is `true`, and to `sqlite:///tradesv3.sqlite` for production instances.
**Datatype:** String, SQLAlchemy connect string -| `initial_state` | Defines the initial application state. More information below.
*Defaults to `stopped`.*
**Datatype:** Enum, either `stopped` or `running` +| `initial_state` | Defines the initial application state. If set to stopped, then the bot has to be explicitly started via `/start` RPC command.
*Defaults to `stopped`.*
**Datatype:** Enum, either `stopped` or `running` | `forcebuy_enable` | Enables the RPC Commands to force a buy. More information below.
**Datatype:** Boolean | `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).
*Defaults to `False`*.
**Datatype:** Boolean | `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`.
**Datatype:** ClassName | `strategy_path` | Adds an additional strategy lookup path (must be a directory).
**Datatype:** String -| `internals.process_throttle_secs` | Set the process throttle. Value in second.
*Defaults to `5` seconds.*
**Datatype:** Positive Integer +| `internals.process_throttle_secs` | Set the process throttle, or minimum loop duration for one bot iteration loop. Value in second.
*Defaults to `5` seconds.*
**Datatype:** Positive Integer | `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages.
*Defaults to `60` seconds.*
**Datatype:** Positive Integer or 0 | `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details.
**Datatype:** Boolean | `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file.
**Datatype:** String @@ -136,6 +137,7 @@ Values set in the configuration file always overwrite values set in the strategy * `trailing_stop_positive` * `trailing_stop_positive_offset` * `trailing_only_offset_is_reached` +* `use_custom_stoploss` * `process_only_new_candles` * `order_types` * `order_time_in_force` @@ -245,38 +247,16 @@ If it is not set in either Strategy or Configuration, a default of 1000% `{"0": !!! Note "Special case to forcesell after a specific time" A special case presents using `"": -1` as ROI. This forces the bot to sell a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-sell. -### Understand stoploss - -Go to the [stoploss documentation](stoploss.md) for more details. - -### Understand trailing stoploss - -Go to the [trailing stoploss Documentation](stoploss.md#trailing-stop-loss) for details on trailing stoploss. - -### Understand initial_state - -The `initial_state` configuration parameter is an optional field that defines the initial application state. -Possible values are `running` or `stopped`. (default=`running`) -If the value is `stopped` the bot has to be started with `/start` first. - ### Understand forcebuy_enable -The `forcebuy_enable` configuration parameter enables the usage of forcebuy commands via Telegram. -This is disabled for security reasons by default, and will show a warning message on startup if enabled. -For example, you can send `/forcebuy ETH/BTC` Telegram command when this feature if enabled to the bot, -who then buys the pair and holds it until a regular sell-signal (ROI, stoploss, /forcesell) appears. +The `forcebuy_enable` configuration parameter enables the usage of forcebuy commands via Telegram and REST API. +For security reasons, it's disabled by default, and freqtrade will show a warning message on startup if enabled. +For example, you can send `/forcebuy ETH/BTC` to the bot, which will result in freqtrade buying the pair and holds it until a regular sell-signal (ROI, stoploss, /forcesell) appears. This can be dangerous with some strategies, so use with care. See [the telegram documentation](telegram-usage.md) for details on usage. -### Understand process_throttle_secs - -The `process_throttle_secs` configuration parameter is an optional field that defines in seconds how long the bot should wait -before asking the strategy if we should buy or a sell an asset. After each wait period, the strategy is asked again for -every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or -the static list of pairs) if we should buy. - ### Ignoring expired candles When working with larger timeframes (for example 1h or more) and using a low `max_open_trades` value, the last candle can be processed as soon as a trade slot becomes available. When processing the last candle, this can lead to a situation where it may not be desirable to use the buy signal on that candle. For example, when using a condition in your strategy where you use a cross-over, that point may have passed too long ago for you to start a trade on it. @@ -469,137 +449,9 @@ The valid values are: "BTC", "ETH", "XRP", "LTC", "BCH", "USDT" ``` -## Prices used for orders +--8<-- "includes/pricing.md" -Prices for regular orders can be controlled via the parameter structures `bid_strategy` for buying and `ask_strategy` for selling. -Prices are always retrieved right before an order is placed, either by querying the exchange tickers or by using the orderbook data. - -!!! Note - Orderbook data used by Freqtrade are the data retrieved from exchange by the ccxt's function `fetch_order_book()`, i.e. are usually data from the L2-aggregated orderbook, while the ticker data are the structures returned by the ccxt's `fetch_ticker()`/`fetch_tickers()` functions. Refer to the ccxt library [documentation](https://github.com/ccxt/ccxt/wiki/Manual#market-data) for more details. - -!!! Warning "Using market orders" - Please read the section [Market order pricing](#market-order-pricing) section when using market orders. - -### Buy price - -#### Check depth of market - -When check depth of market is enabled (`bid_strategy.check_depth_of_market.enabled=True`), the buy signals are filtered based on the orderbook depth (sum of all amounts) for each orderbook side. - -Orderbook `bid` (buy) side depth is then divided by the orderbook `ask` (sell) side depth and the resulting delta is compared to the value of the `bid_strategy.check_depth_of_market.bids_to_ask_delta` parameter. The buy order is only executed if the orderbook delta is greater than or equal to the configured delta value. - -!!! Note - A delta value below 1 means that `ask` (sell) orderbook side depth is greater than the depth of the `bid` (buy) orderbook side, while a value greater than 1 means opposite (depth of the buy side is higher than the depth of the sell side). - -#### Buy price side - -The configuration setting `bid_strategy.price_side` defines the side of the spread the bot looks for when buying. - -The following displays an orderbook. - -``` explanation -... -103 -102 -101 # ask --------------Current spread -99 # bid -98 -97 -... -``` - -If `bid_strategy.price_side` is set to `"bid"`, then the bot will use 99 as buying price. -In line with that, if `bid_strategy.price_side` is set to `"ask"`, then the bot will use 101 as buying price. - -Using `ask` price often guarantees quicker filled orders, but the bot can also end up paying more than what would have been necessary. -Taker fees instead of maker fees will most likely apply even when using limit buy orders. -Also, prices at the "ask" side of the spread are higher than prices at the "bid" side in the orderbook, so the order behaves similar to a market order (however with a maximum price). - -#### Buy price with Orderbook enabled - -When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and then uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on. - -#### Buy price without Orderbook enabled - -The following section uses `side` as the configured `bid_strategy.price_side`. - -When not using orderbook (`bid_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 `bid_strategy.ask_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 ask and last price. - -### Sell price - -#### Sell price side - -The configuration setting `ask_strategy.price_side` defines the side of the spread the bot looks for when selling. - -The following displays an orderbook: - -``` explanation -... -103 -102 -101 # ask --------------Current spread -99 # bid -98 -97 -... -``` - -If `ask_strategy.price_side` is set to `"ask"`, then the bot will use 101 as selling price. -In line with that, if `ask_strategy.price_side` is set to `"bid"`, then the bot will use 99 as selling price. - -#### Sell price with Orderbook enabled - -When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_max` entries in the orderbook. Then each of the orderbook steps between `ask_strategy.order_book_min` and `ask_strategy.order_book_max` on the configured orderbook side are validated for a profitable sell-possibility based on the strategy configuration (`minimal_roi` conditions) and the sell order is placed at the first profitable spot. - -!!! Note - Using `order_book_max` higher than `order_book_min` only makes sense when ask_strategy.price_side is set to `"ask"`. - -The idea here is to place the sell order early, to be ahead in the queue. - -A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting `ask_strategy.order_book_min` and `ask_strategy.order_book_max` to the same number. - -!!! Warning "Order_book_max > 1 - increased risks for stoplosses!" - Using `ask_strategy.order_book_max` higher than 1 will increase the risk the stoploss on exchange is cancelled too early, since an eventual [stoploss on exchange](#understand-order_types) will be cancelled as soon as the order is placed. - Also, the sell order will remain on the exchange for `unfilledtimeout.sell` (or until it's filled) - which can lead to missed stoplosses (with or without using stoploss on exchange). - -!!! Warning "Order_book_max > 1 in dry-run" - Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly. - It is therefore advised to not use this setting for dry-runs. - -#### Sell price without Orderbook enabled - -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. - -### Market order pricing - -When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection. -Assuming both buy and sell are using market orders, a configuration similar to the following might be used - -``` jsonc - "order_types": { - "buy": "market", - "sell": "market" - // ... - }, - "bid_strategy": { - "price_side": "ask", - // ... - }, - "ask_strategy":{ - "price_side": "bid", - // ... - }, -``` - -Obviously, if only one side is using limit orders, different pricing combinations can be used. ---8<-- "includes/pairlists.md" ---8<-- "includes/protections.md" - -## Switch to Dry-run mode +## Using Dry-run mode We recommend starting the bot in the Dry-run mode to see how your bot will behave and what is the performance of your strategy. In the Dry-run mode the @@ -632,9 +484,10 @@ Once you will be happy with your bot performance running in the Dry-run mode, yo ### Considerations for dry-run -* API-keys may or may not be provided. Only Read-Only operations (i.e. operations that do not alter account state) on the exchange are performed in the dry-run mode. -* Wallets (`/balance`) are simulated. +* API-keys may or may not be provided. Only Read-Only operations (i.e. operations that do not alter account state) on the exchange are performed in dry-run mode. +* Wallets (`/balance`) are simulated based on `dry_run_wallet`. * Orders are simulated, and will not be posted to the exchange. +* Orders are assumed to fill immediately, and will never time out. * In combination with `stoploss_on_exchange`, the stop_loss price is assumed to be filled. * Open orders (not trades, which are stored in the database) are reset on bot restart. diff --git a/docs/data-download.md b/docs/data-download.md index 4c7376933..04f444a8b 100644 --- a/docs/data-download.md +++ b/docs/data-download.md @@ -264,7 +264,19 @@ If you are using Binance for example: ```bash mkdir -p user_data/data/binance -cp freqtrade/tests/testdata/pairs.json user_data/data/binance +cp tests/testdata/pairs.json user_data/data/binance +``` + +If you your configuration directory `user_data` was made by docker, you may get the following error: + +``` +cp: cannot create regular file 'user_data/data/binance/pairs.json': Permission denied +``` + +You can fix the permissions of your user-data directory as follows: + +``` +sudo chown -R $UID:$GID user_data ``` The format of the `pairs.json` file is a simple json list. diff --git a/docs/developer.md b/docs/developer.md index 831d9d2f8..4b8c64530 100644 --- a/docs/developer.md +++ b/docs/developer.md @@ -2,7 +2,7 @@ This page is intended for developers of Freqtrade, people who want to contribute to the Freqtrade codebase or documentation, or people who want to understand the source code of the application they're running. -All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/MA9v74M) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-l9d9iqgl-9cVBIeBkCBa8j6upSmd_NA) where you can ask questions. +All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/MA9v74M) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) where you can ask questions. ## Documentation @@ -177,7 +177,7 @@ In `VolumePairList`, this implements different methods of sorting, does early va ### Protections -Best read the [Protection documentation](configuration.md#protections) to understand protections. +Best read the [Protection documentation](plugins.md#protections) to understand protections. This Guide is directed towards Developers who want to develop a new protection. No protection should use datetime directly, but use the provided `date_now` variable for date calculations. This preserves the ability to backtest protections. diff --git a/docs/edge.md b/docs/edge.md index 6f01fcf65..5565ca2f9 100644 --- a/docs/edge.md +++ b/docs/edge.md @@ -9,6 +9,7 @@ The `Edge Positioning` module uses probability to calculate your win rate and ri `Edge Positioning` only considers *its own* buy/sell/stoploss signals. It ignores the stoploss, trailing stoploss, and ROI settings in the strategy configuration file. `Edge Positioning` improves the performance of some trading strategies and *decreases* the performance of others. + ## Introduction 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. @@ -208,6 +209,60 @@ Let's say the stake currency is **ETH** and there is $10$ **ETH** on the wallet. - **Trade 4** The strategy detects a new buy signal int the **XLM/ETH** market. `Edge Positioning` calculates the stoploss of $2\%$, and the position size of $0.055 / 0.02 = 2.75$ **ETH**. +## Edge command reference + +``` +usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] + [--userdir PATH] [-s NAME] [--strategy-path PATH] + [-i TIMEFRAME] [--timerange TIMERANGE] + [--max-open-trades INT] [--stake-amount STAKE_AMOUNT] + [--fee FLOAT] [--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`). + --timerange TIMERANGE + Specify what timerange of data to use. + --max-open-trades INT + Override the value of the `max_open_trades` + configuration setting. + --stake-amount STAKE_AMOUNT + Override the value of the `stake_amount` configuration + setting. + --fee FLOAT Specify fee ratio. Will be applied twice (on trade + entry and exit). + --stoplosses STOPLOSS_RANGE + Defines a range of stoploss values against which edge + will assess the strategy. The format is "min,max,step" + (without any space). Example: + `--stoplosses=-0.01,-0.1,-0.001` + +Common arguments: + -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). + --logfile FILE Log to the file specified. Special values are: + 'syslog', 'journald'. See the documentation for more + details. + -V, --version show program's version number and exit + -c PATH, --config PATH + Specify configuration file (default: + `userdir/config.json` or `config.json` whichever + exists). Multiple --config options may be used. Can be + set to `-` to read config from stdin. + -d PATH, --datadir PATH + Path to directory with historical backtesting data. + --userdir PATH, --user-data-dir PATH + Path to userdata directory. + +Strategy arguments: + -s NAME, --strategy NAME + Specify strategy class name which will be used by the + bot. + --strategy-path PATH Specify additional strategy lookup path. + +``` + ## Configurations Edge module has following configuration options: diff --git a/docs/faq.md b/docs/faq.md index 8a0c61b29..93b806dca 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -38,12 +38,11 @@ you can't say much from few trades. ### I’d like to make changes to the config. Can I do that without having to kill the bot? -Yes. You can edit your config, use the `/stop` command in Telegram, followed by `/reload_config` and the bot will run with the new config. +Yes. You can edit your config and use the `/reload_config` command to reload the configuration. The bot will stop, reload the configuration and strategy and will restart with the new configuration and strategy. ### I want to improve the bot with a new strategy -That's great. We have a nice backtesting and hyperoptimization setup. See -the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands). +That's great. We have a nice backtesting and hyperoptimization setup. See the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands). ### Is there a setting to only SELL the coins being held and not perform anymore BUYS? @@ -143,7 +142,7 @@ 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-l9d9iqgl-9cVBIeBkCBa8j6upSmd_NA) - 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/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. * 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 f88d9cd4f..ec155062f 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -32,6 +32,107 @@ source .env/bin/activate 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] + [-i TIMEFRAME] [--timerange TIMERANGE] + [--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] + [--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] + [--hyperopt-loss NAME] + +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`). + --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. + --stake-amount STAKE_AMOUNT + Override the value of the `stake_amount` configuration + setting. + --fee FLOAT Specify fee ratio. Will be applied twice (on trade + entry and exit). + --hyperopt NAME Specify hyperopt class name which will be used by the + bot. + --hyperopt-path PATH Specify additional lookup path for Hyperopt and + Hyperopt Loss functions. + --eps, --enable-position-stacking + Allow buying the same pair multiple times (position + stacking). + --dmmp, --disable-max-market-positions + Disable applying `max_open_trades` during backtest + (same as setting `max_open_trades` to a very high + number). + --enable-protections, --enableprotections + Enable protections for backtesting.Will slow + backtesting down by a considerable amount, but will + include configured protections + -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 + list. + --print-all Print all results, not only the best ones. + --no-color Disable colorization of hyperopt results. May be + useful if you are redirecting output to a file. + --print-json Print output in JSON format. + -j JOBS, --job-workers JOBS + The number of concurrently running jobs for + hyperoptimization (hyperopt worker processes). If -1 + (default), all CPUs are used, for -2, all CPUs but one + are used, etc. If 1 is given, no parallel computing + code is used at all. + --random-state INT Set random state to some positive integer for + 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 + class (IHyperOptLoss). Different functions can + generate completely different results, since the + target for optimization is different. Built-in + Hyperopt-loss-functions are: + ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss, + SharpeHyperOptLoss, SharpeHyperOptLossDaily, + SortinoHyperOptLoss, SortinoHyperOptLossDaily + +Common arguments: + -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). + --logfile FILE Log to the file specified. Special values are: + 'syslog', 'journald'. See the documentation for more + details. + -V, --version show program's version number and exit + -c PATH, --config PATH + Specify configuration file (default: + `userdir/config.json` or `config.json` whichever + exists). Multiple --config options may be used. Can be + set to `-` to read config from stdin. + -d PATH, --datadir PATH + Path to directory with historical backtesting data. + --userdir PATH, --user-data-dir PATH + Path to userdata directory. + +Strategy arguments: + -s NAME, --strategy NAME + Specify strategy class name which will be used by the + bot. + --strategy-path PATH Specify additional strategy lookup path. + +``` + ## Prepare Hyperopting Before we start digging into Hyperopt, we recommend you to take a look at diff --git a/docs/includes/pricing.md b/docs/includes/pricing.md new file mode 100644 index 000000000..d8a72cc58 --- /dev/null +++ b/docs/includes/pricing.md @@ -0,0 +1,127 @@ +## Prices used for orders + +Prices for regular orders can be controlled via the parameter structures `bid_strategy` for buying and `ask_strategy` for selling. +Prices are always retrieved right before an order is placed, either by querying the exchange tickers or by using the orderbook data. + +!!! Note + Orderbook data used by Freqtrade are the data retrieved from exchange by the ccxt's function `fetch_order_book()`, i.e. are usually data from the L2-aggregated orderbook, while the ticker data are the structures returned by the ccxt's `fetch_ticker()`/`fetch_tickers()` functions. Refer to the ccxt library [documentation](https://github.com/ccxt/ccxt/wiki/Manual#market-data) for more details. + +!!! Warning "Using market orders" + Please read the section [Market order pricing](#market-order-pricing) section when using market orders. + +### Buy price + +#### Check depth of market + +When check depth of market is enabled (`bid_strategy.check_depth_of_market.enabled=True`), the buy signals are filtered based on the orderbook depth (sum of all amounts) for each orderbook side. + +Orderbook `bid` (buy) side depth is then divided by the orderbook `ask` (sell) side depth and the resulting delta is compared to the value of the `bid_strategy.check_depth_of_market.bids_to_ask_delta` parameter. The buy order is only executed if the orderbook delta is greater than or equal to the configured delta value. + +!!! Note + A delta value below 1 means that `ask` (sell) orderbook side depth is greater than the depth of the `bid` (buy) orderbook side, while a value greater than 1 means opposite (depth of the buy side is higher than the depth of the sell side). + +#### Buy price side + +The configuration setting `bid_strategy.price_side` defines the side of the spread the bot looks for when buying. + +The following displays an orderbook. + +``` explanation +... +103 +102 +101 # ask +-------------Current spread +99 # bid +98 +97 +... +``` + +If `bid_strategy.price_side` is set to `"bid"`, then the bot will use 99 as buying price. +In line with that, if `bid_strategy.price_side` is set to `"ask"`, then the bot will use 101 as buying price. + +Using `ask` price often guarantees quicker filled orders, but the bot can also end up paying more than what would have been necessary. +Taker fees instead of maker fees will most likely apply even when using limit buy orders. +Also, prices at the "ask" side of the spread are higher than prices at the "bid" side in the orderbook, so the order behaves similar to a market order (however with a maximum price). + +#### Buy price with Orderbook enabled + +When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and then uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on. + +#### Buy price without Orderbook enabled + +The following section uses `side` as the configured `bid_strategy.price_side`. + +When not using orderbook (`bid_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 `bid_strategy.ask_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 ask and last price. + +### Sell price + +#### Sell price side + +The configuration setting `ask_strategy.price_side` defines the side of the spread the bot looks for when selling. + +The following displays an orderbook: + +``` explanation +... +103 +102 +101 # ask +-------------Current spread +99 # bid +98 +97 +... +``` + +If `ask_strategy.price_side` is set to `"ask"`, then the bot will use 101 as selling price. +In line with that, if `ask_strategy.price_side` is set to `"bid"`, then the bot will use 99 as selling price. + +#### Sell price with Orderbook enabled + +When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_max` entries in the orderbook. Then each of the orderbook steps between `ask_strategy.order_book_min` and `ask_strategy.order_book_max` on the configured orderbook side are validated for a profitable sell-possibility based on the strategy configuration (`minimal_roi` conditions) and the sell order is placed at the first profitable spot. + +!!! Note + Using `order_book_max` higher than `order_book_min` only makes sense when ask_strategy.price_side is set to `"ask"`. + +The idea here is to place the sell order early, to be ahead in the queue. + +A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting `ask_strategy.order_book_min` and `ask_strategy.order_book_max` to the same number. + +!!! Warning "Order_book_max > 1 - increased risks for stoplosses!" + Using `ask_strategy.order_book_max` higher than 1 will increase the risk the stoploss on exchange is cancelled too early, since an eventual [stoploss on exchange](#understand-order_types) will be cancelled as soon as the order is placed. + Also, the sell order will remain on the exchange for `unfilledtimeout.sell` (or until it's filled) - which can lead to missed stoplosses (with or without using stoploss on exchange). + +!!! Warning "Order_book_max > 1 in dry-run" + Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly. + It is therefore advised to not use this setting for dry-runs. + +#### Sell price without Orderbook enabled + +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. + +### Market order pricing + +When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection. +Assuming both buy and sell are using market orders, a configuration similar to the following might be used + +``` jsonc + "order_types": { + "buy": "market", + "sell": "market" + // ... + }, + "bid_strategy": { + "price_side": "ask", + // ... + }, + "ask_strategy":{ + "price_side": "bid", + // ... + }, +``` + +Obviously, if only one side is using limit orders, different pricing combinations can be used. diff --git a/docs/includes/protections.md b/docs/includes/protections.md index de34383ac..6bc57153e 100644 --- a/docs/includes/protections.md +++ b/docs/includes/protections.md @@ -40,7 +40,9 @@ All protection end times are rounded up to the next candle to avoid sudden, unex #### Stoploss Guard -`StoplossGuard` selects all trades within `lookback_period` in minutes (or in candles when using `lookback_period_candles`), and determines if the amount of trades that resulted in stoploss are above `trade_limit` - in which case trading will stop for `stop_duration` in minutes (or in candles when using `stop_duration_candles`). +`StoplossGuard` selects all trades within `lookback_period` in minutes (or in candles when using `lookback_period_candles`). +If `trade_limit` or more trades resulted in stoploss, trading will stop for `stop_duration` in minutes (or in candles when using `stop_duration_candles`). + This applies across all pairs, unless `only_per_pair` is set to true, which will then only look at one pair at a time. The below example stops trading for all pairs for 4 candles after the last trade if the bot hit stoploss 4 times within the last 24 candles. diff --git a/docs/index.md b/docs/index.md index b489861f0..9d1a1532e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -35,6 +35,22 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python - Control/Monitor: Use Telegram or a REST API (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.). - Analyse: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md). +## Supported exchange marketplaces + +Please read the [exchange specific notes](exchanges.md) to learn about eventual, special configurations needed for each exchange. + +- [X] [Binance](https://www.binance.com/) ([*Note for binance users](exchanges.md#blacklists)) +- [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)_ + +### Community tested + +Exchanges confirmed working by the community: + +- [X] [Bitvavo](https://bitvavo.com/) + ## Requirements ### Hardware requirements @@ -65,7 +81,7 @@ For any questions not covered by the documentation or for further information ab Please check out our [discord server](https://discord.gg/MA9v74M). -You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-l9d9iqgl-9cVBIeBkCBa8j6upSmd_NA). +You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). ## Ready to try? diff --git a/docs/installation.md b/docs/installation.md index 8cb6724cb..d2661f88f 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -2,94 +2,49 @@ This page explains how to prepare your environment for running the bot. +The freqtrade documentation describes various ways to install freqtrade + +* [Docker images](docker_quickstart.md) (separate page) +* [Script Installation](#script-installation) +* [Manual Installation](#manual-installation) +* [Installation with Conda](#installation-with-conda) + Please consider using the prebuilt [docker images](docker_quickstart.md) to get started quickly while evaluating how freqtrade works. -## Prerequisite +------ -### Requirements +## Information -Click each one for install guide: +For Windows installation, please use the [windows installation guide](windows_installation.md). -* [Python >= 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/) -* [pip](https://pip.pypa.io/en/stable/installing/) -* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) -* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended) -* [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) (install instructions below) - - We also recommend a [Telegram bot](telegram-usage.md#setup-your-telegram-bot), which is optional but recommended. - -!!! Warning "Up-to-date clock" - The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges. - -## Quick start - -Freqtrade provides the Linux/MacOS Easy Installation script to install all dependencies and help you configure the bot. - -!!! Note - Windows installation is explained [here](#windows). - -The easiest way to install and run Freqtrade is to clone the bot Github repository and then run the Easy Installation script, if it's available for your platform. +The easiest way to install and run Freqtrade is to clone the bot Github repository and then run the `./setup.sh` script, if it's available for your platform. !!! Note "Version considerations" - When cloning the repository the default working branch has the name `develop`. This branch contains all last features (can be considered as relatively stable, thanks to automated tests). The `stable` branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the `develop` branch to prevent packaging bugs, so potentially it's more stable). + When cloning the repository the default working branch has the name `develop`. This branch contains all last features (can be considered as relatively stable, thanks to automated tests). + The `stable` branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the `develop` branch to prevent packaging bugs, so potentially it's more stable). !!! Note Python3.7 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository. Also, python headers (`python-dev` / `python-devel`) must be available for the installation to complete successfully. -This can be achieved with the following commands: - -```bash -git clone https://github.com/freqtrade/freqtrade.git -cd freqtrade -# git checkout stable # Optional, see (1) -./setup.sh --install -``` - -(1) This command switches the cloned repository to the use of the `stable` branch. It's not needed if you wish to stay on the `develop` branch. You may later switch between branches at any time with the `git checkout stable`/`git checkout develop` commands. - -## Easy Installation Script (Linux/MacOS) - -If you are on Debian, Ubuntu or MacOS Freqtrade provides the script to install, update, configure and reset the codebase of your bot. - -```bash -$ ./setup.sh -usage: - -i,--install Install freqtrade from scratch - -u,--update Command git pull to update. - -r,--reset Hard reset your develop/stable branch. - -c,--config Easy config generator (Will override your existing file). -``` - -** --install ** - -With this option, the script will install the bot and most dependencies: -You will need to have git and python3.7+ installed beforehand for this to work. - -* Mandatory software as: `ta-lib` -* Setup your virtualenv under `.env/` - -This option is a combination of installation tasks, `--reset` and `--config`. - -** --update ** - -This option will pull the last version of your current branch and update your virtualenv. Run the script with this option periodically to update your bot. - -** --reset ** - -This option will hard reset your branch (only if you are on either `stable` or `develop`) and recreate your virtualenv. - -** --config ** - -DEPRECATED - use `freqtrade new-config -c config.json` instead. - -### Activate your virtual environment - -Each time you open a new terminal, you must run `source .env/bin/activate`. +!!! Warning "Up-to-date clock" + The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges. ------ -## Custom Installation +## Requirements + +These requirements apply to both [Script Installation](#script-installation) and [Manual Installation](#manual-installation). + +### Install guide + +* [Python >= 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/) +* [pip](https://pip.pypa.io/en/stable/installing/) +* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) +* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended) +* [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) (install instructions [below](#install-ta-lib)) + +### Install code We've included/collected install instructions for Ubuntu, MacOS, and Windows. These are guidelines and your success may vary with other distros. OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems. @@ -97,12 +52,15 @@ OS Specific steps are listed first, the [Common](#common) section below is neces !!! Note Python3.7 or higher and the corresponding pip are assumed to be available. -=== "Ubuntu/Debian" +=== "Debian/Ubuntu" #### Install necessary dependencies ```bash + # update repository sudo apt-get update - sudo apt-get install build-essential git + + # install packages + sudo apt install -y python3-pip python3-venv python3-pandas python3-pip git ``` === "RaspberryPi/Raspbian" @@ -110,9 +68,9 @@ OS Specific steps are listed first, the [Common](#common) section below is neces This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running. Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied. - - ``` bash + + ```bash sudo apt-get install python3-venv libatlas-base-dev cmake # Use pywheels.org to speed up installation sudo echo "[global]\nextra-index-url=https://www.piwheels.org/simple" > tee /etc/pip.conf @@ -125,17 +83,106 @@ OS Specific steps are listed first, the [Common](#common) section below is neces !!! Note "Installation duration" Depending on your internet speed and the Raspberry Pi version, installation can take multiple hours to complete. - Due to this, we recommend to use the prebuild docker-image for Raspberry, by following the [Docker quickstart documentation](docker_quickstart.md) + Due to this, we recommend to use the pre-build docker-image for Raspberry, by following the [Docker quickstart documentation](docker_quickstart.md) !!! Note The above does not install hyperopt dependencies. To install these, please use `python3 -m pip install -e .[hyperopt]`. We do not advise to run hyperopt on a Raspberry Pi, since this is a very resource-heavy operation, which should be done on powerful machine. -### Common +------ -#### 1. Install TA-Lib +## Freqtrade repository -Use the provided ta-lib installation script +Freqtrade is an open source crypto-currency trading bot, whose code is hosted on `github.com` + +```bash +# Download `develop` branch of freqtrade repository +git clone https://github.com/freqtrade/freqtrade.git + +# Enter downloaded directory +cd freqtrade + +# your choice (1): novice user +git checkout stable + +# your choice (2): advanced user +git checkout develop +``` + +(1) This command switches the cloned repository to the use of the `stable` branch. It's not needed, if you wish to stay on the (2) `develop` branch. + +You may later switch between branches at any time with the `git checkout stable`/`git checkout develop` commands. + +------ + +## Script Installation + +First of the ways to install Freqtrade, is to use provided the Linux/MacOS `./setup.sh` script, which install all dependencies and help you configure the bot. + +Make sure you fulfill the [Requirements](#requirements) and have downloaded the [Freqtrade repository](#freqtrade-repository). + +### Use /setup.sh -install (Linux/MacOS) + +If you are on Debian, Ubuntu or MacOS, freqtrade provides the script to install freqtrade. + +```bash +# --install, Install freqtrade from scratch +./setup.sh -i +``` + +### Activate your virtual environment + +Each time you open a new terminal, you must run `source .env/bin/activate` to activate your virtual environment. + +```bash +# then activate your .env +source ./.env/bin/activate +``` + +### Congratulations + +[You are ready](#you-are-ready), and run the bot + +### Other options of /setup.sh script + +You can as well update, configure and reset the codebase of your bot with `./script.sh` + +```bash +# --update, Command git pull to update. +./setup.sh -u +# --reset, Hard reset your develop/stable branch. +./setup.sh -r +``` + +``` +** --install ** + +With this option, the script will install the bot and most dependencies: +You will need to have git and python3.7+ installed beforehand for this to work. + +* Mandatory software as: `ta-lib` +* Setup your virtualenv under `.env/` + +This option is a combination of installation tasks and `--reset` + +** --update ** + +This option will pull the last version of your current branch and update your virtualenv. Run the script with this option periodically to update your bot. + +** --reset ** + +This option will hard reset your branch (only if you are on either `stable` or `develop`) and recreate your virtualenv. +``` + +----- + +## Manual Installation + +Make sure you fulfill the [Requirements](#requirements) and have downloaded the [Freqtrade repository](#freqtrade-repository). + +### Install TA-Lib + +#### TA-Lib script installation ```bash sudo ./build_helpers/install_ta-lib.sh @@ -160,77 +207,193 @@ cd .. rm -rf ./ta-lib* ``` -!!! Note - An already downloaded version of ta-lib is included in the repository, as the sourceforge.net source seems to have problems frequently. +#### Setup Python virtual environment (virtualenv) -#### 2. Setup your Python virtual environment (virtualenv) - -!!! Note - This step is optional but strongly recommended to keep your system organized +You will run freqtrade in separated `virtual environment` ```bash +# create virtualenv in directory /freqtrade/.env python3 -m venv .env + +# run virtualenv source .env/bin/activate ``` -#### 3. Install Freqtrade - -Clone the git repository: +#### Install python dependencies ```bash -git clone https://github.com/freqtrade/freqtrade.git -cd freqtrade -git checkout stable -``` - -#### 4. Install python dependencies - -``` bash python3 -m pip install --upgrade pip python3 -m pip install -e . ``` -#### 5. Initialize the configuration +### Congratulations -```bash -# Initialize the user_directory -freqtrade create-userdir --userdir user_data/ +[You are ready](#you-are-ready), and run the bot -# Create a new configuration file -freqtrade new-config --config config.json -``` +#### (Optional) Post-installation Tasks -> *To edit the config please refer to [Bot Configuration](configuration.md).* +!!! Note + If you run the bot on a server, you should consider using [Docker](docker_quickstart.md) or a terminal multiplexer like `screen` or [`tmux`](https://en.wikipedia.org/wiki/Tmux) to avoid that the bot is stopped on logout. -#### 6. Run the Bot - -If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins. - -```bash -freqtrade trade -c config.json -``` - -*Note*: If you run the bot on a server, you should consider using [Docker compose](docker_quickstart.md) or a terminal multiplexer like `screen` or [`tmux`](https://en.wikipedia.org/wiki/Tmux) to avoid that the bot is stopped on logout. - -#### 7. (Optional) Post-installation Tasks - -On Linux, as an optional post-installation task, you may wish to setup the bot to run as a `systemd` service or configure it to send the log messages to the `syslog`/`rsyslog` or `journald` daemons. See [Advanced Logging](advanced-setup.md#advanced-logging) for details. +On Linux with software suite `systemd`, as an optional post-installation task, you may wish to setup the bot to run as a `systemd service` or configure it to send the log messages to the `syslog`/`rsyslog` or `journald` daemons. See [Advanced Logging](advanced-setup.md#advanced-logging) for details. ------ -### Anaconda +## Installation with Conda -Freqtrade can also be installed using Anaconda (or Miniconda). +Freqtrade can also be installed with Miniconda or Anaconda. We recommend using Miniconda as it's installation footprint is smaller. Conda will automatically prepare and manage the extensive library-dependencies of the Freqtrade program. -!!! Note - This requires the [ta-lib](#1-install-ta-lib) C-library to be installed first. See below. +### What is Conda? -``` bash -conda env create -f environment.yml +Conda is a package, dependency and environment manager for multiple programming languages: [conda docs](https://docs.conda.io/projects/conda/en/latest/index.html) + +### Installation with conda + +#### Install Conda + +[Installing on linux](https://conda.io/projects/conda/en/latest/user-guide/install/linux.html#install-linux-silent) + +[Installing on windows](https://conda.io/projects/conda/en/latest/user-guide/install/windows.html) + +Answer all questions. After installation, it is mandatory to turn your terminal OFF and ON again. + +#### Freqtrade download + +Download and install freqtrade. + +```bash +# download freqtrade +git clone https://github.com/freqtrade/freqtrade.git + +# enter downloaded directory 'freqtrade' +cd freqtrade ``` +#### Freqtrade instal: Conda Environment + +Prepare conda-freqtrade environment, using file `environment.yml`, which exist in main freqtrade directory + +```bash +conda env create -n freqtrade-conda -f environment.yml +``` + +!!! Note "Creating Conda Environment" + The conda command `create -n` automatically installs all nested dependencies for the selected libraries, general structure of installation command is: + + ```bash + # choose your own packages + conda env create -n [name of the environment] [python version] [packages] + + # point to file with packages + conda env create -n [name of the environment] -f [file] + ``` + +#### Enter/exit freqtrade-conda environment + +To check available environments, type + +```bash +conda env list +``` + +Enter installed environment + +```bash +# enter conda environment +conda activate freqtrade-conda + +# exit conda environment - don't do it now +conda deactivate +``` + +Install last python dependencies with pip + +```bash +python3 -m pip install --upgrade pip +python3 -m pip install -e . +``` + +### Congratulations + +[You are ready](#you-are-ready), and run the bot + +### Important shortcuts + +```bash +# list installed conda environments +conda env list + +# activate base environment +conda activate + +# activate freqtrade-conda environment +conda activate freqtrade-conda + +#deactivate any conda environments +conda deactivate +``` + +### Further info on anaconda + +!!! Info "New heavy packages" + It may happen that creating a new Conda environment, populated with selected packages at the moment of creation takes less time than installing a large, heavy library or application, into previously set environment. + +!!! Warning "pip install within conda" + The documentation of conda says that pip should NOT be used within conda, because internal problems can occur. + However, they are rare. [Anaconda Blogpost](https://www.anaconda.com/blog/using-pip-in-a-conda-environment) + + Nevertheless, that is why, the `conda-forge` channel is preferred: + + * more libraries are available (less need for `pip`) + * `conda-forge` works better with `pip` + * the libraries are newer + +Happy trading! + ----- -## Troubleshooting + +## You are ready + +You've made it this far, so you have successfully installed freqtrade. + +### Initialize the configuration + +```bash +# Step 1 - Initialize user folder +freqtrade create-userdir --userdir user_data + +# Step 2 - Create a new configuration file +freqtrade new-config --config config.json +``` + +You are ready to run, read [Bot Configuration](configuration.md), remember to start with `dry_run: True` and verify that everything is working. + +To learn how to setup your configuration, please refer to the [Bot Configuration](configuration.md) documentation page. + +### Start the Bot + +```bash +freqtrade trade --config config.json --strategy SampleStrategy +``` + +!!! Warning + You should read through the rest of the documentation, backtest the strategy you're going to use, and use dry-run before enabling trading with real money. + +----- + +## Troubleshooting + +### Common problem: "command not found" + +If you used (1)`Script` or (2)`Manual` installation, you need to run the bot in virtual environment. If you get error as below, make sure venv is active. + +```bash +# if: +bash: freqtrade: command not found + +# then activate your .env +source ./.env/bin/activate +``` ### MacOS installation error @@ -239,7 +402,7 @@ Newer versions of MacOS may have installation failed with errors like `error: co This error will require explicit installation of the SDK Headers, which are not installed by default in this version of MacOS. For MacOS 10.14, this can be accomplished with the below command. -``` bash +```bash open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg ``` @@ -252,13 +415,8 @@ The errors you'll see happen during installation and are related to the installa You can install the necessary libraries with the following command: -``` bash +```bash brew install hdf5 c-blosc ``` After this, please run the installation (script) again. - ------ - -Now you have an environment ready, the next step is -[Bot Configuration](configuration.md). diff --git a/docs/plotting.md b/docs/plotting.md index 19ddb4f57..d7ed5ab1f 100644 --- a/docs/plotting.md +++ b/docs/plotting.md @@ -188,7 +188,7 @@ Sample configuration with inline comments explaining the process: 'senkou_a': { 'color': 'green', #optional 'fill_to': 'senkou_b', - 'fill_label': 'Ichimoku Cloud' #optional, + 'fill_label': 'Ichimoku Cloud', #optional 'fill_color': 'rgba(255,76,46,0.2)', #optional }, # plot senkou_b, too. Not only the area to it. diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt index 6fef05f0c..94b2fca39 100644 --- a/docs/requirements-docs.txt +++ b/docs/requirements-docs.txt @@ -1,3 +1,3 @@ -mkdocs-material==6.2.5 +mkdocs-material==6.2.8 mdx_truly_sane_lists==1.2 -pymdown-extensions==8.1 +pymdown-extensions==8.1.1 diff --git a/docs/rest-api.md b/docs/rest-api.md index 2c7142c61..e2b94f080 100644 --- a/docs/rest-api.md +++ b/docs/rest-api.md @@ -1,4 +1,19 @@ -# REST API Usage +# REST API & FreqUI + +## FreqUI + +Freqtrade provides a builtin webserver, which can serve [FreqUI](https://github.com/freqtrade/frequi), the freqtrade UI. + +By default, the UI is not included in the installation (except for docker images), and must be installed explicitly with `freqtrade install-ui`. +This same command can also be used to update freqUI, should there be a new release. + +Once the bot is started in trade / dry-run mode (with `freqtrade trade`) - the UI will be available under the configured port below (usually `http://127.0.0.1:8080`). + +!!! info "Alpha release" + FreqUI is still considered an alpha release - if you encounter bugs or inconsistencies please open a [FreqUI issue](https://github.com/freqtrade/frequi/issues/new/choose). + +!!! Note "developers" + Developers should not use this method, but instead use the method described in the [freqUI repository](https://github.com/freqtrade/frequi) to get the source-code of freqUI. ## Configuration @@ -23,9 +38,6 @@ Sample configuration: !!! Danger "Security warning" By default, the configuration listens on localhost only (so it's not reachable from other systems). We strongly recommend to not expose this API to the internet and choose a strong, unique password, since others will potentially be able to control your bot. -!!! Danger "Password selection" - Please make sure to select a very strong, unique password to protect your bot from unauthorized access. - You can then access the API by going to `http://127.0.0.1:8080/api/v1/ping` in a browser to check if the API is running correctly. This should return the response: @@ -35,16 +47,22 @@ This should return the response: All other endpoints return sensitive info and require authentication and are therefore not available through a web browser. -To generate a secure password, either use a password manager, or use the below code snipped. +### Security + +To generate a secure password, best use a password manager, or use the below code. ``` python import secrets secrets.token_hex() ``` -!!! Hint +!!! Hint "JWT token" Use the same method to also generate a JWT secret key (`jwt_secret_key`). +!!! Danger "Password selection" + Please make sure to select a very strong, unique password to protect your bot from unauthorized access. + Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!). + ### Configuration with docker If you run your bot using docker, you'll need to have the bot listen to incoming connections. The security is then handled by docker. @@ -57,28 +75,20 @@ If you run your bot using docker, you'll need to have the bot listen to incoming }, ``` -Add the following to your docker command: +Uncomment the following from your docker-compose file: -``` bash - -p 127.0.0.1:8080:8080 -``` - -A complete sample-command may then look as follows: - -```bash -docker run -d \ - --name freqtrade \ - -v ~/.freqtrade/config.json:/freqtrade/config.json \ - -v ~/.freqtrade/user_data/:/freqtrade/user_data \ - -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \ - -p 127.0.0.1:8080:8080 \ - freqtrade trade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy +```yml + ports: + - "127.0.0.1:8080:8080" ``` !!! Danger "Security warning" - By using `-p 8080:8080` the API is available to everyone connecting to the server under the correct port, so others may be able to control your bot. + By using `8080:8080` in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot. -## Consuming the API + +## Rest API + +### Consuming the API You can consume the API by using the script `scripts/rest_client.py`. The client script only requires the `requests` module, so Freqtrade does not need to be installed on the system. @@ -89,7 +99,7 @@ python3 scripts/rest_client.py [optional parameters] By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be used, however you can specify a configuration file to override this behaviour. -### Minimalistic client config +#### Minimalistic client config ``` json { @@ -105,7 +115,7 @@ By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be use python3 scripts/rest_client.py --config rest_config.json [optional parameters] ``` -## Available endpoints +### Available endpoints | Command | Description | |----------|-------------| @@ -264,12 +274,12 @@ whitelist ``` -## OpenAPI interface +### OpenAPI interface To enable the builtin openAPI interface (Swagger UI), specify `"enable_openapi": true` in the api_server configuration. This will enable the Swagger UI at the `/docs` endpoint. By default, that's running at http://localhost:8080/docs/ - but it'll depend on your settings. -## Advanced API usage using JWT tokens +### Advanced API usage using JWT tokens !!! Note The below should be done in an application (a Freqtrade REST API client, which fetches info via API), and is not intended to be used on a regular basis. @@ -294,9 +304,9 @@ Since the access token has a short timeout (15 min) - the `token/refresh` reques {"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk5NzQsIm5iZiI6MTU4OTExOTk3NCwianRpIjoiMDBjNTlhMWUtMjBmYS00ZTk0LTliZjAtNWQwNTg2MTdiZDIyIiwiZXhwIjoxNTg5MTIwODc0LCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.1seHlII3WprjjclY6DpRhen0rqdF4j6jbvxIhUFaSbs"} ``` -## CORS +### CORS -All web-based frontends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing. +All web-based front-ends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing. Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems. Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately. diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md index 25d217d34..c051e2232 100644 --- a/docs/strategy-advanced.md +++ b/docs/strategy-advanced.md @@ -33,8 +33,8 @@ class AwesomeStrategy(IStrategy): use_custom_stoploss = True - def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, - current_profit: float, **kwargs) -> float: + def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, + current_rate: float, current_profit: float, **kwargs) -> float: """ Custom stoploss logic, returning the new distance relative to current_rate (as ratio). e.g. returning -0.05 would create a stoploss 5% below current_rate. @@ -83,8 +83,8 @@ class AwesomeStrategy(IStrategy): use_custom_stoploss = True - def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, - current_profit: float, **kwargs) -> float: + def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, + current_rate: float, current_profit: float, **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: @@ -109,8 +109,8 @@ class AwesomeStrategy(IStrategy): use_custom_stoploss = True - def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, - current_profit: float, **kwargs) -> float: + def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, + current_rate: float, current_profit: float, **kwargs) -> float: if pair in ('ETH/BTC', 'XRP/BTC'): return -0.10 @@ -135,8 +135,8 @@ class AwesomeStrategy(IStrategy): use_custom_stoploss = True - def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, - current_profit: float, **kwargs) -> float: + def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, + current_rate: float, current_profit: float, **kwargs) -> float: if current_profit < 0.04: return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss @@ -167,8 +167,8 @@ class AwesomeStrategy(IStrategy): use_custom_stoploss = True - def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, - current_profit: float, **kwargs) -> float: + def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, + current_rate: float, current_profit: float, **kwargs) -> float: # Calculate as `-desired_stop_from_open + current_profit` to get the distance between current_profit and initial price if current_profit > 0.40: @@ -399,6 +399,17 @@ class MyAwesomeStrategy2(MyAwesomeStrategy): Both attributes and methods may be overridden, altering behavior of the original strategy in a way you need. +!!! Note "Parent-strategy in different files" + If you have the parent-strategy in a different file, you'll need to add the following to the top of your "child"-file to ensure proper loading, otherwise freqtrade may not be able to load the parent strategy correctly. + + ``` python + import sys + from pathlib import Path + sys.path.append(str(Path(__file__).parent)) + + from myawesomestrategy import MyAwesomeStrategy + ``` + ## Embedding Strategies Freqtrade provides you with with an easy way to embed the strategy into your configuration file. diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index 7e998570f..fdc95a3c1 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -315,11 +315,11 @@ class AwesomeStrategy(IStrategy): def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Check if the entry already exists - if not metadata["pair"] in self._cust_info: + if not metadata["pair"] in self.cust_info: # Create empty entry for this pair - self._cust_info[metadata["pair"]] = {} + self.cust_info[metadata["pair"]] = {} - if "crosstime" in 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 @@ -444,14 +444,19 @@ It can also be used in specific callbacks to get the signal that caused the acti ``` python # fetch current dataframe if self.dp: - dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'], - timeframe=self.timeframe) + if self.dp.runmode.value in ('live', 'dry_run'): + dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'], + timeframe=self.timeframe) ``` !!! Note "No data available" Returns an empty dataframe if the requested pair was not cached. This should not happen when using whitelisted pairs. + +!!! Warning "Warning about backtesting" + This method will return an empty dataframe during backtesting. + ### *orderbook(pair, maximum)* ``` python @@ -462,8 +467,8 @@ if self.dp: dataframe['best_ask'] = ob['asks'][0][0] ``` -!!! Warning - The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used. +!!! 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. ### *ticker(pair)* diff --git a/docs/strategy_analysis_example.md b/docs/strategy_analysis_example.md index 90e39fd76..5c479aa0b 100644 --- a/docs/strategy_analysis_example.md +++ b/docs/strategy_analysis_example.md @@ -24,7 +24,7 @@ config["strategy"] = "SampleStrategy" # Location of the data data_location = Path(config['user_data_dir'], 'data', 'binance') # Pair to analyze - Only use one pair here -pair = "BTC_USDT" +pair = "BTC/USDT" ``` @@ -34,7 +34,9 @@ from freqtrade.data.history import load_pair_history candles = load_pair_history(datadir=data_location, timeframe=config["timeframe"], - pair=pair) + pair=pair, + data_format = "hdf5", + ) # Confirm success print("Loaded " + str(len(candles)) + f" rows of data for {pair} from {data_location}") diff --git a/docs/utils.md b/docs/utils.md index 409bcc134..cf7d5f1d1 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -391,7 +391,7 @@ $ freqtrade list-markets --exchange kraken --all ## Test pairlist -Use the `test-pairlist` subcommand to test the configuration of [dynamic pairlists](configuration.md#pairlists). +Use the `test-pairlist` subcommand to test the configuration of [dynamic pairlists](plugins.md#pairlists). Requires a configuration with specified `pairlists` attribute. Can be used to generate static pairlists to be used during backtesting / hyperopt. @@ -415,7 +415,7 @@ optional arguments: ### Examples -Show whitelist when using a [dynamic pairlist](configuration.md#pairlists). +Show whitelist when using a [dynamic pairlist](plugins.md#pairlists). ``` freqtrade test-pairlist --config config.json --quote USDT BTC diff --git a/environment.yml b/environment.yml index 746c4b912..938b5b6b8 100644 --- a/environment.yml +++ b/environment.yml @@ -1,60 +1,71 @@ name: freqtrade channels: - - defaults - conda-forge +# - defaults dependencies: - # Required for app - - python>=3.7 - - pip - - wheel - - numpy - - pandas - - SQLAlchemy - - arrow - - requests - - urllib3 - - wrapt - - jsonschema - - tabulate - - python-rapidjson - - flask - - python-dotenv - - cachetools - - python-telegram-bot - # Optional for plotting - - plotly - # Optional for hyperopt - - scipy - - scikit-optimize - - scikit-learn - - filelock - - joblib - # Optional for development - - flake8 - - pytest - - pytest-mock - - pytest-asyncio - - pytest-cov - - coveralls - - mypy - # Useful for jupyter - - jupyter - - ipykernel - - isort - - yapf - - pip: - # Required for app - - cython - - pycoingecko - - ccxt +# 1/4 req main + - python>=3.7 + - numpy + - pandas + - pip + + - aiohttp + - SQLAlchemy + - python-telegram-bot + - arrow + - cachetools + - requests + - urllib3 + - wrapt + - jsonschema - TA-Lib - - py_find_1st + - tabulate + - jinja2 + - blosc - sdnotify - # Optional for develpment - - flake8-tidy-imports - - flake8-type-annotations - - pytest-random-order - - -e . + - fastapi + - uvicorn + - pyjwt + - colorama + - questionary + - prompt-toolkit + # ============================ + # 2/4 req dev + - coveralls + - flake8 + - mypy + - pytest + - pytest-asyncio + - pytest-cov + - pytest-mock + - isort + - nbconvert + + # ============================ + # 3/4 req hyperopt + + - scipy + - scikit-learn + - filelock + - scikit-optimize + - joblib + - progressbar2 + # ============================ + # 4/4 req plot + + - plotly + - jupyter + + - pip: + - pycoingecko + - py_find_1st + - tables + - pytest-random-order + - flake8-type-annotations + - ccxt + - flake8-tidy-imports + - -e . + # - python-rapidjso diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py index 74c8c412c..2205d284d 100644 --- a/freqtrade/__init__.py +++ b/freqtrade/__init__.py @@ -1,5 +1,5 @@ """ Freqtrade bot """ -__version__ = '2021.1' +__version__ = '2021.2' if __version__ == 'develop': diff --git a/freqtrade/commands/__init__.py b/freqtrade/commands/__init__.py index 21c5d6812..784b99bed 100644 --- a/freqtrade/commands/__init__.py +++ b/freqtrade/commands/__init__.py @@ -10,8 +10,8 @@ from freqtrade.commands.arguments import Arguments from freqtrade.commands.build_config_commands import start_new_config from freqtrade.commands.data_commands import (start_convert_data, start_download_data, start_list_data) -from freqtrade.commands.deploy_commands import (start_create_userdir, start_new_hyperopt, - start_new_strategy) +from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui, + start_new_hyperopt, start_new_strategy) from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show from freqtrade.commands.list_commands import (start_list_exchanges, start_list_hyperopts, start_list_markets, start_list_strategies, diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index a6c8a245f..c64c11a18 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -70,6 +70,8 @@ ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit", ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url", "trade_source", "timeframe"] +ARGS_INSTALL_UI = ["erase_ui_only"] + ARGS_SHOW_TRADES = ["db_url", "trade_ids", "print_json"] ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable", @@ -167,8 +169,8 @@ class Arguments: from freqtrade.commands import (start_backtesting, start_convert_data, start_create_userdir, start_download_data, start_edge, start_hyperopt, - start_hyperopt_list, start_hyperopt_show, start_list_data, - start_list_exchanges, start_list_hyperopts, + start_hyperopt_list, start_hyperopt_show, start_install_ui, + start_list_data, start_list_exchanges, start_list_hyperopts, start_list_markets, start_list_strategies, start_list_timeframes, start_new_config, start_new_hyperopt, start_new_strategy, start_plot_dataframe, start_plot_profit, @@ -355,6 +357,14 @@ class Arguments: test_pairlist_cmd.set_defaults(func=start_test_pairlist) self._build_args(optionlist=ARGS_TEST_PAIRLIST, parser=test_pairlist_cmd) + # Add install-ui subcommand + install_ui_cmd = subparsers.add_parser( + 'install-ui', + help='Install FreqUI', + ) + install_ui_cmd.set_defaults(func=start_install_ui) + self._build_args(optionlist=ARGS_INSTALL_UI, parser=install_ui_cmd) + # Add Plotting subcommand plot_dataframe_cmd = subparsers.add_parser( 'plot-dataframe', diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index 668b4abf5..7dc85377d 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -387,6 +387,12 @@ AVAILABLE_CLI_OPTIONS = { help='Clean all existing data for the selected exchange/pairs/timeframes.', action='store_true', ), + "erase_ui_only": Arg( + '--erase', + help="Clean UI folder, don't download new version.", + action='store_true', + default=False, + ), # Templating options "template": Arg( '--template', diff --git a/freqtrade/commands/deploy_commands.py b/freqtrade/commands/deploy_commands.py index a0105e140..5ba3db9f9 100644 --- a/freqtrade/commands/deploy_commands.py +++ b/freqtrade/commands/deploy_commands.py @@ -1,7 +1,9 @@ import logging import sys from pathlib import Path -from typing import Any, Dict +from typing import Any, Dict, Optional, Tuple + +import requests from freqtrade.configuration import setup_utils_configuration from freqtrade.configuration.directory_operations import copy_sample_files, create_userdata_dir @@ -137,3 +139,87 @@ def start_new_hyperopt(args: Dict[str, Any]) -> None: deploy_new_hyperopt(args['hyperopt'], new_path, args['template']) else: raise OperationalException("`new-hyperopt` requires --hyperopt to be set.") + + +def clean_ui_subdir(directory: Path): + if directory.is_dir(): + logger.info("Removing UI directory content.") + + for p in reversed(list(directory.glob('**/*'))): # iterate contents from leaves to root + if p.name in ('.gitkeep', 'fallback_file.html'): + continue + if p.is_file(): + p.unlink() + elif p.is_dir(): + p.rmdir() + + +def read_ui_version(dest_folder: Path) -> Optional[str]: + file = dest_folder / '.uiversion' + if not file.is_file(): + return None + + with file.open('r') as f: + return f.read() + + +def download_and_install_ui(dest_folder: Path, dl_url: str, version: str): + from io import BytesIO + from zipfile import ZipFile + + logger.info(f"Downloading {dl_url}") + resp = requests.get(dl_url).content + dest_folder.mkdir(parents=True, exist_ok=True) + with ZipFile(BytesIO(resp)) as zf: + for fn in zf.filelist: + with zf.open(fn) as x: + destfile = dest_folder / fn.filename + if fn.is_dir(): + destfile.mkdir(exist_ok=True) + else: + destfile.write_bytes(x.read()) + with (dest_folder / '.uiversion').open('w') as f: + f.write(version) + + +def get_ui_download_url() -> Tuple[str, str]: + base_url = 'https://api.github.com/repos/freqtrade/frequi/' + # Get base UI Repo path + + resp = requests.get(f"{base_url}releases") + resp.raise_for_status() + r = resp.json() + + latest_version = r[0]['name'] + assets = r[0].get('assets', []) + dl_url = '' + if assets and len(assets) > 0: + dl_url = assets[0]['browser_download_url'] + + # URL not found - try assets url + if not dl_url: + assets = r[0]['assets_url'] + resp = requests.get(assets) + r = resp.json() + dl_url = r[0]['browser_download_url'] + + return dl_url, latest_version + + +def start_install_ui(args: Dict[str, Any]) -> None: + + dest_folder = Path(__file__).parents[1] / 'rpc/api_server/ui/installed/' + # First make sure the assets are removed. + dl_url, latest_version = get_ui_download_url() + + curr_version = read_ui_version(dest_folder) + if curr_version == latest_version and not args.get('erase_ui_only'): + logger.info(f"UI already up-to-date, FreqUI Version {curr_version}.") + return + + clean_ui_subdir(dest_folder) + if args.get('erase_ui_only'): + logger.info("Erased UI directory content. Not downloading new version.") + else: + # Download a new version + download_and_install_ui(dest_folder, dl_url, latest_version) diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 69301ca0e..802ddc2b1 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -45,6 +45,16 @@ USERPATH_NOTEBOOKS = 'notebooks' TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent'] + +# Define decimals per coin for outputs +# Only used for outputs. +DECIMAL_PER_COIN_FALLBACK = 3 # Should be low to avoid listing all possible FIAT's +DECIMALS_PER_COIN = { + 'BTC': 8, + 'ETH': 5, +} + + # Soure files with destination directories within user-directory USER_DATA_FILES = { 'sample_strategy.py': USERPATH_STRATEGIES, diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index 2b51f5371..8e851a8e8 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -2,9 +2,8 @@ Helpers when analyzing backtest data """ import logging -from datetime import timezone from pathlib import Path -from typing import Any, Dict, Optional, Tuple, Union +from typing import Any, Dict, List, Optional, Tuple, Union import numpy as np import pandas as pd @@ -16,9 +15,22 @@ from freqtrade.persistence import Trade, init_db logger = logging.getLogger(__name__) -# must align with columns in backtest.py -BT_DATA_COLUMNS = ["pair", "profit_percent", "open_date", "close_date", "index", "trade_duration", - "open_rate", "close_rate", "open_at_end", "sell_reason"] +# Old format - maybe remove? +BT_DATA_COLUMNS_OLD = ["pair", "profit_percent", "open_date", "close_date", "index", + "trade_duration", "open_rate", "close_rate", "open_at_end", "sell_reason"] + +# Mid-term format, crated by BacktestResult Named Tuple +BT_DATA_COLUMNS_MID = ['pair', 'profit_percent', 'open_date', 'close_date', 'trade_duration', + 'open_rate', 'close_rate', 'open_at_end', 'sell_reason', 'fee_open', + 'fee_close', 'amount', 'profit_abs', 'profit_ratio'] + +# Newest format +BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date', + 'open_rate', 'close_rate', + 'fee_open', 'fee_close', 'trade_duration', + 'profit_ratio', 'profit_abs', 'sell_reason', + 'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs', + 'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', ] def get_latest_optimize_filename(directory: Union[Path, str], variant: str) -> str: @@ -154,7 +166,7 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non ) else: # old format - only with lists. - df = pd.DataFrame(data, columns=BT_DATA_COLUMNS) + df = pd.DataFrame(data, columns=BT_DATA_COLUMNS_OLD) df['open_date'] = pd.to_datetime(df['open_date'], unit='s', @@ -166,7 +178,10 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non utc=True, infer_datetime_format=True ) + # Create compatibility with new format df['profit_abs'] = df['close_rate'] - df['open_rate'] + if 'profit_ratio' not in df.columns: + df['profit_ratio'] = df['profit_percent'] df = df.sort_values("open_date").reset_index(drop=True) return df @@ -209,6 +224,20 @@ 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: + """ + Convert list of Trade objects to pandas Dataframe + :param trades: List of trade objects + :return: Dataframe with BT_DATA_COLUMNS + """ + df = pd.DataFrame.from_records([t.to_json() for t in trades], columns=BT_DATA_COLUMNS) + if len(df) > 0: + df.loc[:, 'close_date'] = pd.to_datetime(df['close_date'], utc=True) + df.loc[:, 'open_date'] = pd.to_datetime(df['open_date'], utc=True) + df.loc[:, 'close_rate'] = df['close_rate'].astype('float64') + return df + + def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataFrame: """ Load trades from a DB (using dburl) @@ -219,36 +248,10 @@ def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataF """ init_db(db_url, clean_open_orders=False) - columns = ["pair", "open_date", "close_date", "profit", "profit_percent", - "open_rate", "close_rate", "amount", "trade_duration", "sell_reason", - "fee_open", "fee_close", "open_rate_requested", "close_rate_requested", - "stake_amount", "max_rate", "min_rate", "id", "exchange", - "stop_loss", "initial_stop_loss", "strategy", "timeframe"] - filters = [] if strategy: filters.append(Trade.strategy == strategy) - - trades = pd.DataFrame([(t.pair, - t.open_date.replace(tzinfo=timezone.utc), - t.close_date.replace(tzinfo=timezone.utc) if t.close_date else None, - t.calc_profit(), t.calc_profit_ratio(), - t.open_rate, t.close_rate, t.amount, - (round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2) - if t.close_date else None), - t.sell_reason, - t.fee_open, t.fee_close, - t.open_rate_requested, - t.close_rate_requested, - t.stake_amount, - t.max_rate, - t.min_rate, - t.id, t.exchange, - t.stop_loss, t.initial_stop_loss, - t.strategy, t.timeframe - ) - for t in Trade.get_trades(filters).all()], - columns=columns) + trades = trade_list_to_dataframe(Trade.get_trades(filters).all()) return trades @@ -309,7 +312,7 @@ def calculate_market_change(data: Dict[str, pd.DataFrame], column: str = "close" end = df[column].dropna().iloc[-1] tmp_means.append((end - start) / start) - return np.mean(tmp_means) + return float(np.mean(tmp_means)) def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame], @@ -334,7 +337,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, """ Adds a column `col_name` with the cumulative profit for the given trades array. :param df: DataFrame with date index - :param trades: DataFrame containing trades (requires columns close_date and profit_percent) + :param trades: DataFrame containing trades (requires columns close_date and profit_ratio) :param col_name: Column name that will be assigned the results :param timeframe: Timeframe used during the operations :return: Returns df with one additional column, col_name, containing the cumulative profit. @@ -346,8 +349,8 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, timeframe_minutes = timeframe_to_minutes(timeframe) # Resample to timeframe to make sure trades match candles _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_date' - )[['profit_percent']].sum() - df.loc[:, col_name] = _trades_sum['profit_percent'].cumsum() + )[['profit_ratio']].sum() + df.loc[:, col_name] = _trades_sum['profit_ratio'].cumsum() # Set first value to 0 df.loc[df.iloc[0].name, col_name] = 0 # FFill to get continuous @@ -356,13 +359,13 @@ 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_percent' + value_col: str = 'profit_ratio' ) -> Tuple[float, pd.Timestamp, pd.Timestamp]: """ Calculate max drawdown and the corresponding close dates - :param trades: DataFrame containing trades (requires columns close_date and profit_percent) + :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_percent') + :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 :raise: ValueError if trade-dataframe was found empty. """ @@ -380,3 +383,21 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date' 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 + + +def calculate_csum(trades: pd.DataFrame) -> 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) + :return: Tuple (float, float) with cumsum of profit_abs + :raise: ValueError if trade-dataframe was found empty. + """ + if len(trades) == 0: + raise ValueError("Trade dataframe empty.") + + csum_df = pd.DataFrame() + csum_df['sum'] = trades['profit_abs'].cumsum() + csum_min = csum_df['sum'].min() + csum_max = csum_df['sum'].max() + + return csum_min, csum_max diff --git a/freqtrade/data/history/jsondatahandler.py b/freqtrade/data/history/jsondatahandler.py index 9122170d5..301d228a8 100644 --- a/freqtrade/data/history/jsondatahandler.py +++ b/freqtrade/data/history/jsondatahandler.py @@ -86,8 +86,12 @@ class JsonDataHandler(IDataHandler): filename = self._pair_data_filename(self._datadir, pair, timeframe) if not filename.exists(): return DataFrame(columns=self._columns) - pairdata = read_json(filename, orient='values') - pairdata.columns = self._columns + try: + pairdata = read_json(filename, orient='values') + pairdata.columns = self._columns + except ValueError: + logger.error(f"Could not load data for {pair}.") + return DataFrame(columns=self._columns) pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float', 'low': 'float', 'close': 'float', 'volume': 'float'}) pairdata['date'] = to_datetime(pairdata['date'], diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py index e549a3701..ff86e522e 100644 --- a/freqtrade/edge/edge_positioning.py +++ b/freqtrade/edge/edge_positioning.py @@ -104,6 +104,7 @@ class Edge: exchange=self.exchange, timeframe=self.strategy.timeframe, timerange=self._timerange, + data_format=self.config.get('dataformat_ohlcv', 'json'), ) data = load_data( @@ -159,7 +160,8 @@ class Edge: available_capital = (total_capital + capital_in_trade) * self._capital_ratio allowed_capital_at_risk = available_capital * self._allowed_risk max_position_size = abs(allowed_capital_at_risk / stoploss) - position_size = min(max_position_size, free_capital) + # Position size must be below available capital. + position_size = min(min(max_position_size, free_capital), available_capital) if pair in self._cached_pairs: logger.info( 'winrate: %s, expectancy: %s, position size: %s, pair: %s,' diff --git a/freqtrade/exchange/bittrex.py b/freqtrade/exchange/bittrex.py index 4318f9cf0..fd7d47668 100644 --- a/freqtrade/exchange/bittrex.py +++ b/freqtrade/exchange/bittrex.py @@ -19,5 +19,11 @@ class Bittrex(Exchange): """ _ft_has: Dict = { + "ohlcv_candle_limit_per_timeframe": { + '1m': 1440, + '5m': 288, + '1h': 744, + '1d': 365, + }, "l2_limit_range": [1, 25, 500], } diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 436c8e4e9..617cd6c26 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -3,6 +3,7 @@ Cryptocurrency Exchanges support """ import asyncio +import http import inspect import logging from copy import deepcopy @@ -17,7 +18,7 @@ from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE, TRU decimal_to_precision) from pandas import DataFrame -from freqtrade.constants import ListPairsWithTimeframes +from freqtrade.constants import DEFAULT_AMOUNT_RESERVE_PERCENT, ListPairsWithTimeframes from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError, InvalidOrderException, OperationalException, RetryableOrderError, @@ -34,6 +35,12 @@ CcxtModuleType = Any logger = logging.getLogger(__name__) +# Workaround for adding samesite support to pre 3.8 python +# Only applies to python3.7, and only on certain exchanges (kraken) +# Replicates the fix from starlette (which is actually causing this problem) +http.cookies.Morsel._reserved["samesite"] = "SameSite" # type: ignore + + class Exchange: _config: Dict = {} @@ -66,6 +73,7 @@ class Exchange: """ self._api: ccxt.Exchange = None self._api_async: ccxt_async.Exchange = None + self._markets: Dict = {} self._config.update(config) @@ -93,7 +101,6 @@ class Exchange: logger.info("Overriding exchange._ft_has with config params, result: %s", self._ft_has) # Assign this directly for easy access - self._ohlcv_candle_limit = self._ft_has['ohlcv_candle_limit'] self._ohlcv_partial_candle = self._ft_has['ohlcv_partial_candle'] self._trades_pagination = self._ft_has['trades_pagination'] @@ -129,7 +136,8 @@ class Exchange: self.validate_pairs(config['exchange']['pair_whitelist']) self.validate_ordertypes(config.get('order_types', {})) self.validate_order_time_in_force(config.get('order_time_in_force', {})) - self.validate_required_startup_candles(config.get('startup_candle_count', 0)) + self.validate_required_startup_candles(config.get('startup_candle_count', 0), + config.get('timeframe', '')) # Converts the interval provided in minutes in config to seconds self.markets_refresh_interval: int = exchange_config.get( @@ -190,24 +198,30 @@ class Exchange: def timeframes(self) -> List[str]: return list((self._api.timeframes or {}).keys()) - @property - def ohlcv_candle_limit(self) -> int: - """exchange ohlcv candle limit""" - return int(self._ohlcv_candle_limit) - @property def markets(self) -> Dict: """exchange ccxt markets""" - if not self._api.markets: + if not self._markets: logger.info("Markets were not loaded. Loading them now..") self._load_markets() - return self._api.markets + return self._markets @property def precisionMode(self) -> str: """exchange ccxt precisionMode""" return self._api.precisionMode + def ohlcv_candle_limit(self, timeframe: str) -> int: + """ + Exchange ohlcv candle limit + Uses ohlcv_candle_limit_per_timeframe if the exchange has different limts + per timeframe (e.g. bittrex), otherwise falls back to ohlcv_candle_limit + :param timeframe: Timeframe to check + :return: Candle limit as integer + """ + return int(self._ft_has.get('ohlcv_candle_limit_per_timeframe', {}).get( + timeframe, self._ft_has.get('ohlcv_candle_limit'))) + def get_markets(self, base_currencies: List[str] = None, quote_currencies: List[str] = None, pairs_only: bool = False, active_only: bool = False) -> Dict[str, Any]: """ @@ -291,7 +305,7 @@ class Exchange: def _load_markets(self) -> None: """ Initialize markets both sync and async """ try: - self._api.load_markets() + self._markets = self._api.load_markets() self._load_async_markets() self._last_markets_refresh = arrow.utcnow().int_timestamp except ccxt.BaseError as e: @@ -306,7 +320,7 @@ class Exchange: return None logger.debug("Performing scheduled market reload..") try: - self._api.load_markets(reload=True) + self._markets = self._api.load_markets(reload=True) # Also reload async markets to avoid issues with newly listed pairs self._load_async_markets(reload=True) self._last_markets_refresh = arrow.utcnow().int_timestamp @@ -420,15 +434,16 @@ class Exchange: raise OperationalException( f'Time in force policies are not supported for {self.name} yet.') - def validate_required_startup_candles(self, startup_candles: int) -> None: + def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> None: """ - Checks if required startup_candles is more than ohlcv_candle_limit. + Checks if required startup_candles is more than ohlcv_candle_limit(). Requires a grace-period of 5 candles - so a startup-period up to 494 is allowed by default. """ - if startup_candles + 5 > self._ft_has['ohlcv_candle_limit']: + candle_limit = self.ohlcv_candle_limit(timeframe) + if startup_candles + 5 > candle_limit: raise OperationalException( f"This strategy requires {startup_candles} candles to start. " - f"{self.name} only provides {self._ft_has['ohlcv_candle_limit']}.") + f"{self.name} only provides {candle_limit} for {timeframe}.") def exchange_has(self, endpoint: str) -> bool: """ @@ -489,6 +504,41 @@ class Exchange: else: return 1 / pow(10, precision) + def get_min_pair_stake_amount(self, pair: str, price: float, + stoploss: float) -> Optional[float]: + try: + market = self.markets[pair] + except KeyError: + raise ValueError(f"Can't get market information for symbol {pair}") + + if 'limits' not in market: + return None + + min_stake_amounts = [] + limits = market['limits'] + if ('cost' in limits and 'min' in limits['cost'] + and limits['cost']['min'] is not None): + min_stake_amounts.append(limits['cost']['min']) + + if ('amount' in limits and 'min' in limits['amount'] + and limits['amount']['min'] is not None): + min_stake_amounts.append(limits['amount']['min'] * price) + + if not min_stake_amounts: + return None + + # reserve some percent defined in config (5% default) + stoploss + amount_reserve_percent = 1.0 - self._config.get('amount_reserve_percent', + DEFAULT_AMOUNT_RESERVE_PERCENT) + amount_reserve_percent += stoploss + # it should not be more than 50% + amount_reserve_percent = max(amount_reserve_percent, 0.5) + + # 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 + def 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()}' @@ -660,8 +710,8 @@ class Exchange: @retrier def fetch_ticker(self, pair: str) -> dict: try: - if (pair not in self._api.markets or - self._api.markets[pair].get('active', False) is False): + if (pair not in self.markets or + self.markets[pair].get('active', False) is False): raise ExchangeError(f"Pair {pair} not available") data = self._api.fetch_ticker(pair) return data @@ -678,7 +728,7 @@ class Exchange: """ Get candle history using asyncio and returns the list of candles. Handles all async work for this. - Async over one pair, assuming we get `self._ohlcv_candle_limit` candles per call. + Async over one pair, assuming we get `self.ohlcv_candle_limit()` candles per call. :param pair: Pair to download :param timeframe: Timeframe to get data for :param since_ms: Timestamp in milliseconds to get history from @@ -708,7 +758,7 @@ class Exchange: Download historic ohlcv """ - one_call = timeframe_to_msecs(timeframe) * self._ohlcv_candle_limit + one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe) logger.debug( "one_call: %s msecs (%s)", one_call, @@ -810,7 +860,7 @@ class Exchange: data = await self._api_async.fetch_ohlcv(pair, timeframe=timeframe, since=since_ms, - limit=self._ohlcv_candle_limit) + limit=self.ohlcv_candle_limit(timeframe)) # Some exchanges sort OHLCV in ASC order and others in DESC. # Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last) @@ -983,7 +1033,7 @@ class Exchange: """ Get trade history data using asyncio. Handles all async work and returns the list of candles. - Async over one pair, assuming we get `self._ohlcv_candle_limit` candles per call. + Async over one pair, assuming we get `self.ohlcv_candle_limit()` candles per call. :param pair: Pair to download :param since: Timestamp in milliseconds to get history from :param until: Timestamp in milliseconds. Defaults to current timestamp if not defined. diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index f45d4cacc..d546dd6d2 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -179,6 +179,7 @@ class FreqtradeBot(LoggingMixin): # Without this, freqtrade my try to recreate stoploss_on_exchange orders # while selling is in process, since telegram messages arrive in an different thread. with self._sell_lock: + trades = Trade.get_open_trades() # First process current opened trades (positions) self.exit_positions(trades) @@ -233,7 +234,7 @@ class FreqtradeBot(LoggingMixin): _whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist]) return _whitelist - def get_free_open_trades(self): + def get_free_open_trades(self) -> int: """ Return the number of free open trades slots or 0 if max number of open trades reached @@ -246,7 +247,7 @@ class FreqtradeBot(LoggingMixin): Updates open orders based on order list kept in the database. Mainly updates the state of orders - but may also close trades """ - if self.config['dry_run']: + if self.config['dry_run'] or self.config['exchange'].get('skip_open_order_update', False): # Updating open orders in dry-run does not make sense and will fail. return @@ -439,117 +440,6 @@ class FreqtradeBot(LoggingMixin): return used_rate - def get_trade_stake_amount(self, pair: str) -> float: - """ - Calculate stake amount for the trade - :return: float: Stake amount - :raise: DependencyException if the available stake amount is too low - """ - stake_amount: float - # Ensure wallets are uptodate. - self.wallets.update() - - if self.edge: - stake_amount = self.edge.stake_amount( - pair, - self.wallets.get_free(self.config['stake_currency']), - self.wallets.get_total(self.config['stake_currency']), - Trade.total_open_trades_stakes() - ) - else: - stake_amount = self.config['stake_amount'] - if stake_amount == constants.UNLIMITED_STAKE_AMOUNT: - stake_amount = self._calculate_unlimited_stake_amount() - - return self._check_available_stake_amount(stake_amount) - - def _get_available_stake_amount(self) -> float: - """ - Return the total currently available balance in stake currency, - respecting tradable_balance_ratio. - Calculated as - + free amount ) * tradable_balance_ratio - - """ - val_tied_up = Trade.total_open_trades_stakes() - - # Ensure % is used from the overall balance - # Otherwise we'd risk lowering stakes with each open trade. - # (tied up + current free) * ratio) - tied up - available_amount = ((val_tied_up + self.wallets.get_free(self.config['stake_currency'])) * - self.config['tradable_balance_ratio']) - val_tied_up - return available_amount - - def _calculate_unlimited_stake_amount(self) -> float: - """ - Calculate stake amount for "unlimited" stake amount - :return: 0 if max number of trades reached, else stake_amount to use. - """ - free_open_trades = self.get_free_open_trades() - if not free_open_trades: - return 0 - - available_amount = self._get_available_stake_amount() - - return available_amount / free_open_trades - - def _check_available_stake_amount(self, stake_amount: float) -> float: - """ - Check if stake amount can be fulfilled with the available balance - for the stake currency - :return: float: Stake amount - """ - available_amount = self._get_available_stake_amount() - - if self.config['amend_last_stake_amount']: - # Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio - # Otherwise the remaining amount is too low to trade. - if available_amount > (stake_amount * self.config['last_stake_amount_min_ratio']): - stake_amount = min(stake_amount, available_amount) - else: - stake_amount = 0 - - if available_amount < stake_amount: - raise DependencyException( - f"Available balance ({available_amount} {self.config['stake_currency']}) is " - f"lower than stake amount ({stake_amount} {self.config['stake_currency']})" - ) - - return stake_amount - - def _get_min_pair_stake_amount(self, pair: str, price: float) -> Optional[float]: - try: - market = self.exchange.markets[pair] - except KeyError: - raise ValueError(f"Can't get market information for symbol {pair}") - - if 'limits' not in market: - return None - - min_stake_amounts = [] - limits = market['limits'] - if ('cost' in limits and 'min' in limits['cost'] - and limits['cost']['min'] is not None): - min_stake_amounts.append(limits['cost']['min']) - - if ('amount' in limits and 'min' in limits['amount'] - and limits['amount']['min'] is not None): - min_stake_amounts.append(limits['amount']['min'] * price) - - if not min_stake_amounts: - return None - - # reserve some percent defined in config (5% default) + stoploss - amount_reserve_percent = 1.0 - self.config.get('amount_reserve_percent', - constants.DEFAULT_AMOUNT_RESERVE_PERCENT) - amount_reserve_percent += self.strategy.stoploss - # it should not be more than 50% - amount_reserve_percent = max(amount_reserve_percent, 0.5) - - # 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 - def create_trade(self, pair: str) -> bool: """ Check the implemented trading strategy for buy signals. @@ -583,7 +473,8 @@ class FreqtradeBot(LoggingMixin): (buy, sell) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df) if buy and not sell: - stake_amount = self.get_trade_stake_amount(pair) + stake_amount = self.wallets.get_trade_stake_amount(pair, self.get_free_open_trades(), + self.edge) if not stake_amount: logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.") return False @@ -646,7 +537,8 @@ class FreqtradeBot(LoggingMixin): if not buy_limit_requested: raise PricingError('Could not determine buy price.') - min_stake_amount = self._get_min_pair_stake_amount(pair, buy_limit_requested) + min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, buy_limit_requested, + self.strategy.stoploss) if min_stake_amount is not None and min_stake_amount > stake_amount: logger.warning( f"Can't open a new trade for {pair}: stake amount " @@ -998,7 +890,8 @@ class FreqtradeBot(LoggingMixin): logger.warning('Stoploss order was cancelled, but unable to recreate one.') # Finally we check if stoploss on exchange should be moved up because of trailing. - if stoploss_order and self.config.get('trailing_stop', False): + if stoploss_order and (self.config.get('trailing_stop', False) + or self.config.get('use_custom_stoploss', False)): # if trailing stoploss is enabled we check if stoploss value has changed # in which case we cancel stoploss order and put another one with new # value immediately @@ -1178,7 +1071,9 @@ class FreqtradeBot(LoggingMixin): if not self.exchange.check_order_canceled_empty(order): try: # if trade is not partially completed, just delete the order - self.exchange.cancel_order(trade.open_order_id, trade.pair) + co = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, + trade.amount) + trade.update_order(co) except InvalidOrderException: logger.exception(f"Could not cancel sell order {trade.open_order_id}") return 'error cancelling order' @@ -1186,6 +1081,7 @@ class FreqtradeBot(LoggingMixin): else: reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] logger.info('Sell order %s for %s.', reason, trade) + trade.update_order(order) trade.close_rate = None trade.close_rate_requested = None @@ -1288,6 +1184,7 @@ class FreqtradeBot(LoggingMixin): trade.orders.append(order_obj) trade.open_order_id = order['id'] + trade.sell_order_status = '' trade.close_rate_requested = limit trade.sell_reason = sell_reason.value # In case of market sell orders the order can be closed immediately diff --git a/freqtrade/misc.py b/freqtrade/misc.py index 359d0d0e4..7bbc24056 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -9,13 +9,37 @@ from pathlib import Path from typing import Any from typing.io import IO -import numpy as np import rapidjson +from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN + logger = logging.getLogger(__name__) +def decimals_per_coin(coin: str): + """ + Helper method getting decimal amount for this coin + example usage: f".{decimals_per_coin('USD')}f" + :param coin: Which coin are we printing the price / value for + """ + return DECIMALS_PER_COIN.get(coin, DECIMAL_PER_COIN_FALLBACK) + + +def round_coin_value(value: float, coin: str, show_coin_name=True) -> str: + """ + Get price value for this coin + :param value: Value to be printed + :param coin: Which coin are we printing the price / value for + :param show_coin_name: Return string in format: "222.22 USDT" or "222.22" + :return: Formatted / rounded value (with or without coin name) + """ + if show_coin_name: + return f"{value:.{decimals_per_coin(coin)}f} {coin}" + else: + return f"{value:.{decimals_per_coin(coin)}f}" + + def shorten_date(_date: str) -> str: """ Trim the date so it fits on small screens @@ -28,20 +52,6 @@ def shorten_date(_date: str) -> str: return new_date -############################################ -# Used by scripts # -# Matplotlib doesn't support ::datetime64, # -# so we need to convert it into ::datetime # -############################################ -def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray: - """ - Convert an pandas-array of timestamps into - An numpy-array of datetimes - :return: numpy-array of datetime - """ - return dates.dt.to_pydatetime() - - def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool = True) -> None: """ Dump JSON data into a file diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index 106d0f200..3186313e1 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -7,13 +7,14 @@ import logging from collections import defaultdict from copy import deepcopy from datetime import datetime, timedelta, timezone -from typing import Any, Dict, List, NamedTuple, Optional, Tuple +from typing import Any, Dict, List, Optional, Tuple from pandas import DataFrame from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.data import history +from freqtrade.data.btanalysis import trade_list_to_dataframe from freqtrade.data.converter import trim_dataframe from freqtrade.data.dataprovider import DataProvider from freqtrade.exceptions import OperationalException @@ -41,25 +42,6 @@ LOW_IDX = 5 HIGH_IDX = 6 -class BacktestResult(NamedTuple): - """ - NamedTuple Defining BacktestResults inputs. - """ - pair: str - profit_percent: float - profit_abs: float - open_date: datetime - open_rate: float - open_fee: float - close_date: datetime - close_rate: float - close_fee: float - amount: float - trade_duration: float - open_at_end: bool - sell_reason: SellType - - class Backtesting: """ Backtesting class, this class contains all the logic to run a backtest @@ -264,7 +246,7 @@ class Backtesting: else: return sell_row[OPEN_IDX] - def _get_sell_trade_entry(self, trade: Trade, sell_row: Tuple) -> Optional[BacktestResult]: + def _get_sell_trade_entry(self, trade: Trade, sell_row: Tuple) -> Optional[Trade]: sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], sell_row[DATE_IDX], sell_row[BUY_IDX], sell_row[SELL_IDX], @@ -276,25 +258,12 @@ class Backtesting: trade.close_date = sell_row[DATE_IDX] trade.sell_reason = sell.sell_type trade.close(closerate, show_msg=False) + return trade - return BacktestResult(pair=trade.pair, - profit_percent=trade.calc_profit_ratio(rate=closerate), - profit_abs=trade.calc_profit(rate=closerate), - open_date=trade.open_date, - open_rate=trade.open_rate, - open_fee=self.fee, - close_date=sell_row[DATE_IDX], - close_rate=closerate, - close_fee=self.fee, - amount=trade.amount, - trade_duration=trade_dur, - open_at_end=False, - sell_reason=sell.sell_type - ) return None def handle_left_open(self, open_trades: Dict[str, List[Trade]], - data: Dict[str, List[Tuple]]) -> List[BacktestResult]: + data: Dict[str, List[Tuple]]) -> List[Trade]: """ Handling of left open trades at the end of backtesting """ @@ -304,24 +273,11 @@ class Backtesting: for trade in open_trades[pair]: sell_row = data[pair][-1] - trade_entry = BacktestResult(pair=trade.pair, - profit_percent=trade.calc_profit_ratio( - rate=sell_row[OPEN_IDX]), - profit_abs=trade.calc_profit(sell_row[OPEN_IDX]), - open_date=trade.open_date, - open_rate=trade.open_rate, - open_fee=self.fee, - close_date=sell_row[DATE_IDX], - close_rate=sell_row[OPEN_IDX], - close_fee=self.fee, - amount=trade.amount, - trade_duration=int(( - sell_row[DATE_IDX] - trade.open_date - ).total_seconds() // 60), - open_at_end=True, - sell_reason=SellType.FORCE_SELL - ) - trades.append(trade_entry) + trade.close_date = sell_row[DATE_IDX] + trade.sell_reason = SellType.FORCE_SELL + trade.close(sell_row[OPEN_IDX], show_msg=False) + trade.is_open = True + trades.append(trade) return trades def backtest(self, processed: Dict, stake_amount: float, @@ -348,7 +304,7 @@ class Backtesting: f"start_date: {start_date}, end_date: {end_date}, " f"max_open_trades: {max_open_trades}, position_stacking: {position_stacking}" ) - trades = [] + trades: List[Trade] = [] self.prepare_backtest(enable_protections) # Use dict of lists with data for performance @@ -429,7 +385,7 @@ class Backtesting: trades += self.handle_left_open(open_trades, data=data) - return DataFrame.from_records(trades, columns=BacktestResult._fields) + return trade_list_to_dataframe(trades) def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any], timerange: TimeRange): logger.info("Running backtesting for Strategy %s", strat.get_strategy_name()) diff --git a/freqtrade/optimize/default_hyperopt_loss.py b/freqtrade/optimize/default_hyperopt_loss.py index 9dbdc4403..3712fd9a6 100644 --- a/freqtrade/optimize/default_hyperopt_loss.py +++ b/freqtrade/optimize/default_hyperopt_loss.py @@ -42,7 +42,7 @@ class ShortTradeDurHyperOptLoss(IHyperOptLoss): * 0.25: Avoiding trade loss * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above """ - total_profit = results['profit_percent'].sum() + total_profit = results['profit_ratio'].sum() trade_duration = results['trade_duration'].mean() trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index d4b9f4c3b..eee0f13b3 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -546,10 +546,11 @@ class Hyperopt: ) return self._get_results_dict(backtesting_results, min_date, max_date, - params_dict, params_details) + params_dict, params_details, + processed=processed) def _get_results_dict(self, backtesting_results, min_date, max_date, - params_dict, params_details): + params_dict, params_details, processed: Dict[str, DataFrame]): results_metrics = self._calculate_results_metrics(backtesting_results) results_explanation = self._format_results_explanation_string(results_metrics) @@ -563,7 +564,8 @@ class Hyperopt: loss: float = MAX_LOSS if trade_count >= self.config['hyperopt_min_trades']: loss = self.calculate_loss(results=backtesting_results, trade_count=trade_count, - min_date=min_date.datetime, max_date=max_date.datetime) + min_date=min_date.datetime, max_date=max_date.datetime, + config=self.config, processed=processed) return { 'loss': loss, 'params_dict': params_dict, @@ -574,20 +576,20 @@ class Hyperopt: } def _calculate_results_metrics(self, backtesting_results: DataFrame) -> Dict: - wins = len(backtesting_results[backtesting_results.profit_percent > 0]) - draws = len(backtesting_results[backtesting_results.profit_percent == 0]) - losses = len(backtesting_results[backtesting_results.profit_percent < 0]) + wins = len(backtesting_results[backtesting_results['profit_ratio'] > 0]) + draws = len(backtesting_results[backtesting_results['profit_ratio'] == 0]) + losses = len(backtesting_results[backtesting_results['profit_ratio'] < 0]) return { 'trade_count': len(backtesting_results.index), 'wins': wins, 'draws': draws, 'losses': losses, 'winsdrawslosses': f"{wins:>4} {draws:>4} {losses:>4}", - 'avg_profit': backtesting_results.profit_percent.mean() * 100.0, - 'median_profit': backtesting_results.profit_percent.median() * 100.0, - 'total_profit': backtesting_results.profit_abs.sum(), - 'profit': backtesting_results.profit_percent.sum() * 100.0, - 'duration': backtesting_results.trade_duration.mean(), + 'avg_profit': backtesting_results['profit_ratio'].mean() * 100.0, + 'median_profit': backtesting_results['profit_ratio'].median() * 100.0, + 'total_profit': backtesting_results['profit_abs'].sum(), + 'profit': backtesting_results['profit_ratio'].sum() * 100.0, + 'duration': backtesting_results['trade_duration'].mean(), } def _format_results_explanation_string(self, results_metrics: Dict) -> str: diff --git a/freqtrade/optimize/hyperopt_loss_interface.py b/freqtrade/optimize/hyperopt_loss_interface.py index 48407a8a8..b5aa588b2 100644 --- a/freqtrade/optimize/hyperopt_loss_interface.py +++ b/freqtrade/optimize/hyperopt_loss_interface.py @@ -5,6 +5,7 @@ This module defines the interface for the loss-function for hyperopt from abc import ABC, abstractmethod from datetime import datetime +from typing import Dict from pandas import DataFrame @@ -19,7 +20,9 @@ class IHyperOptLoss(ABC): @staticmethod @abstractmethod def hyperopt_loss_function(results: DataFrame, trade_count: int, - min_date: datetime, max_date: datetime, *args, **kwargs) -> float: + min_date: datetime, max_date: datetime, + config: Dict, processed: Dict[str, DataFrame], + *args, **kwargs) -> float: """ Objective function, returns smaller number for better results """ diff --git a/freqtrade/optimize/hyperopt_loss_onlyprofit.py b/freqtrade/optimize/hyperopt_loss_onlyprofit.py index 43176dbad..33f3f5bc6 100644 --- a/freqtrade/optimize/hyperopt_loss_onlyprofit.py +++ b/freqtrade/optimize/hyperopt_loss_onlyprofit.py @@ -34,5 +34,5 @@ class OnlyProfitHyperOptLoss(IHyperOptLoss): """ Objective function, returns smaller number for better results. """ - total_profit = results['profit_percent'].sum() + total_profit = results['profit_ratio'].sum() return 1 - total_profit / EXPECTED_MAX_PROFIT diff --git a/freqtrade/optimize/hyperopt_loss_sharpe.py b/freqtrade/optimize/hyperopt_loss_sharpe.py index 232fb33b6..2c8ae552d 100644 --- a/freqtrade/optimize/hyperopt_loss_sharpe.py +++ b/freqtrade/optimize/hyperopt_loss_sharpe.py @@ -28,7 +28,7 @@ class SharpeHyperOptLoss(IHyperOptLoss): Uses Sharpe Ratio calculation. """ - total_profit = results["profit_percent"] + total_profit = results["profit_ratio"] days_period = (max_date - min_date).days # adding slippage of 0.1% per trade diff --git a/freqtrade/optimize/hyperopt_loss_sharpe_daily.py b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py index bcba73a7f..9520123ee 100644 --- a/freqtrade/optimize/hyperopt_loss_sharpe_daily.py +++ b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py @@ -34,9 +34,9 @@ class SharpeHyperOptLossDaily(IHyperOptLoss): annual_risk_free_rate = 0.0 risk_free_rate = annual_risk_free_rate / days_in_year - # apply slippage per trade to profit_percent - results.loc[:, 'profit_percent_after_slippage'] = \ - results['profit_percent'] - slippage_per_trade_ratio + # apply slippage per trade to profit_ratio + results.loc[:, 'profit_ratio_after_slippage'] = \ + results['profit_ratio'] - slippage_per_trade_ratio # create the index within the min_date and end max_date t_index = date_range(start=min_date, end=max_date, freq=resample_freq, @@ -44,10 +44,10 @@ class SharpeHyperOptLossDaily(IHyperOptLoss): sum_daily = ( results.resample(resample_freq, on='close_date').agg( - {"profit_percent_after_slippage": sum}).reindex(t_index).fillna(0) + {"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0) ) - total_profit = sum_daily["profit_percent_after_slippage"] - risk_free_rate + total_profit = sum_daily["profit_ratio_after_slippage"] - risk_free_rate expected_returns_mean = total_profit.mean() up_stdev = total_profit.std() diff --git a/freqtrade/optimize/hyperopt_loss_sortino.py b/freqtrade/optimize/hyperopt_loss_sortino.py index c0ff0773a..b231370dd 100644 --- a/freqtrade/optimize/hyperopt_loss_sortino.py +++ b/freqtrade/optimize/hyperopt_loss_sortino.py @@ -28,7 +28,7 @@ class SortinoHyperOptLoss(IHyperOptLoss): Uses Sortino Ratio calculation. """ - total_profit = results["profit_percent"] + total_profit = results["profit_ratio"] days_period = (max_date - min_date).days # adding slippage of 0.1% per trade @@ -36,7 +36,7 @@ class SortinoHyperOptLoss(IHyperOptLoss): expected_returns_mean = total_profit.sum() / days_period results['downside_returns'] = 0 - results.loc[total_profit < 0, 'downside_returns'] = results['profit_percent'] + results.loc[total_profit < 0, 'downside_returns'] = results['profit_ratio'] down_stdev = np.std(results['downside_returns']) if down_stdev != 0: diff --git a/freqtrade/optimize/hyperopt_loss_sortino_daily.py b/freqtrade/optimize/hyperopt_loss_sortino_daily.py index 3b099a253..fac96664d 100644 --- a/freqtrade/optimize/hyperopt_loss_sortino_daily.py +++ b/freqtrade/optimize/hyperopt_loss_sortino_daily.py @@ -36,9 +36,9 @@ class SortinoHyperOptLossDaily(IHyperOptLoss): days_in_year = 365 minimum_acceptable_return = 0.0 - # apply slippage per trade to profit_percent - results.loc[:, 'profit_percent_after_slippage'] = \ - results['profit_percent'] - slippage_per_trade_ratio + # apply slippage per trade to profit_ratio + results.loc[:, 'profit_ratio_after_slippage'] = \ + results['profit_ratio'] - slippage_per_trade_ratio # create the index within the min_date and end max_date t_index = date_range(start=min_date, end=max_date, freq=resample_freq, @@ -46,17 +46,17 @@ class SortinoHyperOptLossDaily(IHyperOptLoss): sum_daily = ( results.resample(resample_freq, on='close_date').agg( - {"profit_percent_after_slippage": sum}).reindex(t_index).fillna(0) + {"profit_ratio_after_slippage": sum}).reindex(t_index).fillna(0) ) - total_profit = sum_daily["profit_percent_after_slippage"] - minimum_acceptable_return + total_profit = sum_daily["profit_ratio_after_slippage"] - minimum_acceptable_return expected_returns_mean = total_profit.mean() sum_daily['downside_returns'] = 0 sum_daily.loc[total_profit < 0, 'downside_returns'] = total_profit total_downside = sum_daily['downside_returns'] # Here total_downside contains min(0, P - MAR) values, - # where P = sum_daily["profit_percent_after_slippage"] + # where P = sum_daily["profit_ratio_after_slippage"] down_stdev = math.sqrt((total_downside**2).sum() / len(total_downside)) if down_stdev != 0: diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index 96ddb91a0..88b2028ba 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -9,8 +9,9 @@ from pandas import DataFrame from tabulate import tabulate from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN -from freqtrade.data.btanalysis import calculate_market_change, calculate_max_drawdown -from freqtrade.misc import file_dump_json +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 logger = logging.getLogger(__name__) @@ -38,11 +39,12 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N file_dump_json(latest_filename, {'latest_backtest': str(filename.name)}) -def _get_line_floatfmt() -> List[str]: +def _get_line_floatfmt(stake_currency: str) -> List[str]: """ Generate floatformat (goes in line with _generate_result_line()) """ - return ['s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', 'd', 'd', 'd'] + return ['s', 'd', '.2f', '.2f', f'.{decimals_per_coin(stake_currency)}f', + '.2f', 'd', 'd', 'd', 'd'] def _get_line_header(first_column: str, stake_currency: str) -> List[str]: @@ -58,14 +60,14 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: """ Generate one result dict, with "first_column" as key. """ - profit_sum = result['profit_percent'].sum() + profit_sum = result['profit_ratio'].sum() profit_total = profit_sum / max_open_trades return { 'key': first_column, 'trades': len(result), - 'profit_mean': result['profit_percent'].mean() if len(result) > 0 else 0.0, - 'profit_mean_pct': result['profit_percent'].mean() * 100.0 if len(result) > 0 else 0.0, + 'profit_mean': result['profit_ratio'].mean() if len(result) > 0 else 0.0, + 'profit_mean_pct': result['profit_ratio'].mean() * 100.0 if len(result) > 0 else 0.0, 'profit_sum': profit_sum, 'profit_sum_pct': round(profit_sum * 100.0, 2), 'profit_total_abs': result['profit_abs'].sum(), @@ -124,8 +126,8 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List for reason, count in results['sell_reason'].value_counts().iteritems(): result = results.loc[results['sell_reason'] == reason] - profit_mean = result['profit_percent'].mean() - profit_sum = result['profit_percent'].sum() + profit_mean = result['profit_ratio'].mean() + profit_sum = result['profit_ratio'].sum() profit_total = profit_sum / max_open_trades tabular_data.append( @@ -150,7 +152,7 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List def generate_strategy_metrics(all_results: Dict) -> List[Dict]: """ Generate summary per strategy - :param all_results: Dict of containing results for all strategies + :param all_results: Dict of containing results for all strategies :return: List of Dicts containing the metrics per Strategy """ @@ -199,15 +201,15 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]: 'winner_holding_avg': timedelta(), 'loser_holding_avg': timedelta(), } - daily_profit = results.resample('1d', on='close_date')['profit_percent'].sum() + daily_profit = results.resample('1d', on='close_date')['profit_ratio'].sum() worst = min(daily_profit) best = max(daily_profit) winning_days = sum(daily_profit > 0) draw_days = sum(daily_profit == 0) losing_days = sum(daily_profit < 0) - winning_trades = results.loc[results['profit_percent'] > 0] - losing_trades = results.loc[results['profit_percent'] < 0] + winning_trades = results.loc[results['profit_ratio'] > 0] + losing_trades = results.loc[results['profit_ratio'] < 0] return { 'backtest_best_day': best, @@ -243,7 +245,7 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], if not isinstance(results, DataFrame): continue config = content['config'] - max_open_trades = config['max_open_trades'] + max_open_trades = min(config['max_open_trades'], len(btdata.keys())) stake_currency = config['stake_currency'] pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency, @@ -253,7 +255,7 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], results=results) left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency, max_open_trades=max_open_trades, - results=results.loc[results['open_at_end']], + results=results.loc[results['is_open']], skip_nan=True) daily_stats = generate_daily_stats(results) best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'], @@ -273,8 +275,8 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], 'sell_reason_summary': sell_reason_stats, 'left_open_trades': left_open_results, 'total_trades': len(results), - 'profit_mean': results['profit_percent'].mean() if len(results) > 0 else 0, - 'profit_total': results['profit_percent'].sum(), + 'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0, + 'profit_total': results['profit_ratio'].sum() / max_open_trades, 'profit_total_abs': results['profit_abs'].sum(), 'backtest_start': min_date.datetime, 'backtest_start_ts': min_date.int_timestamp * 1000, @@ -290,8 +292,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], 'pairlist': list(btdata.keys()), 'stake_amount': config['stake_amount'], 'stake_currency': config['stake_currency'], - 'max_open_trades': (config['max_open_trades'] - if config['max_open_trades'] != float('inf') else -1), + 'max_open_trades': max_open_trades, + 'max_open_trades_setting': (config['max_open_trades'] + if config['max_open_trades'] != float('inf') else -1), 'timeframe': config['timeframe'], 'timerange': config.get('timerange', ''), 'enable_protections': config.get('enable_protections', False), @@ -314,7 +317,7 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], try: max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown( - results, value_col='profit_percent') + results, value_col='profit_ratio') strat_stats.update({ 'max_drawdown': max_drawdown, 'drawdown_start': drawdown_start, @@ -322,6 +325,13 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], 'drawdown_end': drawdown_end, 'drawdown_end_ts': drawdown_end.timestamp() * 1000, }) + + csum_min, csum_max = calculate_csum(results) + strat_stats.update({ + 'csum_min': csum_min, + 'csum_max': csum_max + }) + except ValueError: strat_stats.update({ 'max_drawdown': 0.0, @@ -329,6 +339,8 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame], 'drawdown_start_ts': 0, 'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc), 'drawdown_end_ts': 0, + 'csum_min': 0, + 'csum_max': 0 }) strategy_results = generate_strategy_metrics(all_results=all_results) @@ -351,7 +363,7 @@ def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: st """ headers = _get_line_header('Pair', stake_currency) - floatfmt = _get_line_floatfmt() + floatfmt = _get_line_floatfmt(stake_currency) output = [[ t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] @@ -382,7 +394,9 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren output = [[ t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'], - t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_total_pct'], + t['profit_mean_pct'], t['profit_sum_pct'], + round_coin_value(t['profit_total_abs'], stake_currency, False), + t['profit_total_pct'], ] for t in sell_reason_stats] return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right") @@ -392,10 +406,10 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str: Generate summary table per strategy :param stake_currency: stake-currency - used to correctly name headers :param max_open_trades: Maximum allowed open trades used for backtest - :param all_results: Dict of containing results for all strategies + :param all_results: Dict of containing results for all strategies :return: pretty printed table with tabulate as string """ - floatfmt = _get_line_floatfmt() + floatfmt = _get_line_floatfmt(stake_currency) headers = _get_line_header('Strategy', stake_currency) output = [[ @@ -409,8 +423,8 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str: def text_table_add_metrics(strat_results: Dict) -> str: if len(strat_results['trades']) > 0: - best_trade = max(strat_results['trades'], key=lambda x: x['profit_percent']) - worst_trade = min(strat_results['trades'], key=lambda x: x['profit_percent']) + best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio']) + worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio']) metrics = [ ('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)), ('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)), @@ -424,9 +438,9 @@ def text_table_add_metrics(strat_results: Dict) -> str: f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"), ('Worst Pair', f"{strat_results['worst_pair']['key']} " f"{round(strat_results['worst_pair']['profit_sum_pct'], 2)}%"), - ('Best trade', f"{best_trade['pair']} {round(best_trade['profit_percent'] * 100, 2)}%"), + ('Best trade', f"{best_trade['pair']} {round(best_trade['profit_ratio'] * 100, 2)}%"), ('Worst trade', f"{worst_trade['pair']} " - f"{round(worst_trade['profit_percent'] * 100, 2)}%"), + 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)}%"), @@ -435,6 +449,12 @@ def text_table_add_metrics(strat_results: Dict) -> str: ('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'])), + ('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)), ('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)), diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py index e803b4383..dff59819c 100644 --- a/freqtrade/persistence/models.py +++ b/freqtrade/persistence/models.py @@ -171,6 +171,10 @@ class Order(_DECL_BASE): """ Get all non-closed orders - useful when trying to batch-update orders """ + if not isinstance(order, dict): + logger.warning(f"{order} is not a valid response object.") + return + filtered_orders = [o for o in orders if o.order_id == order.get('id')] if filtered_orders: oobj = filtered_orders[0] @@ -302,6 +306,11 @@ 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()) + if self.close_date else None), + 'trade_duration': (int((self.close_date - self.open_date).total_seconds() // 60) + if self.close_date else None), + 'profit_ratio': self.close_profit, 'profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None, 'profit_abs': self.close_profit_abs, diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py index 996c5276c..4325e537e 100644 --- a/freqtrade/plot/plotting.py +++ b/freqtrade/plot/plotting.py @@ -53,7 +53,7 @@ def init_plotscript(config, markets: List, startup_candles: int = 0): data_format=config.get('dataformat_ohlcv', 'json'), ) - if startup_candles: + if startup_candles and data: min_date, max_date = get_timerange(data) logger.info(f"Loading data from {min_date} to {max_date}") timerange.adjust_start_if_necessary(timeframe_to_seconds(config.get('timeframe', '5m')), @@ -67,14 +67,16 @@ def init_plotscript(config, markets: List, startup_candles: int = 0): if not filename.is_dir() and not filename.is_file(): logger.warning("Backtest file is missing skipping trades.") no_trades = True - - trades = load_trades( - config['trade_source'], - db_url=config.get('db_url'), - exportfilename=filename, - no_trades=no_trades, - strategy=config.get('strategy'), - ) + try: + trades = load_trades( + config['trade_source'], + db_url=config.get('db_url'), + exportfilename=filename, + no_trades=no_trades, + strategy=config.get('strategy'), + ) + except ValueError as e: + raise OperationalException(e) from e trades = trim_dataframe(trades, timerange, 'open_date') return {"ohlcv": data, @@ -175,7 +177,7 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: # Trades can be empty if trades is not None and len(trades) > 0: # Create description for sell summarizing the trade - trades['desc'] = trades.apply(lambda row: f"{round(row['profit_percent'] * 100, 1)}%, " + trades['desc'] = trades.apply(lambda row: f"{round(row['profit_ratio'] * 100, 1)}%, " f"{row['sell_reason']}, " f"{row['trade_duration']} min", axis=1) @@ -195,9 +197,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: ) trade_sells = go.Scatter( - x=trades.loc[trades['profit_percent'] > 0, "close_date"], - y=trades.loc[trades['profit_percent'] > 0, "close_rate"], - text=trades.loc[trades['profit_percent'] > 0, "desc"], + x=trades.loc[trades['profit_ratio'] > 0, "close_date"], + y=trades.loc[trades['profit_ratio'] > 0, "close_rate"], + text=trades.loc[trades['profit_ratio'] > 0, "desc"], mode='markers', name='Sell - Profit', marker=dict( @@ -208,9 +210,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: ) ) trade_sells_loss = go.Scatter( - x=trades.loc[trades['profit_percent'] <= 0, "close_date"], - y=trades.loc[trades['profit_percent'] <= 0, "close_rate"], - text=trades.loc[trades['profit_percent'] <= 0, "desc"], + x=trades.loc[trades['profit_ratio'] <= 0, "close_date"], + y=trades.loc[trades['profit_ratio'] <= 0, "close_rate"], + text=trades.loc[trades['profit_ratio'] <= 0, "desc"], mode='markers', name='Sell - Loss', marker=dict( diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py index 8c3a5d22f..8a5379ca6 100644 --- a/freqtrade/plugins/pairlist/AgeFilter.py +++ b/freqtrade/plugins/pairlist/AgeFilter.py @@ -30,10 +30,10 @@ class AgeFilter(IPairList): if self._min_days_listed < 1: raise OperationalException("AgeFilter requires min_days_listed to be >= 1") - if self._min_days_listed > exchange.ohlcv_candle_limit: + if self._min_days_listed > exchange.ohlcv_candle_limit('1d'): raise OperationalException("AgeFilter requires min_days_listed to not exceed " "exchange max request size " - f"({exchange.ohlcv_candle_limit})") + f"({exchange.ohlcv_candle_limit('1d')})") @property def needstickers(self) -> bool: diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py index 95d776ae6..184feff9e 100644 --- a/freqtrade/plugins/pairlist/IPairList.py +++ b/freqtrade/plugins/pairlist/IPairList.py @@ -168,7 +168,7 @@ class IPairList(LoggingMixin, ABC): # Check if market is active market = markets[pair] if not market_is_active(market): - logger.info(f"Ignoring {pair} from whitelist. Market is not active.") + self.log_once(f"Ignoring {pair} from whitelist. Market is not active.", logger.info) continue if pair not in sanitized_whitelist: sanitized_whitelist.append(pair) diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py index f2e84930b..db51a9c77 100644 --- a/freqtrade/plugins/pairlist/rangestabilityfilter.py +++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py @@ -32,10 +32,10 @@ class RangeStabilityFilter(IPairList): if self._days < 1: raise OperationalException("RangeStabilityFilter requires lookback_days to be >= 1") - if self._days > exchange.ohlcv_candle_limit: + if self._days > exchange.ohlcv_candle_limit('1d'): raise OperationalException("RangeStabilityFilter requires lookback_days to not " "exceed exchange max request size " - f"({exchange.ohlcv_candle_limit})") + f"({exchange.ohlcv_candle_limit('1d')})") @property def needstickers(self) -> bool: diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py index 7ce77da59..4e4135981 100644 --- a/freqtrade/plugins/pairlistmanager.py +++ b/freqtrade/plugins/pairlistmanager.py @@ -59,17 +59,6 @@ class PairListManager(): """The expanded blacklist (including wildcard expansion)""" return expand_pairlist(self._blacklist, self._exchange.get_markets().keys()) - @property - def expanded_whitelist_keep_invalid(self) -> List[str]: - """The expanded whitelist (including wildcard expansion), maintaining invalid pairs""" - return expand_pairlist(self._whitelist, self._exchange.get_markets().keys(), - keep_invalid=True) - - @property - def expanded_whitelist(self) -> List[str]: - """The expanded whitelist (including wildcard expansion), filtering invalid pairs""" - return expand_pairlist(self._whitelist, self._exchange.get_markets().keys()) - @property def name_list(self) -> List[str]: """Get list of loaded Pairlist Handler names""" @@ -153,10 +142,8 @@ class PairListManager(): :return: pairlist - whitelisted pairs """ try: - if keep_invalid: - whitelist = self.expanded_whitelist_keep_invalid - else: - whitelist = self.expanded_whitelist + + whitelist = expand_pairlist(pairlist, self._exchange.get_markets().keys(), keep_invalid) except ValueError as err: logger.error(f"Pair whitelist contains an invalid Wildcard: {err}") return [] diff --git a/freqtrade/plugins/protections/stoploss_guard.py b/freqtrade/plugins/protections/stoploss_guard.py index 92fae54cb..5a9b9ddd0 100644 --- a/freqtrade/plugins/protections/stoploss_guard.py +++ b/freqtrade/plugins/protections/stoploss_guard.py @@ -58,13 +58,13 @@ class StoplossGuard(IProtection): SellType.STOPLOSS_ON_EXCHANGE.value) and trade.close_profit < 0)] - if len(trades) > self._trade_limit: - self.log_once(f"Trading stopped due to {self._trade_limit} " - f"stoplosses within {self._lookback_period} minutes.", logger.info) - until = self.calculate_lock_end(trades, self._stop_duration) - return True, until, self._reason() + if len(trades) < self._trade_limit: + return False, None, None - return False, None, None + self.log_once(f"Trading stopped due to {self._trade_limit} " + f"stoplosses within {self._lookback_period} minutes.", logger.info) + until = self.calculate_lock_end(trades, self._stop_duration) + return True, until, self._reason() def global_stop(self, date_now: datetime) -> ProtectionReturn: """ diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py index 26a316873..b1b66e3ae 100644 --- a/freqtrade/resolvers/strategy_resolver.py +++ b/freqtrade/resolvers/strategy_resolver.py @@ -68,6 +68,7 @@ class StrategyResolver(IResolver): ("trailing_stop_positive", None, None), ("trailing_stop_positive_offset", 0.0, None), ("trailing_only_offset_is_reached", None, None), + ("use_custom_stoploss", None, None), ("process_only_new_candles", None, None), ("order_types", None, None), ("order_time_in_force", None, None), diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py index c9e8aaceb..050540cc6 100644 --- a/freqtrade/rpc/api_server/api_schemas.py +++ b/freqtrade/rpc/api_server/api_schemas.py @@ -113,7 +113,7 @@ class Daily(BaseModel): class ShowConfig(BaseModel): - dry_run: str + dry_run: bool stake_currency: str stake_amount: Union[float, str] max_open_trades: int @@ -123,6 +123,7 @@ class ShowConfig(BaseModel): trailing_stop_positive: Optional[float] trailing_stop_positive_offset: Optional[float] trailing_only_offset_is_reached: Optional[bool] + use_custom_stoploss: Optional[bool] timeframe: str timeframe_ms: int timeframe_min: int diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index a2082103b..3588f2196 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -167,7 +167,7 @@ def reload_config(rpc: RPC = Depends(get_rpc)): @router.get('/pair_candles', response_model=PairHistory, tags=['candle data']) -def pair_candles(pair: str, timeframe: str, limit: Optional[int], rpc=Depends(get_rpc)): +def pair_candles(pair: str, timeframe: str, limit: Optional[int], rpc: RPC = Depends(get_rpc)): return rpc._rpc_analysed_dataframe(pair, timeframe, limit) diff --git a/freqtrade/rpc/api_server/ui/fallback_file.html b/freqtrade/rpc/api_server/ui/fallback_file.html new file mode 100644 index 000000000..7943530af --- /dev/null +++ b/freqtrade/rpc/api_server/ui/fallback_file.html @@ -0,0 +1,31 @@ + + + + + + Freqtrade UI + + + +
+

Freqtrade UI not installed.

+

Please run `freqtrade install-ui` in your terminal to install the UI files and restart your bot.

+

You can then refresh this page and you should see the UI.

+
+ + diff --git a/freqtrade/rpc/api_server/ui/favicon.ico b/freqtrade/rpc/api_server/ui/favicon.ico new file mode 100644 index 000000000..78c7e43b1 Binary files /dev/null and b/freqtrade/rpc/api_server/ui/favicon.ico differ diff --git a/freqtrade/rpc/api_server/ui/installed/.gitkeep b/freqtrade/rpc/api_server/ui/installed/.gitkeep new file mode 100644 index 000000000..e69de29bb diff --git a/freqtrade/rpc/api_server/web_ui.py b/freqtrade/rpc/api_server/web_ui.py new file mode 100644 index 000000000..6d7e77953 --- /dev/null +++ b/freqtrade/rpc/api_server/web_ui.py @@ -0,0 +1,31 @@ +from pathlib import Path + +from fastapi import APIRouter +from fastapi.exceptions import HTTPException +from starlette.responses import FileResponse + + +router_ui = APIRouter() + + +@router_ui.get('/favicon.ico', include_in_schema=False) +async def favicon(): + return FileResponse(Path(__file__).parent / 'ui/favicon.ico') + + +@router_ui.get('/{rest_of_path:path}', include_in_schema=False) +async def index_html(rest_of_path: str): + """ + Emulate path fallback to index.html. + """ + if rest_of_path.startswith('api') or rest_of_path.startswith('.'): + raise HTTPException(status_code=404, detail="Not Found") + uibase = Path(__file__).parent / 'ui/installed/' + if (uibase / rest_of_path).is_file(): + return FileResponse(str(uibase / rest_of_path)) + + index_file = uibase / 'index.html' + if not index_file.is_file(): + return FileResponse(str(uibase.parent / 'fallback_file.html')) + # Fall back to index.html, as indicated by vue router docs + return FileResponse(str(index_file)) diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py index 9c0779274..8a5c958e9 100644 --- a/freqtrade/rpc/api_server/webserver.py +++ b/freqtrade/rpc/api_server/webserver.py @@ -2,6 +2,7 @@ import logging from ipaddress import IPv4Address from typing import Any, Dict +import rapidjson import uvicorn from fastapi import Depends, FastAPI from fastapi.middleware.cors import CORSMiddleware @@ -14,6 +15,17 @@ from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler logger = logging.getLogger(__name__) +class FTJSONResponse(JSONResponse): + media_type = "application/json" + + def render(self, content: Any) -> bytes: + """ + Use rapidjson for responses + Handles NaN and Inf / -Inf in a javascript way by default. + """ + return rapidjson.dumps(content).encode("utf-8") + + class ApiServer(RPCHandler): _rpc: RPC @@ -32,6 +44,7 @@ class ApiServer(RPCHandler): self.app = FastAPI(title="Freqtrade API", docs_url='/docs' if api_config.get('enable_openapi', False) else None, redoc_url=None, + default_response_class=FTJSONResponse, ) self.configure_app(self.app, self._config) @@ -57,12 +70,16 @@ class ApiServer(RPCHandler): from freqtrade.rpc.api_server.api_auth import http_basic_or_jwt_token, router_login from freqtrade.rpc.api_server.api_v1 import router as api_v1 from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public + from freqtrade.rpc.api_server.web_ui import router_ui + app.include_router(api_v1_public, prefix="/api/v1") app.include_router(api_v1, prefix="/api/v1", dependencies=[Depends(http_basic_or_jwt_token)], ) app.include_router(router_login, prefix="/api/v1", tags=["auth"]) + # UI Router MUST be last! + app.include_router(router_ui, prefix='') app.add_middleware( CORSMiddleware, diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 92cd6caf9..7549c38be 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -9,7 +9,7 @@ from math import isnan from typing import Any, Dict, List, Optional, Tuple, Union import arrow -from numpy import NAN, int64, mean +from numpy import NAN, inf, int64, mean from pandas import DataFrame from freqtrade.configuration.timerange import TimeRange @@ -129,6 +129,7 @@ class RPC: 'trailing_stop_positive': config.get('trailing_stop_positive'), 'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'), 'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'), + 'use_custom_stoploss': config.get('use_custom_stoploss'), 'bot_name': config.get('bot_name', 'freqtrade'), 'timeframe': config.get('timeframe'), 'timeframe_ms': timeframe_to_msecs(config['timeframe'] @@ -377,7 +378,7 @@ class RPC: # Prepare data to display profit_closed_coin_sum = round(sum(profit_closed_coin), 8) - profit_closed_ratio_mean = mean(profit_closed_ratio) if profit_closed_ratio else 0.0 + profit_closed_ratio_mean = float(mean(profit_closed_ratio) if profit_closed_ratio else 0.0) profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0 profit_closed_fiat = self._fiat_converter.convert_amount( @@ -387,7 +388,7 @@ class RPC: ) if self._fiat_converter else 0 profit_all_coin_sum = round(sum(profit_all_coin), 8) - profit_all_ratio_mean = mean(profit_all_ratio) if profit_all_ratio else 0.0 + profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0) profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0 profit_all_fiat = self._fiat_converter.convert_amount( profit_all_coin_sum, @@ -450,7 +451,7 @@ class RPC: pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency) rate = tickers.get(pair, {}).get('bid', None) if rate: - if pair.startswith(stake_currency): + if pair.startswith(stake_currency) and not pair.endswith(stake_currency): rate = 1.0 / rate est_stake = rate * balance.total except (ExchangeError): @@ -589,7 +590,8 @@ class RPC: raise RPCException(f'position for {pair} already open - id: {trade.id}') # gen stake amount - stakeamount = self._freqtrade.get_trade_stake_amount(pair) + stakeamount = self._freqtrade.wallets.get_trade_stake_amount( + pair, self._freqtrade.get_free_open_trades()) # execute buy if self._freqtrade.execute_buy(pair, stakeamount, price): @@ -745,6 +747,7 @@ class RPC: sell_mask = (dataframe['sell'] == 1) sell_signals = int(sell_mask.sum()) dataframe.loc[sell_mask, '_sell_signal_open'] = dataframe.loc[sell_mask, 'open'] + dataframe = dataframe.replace([inf, -inf], NAN) dataframe = dataframe.replace({NAN: None}) res = { @@ -773,7 +776,8 @@ class RPC: }) return res - def _rpc_analysed_dataframe(self, pair: str, timeframe: str, limit: int) -> Dict[str, Any]: + def _rpc_analysed_dataframe(self, pair: str, timeframe: str, + limit: Optional[int]) -> Dict[str, Any]: _data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe( pair, timeframe) diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py index 99f9a8a91..88019601c 100644 --- a/freqtrade/rpc/telegram.py +++ b/freqtrade/rpc/telegram.py @@ -18,6 +18,7 @@ from telegram.utils.helpers import escape_markdown from freqtrade.__init__ import __version__ from freqtrade.exceptions import OperationalException +from freqtrade.misc import round_coin_value from freqtrade.rpc import RPC, RPCException, RPCHandler, RPCMessageType @@ -189,14 +190,14 @@ class Telegram(RPCHandler): else: msg['stake_amount_fiat'] = 0 - message = ("\N{LARGE BLUE CIRCLE} *{exchange}:* Buying {pair}\n" - "*Amount:* `{amount:.8f}`\n" - "*Open Rate:* `{limit:.8f}`\n" - "*Current Rate:* `{current_rate:.8f}`\n" - "*Total:* `({stake_amount:.6f} {stake_currency}").format(**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 += ", {stake_amount_fiat:.3f} {fiat_currency}".format(**msg) + message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}" message += ")`" elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION: @@ -365,7 +366,7 @@ class Telegram(RPCHandler): ) stats_tab = tabulate( [[day['date'], - f"{day['abs_profit']:.8f} {stats['stake_currency']}", + f"{round_coin_value(day['abs_profit'], stats['stake_currency'])}", f"{day['fiat_value']:.3f} {stats['fiat_display_currency']}", f"{day['trade_count']} trades"] for day in stats['data']], headers=[ @@ -415,18 +416,18 @@ class Telegram(RPCHandler): # Message to display if stats['closed_trade_count'] > 0: markdown_msg = ("*ROI:* Closed trades\n" - f"∙ `{profit_closed_coin:.8f} {stake_cur} " + f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} " f"({profit_closed_percent_mean:.2f}%) " f"({profit_closed_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n" - f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n") + f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n") else: markdown_msg = "`No closed trade` \n" markdown_msg += (f"*ROI:* All trades\n" - f"∙ `{profit_all_coin:.8f} {stake_cur} " + f"∙ `{round_coin_value(profit_all_coin, stake_cur)} " f"({profit_all_percent_mean:.2f}%) " f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n" - f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n" + f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n" f"*Total Trade Count:* `{trade_count}`\n" f"*First Trade opened:* `{first_trade_date}`\n" f"*Latest Trade opened:* `{latest_trade_date}\n`" @@ -494,15 +495,17 @@ class Telegram(RPCHandler): "Starting capital: " f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n" ) - for currency in result['currencies']: - if currency['est_stake'] > 0.0001: - curr_output = ("*{currency}:*\n" - "\t`Available: {free: .8f}`\n" - "\t`Balance: {balance: .8f}`\n" - "\t`Pending: {used: .8f}`\n" - "\t`Est. {stake}: {est_stake: .8f}`\n").format(**currency) + for curr in result['currencies']: + if curr['est_stake'] > 0.0001: + curr_output = ( + f"*{curr['currency']}:*\n" + f"\t`Available: {curr['free']:.8f}`\n" + f"\t`Balance: {curr['balance']:.8f}`\n" + f"\t`Pending: {curr['used']:.8f}`\n" + f"\t`Est. {curr['stake']}: " + f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n") else: - curr_output = "*{currency}:* not showing <1$ amount \n".format(**currency) + curr_output = f"*{curr['currency']}:* not showing <1$ amount \n" # Handle overflowing messsage length if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH: @@ -512,8 +515,9 @@ class Telegram(RPCHandler): output += curr_output output += ("\n*Estimated Value*:\n" - "\t`{stake}: {total: .8f}`\n" - "\t`{symbol}: {value: .2f}`\n").format(**result) + f"\t`{result['stake']}: {result['total']: .8f}`\n" + f"\t`{result['symbol']}: " + f"{round_coin_value(result['value'], result['symbol'], False)}`\n") self._send_msg(output) except RPCException as e: self._send_msg(str(e)) @@ -910,7 +914,7 @@ class Telegram(RPCHandler): :param parse_mode: telegram parse mode :return: None """ - reply_markup = ReplyKeyboardMarkup(self._keyboard) + reply_markup = ReplyKeyboardMarkup(self._keyboard, resize_keyboard=True) try: try: self._updater.bot.send_message( diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index c58d9aa5d..da4ce6c50 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -530,8 +530,8 @@ class IStrategy(ABC): current_time=date)) if (ask_strategy.get('sell_profit_only', False) - and trade.calc_profit(rate=rate) <= ask_strategy.get('sell_profit_offset', 0)): - # Negative profits and sell_profit_only - ignore sell signal + and current_profit <= ask_strategy.get('sell_profit_offset', 0)): + # sell_profit_only and profit doesn't reach the offset - ignore sell signal sell_signal = False else: sell_signal = sell and not buy and ask_strategy.get('use_sell_signal', True) diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2 index 4a1b43e36..dd6b773e1 100644 --- a/freqtrade/templates/base_strategy.py.j2 +++ b/freqtrade/templates/base_strategy.py.j2 @@ -5,7 +5,7 @@ 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 # -------------------------------- # Add your lib to import here diff --git a/freqtrade/templates/sample_hyperopt_loss.py b/freqtrade/templates/sample_hyperopt_loss.py index 59e6d814a..343349508 100644 --- a/freqtrade/templates/sample_hyperopt_loss.py +++ b/freqtrade/templates/sample_hyperopt_loss.py @@ -1,5 +1,6 @@ from datetime import datetime from math import exp +from typing import Dict from pandas import DataFrame @@ -35,12 +36,13 @@ class SampleHyperOptLoss(IHyperOptLoss): @staticmethod def hyperopt_loss_function(results: DataFrame, trade_count: int, min_date: datetime, max_date: datetime, + config: Dict, processed: Dict[str, DataFrame], *args, **kwargs) -> float: """ Objective function, returns smaller number for better results """ - total_profit = results.profit_percent.sum() - trade_duration = results.trade_duration.mean() + total_profit = results['profit_ratio'].sum() + trade_duration = results['trade_duration'].mean() trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8) profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT) diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index b3f9fef07..db1ba48b8 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -17,7 +17,7 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib class SampleStrategy(IStrategy): """ This is a sample strategy to inspire you. - More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md + More information in https://www.freqtrade.io/en/latest/strategy-customization/ You can: :return: a Dataframe with all mandatory indicators for the strategies diff --git a/freqtrade/templates/strategy_analysis_example.ipynb b/freqtrade/templates/strategy_analysis_example.ipynb index c6e64c74e..491afbdd7 100644 --- a/freqtrade/templates/strategy_analysis_example.ipynb +++ b/freqtrade/templates/strategy_analysis_example.ipynb @@ -40,7 +40,7 @@ "# Location of the data\n", "data_location = Path(config['user_data_dir'], 'data', 'binance')\n", "# Pair to analyze - Only use one pair here\n", - "pair = \"BTC_USDT\"" + "pair = \"BTC/USDT\"" ] }, { @@ -54,7 +54,9 @@ "\n", "candles = load_pair_history(datadir=data_location,\n", " timeframe=config[\"timeframe\"],\n", - " pair=pair)\n", + " pair=pair,\n", + " data_format = \"hdf5\",\n", + " )\n", "\n", "# Confirm success\n", "print(\"Loaded \" + str(len(candles)) + f\" rows of data for {pair} from {data_location}\")\n", diff --git a/freqtrade/wallets.py b/freqtrade/wallets.py index 3680dd416..d7dcfd487 100644 --- a/freqtrade/wallets.py +++ b/freqtrade/wallets.py @@ -7,6 +7,8 @@ from typing import Any, Dict, NamedTuple import arrow +from freqtrade.constants import UNLIMITED_STAKE_AMOUNT +from freqtrade.exceptions import DependencyException from freqtrade.exchange import Exchange from freqtrade.persistence import Trade @@ -118,3 +120,79 @@ class Wallets: def get_all_balances(self) -> Dict[str, Any]: return self._wallets + + def _get_available_stake_amount(self) -> float: + """ + Return the total currently available balance in stake currency, + respecting tradable_balance_ratio. + Calculated as + ( + free amount ) * tradable_balance_ratio - + """ + val_tied_up = Trade.total_open_trades_stakes() + + # Ensure % is used from the overall balance + # Otherwise we'd risk lowering stakes with each open trade. + # (tied up + current free) * ratio) - tied up + available_amount = ((val_tied_up + self.get_free(self._config['stake_currency'])) * + self._config['tradable_balance_ratio']) - val_tied_up + return available_amount + + def _calculate_unlimited_stake_amount(self, free_open_trades: int) -> float: + """ + Calculate stake amount for "unlimited" stake amount + :return: 0 if max number of trades reached, else stake_amount to use. + """ + if not free_open_trades: + return 0 + + available_amount = self._get_available_stake_amount() + + return available_amount / free_open_trades + + def _check_available_stake_amount(self, stake_amount: float) -> float: + """ + Check if stake amount can be fulfilled with the available balance + for the stake currency + :return: float: Stake amount + """ + available_amount = self._get_available_stake_amount() + + if self._config['amend_last_stake_amount']: + # Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio + # Otherwise the remaining amount is too low to trade. + if available_amount > (stake_amount * self._config['last_stake_amount_min_ratio']): + stake_amount = min(stake_amount, available_amount) + else: + stake_amount = 0 + + if available_amount < stake_amount: + raise DependencyException( + f"Available balance ({available_amount} {self._config['stake_currency']}) is " + f"lower than stake amount ({stake_amount} {self._config['stake_currency']})" + ) + + return stake_amount + + def get_trade_stake_amount(self, pair: str, free_open_trades: int, edge=None) -> float: + """ + Calculate stake amount for the trade + :return: float: Stake amount + :raise: DependencyException if the available stake amount is too low + """ + stake_amount: float + # Ensure wallets are uptodate. + self.update() + + if edge: + stake_amount = edge.stake_amount( + pair, + self.get_free(self._config['stake_currency']), + self.get_total(self._config['stake_currency']), + Trade.total_open_trades_stakes() + ) + else: + stake_amount = self._config['stake_amount'] + if stake_amount == UNLIMITED_STAKE_AMOUNT: + stake_amount = self._calculate_unlimited_stake_amount(free_open_trades) + + return self._check_available_stake_amount(stake_amount) diff --git a/mkdocs.yml b/mkdocs.yml index 4545e8d84..18fccc333 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -8,29 +8,30 @@ nav: - Freqtrade Basics: bot-basics.md - Configuration: configuration.md - Strategy Customization: strategy-customization.md + - Plugins: plugins.md - Stoploss: stoploss.md - Start the bot: bot-usage.md - Control the bot: - Telegram: telegram-usage.md - Web Hook: webhook-config.md - - REST API: rest-api.md + - REST API & FreqUI: rest-api.md - Data Downloading: data-download.md - Backtesting: backtesting.md - Hyperopt: hyperopt.md - - Edge Positioning: edge.md - - Plugins: plugins.md - - Utility Subcommands: utils.md - - FAQ: faq.md + - Utility Sub-commands: utils.md - Data Analysis: - Jupyter Notebooks: data-analysis.md - Strategy analysis: strategy_analysis_example.md - Plotting: plotting.md - - SQL Cheatsheet: sql_cheatsheet.md - Exchange-specific Notes: exchanges.md - - Advanced Post-installation Tasks: advanced-setup.md - - Advanced Strategy: strategy-advanced.md - - Advanced Hyperopt: advanced-hyperopt.md - - Sandbox Testing: sandbox-testing.md + - Advanced Topics: + - Advanced Post-installation Tasks: advanced-setup.md + - Edge Positioning: edge.md + - Advanced Strategy: strategy-advanced.md + - Advanced Hyperopt: advanced-hyperopt.md + - Sandbox Testing: sandbox-testing.md + - FAQ: faq.md + - SQL Cheat-sheet: sql_cheatsheet.md - Updating Freqtrade: updating.md - Deprecated Features: deprecated.md - Contributors Guide: developer.md diff --git a/requirements-dev.txt b/requirements-dev.txt index 01066959a..fa0ead603 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -8,7 +8,7 @@ flake8==3.8.4 flake8-type-annotations==0.1.0 flake8-tidy-imports==4.2.1 mypy==0.790 -pytest==6.2.1 +pytest==6.2.2 pytest-asyncio==0.14.0 pytest-cov==2.11.1 pytest-mock==3.5.1 diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt index 104fbf454..8e87a434c 100644 --- a/requirements-hyperopt.txt +++ b/requirements-hyperopt.txt @@ -2,9 +2,9 @@ -r requirements.txt # Required for hyperopt -scipy==1.6.0 +scipy==1.6.1 scikit-learn==0.24.1 scikit-optimize==0.8.1 filelock==3.0.12 -joblib==1.0.0 +joblib==1.0.1 progressbar2==3.53.1 diff --git a/requirements.txt b/requirements.txt index cc8861d82..51b1ed3d1 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,25 +1,27 @@ -numpy==1.19.5 -pandas==1.2.1 +numpy==1.20.1 +pandas==1.2.2 -ccxt==1.40.99 +ccxt==1.42.19 +# Pin cryptography for now due to rust build errors with piwheels +cryptography==3.4.6 aiohttp==3.7.3 -SQLAlchemy==1.3.22 -python-telegram-bot==13.1 +SQLAlchemy==1.3.23 +python-telegram-bot==13.3 arrow==0.17.0 cachetools==4.2.1 requests==2.25.1 -urllib3==1.26.2 +urllib3==1.26.3 wrapt==1.12.1 jsonschema==3.2.0 TA-Lib==0.4.19 -tabulate==0.8.7 +tabulate==0.8.9 pycoingecko==1.4.0 -jinja2==2.11.2 +jinja2==2.11.3 tables==3.6.1 blosc==1.10.2 # find first, C search in arrays -py_find_1st==1.1.4 +py_find_1st==1.1.5 # Load ticker files 30% faster python-rapidjson==1.0 @@ -29,11 +31,12 @@ sdnotify==0.3.2 # API Server fastapi==0.63.0 -uvicorn==0.13.3 +uvicorn==0.13.4 pyjwt==2.0.1 +aiofiles==0.6.0 # Support for colorized terminal output colorama==0.4.4 # Building config files interactively questionary==1.9.0 -prompt-toolkit==3.0.14 +prompt-toolkit==3.0.16 diff --git a/scripts/rest_client.py b/scripts/rest_client.py index 2232b8421..b6e66cfa4 100755 --- a/scripts/rest_client.py +++ b/scripts/rest_client.py @@ -379,7 +379,7 @@ def main(args): print_commands() return - print(getattr(client, command)(*args["command_arguments"])) + print(json.dumps(getattr(client, command)(*args["command_arguments"]))) if __name__ == "__main__": diff --git a/setup.py b/setup.py index 030980c96..148803cd6 100644 --- a/setup.py +++ b/setup.py @@ -19,7 +19,7 @@ if readme_file.is_file(): readme_long = (Path(__file__).parent / "README.md").read_text() # Requirements used for submodules -api = ['flask', 'flask-jwt-extended', 'flask-cors'] +api = ['fastapi', 'uvicorn', 'pyjwt', 'aiofiles'] plot = ['plotly>=4.0'] hyperopt = [ 'scipy', diff --git a/tests/commands/test_commands.py b/tests/commands/test_commands.py index 2284209a0..c81909025 100644 --- a/tests/commands/test_commands.py +++ b/tests/commands/test_commands.py @@ -1,16 +1,20 @@ import re +from io import BytesIO from pathlib import Path from unittest.mock import MagicMock, PropertyMock +from zipfile import ZipFile import arrow import pytest from freqtrade.commands import (start_convert_data, start_create_userdir, start_download_data, - start_hyperopt_list, start_hyperopt_show, start_list_data, - start_list_exchanges, start_list_hyperopts, start_list_markets, - start_list_strategies, start_list_timeframes, start_new_hyperopt, - start_new_strategy, start_show_trades, start_test_pairlist, - start_trading) + start_hyperopt_list, start_hyperopt_show, start_install_ui, + start_list_data, start_list_exchanges, start_list_hyperopts, + start_list_markets, start_list_strategies, start_list_timeframes, + start_new_hyperopt, start_new_strategy, start_show_trades, + start_test_pairlist, start_trading) +from freqtrade.commands.deploy_commands import (clean_ui_subdir, download_and_install_ui, + get_ui_download_url, read_ui_version) from freqtrade.configuration import setup_utils_configuration from freqtrade.exceptions import OperationalException from freqtrade.state import RunMode @@ -546,7 +550,7 @@ def test_start_new_hyperopt_DefaultHyperopt(mocker, caplog): start_new_hyperopt(get_args(args)) -def test_start_new_hyperopt_no_arg(mocker, caplog): +def test_start_new_hyperopt_no_arg(mocker): args = [ "new-hyperopt", ] @@ -555,6 +559,107 @@ def test_start_new_hyperopt_no_arg(mocker, caplog): start_new_hyperopt(get_args(args)) +def test_start_install_ui(mocker): + clean_mock = mocker.patch('freqtrade.commands.deploy_commands.clean_ui_subdir') + get_url_mock = mocker.patch('freqtrade.commands.deploy_commands.get_ui_download_url', + return_value=('https://example.com/whatever', '0.0.1')) + download_mock = mocker.patch('freqtrade.commands.deploy_commands.download_and_install_ui') + mocker.patch('freqtrade.commands.deploy_commands.read_ui_version', return_value=None) + args = [ + "install-ui", + ] + start_install_ui(get_args(args)) + assert clean_mock.call_count == 1 + assert get_url_mock.call_count == 1 + assert download_mock.call_count == 1 + + clean_mock.reset_mock() + get_url_mock.reset_mock() + download_mock.reset_mock() + + args = [ + "install-ui", + "--erase", + ] + start_install_ui(get_args(args)) + assert clean_mock.call_count == 1 + assert get_url_mock.call_count == 1 + assert download_mock.call_count == 0 + + +def test_clean_ui_subdir(mocker, tmpdir, caplog): + mocker.patch("freqtrade.commands.deploy_commands.Path.is_dir", + side_effect=[True, True]) + mocker.patch("freqtrade.commands.deploy_commands.Path.is_file", + side_effect=[False, True]) + rd_mock = mocker.patch("freqtrade.commands.deploy_commands.Path.rmdir") + ul_mock = mocker.patch("freqtrade.commands.deploy_commands.Path.unlink") + + mocker.patch("freqtrade.commands.deploy_commands.Path.glob", + return_value=[Path('test1'), Path('test2'), Path('.gitkeep')]) + folder = Path(tmpdir) / "uitests" + clean_ui_subdir(folder) + assert log_has("Removing UI directory content.", caplog) + assert rd_mock.call_count == 1 + assert ul_mock.call_count == 1 + + +def test_download_and_install_ui(mocker, tmpdir): + # Create zipfile + requests_mock = MagicMock() + file_like_object = BytesIO() + with ZipFile(file_like_object, mode='w') as zipfile: + for file in ('test1.txt', 'hello/', 'test2.txt'): + zipfile.writestr(file, file) + file_like_object.seek(0) + requests_mock.content = file_like_object.read() + + mocker.patch("freqtrade.commands.deploy_commands.requests.get", return_value=requests_mock) + + mocker.patch("freqtrade.commands.deploy_commands.Path.is_dir", + side_effect=[True, False]) + wb_mock = mocker.patch("freqtrade.commands.deploy_commands.Path.write_bytes") + + folder = Path(tmpdir) / "uitests_dl" + folder.mkdir(exist_ok=True) + + assert read_ui_version(folder) is None + + download_and_install_ui(folder, 'http://whatever.xxx/download/file.zip', '22') + + assert wb_mock.call_count == 2 + + assert read_ui_version(folder) == '22' + + +def test_get_ui_download_url(mocker): + response = MagicMock() + response.json = MagicMock( + side_effect=[[{'assets_url': 'http://whatever.json', 'name': '0.0.1'}], + [{'browser_download_url': 'http://download.zip'}]]) + get_mock = mocker.patch("freqtrade.commands.deploy_commands.requests.get", + return_value=response) + x, last_version = get_ui_download_url() + assert get_mock.call_count == 2 + assert last_version == '0.0.1' + assert x == 'http://download.zip' + + +def test_get_ui_download_url_direct(mocker): + response = MagicMock() + response.json = MagicMock( + side_effect=[[{ + 'assets_url': 'http://whatever.json', + 'name': '0.0.1', + 'assets': [{'browser_download_url': 'http://download11.zip'}]}]]) + get_mock = mocker.patch("freqtrade.commands.deploy_commands.requests.get", + return_value=response) + x, last_version = get_ui_download_url() + assert get_mock.call_count == 1 + assert last_version == '0.0.1' + assert x == 'http://download11.zip' + + def test_download_data_keyboardInterrupt(mocker, caplog, markets): dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data', MagicMock(side_effect=KeyboardInterrupt)) @@ -822,6 +927,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", ] pargs = get_args(args) pargs['config'] = None @@ -835,6 +941,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): "hyperopt-list", "--best", "--no-details", + "--no-color", ] pargs = get_args(args) pargs['config'] = None @@ -849,6 +956,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): "hyperopt-list", "--profitable", "--no-details", + "--no-color", ] pargs = get_args(args) pargs['config'] = None @@ -862,6 +970,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--profitable", + "--no-color", ] pargs = get_args(args) pargs['config'] = None @@ -891,6 +1000,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): "hyperopt-list", "--profitable", "--no-details", + "--no-color", "--max-trades", "20", ] pargs = get_args(args) @@ -906,6 +1016,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): "hyperopt-list", "--profitable", "--no-details", + "--no-color", "--min-avg-profit", "0.11", ] pargs = get_args(args) @@ -920,6 +1031,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--max-avg-profit", "0.10", ] pargs = get_args(args) @@ -934,6 +1046,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--min-total-profit", "0.4", ] pargs = get_args(args) @@ -948,6 +1061,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--max-total-profit", "0.4", ] pargs = get_args(args) @@ -962,6 +1076,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--min-objective", "0.1", ] pargs = get_args(args) @@ -991,6 +1106,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): "hyperopt-list", "--profitable", "--no-details", + "--no-color", "--min-avg-time", "2000", ] pargs = get_args(args) @@ -1005,6 +1121,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--max-avg-time", "1500", ] pargs = get_args(args) @@ -1019,6 +1136,7 @@ def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results): args = [ "hyperopt-list", "--no-details", + "--no-color", "--export-csv", "test_file.csv", ] pargs = get_args(args) @@ -1168,7 +1286,7 @@ def test_start_list_data(testdatadir, capsys): pargs['config'] = None start_list_data(pargs) captured = capsys.readouterr() - assert "Found 16 pair / timeframe combinations." in captured.out + assert "Found 17 pair / timeframe combinations." in captured.out assert "\n| Pair | Timeframe |\n" in captured.out assert "\n| UNITTEST/BTC | 1m, 5m, 8m, 30m |\n" in captured.out diff --git a/tests/conftest.py b/tests/conftest.py index 75a98dcc5..61899dd53 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -73,7 +73,6 @@ def patched_configuration_load_config_file(mocker, config) -> None: def patch_exchange(mocker, api_mock=None, id='bittrex', mock_markets=True) -> None: mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={})) - mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={})) mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock()) mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock()) mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock()) diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index cdd5c08d2..3c4687745 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -7,14 +7,14 @@ from pandas import DataFrame, DateOffset, Timestamp, to_datetime from freqtrade.configuration import TimeRange from freqtrade.constants import LAST_BT_RESULT_FN -from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, analyze_trade_parallelism, +from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, BT_DATA_COLUMNS_MID, BT_DATA_COLUMNS_OLD, + analyze_trade_parallelism, calculate_csum, calculate_market_change, calculate_max_drawdown, combine_dataframes_with_mean, create_cum_profit, extract_trades_of_period, get_latest_backtest_filename, get_latest_hyperopt_file, load_backtest_data, load_trades, load_trades_from_db) from freqtrade.data.history import load_data, load_pair_history -from freqtrade.optimize.backtesting import BacktestResult from tests.conftest import create_mock_trades from tests.conftest_trades import MOCK_TRADE_COUNT @@ -55,7 +55,7 @@ def test_load_backtest_data_old_format(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) assert isinstance(bt_data, DataFrame) - assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profit_abs"] + assert list(bt_data.columns) == BT_DATA_COLUMNS_OLD + ['profit_abs', 'profit_ratio'] assert len(bt_data) == 179 # Test loading from string (must yield same result) @@ -71,7 +71,7 @@ def test_load_backtest_data_new_format(testdatadir): filename = testdatadir / "backtest-result_new.json" bt_data = load_backtest_data(filename) assert isinstance(bt_data, DataFrame) - assert set(bt_data.columns) == set(list(BacktestResult._fields) + ["profit_abs"]) + assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID) assert len(bt_data) == 179 # Test loading from string (must yield same result) @@ -95,7 +95,7 @@ def test_load_backtest_data_multi(testdatadir): for strategy in ('DefaultStrategy', 'TestStrategy'): bt_data = load_backtest_data(filename, strategy=strategy) assert isinstance(bt_data, DataFrame) - assert set(bt_data.columns) == set(list(BacktestResult._fields) + ["profit_abs"]) + assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID) assert len(bt_data) == 179 # Test loading from string (must yield same result) @@ -122,7 +122,7 @@ def test_load_trades_from_db(default_conf, fee, mocker): assert isinstance(trades, DataFrame) assert "pair" in trades.columns assert "open_date" in trades.columns - assert "profit_percent" in trades.columns + assert "profit_ratio" in trades.columns for col in BT_DATA_COLUMNS: if col not in ['index', 'open_at_end']: @@ -143,7 +143,7 @@ def test_extract_trades_of_period(testdatadir): trades = DataFrame( {'pair': [pair, pair, pair, pair], - 'profit_percent': [0.0, 0.1, -0.2, -0.5], + 'profit_ratio': [0.0, 0.1, -0.2, -0.5], 'profit_abs': [0.0, 1, -2, -5], 'open_date': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime, Arrow(2017, 11, 14, 9, 41, 0).datetime, @@ -285,6 +285,20 @@ def test_calculate_max_drawdown(testdatadir): drawdown, h, low = calculate_max_drawdown(DataFrame()) +def test_calculate_csum(testdatadir): + filename = testdatadir / "backtest-result_test.json" + bt_data = load_backtest_data(filename) + csum_min, csum_max = calculate_csum(bt_data) + + assert isinstance(csum_min, float) + assert isinstance(csum_max, float) + assert csum_min < 0.01 + assert csum_max > 0.02 + + with pytest.raises(ValueError, match='Trade dataframe empty.'): + csum_min, csum_max = calculate_csum(DataFrame()) + + def test_calculate_max_drawdown2(): values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024, -0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872, diff --git a/tests/data/test_history.py b/tests/data/test_history.py index 99b22adda..353cfc6f7 100644 --- a/tests/data/test_history.py +++ b/tests/data/test_history.py @@ -646,7 +646,7 @@ def test_datahandler_ohlcv_get_available_data(testdatadir): ('ZEC/BTC', '5m'), ('UNITTEST/BTC', '1m'), ('ADA/BTC', '5m'), ('ETC/BTC', '5m'), ('NXT/BTC', '5m'), ('DASH/BTC', '5m'), ('XRP/ETH', '1m'), ('XRP/ETH', '5m'), ('UNITTEST/BTC', '30m'), - ('UNITTEST/BTC', '8m')} + ('UNITTEST/BTC', '8m'), ('NOPAIR/XXX', '4m')} paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir) assert set(paircombs) == {('UNITTEST/BTC', '8m')} @@ -672,6 +672,18 @@ def test_jsondatahandler_ohlcv_purge(mocker, testdatadir): assert unlinkmock.call_count == 1 +def test_jsondatahandler_ohlcv_load(testdatadir, caplog): + dh = JsonDataHandler(testdatadir) + df = dh.ohlcv_load('XRP/ETH', '5m') + assert len(df) == 711 + + # Failure case (empty array) + df1 = dh.ohlcv_load('NOPAIR/XXX', '4m') + assert len(df1) == 0 + assert log_has("Could not load data for NOPAIR/XXX.", caplog) + assert df.columns.equals(df1.columns) + + def test_jsondatahandler_trades_load(testdatadir, caplog): dh = JsonGzDataHandler(testdatadir) logmsg = "Old trades format detected - converting" diff --git a/tests/edge/test_edge.py b/tests/edge/test_edge.py index f25dad35b..c30bce6a4 100644 --- a/tests/edge/test_edge.py +++ b/tests/edge/test_edge.py @@ -209,7 +209,7 @@ def test_nonexisting_stoploss(mocker, edge_conf): assert edge.stoploss('N/O') == -0.1 -def test_stake_amount(mocker, edge_conf): +def test_edge_stake_amount(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock( @@ -217,20 +217,33 @@ def test_stake_amount(mocker, edge_conf): 'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60), } )) - free = 100 - total = 100 - in_trade = 25 - assert edge.stake_amount('E/F', free, total, in_trade) == 31.25 + assert edge._capital_ratio == 0.5 + assert edge.stake_amount('E/F', free_capital=100, total_capital=100, + capital_in_trade=25) == 31.25 - free = 20 - total = 100 - in_trade = 25 - assert edge.stake_amount('E/F', free, total, in_trade) == 20 + assert edge.stake_amount('E/F', free_capital=20, total_capital=100, + capital_in_trade=25) == 20 - free = 0 - total = 100 - in_trade = 25 - assert edge.stake_amount('E/F', free, total, in_trade) == 0 + assert edge.stake_amount('E/F', free_capital=0, total_capital=100, + capital_in_trade=25) == 0 + + # Test with increased allowed_risk + # Result should be no more than allowed capital + edge._allowed_risk = 0.4 + edge._capital_ratio = 0.5 + assert edge.stake_amount('E/F', free_capital=100, total_capital=100, + capital_in_trade=25) == 62.5 + + assert edge.stake_amount('E/F', free_capital=100, total_capital=100, + capital_in_trade=0) == 50 + + edge._capital_ratio = 1 + # Full capital is available + assert edge.stake_amount('E/F', free_capital=100, total_capital=100, + capital_in_trade=0) == 100 + # Full capital is available + assert edge.stake_amount('E/F', free_capital=0, total_capital=100, + capital_in_trade=0) == 0 def test_nonexisting_stake_amount(mocker, edge_conf): diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py index 0c8b7bdcf..03cb30d62 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange/test_ccxt_compat.py @@ -5,10 +5,12 @@ However, these tests should give a good idea to determine if a new exchange is suitable to run with freqtrade. """ +from datetime import datetime, timedelta, timezone from pathlib import Path import pytest +from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date from freqtrade.resolvers.exchange_resolver import ExchangeResolver from tests.conftest import get_default_conf @@ -18,7 +20,7 @@ EXCHANGES = { 'bittrex': { 'pair': 'BTC/USDT', 'hasQuoteVolume': False, - 'timeframe': '5m', + 'timeframe': '1h', }, 'binance': { 'pair': 'BTC/USDT', @@ -120,7 +122,12 @@ class TestCCXTExchange(): ohlcv = exchange.refresh_latest_ohlcv([pair_tf]) assert isinstance(ohlcv, dict) assert len(ohlcv[pair_tf]) == len(exchange.klines(pair_tf)) - assert len(exchange.klines(pair_tf)) > 200 + # assert len(exchange.klines(pair_tf)) > 200 + # Assume 90% uptime ... + assert len(exchange.klines(pair_tf)) > exchange.ohlcv_candle_limit(timeframe) * 0.90 + # Check if last-timeframe is within the last 2 intervals + now = datetime.now(timezone.utc) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2)) + assert exchange.klines(pair_tf).iloc[-1]['date'] >= timeframe_to_prev_date(timeframe, now) # TODO: tests fetch_trades (?) diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 9d655997f..75db2de26 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -305,6 +305,136 @@ def test_price_get_one_pip(default_conf, mocker, price, precision_mode, precisio assert pytest.approx(exchange.price_get_one_pip(pair, price)) == expected +def test_get_min_pair_stake_amount(mocker, default_conf) -> None: + + exchange = get_patched_exchange(mocker, default_conf, id="binance") + stoploss = -0.05 + markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}} + + # no pair found + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + with pytest.raises(ValueError, match=r'.*get market information.*'): + exchange.get_min_pair_stake_amount('BNB/BTC', 1, stoploss) + + # no 'limits' section + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result is None + + # empty 'limits' section + markets["ETH/BTC"]["limits"] = {} + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result is None + + # no cost Min + markets["ETH/BTC"]["limits"] = { + 'cost': {"min": None}, + 'amount': {} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result is None + + # no amount Min + markets["ETH/BTC"]["limits"] = { + 'cost': {}, + 'amount': {"min": None} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result is None + + # empty 'cost'/'amount' section + markets["ETH/BTC"]["limits"] = { + 'cost': {}, + 'amount': {} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result is None + + # min cost is set + markets["ETH/BTC"]["limits"] = { + 'cost': {'min': 2}, + 'amount': {} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss) + assert result == 2 / 0.9 + + # min amount is set + markets["ETH/BTC"]["limits"] = { + 'cost': {}, + 'amount': {'min': 2} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) + assert result == 2 * 2 / 0.9 + + # min amount and cost are set (cost is minimal) + markets["ETH/BTC"]["limits"] = { + 'cost': {'min': 2}, + 'amount': {'min': 2} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) + assert result == max(2, 2 * 2) / 0.9 + + # min amount and cost are set (amount is minial) + markets["ETH/BTC"]["limits"] = { + 'cost': {'min': 8}, + 'amount': {'min': 2} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + PropertyMock(return_value=markets) + ) + result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss) + assert result == max(8, 2 * 2) / 0.9 + + +def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None: + exchange = get_patched_exchange(mocker, default_conf, id="binance") + stoploss = -0.05 + markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}} + + # Real Binance data + markets["ETH/BTC"]["limits"] = { + 'cost': {'min': 0.0001}, + 'amount': {'min': 0.001} + } + mocker.patch( + 'freqtrade.exchange.Exchange.markets', + 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) + + def test_set_sandbox(default_conf, mocker): """ Test working scenario @@ -373,28 +503,25 @@ def test__load_markets(default_conf, mocker, caplog): expected_return = {'ETH/BTC': 'available'} api_mock = MagicMock() api_mock.load_markets = MagicMock(return_value=expected_return) - type(api_mock).markets = expected_return + mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock)) default_conf['exchange']['pair_whitelist'] = ['ETH/BTC'] - ex = get_patched_exchange(mocker, default_conf, api_mock, id="binance", mock_markets=False) + ex = Exchange(default_conf) + assert ex.markets == expected_return def test_reload_markets(default_conf, mocker, caplog): caplog.set_level(logging.DEBUG) initial_markets = {'ETH/BTC': {}} - - def load_markets(*args, **kwargs): - exchange._api.markets = updated_markets + updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}} api_mock = MagicMock() - api_mock.load_markets = load_markets - type(api_mock).markets = initial_markets + api_mock.load_markets = MagicMock(return_value=initial_markets) default_conf['exchange']['markets_refresh_interval'] = 10 exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance", mock_markets=False) exchange._load_async_markets = MagicMock() exchange._last_markets_refresh = arrow.utcnow().int_timestamp - updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}} assert exchange.markets == initial_markets @@ -403,6 +530,7 @@ def test_reload_markets(default_conf, mocker, caplog): assert exchange.markets == initial_markets assert exchange._load_async_markets.call_count == 0 + api_mock.load_markets = MagicMock(return_value=updated_markets) # more than 10 minutes have passed, reload is executed exchange._last_markets_refresh = arrow.utcnow().int_timestamp - 15 * 60 exchange.reload_markets() @@ -429,7 +557,7 @@ def test_reload_markets_exception(default_conf, mocker, caplog): def test_validate_stake_currency(default_conf, stake_currency, mocker, caplog): default_conf['stake_currency'] = stake_currency api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/ETH': {'quote': 'ETH'}, 'NEO/USDT': {'quote': 'USDT'}, }) @@ -443,7 +571,7 @@ def test_validate_stake_currency(default_conf, stake_currency, mocker, caplog): def test_validate_stake_currency_error(default_conf, mocker, caplog): default_conf['stake_currency'] = 'XRP' api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/ETH': {'quote': 'ETH'}, 'NEO/USDT': {'quote': 'USDT'}, }) @@ -489,7 +617,7 @@ def test_get_pair_base_currency(default_conf, mocker, pair, expected): def test_validate_pairs(default_conf, mocker): # test exchange.validate_pairs directly api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/BTC': {'quote': 'BTC'}, @@ -540,7 +668,7 @@ def test_validate_pairs_exception(default_conf, mocker, caplog): def test_validate_pairs_restricted(default_conf, mocker, caplog): api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/BTC': {'quote': 'BTC', 'info': {'IsRestricted': True}}, 'NEO/BTC': {'quote': 'BTC', 'info': 'TestString'}, # info can also be a string ... @@ -558,7 +686,7 @@ def test_validate_pairs_restricted(default_conf, mocker, caplog): def test_validate_pairs_stakecompatibility(default_conf, mocker, caplog): api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'}, 'HELLO-WORLD': {'quote': 'BTC'}, @@ -574,7 +702,7 @@ def test_validate_pairs_stakecompatibility(default_conf, mocker, caplog): def test_validate_pairs_stakecompatibility_downloaddata(default_conf, mocker, caplog): api_mock = MagicMock() default_conf['stake_currency'] = '' - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'}, 'HELLO-WORLD': {'quote': 'BTC'}, @@ -585,12 +713,13 @@ def test_validate_pairs_stakecompatibility_downloaddata(default_conf, mocker, ca mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency') Exchange(default_conf) + assert type(api_mock).load_markets.call_count == 1 def test_validate_pairs_stakecompatibility_fail(default_conf, mocker, caplog): default_conf['exchange']['pair_whitelist'].append('HELLO-WORLD') api_mock = MagicMock() - type(api_mock).markets = PropertyMock(return_value={ + type(api_mock).load_markets = MagicMock(return_value={ 'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'}, 'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'}, 'HELLO-WORLD': {'quote': 'USDT'}, @@ -1288,7 +1417,7 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name): exchange._async_get_candle_history = Mock(wraps=mock_candle_hist) # one_call calculation * 1.8 should do 2 calls - since = 5 * 60 * exchange._ft_has['ohlcv_candle_limit'] * 1.8 + since = 5 * 60 * exchange.ohlcv_candle_limit('5m') * 1.8 ret = exchange.get_historic_ohlcv(pair, "5m", int(( arrow.utcnow().int_timestamp - since) * 1000)) @@ -1344,7 +1473,7 @@ def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name): exchange._async_get_candle_history = Mock(wraps=mock_candle_hist) # one_call calculation * 1.8 should do 2 calls - since = 5 * 60 * exchange._ft_has['ohlcv_candle_limit'] * 1.8 + since = 5 * 60 * exchange.ohlcv_candle_limit('5m') * 1.8 ret = exchange.get_historic_ohlcv_as_df(pair, "5m", int(( arrow.utcnow().int_timestamp - since) * 1000)) @@ -1943,9 +2072,9 @@ def test_cancel_order_with_result_error(default_conf, mocker, exchange_name, cap def test_cancel_order(default_conf, mocker, exchange_name): default_conf['dry_run'] = False api_mock = MagicMock() - api_mock.cancel_order = MagicMock(return_value=123) + api_mock.cancel_order = MagicMock(return_value={'id': '123'}) exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) - assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == 123 + assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == {'id': '123'} with pytest.raises(InvalidOrderException): api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order")) @@ -1962,9 +2091,9 @@ def test_cancel_order(default_conf, mocker, exchange_name): def test_cancel_stoploss_order(default_conf, mocker, exchange_name): default_conf['dry_run'] = False api_mock = MagicMock() - api_mock.cancel_order = MagicMock(return_value=123) + api_mock.cancel_order = MagicMock(return_value={'id': '123'}) exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name) - assert exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC') == 123 + assert exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC') == {'id': '123'} with pytest.raises(InvalidOrderException): api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order")) @@ -2289,6 +2418,19 @@ def test_get_markets_error(default_conf, mocker): ex.get_markets('LTC', 'USDT', True, False) +@pytest.mark.parametrize("exchange_name", EXCHANGES) +def test_ohlcv_candle_limit(default_conf, mocker, exchange_name): + exchange = get_patched_exchange(mocker, default_conf, id=exchange_name) + timeframes = ('1m', '5m', '1h') + expected = exchange._ft_has['ohlcv_candle_limit'] + for timeframe in timeframes: + if 'ohlcv_candle_limit_per_timeframe' in exchange._ft_has: + expected = exchange._ft_has['ohlcv_candle_limit_per_timeframe'][timeframe] + # This should only run for bittrex + assert exchange_name == 'bittrex' + assert exchange.ohlcv_candle_limit(timeframe) == expected + + def test_timeframe_to_minutes(): assert timeframe_to_minutes("5m") == 5 assert timeframe_to_minutes("10m") == 10 @@ -2333,6 +2475,9 @@ def test_timeframe_to_prev_date(): date = datetime.now(tz=timezone.utc) assert timeframe_to_prev_date("5m") < date + # Does not round + time = datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc) + assert timeframe_to_prev_date('5m', time) == time def test_timeframe_to_next_date(): diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py index f06b0ecd3..df6f22e01 100644 --- a/tests/optimize/conftest.py +++ b/tests/optimize/conftest.py @@ -37,7 +37,7 @@ def hyperopt_results(): return pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], - 'profit_percent': [-0.1, 0.2, 0.3], + 'profit_ratio': [-0.1, 0.2, 0.3], 'profit_abs': [-0.2, 0.4, 0.6], 'trade_duration': [10, 30, 10], 'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI], diff --git a/tests/optimize/test_backtest_detail.py b/tests/optimize/test_backtest_detail.py index 720ed8c13..daf7c2053 100644 --- a/tests/optimize/test_backtest_detail.py +++ b/tests/optimize/test_backtest_detail.py @@ -510,7 +510,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: ) assert len(results) == len(data.trades) - assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3) + assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3) for c, trade in enumerate(data.trades): res = results.iloc[c] diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index e55e166d9..c8d4338af 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -341,12 +341,14 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None: mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats') mocker.patch('freqtrade.optimize.backtesting.show_backtest_results') + sbs = mocker.patch('freqtrade.optimize.backtesting.store_backtest_stats') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) default_conf['timeframe'] = '1m' default_conf['datadir'] = testdatadir - default_conf['export'] = None + default_conf['export'] = 'trades' + default_conf['exportfilename'] = 'export.txt' default_conf['timerange'] = '-1510694220' backtesting = Backtesting(default_conf) @@ -361,6 +363,7 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None: assert log_has(line, caplog) assert backtesting.strategy.dp._pairlists is not None assert backtesting.strategy.bot_loop_start.call_count == 1 + assert sbs.call_count == 1 def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) -> None: @@ -445,7 +448,7 @@ def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, ti Backtesting(default_conf) -def test_backtest(default_conf, fee, mocker, testdatadir) -> 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) patch_exchange(mocker) @@ -469,21 +472,28 @@ def test_backtest(default_conf, fee, mocker, testdatadir) -> None: expected = pd.DataFrame( {'pair': [pair, pair], - 'profit_percent': [0.0, 0.0], - 'profit_abs': [0.0, 0.0], + 'stake_amount': [0.001, 0.001], + 'amount': [0.00957442, 0.0097064], 'open_date': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime, Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True ), - 'open_rate': [0.104445, 0.10302485], - 'open_fee': [0.0025, 0.0025], 'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime, Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True), + 'open_rate': [0.104445, 0.10302485], 'close_rate': [0.104969, 0.103541], - 'close_fee': [0.0025, 0.0025], - 'amount': [0.00957442, 0.0097064], + 'fee_open': [0.0025, 0.0025], + 'fee_close': [0.0025, 0.0025], 'trade_duration': [235, 40], - 'open_at_end': [False, False], - 'sell_reason': [SellType.ROI, SellType.ROI] + 'profit_ratio': [0.0, 0.0], + 'profit_abs': [0.0, 0.0], + 'sell_reason': [SellType.ROI, SellType.ROI], + 'initial_stop_loss_abs': [0.0940005, 0.09272236], + 'initial_stop_loss_ratio': [-0.1, -0.1], + 'stop_loss_abs': [0.0940005, 0.09272236], + 'stop_loss_ratio': [-0.1, -0.1], + 'min_rate': [0.1038, 0.10302485], + 'max_rate': [0.10501, 0.1038888], + 'is_open': [False, False], }) pd.testing.assert_frame_equal(results, expected) data_pair = processed[pair] @@ -629,7 +639,7 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir): # 100 buys signals assert len(results) == 100 # One trade was force-closed at the end - assert len(results.loc[results.open_at_end]) == 0 + assert len(results.loc[results['is_open']]) == 0 @pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC']) @@ -737,7 +747,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): patch_exchange(mocker) - backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS + ['profit_abs'])) + backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS)) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock) @@ -803,7 +813,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat patch_exchange(mocker) backtestmock = MagicMock(side_effect=[ pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'], - 'profit_percent': [0.0, 0.0], + 'profit_ratio': [0.0, 0.0], 'profit_abs': [0.0, 0.0], 'open_date': pd.to_datetime(['2018-01-29 18:40:00', '2018-01-30 03:30:00', ], utc=True @@ -811,13 +821,13 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat 'close_date': pd.to_datetime(['2018-01-29 20:45:00', '2018-01-30 05:35:00', ], utc=True), 'trade_duration': [235, 40], - 'open_at_end': [False, False], + 'is_open': [False, False], 'open_rate': [0.104445, 0.10302485], 'close_rate': [0.104969, 0.103541], 'sell_reason': [SellType.ROI, SellType.ROI] }), pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'], - 'profit_percent': [0.03, 0.01, 0.1], + 'profit_ratio': [0.03, 0.01, 0.1], 'profit_abs': [0.01, 0.02, 0.2], 'open_date': pd.to_datetime(['2018-01-29 18:40:00', '2018-01-30 03:30:00', @@ -827,7 +837,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat '2018-01-30 05:35:00', '2018-01-30 08:30:00'], utc=True), 'trade_duration': [47, 40, 20], - 'open_at_end': [False, False, False], + 'is_open': [False, False, False], '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 82be894d3..68eb3d6f7 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -251,9 +251,9 @@ def test_start_no_data(mocker, hyperopt_conf) -> None: def test_start_filelock(mocker, hyperopt_conf, caplog) -> None: - start_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf))) + hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf))) patched_configuration_load_config_file(mocker, hyperopt_conf) - mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock) + mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.__init__', hyperopt_mock) patch_exchange(mocker) args = [ @@ -427,7 +427,7 @@ def test_format_results(hyperopt): ('LTC/BTC', 1, 1, 123), ('XPR/BTC', -1, -2, -246) ] - labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration'] + labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] df = pd.DataFrame.from_records(trades, columns=labels) results_metrics = hyperopt._calculate_results_metrics(df) results_explanation = hyperopt._format_results_explanation_string(results_metrics) @@ -567,7 +567,7 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: trades = [ ('TRX/BTC', 0.023117, 0.000233, 100) ] - labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration'] + labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] backtest_result = pd.DataFrame.from_records(trades, columns=labels) mocker.patch( diff --git a/tests/optimize/test_hyperoptloss.py b/tests/optimize/test_hyperoptloss.py index f7910e6d6..73feeb007 100644 --- a/tests/optimize/test_hyperoptloss.py +++ b/tests/optimize/test_hyperoptloss.py @@ -60,9 +60,9 @@ def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results) def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf) correct = hl.hyperopt_loss_function(hyperopt_results, 600, @@ -77,9 +77,9 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'}) hl = HyperOptLossResolver.load_hyperoptloss(default_conf) @@ -95,9 +95,9 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'}) hl = HyperOptLossResolver.load_hyperoptloss(default_conf) @@ -113,9 +113,9 @@ def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'}) hl = HyperOptLossResolver.load_hyperoptloss(default_conf) @@ -131,9 +131,9 @@ def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'}) hl = HyperOptLossResolver.load_hyperoptloss(default_conf) @@ -149,9 +149,9 @@ def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_result def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() - results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2 results_under = hyperopt_results.copy() - results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2 default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'}) hl = HyperOptLossResolver.load_hyperoptloss(default_conf) diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index f184cb125..51a78c7cc 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -27,7 +27,7 @@ def test_text_table_bt_results(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC'], - 'profit_percent': [0.1, 0.2], + 'profit_ratio': [0.1, 0.2], 'profit_abs': [0.2, 0.4], 'trade_duration': [10, 30], 'wins': [2, 0], @@ -59,7 +59,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): results = {'DefStrat': { 'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"], - "profit_percent": [0.003312, 0.010801, 0.013803, 0.002780], + "profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780], "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003], "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime, Arrow(2017, 11, 14, 21, 36, 00).datetime, @@ -72,7 +72,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): "open_rate": [0.002543, 0.003003, 0.003089, 0.003214], "close_rate": [0.002546, 0.003014, 0.003103, 0.003217], "trade_duration": [123, 34, 31, 14], - "open_at_end": [False, False, False, True], + "is_open": [False, False, False, True], "sell_reason": [SellType.ROI, SellType.STOP_LOSS, SellType.ROI, SellType.FORCE_SELL] }), @@ -103,7 +103,7 @@ def test_generate_backtest_stats(default_conf, testdatadir): results = {'DefStrat': { 'results': pd.DataFrame( {"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"], - "profit_percent": [0.003312, 0.010801, -0.013803, 0.002780], + "profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780], "profit_abs": [0.000003, 0.000011, -0.000014, 0.000003], "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime, Arrow(2017, 11, 14, 21, 36, 00).datetime, @@ -179,7 +179,7 @@ def test_generate_pair_metrics(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC'], - 'profit_percent': [0.1, 0.2], + 'profit_ratio': [0.1, 0.2], 'profit_abs': [0.2, 0.4], 'trade_duration': [10, 30], 'wins': [2, 0], @@ -227,7 +227,7 @@ def test_text_table_sell_reason(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], - 'profit_percent': [0.1, 0.2, -0.1], + 'profit_ratio': [0.1, 0.2, -0.1], 'profit_abs': [0.2, 0.4, -0.2], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], @@ -259,7 +259,7 @@ def test_generate_sell_reason_stats(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], - 'profit_percent': [0.1, 0.2, -0.1], + 'profit_ratio': [0.1, 0.2, -0.1], 'profit_abs': [0.2, 0.4, -0.2], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], @@ -295,7 +295,7 @@ def test_text_table_strategy(default_conf): results['TestStrategy1'] = {'results': pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], - 'profit_percent': [0.1, 0.2, 0.3], + 'profit_ratio': [0.1, 0.2, 0.3], 'profit_abs': [0.2, 0.4, 0.5], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], @@ -307,7 +307,7 @@ def test_text_table_strategy(default_conf): results['TestStrategy2'] = {'results': pd.DataFrame( { 'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'], - 'profit_percent': [0.4, 0.2, 0.3], + 'profit_ratio': [0.4, 0.2, 0.3], 'profit_abs': [0.4, 0.4, 0.5], 'trade_duration': [15, 30, 15], 'wins': [4, 1, 0], diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py index fda2b1409..67cd96f5b 100644 --- a/tests/plugins/test_pairlist.py +++ b/tests/plugins/test_pairlist.py @@ -126,6 +126,20 @@ def test_load_pairlist_noexist(mocker, markets, default_conf): default_conf, {}, 1) +def test_load_pairlist_verify_multi(mocker, markets, default_conf): + freqtrade = get_patched_freqtradebot(mocker, default_conf) + mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)) + plm = PairListManager(freqtrade.exchange, default_conf) + # Call different versions one after the other, should always consider what was passed in + # and have no side-effects (therefore the same check multiple times) + assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', ], print) == ['ETH/BTC', 'XRP/BTC'] + assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', 'BUUU/BTC'], print) == ['ETH/BTC', 'XRP/BTC'] + assert plm.verify_whitelist(['XRP/BTC', 'BUUU/BTC'], print) == ['XRP/BTC'] + assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', ], print) == ['ETH/BTC', 'XRP/BTC'] + assert plm.verify_whitelist(['ETH/USDT', 'XRP/USDT', ], print) == ['ETH/USDT', ] + assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', ], print) == ['ETH/BTC', 'XRP/BTC'] + + def test_refresh_market_pair_not_in_whitelist(mocker, markets, static_pl_conf): freqtrade = get_patched_freqtradebot(mocker, static_pl_conf) diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py index e36900a96..2e42c1be4 100644 --- a/tests/plugins/test_protections.py +++ b/tests/plugins/test_protections.py @@ -83,7 +83,7 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog): "method": "StoplossGuard", "lookback_period": 60, "stop_duration": 40, - "trade_limit": 2 + "trade_limit": 3 }] freqtrade = get_patched_freqtradebot(mocker, default_conf) message = r"Trading stopped due to .*" @@ -136,7 +136,7 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair default_conf['protections'] = [{ "method": "StoplossGuard", "lookback_period": 60, - "trade_limit": 1, + "trade_limit": 2, "stop_duration": 60, "only_per_pair": only_per_pair }] diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py index 8ec356d54..60d9950aa 100644 --- a/tests/rpc/test_rpc.py +++ b/tests/rpc/test_rpc.py @@ -80,6 +80,8 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'amount': 91.07468123, 'amount_requested': 91.07468123, 'stake_amount': 0.001, + 'trade_duration': None, + 'trade_duration_s': None, 'close_profit': None, 'close_profit_pct': None, 'close_profit_abs': None, @@ -144,6 +146,8 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None: 'current_rate': ANY, 'amount': 91.07468123, 'amount_requested': 91.07468123, + 'trade_duration': ANY, + 'trade_duration_s': ANY, 'stake_amount': 0.001, 'close_profit': None, 'close_profit_pct': None, diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index f5b9a58f3..d7d69d0ae 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -11,9 +11,11 @@ import uvicorn from fastapi import FastAPI from fastapi.exceptions import HTTPException from fastapi.testclient import TestClient +from numpy import isnan from requests.auth import _basic_auth_str from freqtrade.__init__ import __version__ +from freqtrade.exceptions import ExchangeError from freqtrade.loggers import setup_logging, setup_logging_pre from freqtrade.persistence import PairLocks, Trade from freqtrade.rpc import RPC @@ -83,11 +85,26 @@ def assert_response(response, expected_code=200, needs_cors=True): def test_api_not_found(botclient): ftbot, client = botclient - rc = client_post(client, f"{BASE_URI}/invalid_url") + rc = client_get(client, f"{BASE_URI}/invalid_url") assert_response(rc, 404) assert rc.json() == {"detail": "Not Found"} +def test_api_ui_fallback(botclient): + ftbot, client = botclient + + rc = client_get(client, "/favicon.ico") + assert rc.status_code == 200 + + rc = client_get(client, "/fallback_file.html") + assert rc.status_code == 200 + assert '`freqtrade install-ui`' in rc.text + + # Forwarded to fallback_html or index.html (depending if it's installed or not) + rc = client_get(client, "/something") + assert rc.status_code == 200 + + def test_api_auth(): with pytest.raises(ValueError): create_token({'identity': {'u': 'Freqtrade'}}, 'secret1234', token_type="NotATokenType") @@ -280,7 +297,7 @@ def test_api_run(default_conf, mocker, caplog): "Please make sure that this is intentional!", caplog) assert log_has_re("SECURITY WARNING - `jwt_secret_key` seems to be default.*", caplog) - # Test crashing flask + # Test crashing API server caplog.clear() mocker.patch('freqtrade.rpc.api_server.webserver.UvicornServer', MagicMock(side_effect=Exception)) @@ -588,7 +605,7 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, li rc = client_get(client, f"{BASE_URI}/profit") assert_response(rc) - assert rc.json() == {'avg_duration': '0:00:00', + assert rc.json() == {'avg_duration': ANY, 'best_pair': 'ETH/BTC', 'best_rate': 6.2, 'first_trade_date': 'just now', @@ -774,6 +791,15 @@ def test_api_status(botclient, mocker, ticker, fee, markets): 'exchange': 'bittrex', }] + mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate', + MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available"))) + + rc = client_get(client, f"{BASE_URI}/status") + assert_response(rc) + resp_values = rc.json() + assert len(resp_values) == 1 + assert isnan(resp_values[0]['profit_abs']) + def test_api_version(botclient): ftbot, client = botclient @@ -1109,7 +1135,7 @@ def test_list_available_pairs(botclient): rc = client_get(client, f"{BASE_URI}/available_pairs") assert_response(rc) - assert rc.json()['length'] == 12 + assert rc.json()['length'] == 13 assert isinstance(rc.json()['pairs'], list) rc = client_get(client, f"{BASE_URI}/available_pairs?timeframe=5m") diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py index 1c34b6b26..f065bb4c5 100644 --- a/tests/rpc/test_rpc_telegram.py +++ b/tests/rpc/test_rpc_telegram.py @@ -519,7 +519,7 @@ def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance, tick assert '*EUR:*' in result assert 'Balance:' in result assert 'Est. BTC:' in result - assert 'BTC: 12.00000000' in result + assert 'BTC: 12.00000000' in result assert '*XRP:* not showing <1$ amount' in result @@ -1205,7 +1205,7 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None: '*Amount:* `1333.33333333`\n' \ '*Open Rate:* `0.00001099`\n' \ '*Current Rate:* `0.00001099`\n' \ - '*Total:* `(0.001000 BTC, 12.345 USD)`' + '*Total:* `(0.00100000 BTC, 12.345 USD)`' freqtradebot.config['telegram']['notification_settings'] = {'buy': 'off'} caplog.clear() @@ -1389,7 +1389,7 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None: '*Amount:* `1333.33333333`\n' '*Open Rate:* `0.00001099`\n' '*Current Rate:* `0.00001099`\n' - '*Total:* `(0.001000 BTC)`') + '*Total:* `(0.00100000 BTC)`') def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None: diff --git a/tests/test_configuration.py b/tests/test_configuration.py index bebbc1508..94c3e24f6 100644 --- a/tests/test_configuration.py +++ b/tests/test_configuration.py @@ -743,18 +743,18 @@ def test_set_loggers_journald_importerror(mocker, import_fails): logger.handlers = orig_handlers -def test_set_logfile(default_conf, mocker): +def test_set_logfile(default_conf, mocker, tmpdir): patched_configuration_load_config_file(mocker, default_conf) - + f = Path(tmpdir / "test_file.log") + assert not f.is_file() arglist = [ - 'trade', '--logfile', 'test_file.log', + 'trade', '--logfile', str(f), ] args = Arguments(arglist).get_parsed_arg() configuration = Configuration(args) validated_conf = configuration.load_config() - assert validated_conf['logfile'] == "test_file.log" - f = Path("test_file.log") + assert validated_conf['logfile'] == str(f) assert f.is_file() try: f.unlink() diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index 6257a7e0b..3bd2f5607 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -158,7 +158,8 @@ def test_get_trade_stake_amount(default_conf, ticker, mocker) -> None: freqtrade = FreqtradeBot(default_conf) - result = freqtrade.get_trade_stake_amount('ETH/BTC') + result = freqtrade.wallets.get_trade_stake_amount( + 'ETH/BTC', freqtrade.get_free_open_trades()) assert result == default_conf['stake_amount'] @@ -194,12 +195,14 @@ def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_b if expected[i] is not None: limit_buy_order_open['id'] = str(i) - result = freqtrade.get_trade_stake_amount('ETH/BTC') + result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC', + freqtrade.get_free_open_trades()) assert pytest.approx(result) == expected[i] freqtrade.execute_buy('ETH/BTC', result) else: with pytest.raises(DependencyException): - freqtrade.get_trade_stake_amount('ETH/BTC') + freqtrade.wallets.get_trade_stake_amount('ETH/BTC', + freqtrade.get_free_open_trades()) def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None: @@ -210,7 +213,7 @@ def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None: patch_get_signal(freqtrade) with pytest.raises(DependencyException, match=r'.*stake amount.*'): - freqtrade.get_trade_stake_amount('ETH/BTC') + freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.get_free_open_trades()) @pytest.mark.parametrize("balance_ratio,result1", [ @@ -239,25 +242,25 @@ def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_r patch_get_signal(freqtrade) # no open trades, order amount should be 'balance / max_open_trades' - result = freqtrade.get_trade_stake_amount('ETH/BTC') + 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.get_trade_stake_amount('LTC/BTC') + 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.get_trade_stake_amount('XRP/BTC') + 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.get_trade_stake_amount('NEO/BTC') + result = freqtrade.wallets.get_trade_stake_amount('NEO/BTC', freqtrade.get_free_open_trades()) assert result == 0 @@ -283,8 +286,10 @@ def test_edge_overrides_stake_amount(mocker, edge_conf) -> None: edge_conf['dry_run_wallet'] = 999.9 freqtrade = FreqtradeBot(edge_conf) - assert freqtrade.get_trade_stake_amount('NEO/BTC') == (999.9 * 0.5 * 0.01) / 0.20 - assert freqtrade.get_trade_stake_amount('LTC/BTC') == (999.9 * 0.5 * 0.01) / 0.21 + assert freqtrade.wallets.get_trade_stake_amount( + 'NEO/BTC', freqtrade.get_free_open_trades(), freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.20 + assert freqtrade.wallets.get_trade_stake_amount( + 'LTC/BTC', freqtrade.get_free_open_trades(), freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.21 def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf) -> None: @@ -394,139 +399,6 @@ def test_total_open_trades_stakes(mocker, default_conf, ticker, fee) -> None: assert Trade.total_open_trades_stakes() == 1.97502e-03 -def test_get_min_pair_stake_amount(mocker, default_conf) -> None: - patch_RPCManager(mocker) - patch_exchange(mocker) - freqtrade = FreqtradeBot(default_conf) - freqtrade.strategy.stoploss = -0.05 - markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}} - - # no pair found - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - with pytest.raises(ValueError, match=r'.*get market information.*'): - freqtrade._get_min_pair_stake_amount('BNB/BTC', 1) - - # no 'limits' section - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result is None - - # empty 'limits' section - markets["ETH/BTC"]["limits"] = {} - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result is None - - # no cost Min - markets["ETH/BTC"]["limits"] = { - 'cost': {"min": None}, - 'amount': {} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result is None - - # no amount Min - markets["ETH/BTC"]["limits"] = { - 'cost': {}, - 'amount': {"min": None} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result is None - - # empty 'cost'/'amount' section - markets["ETH/BTC"]["limits"] = { - 'cost': {}, - 'amount': {} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result is None - - # min cost is set - markets["ETH/BTC"]["limits"] = { - 'cost': {'min': 2}, - 'amount': {} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1) - assert result == 2 / 0.9 - - # min amount is set - markets["ETH/BTC"]["limits"] = { - 'cost': {}, - 'amount': {'min': 2} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2) - assert result == 2 * 2 / 0.9 - - # min amount and cost are set (cost is minimal) - markets["ETH/BTC"]["limits"] = { - 'cost': {'min': 2}, - 'amount': {'min': 2} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2) - assert result == max(2, 2 * 2) / 0.9 - - # min amount and cost are set (amount is minial) - markets["ETH/BTC"]["limits"] = { - 'cost': {'min': 8}, - 'amount': {'min': 2} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2) - assert result == max(8, 2 * 2) / 0.9 - - -def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None: - patch_RPCManager(mocker) - patch_exchange(mocker) - freqtrade = FreqtradeBot(default_conf) - freqtrade.strategy.stoploss = -0.05 - markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}} - - # Real Binance data - markets["ETH/BTC"]["limits"] = { - 'cost': {'min': 0.0001}, - 'amount': {'min': 0.001} - } - mocker.patch( - 'freqtrade.exchange.Exchange.markets', - PropertyMock(return_value=markets) - ) - result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 0.020405) - assert round(result, 8) == round(max(0.0001, 0.001 * 0.020405) / 0.9, 8) - - def test_create_trade(default_conf, ticker, limit_buy_order, fee, mocker) -> None: patch_RPCManager(mocker) patch_exchange(mocker) @@ -633,7 +505,8 @@ def test_create_trade_limit_reached(default_conf, ticker, limit_buy_order_open, patch_get_signal(freqtrade) assert not freqtrade.create_trade('ETH/BTC') - assert freqtrade.get_trade_stake_amount('ETH/BTC') == 0 + assert freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.get_free_open_trades(), + freqtrade.edge) == 0 def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_open, fee, @@ -1007,7 +880,6 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order mocker.patch.multiple( 'freqtrade.freqtradebot.FreqtradeBot', get_buy_rate=buy_rate_mock, - _get_min_pair_stake_amount=MagicMock(return_value=1) ) buy_mm = MagicMock(return_value=limit_buy_order_open) mocker.patch.multiple( @@ -1018,6 +890,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order 'last': 0.00001172 }), buy=buy_mm, + get_min_pair_stake_amount=MagicMock(return_value=1), get_fee=fee, ) pair = 'ETH/BTC' @@ -1112,7 +985,6 @@ def test_execute_buy_confirm_error(mocker, default_conf, fee, limit_buy_order) - mocker.patch.multiple( 'freqtrade.freqtradebot.FreqtradeBot', get_buy_rate=MagicMock(return_value=0.11), - _get_min_pair_stake_amount=MagicMock(return_value=1) ) mocker.patch.multiple( 'freqtrade.exchange.Exchange', @@ -1122,6 +994,7 @@ def test_execute_buy_confirm_error(mocker, default_conf, fee, limit_buy_order) - 'last': 0.00001172 }), buy=MagicMock(return_value=limit_buy_order), + get_min_pair_stake_amount=MagicMock(return_value=1), get_fee=fee, ) stake_amount = 2 @@ -1570,6 +1443,109 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c assert log_has_re(r"Could not create trailing stoploss order for pair ETH/BTC\..*", caplog) +@pytest.mark.usefixtures("init_persistence") +def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee, + limit_buy_order, limit_sell_order) -> None: + # When trailing stoploss is set + stoploss = MagicMock(return_value={'id': 13434334}) + patch_RPCManager(mocker) + mocker.patch.multiple( + 'freqtrade.exchange.Exchange', + fetch_ticker=MagicMock(return_value={ + 'bid': 0.00001172, + 'ask': 0.00001173, + 'last': 0.00001172 + }), + buy=MagicMock(return_value={'id': limit_buy_order['id']}), + sell=MagicMock(return_value={'id': limit_sell_order['id']}), + get_fee=fee, + stoploss=stoploss, + stoploss_adjust=MagicMock(return_value=True), + ) + + # enabling TSL + default_conf['use_custom_stoploss'] = True + + # disabling ROI + default_conf['minimal_roi']['0'] = 999999999 + + freqtrade = get_patched_freqtradebot(mocker, default_conf) + + # enabling stoploss on exchange + freqtrade.strategy.order_types['stoploss_on_exchange'] = True + + # setting stoploss + freqtrade.strategy.custom_stoploss = lambda *args, **kwargs: -0.04 + + # setting stoploss_on_exchange_interval to 60 seconds + freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60 + + patch_get_signal(freqtrade) + + freqtrade.enter_positions() + trade = Trade.query.first() + trade.is_open = True + trade.open_order_id = None + trade.stoploss_order_id = 100 + + stoploss_order_hanging = MagicMock(return_value={ + 'id': 100, + 'status': 'open', + 'type': 'stop_loss_limit', + 'price': 3, + 'average': 2, + 'info': { + 'stopPrice': '0.000011134' + } + }) + + mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging) + + assert freqtrade.handle_trade(trade) is False + assert freqtrade.handle_stoploss_on_exchange(trade) is False + + # price jumped 2x + mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={ + 'bid': 0.00002344, + 'ask': 0.00002346, + 'last': 0.00002344 + })) + + 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) + + # stoploss should not be updated as the interval is 60 seconds + assert freqtrade.handle_trade(trade) is False + assert freqtrade.handle_stoploss_on_exchange(trade) is False + cancel_order_mock.assert_not_called() + stoploss_order_mock.assert_not_called() + + assert freqtrade.handle_trade(trade) is False + assert trade.stop_loss == 0.00002346 * 0.96 + assert trade.stop_loss_pct == -0.04 + + # setting stoploss_on_exchange_interval to 0 seconds + freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0 + + assert freqtrade.handle_stoploss_on_exchange(trade) is False + + cancel_order_mock.assert_called_once_with(100, 'ETH/BTC') + stoploss_order_mock.assert_called_once_with(amount=85.32423208, + pair='ETH/BTC', + order_types=freqtrade.strategy.order_types, + stop_price=0.00002346 * 0.96) + + # price fell below stoploss, so dry-run sells trade. + mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={ + 'bid': 0.00002144, + 'ask': 0.00002146, + 'last': 0.00002144 + })) + assert freqtrade.handle_trade(trade) is True + + def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog, limit_buy_order, limit_sell_order) -> None: @@ -2100,6 +2076,7 @@ def test_close_trade(default_conf, ticker, limit_buy_order, limit_buy_order_open def test_bot_loop_start_called_once(mocker, default_conf, caplog): ftbot = get_patched_freqtradebot(mocker, default_conf) + mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trade') patch_get_signal(ftbot) ftbot.strategy.bot_loop_start = MagicMock(side_effect=ValueError) ftbot.strategy.analyze = MagicMock() @@ -2632,7 +2609,7 @@ def test_handle_cancel_sell_cancel_exception(mocker, default_conf) -> None: patch_RPCManager(mocker) patch_exchange(mocker) mocker.patch( - 'freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException()) + 'freqtrade.exchange.Exchange.cancel_order_with_result', side_effect=InvalidOrderException()) freqtrade = FreqtradeBot(default_conf) @@ -3055,9 +3032,9 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, limit_buy mocker.patch.multiple( 'freqtrade.exchange.Exchange', fetch_ticker=MagicMock(return_value={ - 'bid': 0.00002172, - 'ask': 0.00002173, - 'last': 0.00002172 + 'bid': 0.00001172, + 'ask': 0.00001173, + 'last': 0.00001172 }), buy=MagicMock(return_value=limit_buy_order_open), get_fee=fee, @@ -3810,6 +3787,8 @@ def test_get_real_amount_fromorder(default_conf, trades_for_order, buy_order_fee open_order_id="123456" ) freqtrade = get_patched_freqtradebot(mocker, default_conf) + # Ticker rate cannot be found for this to work. + mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', side_effect=ExchangeError) # Amount is reduced by "fee" assert freqtrade.get_real_amount(trade, limit_buy_order) == amount - 0.004 diff --git a/tests/test_integration.py b/tests/test_integration.py index 9695977ac..8e3bd251a 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -178,7 +178,8 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc trades = Trade.query.all() assert len(trades) == 4 - assert freqtrade.get_trade_stake_amount('XRP/BTC') == result1 + assert freqtrade.wallets.get_trade_stake_amount( + 'XRP/BTC', freqtrade.get_free_open_trades()) == result1 rpc._rpc_forcebuy('TKN/BTC', None) @@ -199,7 +200,8 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc # One trade sold assert len(trades) == 4 # stake-amount should now be reduced, since one trade was sold at a loss. - assert freqtrade.get_trade_stake_amount('XRP/BTC') < result1 + assert freqtrade.wallets.get_trade_stake_amount( + 'XRP/BTC', freqtrade.get_free_open_trades()) < result1 # Validate that balance of sold trade is not in dry-run balances anymore. bals2 = freqtrade.wallets.get_all_balances() assert bals != bals2 diff --git a/tests/test_misc.py b/tests/test_misc.py index 6dcd9fbe5..e6ba70aee 100644 --- a/tests/test_misc.py +++ b/tests/test_misc.py @@ -6,35 +6,39 @@ from unittest.mock import MagicMock import pytest -from freqtrade.data.converter import ohlcv_to_dataframe -from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json, file_load_json, - format_ms_time, pair_to_filename, plural, render_template, - render_template_with_fallback, safe_value_fallback, +from freqtrade.misc import (decimals_per_coin, file_dump_json, file_load_json, format_ms_time, + pair_to_filename, plural, render_template, + render_template_with_fallback, round_coin_value, safe_value_fallback, safe_value_fallback2, shorten_date) +def test_decimals_per_coin(): + assert decimals_per_coin('USDT') == 3 + assert decimals_per_coin('EUR') == 3 + assert decimals_per_coin('BTC') == 8 + assert decimals_per_coin('ETH') == 5 + + +def test_round_coin_value(): + assert round_coin_value(222.222222, 'USDT') == '222.222 USDT' + assert round_coin_value(222.2, 'USDT') == '222.200 USDT' + assert round_coin_value(222.12745, 'EUR') == '222.127 EUR' + assert round_coin_value(0.1274512123, 'BTC') == '0.12745121 BTC' + assert round_coin_value(0.1274512123, 'ETH') == '0.12745 ETH' + + assert round_coin_value(222.222222, 'USDT', False) == '222.222' + assert round_coin_value(222.2, 'USDT', False) == '222.200' + assert round_coin_value(222.12745, 'EUR', False) == '222.127' + assert round_coin_value(0.1274512123, 'BTC', False) == '0.12745121' + assert round_coin_value(0.1274512123, 'ETH', False) == '0.12745' + + def test_shorten_date() -> None: str_data = '1 day, 2 hours, 3 minutes, 4 seconds ago' str_shorten_data = '1 d, 2 h, 3 min, 4 sec ago' assert shorten_date(str_data) == str_shorten_data -def test_datesarray_to_datetimearray(ohlcv_history_list): - dataframes = ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC", - fill_missing=True) - dates = datesarray_to_datetimearray(dataframes['date']) - - assert isinstance(dates[0], datetime.datetime) - assert dates[0].year == 2017 - assert dates[0].month == 11 - assert dates[0].day == 26 - assert dates[0].hour == 8 - assert dates[0].minute == 50 - - date_len = len(dates) - assert date_len == 2 - - def test_file_dump_json(mocker) -> None: file_open = mocker.patch('freqtrade.misc.open', MagicMock()) json_dump = mocker.patch('rapidjson.dump', MagicMock()) diff --git a/tests/test_persistence.py b/tests/test_persistence.py index 7487b2ef5..d0d29f142 100644 --- a/tests/test_persistence.py +++ b/tests/test_persistence.py @@ -815,6 +815,8 @@ def test_to_json(default_conf, fee): 'amount': 123.0, 'amount_requested': 123.0, 'stake_amount': 0.001, + 'trade_duration': None, + 'trade_duration_s': None, 'close_profit': None, 'close_profit_pct': None, 'close_profit_abs': None, @@ -869,6 +871,8 @@ def test_to_json(default_conf, fee): 'amount': 100.0, 'amount_requested': 101.0, 'stake_amount': 0.001, + 'trade_duration': 60, + 'trade_duration_s': 3600, 'stop_loss_abs': None, 'stop_loss_pct': None, 'stop_loss_ratio': None, @@ -1070,7 +1074,7 @@ def test_get_best_pair(fee): @pytest.mark.usefixtures("init_persistence") -def test_update_order_from_ccxt(): +def test_update_order_from_ccxt(caplog): # Most basic order return (only has orderid) o = Order.parse_from_ccxt_object({'id': '1234'}, 'ETH/BTC', 'buy') assert isinstance(o, Order) @@ -1116,6 +1120,14 @@ def test_update_order_from_ccxt(): with pytest.raises(DependencyException, match=r"Order-id's don't match"): o.update_from_ccxt_object(ccxt_order) + message = "aaaa is not a valid response object." + assert not log_has(message, caplog) + Order.update_orders([o], 'aaaa') + assert log_has(message, caplog) + + # Call regular update - shouldn't fail. + Order.update_orders([o], {'id': '1234'}) + @pytest.mark.usefixtures("init_persistence") def test_select_order(fee): diff --git a/tests/test_plotting.py b/tests/test_plotting.py index 96c9868a9..1752f9b94 100644 --- a/tests/test_plotting.py +++ b/tests/test_plotting.py @@ -179,7 +179,7 @@ def test_plot_trades(testdatadir, caplog): trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit') assert isinstance(trade_sell, go.Scatter) assert trade_sell.yaxis == 'y' - assert len(trades.loc[trades['profit_percent'] > 0]) == len(trade_sell.x) + assert len(trades.loc[trades['profit_ratio'] > 0]) == len(trade_sell.x) assert trade_sell.marker.color == 'green' assert trade_sell.marker.symbol == 'square-open' assert trade_sell.text[0] == '4.0%, roi, 15 min' @@ -187,7 +187,7 @@ def test_plot_trades(testdatadir, caplog): trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss') assert isinstance(trade_sell_loss, go.Scatter) assert trade_sell_loss.yaxis == 'y' - assert len(trades.loc[trades['profit_percent'] <= 0]) == len(trade_sell_loss.x) + assert len(trades.loc[trades['profit_ratio'] <= 0]) == len(trade_sell_loss.x) assert trade_sell_loss.marker.color == 'red' assert trade_sell_loss.marker.symbol == 'square-open' assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min' @@ -432,7 +432,8 @@ def test_start_plot_profit_error(mocker): start_plot_profit(argsp) -def test_plot_profit(default_conf, mocker, testdatadir, caplog): +def test_plot_profit(default_conf, mocker, testdatadir): + patch_exchange(mocker) default_conf['trade_source'] = 'file' default_conf['datadir'] = testdatadir default_conf['exportfilename'] = testdatadir / 'backtest-result_test_nofile.json' diff --git a/tests/testdata/NOPAIR_XXX-4m.json b/tests/testdata/NOPAIR_XXX-4m.json new file mode 100644 index 000000000..fe51488c7 --- /dev/null +++ b/tests/testdata/NOPAIR_XXX-4m.json @@ -0,0 +1 @@ +[] diff --git a/tests/testdata/backtest-result_multistrat.json b/tests/testdata/backtest-result_multistrat.json index 0e5386ef3..6999050b6 100644 --- a/tests/testdata/backtest-result_multistrat.json +++ b/tests/testdata/backtest-result_multistrat.json @@ -1 +1 @@ -{"strategy": {"DefaultStrategy": {"trades": [{"pair": "TRX/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:20:00+00:00", "trade_duration": 5, "open_rate": 9.64e-05, "close_rate": 0.00010074887218045112, "open_at_end": false, "sell_reason": "roi", "open_fee": 0.0025, "close_fee": 0.0025, "amount": 1037.344398340249, "profit_abs": 0.00399999999999999}, {"pair": "ADA/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:30:00+00:00", "trade_duration": 15, "open_rate": 4.756e-05, "close_rate": 4.9705563909774425e-05, "open_at_end": false, "sell_reason": "roi", "open_fee": 0.0025, "close_fee": 0.0025, "amount": 2102.6072329688814, "profit_abs": 0.00399999999999999}, {"pair": "XLM/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:25:00+00:00", "close_date": "2018-01-10 07:35:00+00:00", "trade_duration": 10, "open_rate": 3.339e-05, "close_rate": 3.489631578947368e-05, 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