mirror of
https://github.com/freqtrade/freqtrade.git
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Merge branch 'freqtrade:develop' into develop
This commit is contained in:
Simon Waiblinger
GitHub
commit
060198c04c
20
.github/workflows/ci.yml
vendored
20
.github/workflows/ci.yml
vendored
|
|
@ -25,7 +25,7 @@ jobs:
|
|||
strategy:
|
||||
matrix:
|
||||
os: [ ubuntu-20.04, ubuntu-22.04 ]
|
||||
python-version: ["3.9", "3.10", "3.11"]
|
||||
python-version: ["3.9", "3.10", "3.11", "3.12"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
|
@ -36,14 +36,14 @@ jobs:
|
|||
python-version: ${{ matrix.python-version }}
|
||||
|
||||
- name: Cache_dependencies
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
id: cache
|
||||
with:
|
||||
path: ~/dependencies/
|
||||
key: ${{ runner.os }}-dependencies
|
||||
|
||||
- name: pip cache (linux)
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
|
|
@ -125,7 +125,7 @@ jobs:
|
|||
strategy:
|
||||
matrix:
|
||||
os: [ "macos-latest", "macos-13" ]
|
||||
python-version: ["3.9", "3.10", "3.11"]
|
||||
python-version: ["3.9", "3.10", "3.11", "3.12"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
|
@ -137,14 +137,14 @@ jobs:
|
|||
check-latest: true
|
||||
|
||||
- name: Cache_dependencies
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
id: cache
|
||||
with:
|
||||
path: ~/dependencies/
|
||||
key: ${{ matrix.os }}-dependencies
|
||||
|
||||
- name: pip cache (macOS)
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/Library/Caches/pip
|
||||
key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
|
|
@ -238,7 +238,7 @@ jobs:
|
|||
strategy:
|
||||
matrix:
|
||||
os: [ windows-latest ]
|
||||
python-version: ["3.9", "3.10", "3.11"]
|
||||
python-version: ["3.9", "3.10", "3.11", "3.12"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
|
@ -249,7 +249,7 @@ jobs:
|
|||
python-version: ${{ matrix.python-version }}
|
||||
|
||||
- name: Pip cache (Windows)
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~\AppData\Local\pip\Cache
|
||||
key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
|
|
@ -368,14 +368,14 @@ jobs:
|
|||
python-version: "3.11"
|
||||
|
||||
- name: Cache_dependencies
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
id: cache
|
||||
with:
|
||||
path: ~/dependencies/
|
||||
key: ${{ runner.os }}-dependencies
|
||||
|
||||
- name: pip cache (linux)
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@
|
|||
# See https://pre-commit.com/hooks.html for more hooks
|
||||
repos:
|
||||
- repo: https://github.com/pycqa/flake8
|
||||
rev: "6.1.0"
|
||||
rev: "7.0.0"
|
||||
hooks:
|
||||
- id: flake8
|
||||
additional_dependencies: [Flake8-pyproject]
|
||||
|
|
@ -19,7 +19,7 @@ repos:
|
|||
- types-requests==2.31.0.20240106
|
||||
- types-tabulate==0.9.0.20240106
|
||||
- types-python-dateutil==2.8.19.20240106
|
||||
- SQLAlchemy==2.0.23
|
||||
- SQLAlchemy==2.0.25
|
||||
# stages: [push]
|
||||
|
||||
- repo: https://github.com/pycqa/isort
|
||||
|
|
@ -31,7 +31,7 @@ repos:
|
|||
|
||||
- repo: https://github.com/charliermarsh/ruff-pre-commit
|
||||
# Ruff version.
|
||||
rev: 'v0.1.9'
|
||||
rev: 'v0.1.14'
|
||||
hooks:
|
||||
- id: ruff
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
FROM python:3.11.6-slim-bookworm as base
|
||||
FROM python:3.11.7-slim-bookworm as base
|
||||
|
||||
# Setup env
|
||||
ENV LANG C.UTF-8
|
||||
|
|
|
|||
|
|
@ -30,7 +30,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
|
|||
- [X] [Binance](https://www.binance.com/)
|
||||
- [X] [Bitmart](https://bitmart.com/)
|
||||
- [X] [Gate.io](https://www.gate.io/ref/6266643)
|
||||
- [X] [Huobi](http://huobi.com/)
|
||||
- [X] [HTX](https://www.htx.com/) (Former Huobi)
|
||||
- [X] [Kraken](https://kraken.com/)
|
||||
- [X] [OKX](https://okx.com/) (Former OKEX)
|
||||
- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
|
||||
|
|
|
|||
Binary file not shown.
Binary file not shown.
|
|
@ -1,4 +1,4 @@
|
|||
FROM python:3.11.6-slim-bookworm as base
|
||||
FROM python:3.11.7-slim-bookworm as base
|
||||
|
||||
# Setup env
|
||||
ENV LANG C.UTF-8
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
FROM freqtradeorg/freqtrade:develop_plot
|
||||
|
||||
|
||||
# Pin jupyter-client to avoid tornado version conflict
|
||||
RUN pip install jupyterlab jupyter-client==7.3.4 --user --no-cache-dir
|
||||
# Pin prompt-toolkit to avoid questionary version conflict
|
||||
RUN pip install jupyterlab "prompt-toolkit<=3.0.36" jupyter-client --user --no-cache-dir
|
||||
|
||||
# Empty the ENTRYPOINT to allow all commands
|
||||
ENTRYPOINT []
|
||||
|
|
|
|||
|
|
@ -6,7 +6,7 @@ services:
|
|||
context: ..
|
||||
dockerfile: docker/Dockerfile.jupyter
|
||||
restart: unless-stopped
|
||||
container_name: freqtrade
|
||||
# container_name: freqtrade
|
||||
ports:
|
||||
- "127.0.0.1:8888:8888"
|
||||
volumes:
|
||||
|
|
|
|||
|
|
@ -208,10 +208,10 @@ Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force)
|
|||
For Kucoin, it is suggested to add `"KCS/<STAKE>"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `KCS` on the account or unless you're willing to disable using `KCS` for fees.
|
||||
Kucoin accounts may use `KCS` for fees, and if a trade happens to be on `KCS`, further trades may consume this position and make the initial `KCS` trade unsellable as the expected amount is not there anymore.
|
||||
|
||||
## Huobi
|
||||
## HTX (formerly Huobi)
|
||||
|
||||
!!! Tip "Stoploss on Exchange"
|
||||
Huobi supports `stoploss_on_exchange` and uses `stop-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
|
||||
HTX supports `stoploss_on_exchange` and uses `stop-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
|
||||
|
||||
## OKX (former OKEX)
|
||||
|
||||
|
|
|
|||
|
|
@ -162,7 +162,8 @@ Below are the values you can expect to include/use inside a typical strategy dat
|
|||
| `df['&*_std/mean']` | Standard deviation and mean values of the defined labels during training (or live tracking with `fit_live_predictions_candles`). Commonly used to understand the rarity of a prediction (use the z-score as shown in `templates/FreqaiExampleStrategy.py` and explained [here](#creating-a-dynamic-target-threshold) to evaluate how often a particular prediction was observed during training or historically with `fit_live_predictions_candles`). <br> **Datatype:** Float.
|
||||
| `df['do_predict']` | Indication of an outlier data point. The return value is integer between -2 and 2, which lets you know if the prediction is trustworthy or not. `do_predict==1` means that the prediction is trustworthy. If the Dissimilarity Index (DI, see details [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di)) of the input data point is above the threshold defined in the config, FreqAI will subtract 1 from `do_predict`, resulting in `do_predict==0`. If `use_SVM_to_remove_outliers` is active, the Support Vector Machine (SVM, see details [here](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm)) may also detect outliers in training and prediction data. In this case, the SVM will also subtract 1 from `do_predict`. If the input data point was considered an outlier by the SVM but not by the DI, or vice versa, the result will be `do_predict==0`. If both the DI and the SVM considers the input data point to be an outlier, the result will be `do_predict==-1`. As with the SVM, if `use_DBSCAN_to_remove_outliers` is active, DBSCAN (see details [here](freqai-feature-engineering.md#identifying-outliers-with-dbscan)) may also detect outliers and subtract 1 from `do_predict`. Hence, if both the SVM and DBSCAN are active and identify a datapoint that was above the DI threshold as an outlier, the result will be `do_predict==-2`. A particular case is when `do_predict == 2`, which means that the model has expired due to exceeding `expired_hours`. <br> **Datatype:** Integer between -2 and 2.
|
||||
| `df['DI_values']` | Dissimilarity Index (DI) values are proxies for the level of confidence FreqAI has in the prediction. A lower DI means the prediction is close to the training data, i.e., higher prediction confidence. See details about the DI [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di). <br> **Datatype:** Float.
|
||||
| `df['%*']` | Any dataframe column prepended with `%` in `feature_engineering_*()` is treated as a training feature. For example, you can include the RSI in the training feature set (similar to in `templates/FreqaiExampleStrategy.py`) by setting `df['%-rsi']`. See more details on how this is done [here](freqai-feature-engineering.md). <br> **Note:** Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features are easily engineered using the multiplictative functionality of, e.g., `include_shifted_candles` and `include_timeframes` as described in the [parameter table](freqai-parameter-table.md)), these features are removed from the dataframe that is returned from FreqAI to the strategy. To keep a particular type of feature for plotting purposes, you would prepend it with `%%`. <br> **Datatype:** Depends on the output of the model.
|
||||
| `df['%*']` | Any dataframe column prepended with `%` in `feature_engineering_*()` is treated as a training feature. For example, you can include the RSI in the training feature set (similar to in `templates/FreqaiExampleStrategy.py`) by setting `df['%-rsi']`. See more details on how this is done [here](freqai-feature-engineering.md). <br> **Note:** Since the number of features prepended with `%` can multiply very quickly (10s of thousands of features are easily engineered using the multiplictative functionality of, e.g., `include_shifted_candles` and `include_timeframes` as described in the [parameter table](freqai-parameter-table.md)), these features are removed from the dataframe that is returned from FreqAI to the strategy. To keep a particular type of feature for plotting purposes, you would prepend it with `%%` (see details below). <br> **Datatype:** Depends on the feature created by the user.
|
||||
| `df['%%*']` | Any dataframe column prepended with `%%` in `feature_engineering_*()` is treated as a training feature, just the same as the above `%` prepend. However, in this case, the features are returned back to the strategy for FreqUI/plot-dataframe plotting and monitoring in Dry/Live/Backtesting <br> **Datatype:** Depends on the feature created by the user. Please note that features created in `feature_engineering_expand()` will have automatic FreqAI naming schemas depending on the expansions that you configured (i.e. `include_timeframes`, `include_corr_pairlist`, `indicators_periods_candles`, `include_shifted_candles`). So if you want to plot `%%-rsi` from `feature_engineering_expand_all()`, the final naming scheme for your plotting config would be: `%%-rsi-period_10_ETH/USDT:USDT_1h` for the `rsi` feature with `period=10`, `timeframe=1h`, and `pair=ETH/USDT:USDT` (the `:USDT` is added if you are using futures pairs). It is useful to simply add `print(dataframe.columns)` in your `populate_indicators()` after `self.freqai.start()` to see the full list of available features that are returned to the strategy for plotting purposes.
|
||||
|
||||
## Setting the `startup_candle_count`
|
||||
|
||||
|
|
|
|||
|
|
@ -439,7 +439,7 @@ While this strategy is most likely too simple to provide consistent profit, it s
|
|||
??? Hint "Performance tip"
|
||||
During normal hyperopting, indicators are calculated once and supplied to each epoch, linearly increasing RAM usage as a factor of increasing cores. As this also has performance implications, there are two alternatives to reduce RAM usage
|
||||
|
||||
* Move `ema_short` and `ema_long` calculations from `populate_indicators()` to `populate_entry_trend()`. Since `populate_entry_trend()` gonna be calculated every epochs, you don't need to use `.range` functionality.
|
||||
* Move `ema_short` and `ema_long` calculations from `populate_indicators()` to `populate_entry_trend()`. Since `populate_entry_trend()` will be calculated every epoch, you don't need to use `.range` functionality.
|
||||
* hyperopt provides `--analyze-per-epoch` which will move the execution of `populate_indicators()` to the epoch process, calculating a single value per parameter per epoch instead of using the `.range` functionality. In this case, `.range` functionality will only return the actually used value.
|
||||
|
||||
These alternatives will reduce RAM usage, but increase CPU usage. However, your hyperopting run will be less likely to fail due to Out Of Memory (OOM) issues.
|
||||
|
|
@ -926,6 +926,12 @@ Once the optimized strategy has been implemented into your strategy, you should
|
|||
|
||||
To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
|
||||
|
||||
Should results not match, please double-check to make sure you transferred all conditions correctly.
|
||||
Pay special care to the stoploss, max_open_trades and trailing stoploss parameters, as these are often set in configuration files, which override changes to the strategy.
|
||||
You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss`, `max_open_trades` or `trailing_stop`).
|
||||
### Why do my backtest results not match my hyperopt results?
|
||||
Should results not match, check the following factors:
|
||||
|
||||
* You may have added parameters to hyperopt in `populate_indicators()` where they will be calculated only once **for all epochs**. If you are, for example, trying to optimise multiple SMA timeperiod values, the hyperoptable timeperiod parameter should be placed in `populate_entry_trend()` which is calculated every epoch. See [Optimizing an indicator parameter](https://www.freqtrade.io/en/stable/hyperopt/#optimizing-an-indicator-parameter).
|
||||
* If you have disabled the auto-export of hyperopt parameters into the JSON parameters file, double-check to make sure you transferred all hyperopted values into your strategy correctly.
|
||||
* Check the logs to verify what parameters are being set and what values are being used.
|
||||
* Pay special care to the stoploss, max_open_trades and trailing stoploss parameters, as these are often set in configuration files, which override changes to the strategy. Check the logs of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss`, `max_open_trades` or `trailing_stop`).
|
||||
* Verify that you do not have an unexpected parameters JSON file overriding the parameters or the default hyperopt settings in your strategy.
|
||||
* Verify that any protections that are enabled in backtesting are also enabled when hyperopting, and vice versa. When using `--space protection`, protections are auto-enabled for hyperopting.
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@ This section will highlight a few projects from members of the community.
|
|||
- [Example freqtrade strategies](https://github.com/freqtrade/freqtrade-strategies/)
|
||||
- [FrequentHippo - Grafana dashboard with dry/live runs and backtests](http://frequenthippo.ddns.net:3000/) (by hippocritical).
|
||||
- [Online pairlist generator](https://remotepairlist.com/) (by Blood4rc).
|
||||
- [Freqtrade Backtesting Project](https://bt.robot.co.network/) (by Blood4rc).
|
||||
- [Freqtrade Backtesting Project](https://strat.ninja/) (by Blood4rc).
|
||||
- [Freqtrade analysis notebook](https://github.com/froggleston/freqtrade_analysis_notebook) (by Froggleston).
|
||||
- [TUI for freqtrade](https://github.com/froggleston/freqtrade-frogtrade9000) (by Froggleston).
|
||||
- [Bot Academy](https://botacademy.ddns.net/) (by stash86) - Blog about crypto bot projects.
|
||||
|
|
|
|||
|
|
@ -42,7 +42,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
|
|||
- [X] [Binance](https://www.binance.com/)
|
||||
- [X] [Bitmart](https://bitmart.com/)
|
||||
- [X] [Gate.io](https://www.gate.io/ref/6266643)
|
||||
- [X] [Huobi](http://huobi.com/)
|
||||
- [X] [HTX](https://www.htx.com/) (Former Huobi)
|
||||
- [X] [Kraken](https://kraken.com/)
|
||||
- [X] [OKX](https://okx.com/) (Former OKEX)
|
||||
- [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
markdown==3.5.1
|
||||
markdown==3.5.2
|
||||
mkdocs==1.5.3
|
||||
mkdocs-material==9.5.3
|
||||
mkdocs-material==9.5.4
|
||||
mdx_truly_sane_lists==1.3
|
||||
pymdown-extensions==10.7
|
||||
jinja2==3.1.2
|
||||
jinja2==3.1.3
|
||||
|
|
|
|||
|
|
@ -30,7 +30,7 @@ The Order-type will be ignored if only one mode is available.
|
|||
|----------|-------------|
|
||||
| Binance | limit |
|
||||
| Binance Futures | market, limit |
|
||||
| Huobi | limit |
|
||||
| HTX (former Huobi) | limit |
|
||||
| kraken | market, limit |
|
||||
| Gate | limit |
|
||||
| Okx | limit |
|
||||
|
|
|
|||
|
|
@ -156,9 +156,9 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
|
|||
|
||||
Out of the box, freqtrade installs the following technical libraries:
|
||||
|
||||
* [ta-lib](http://mrjbq7.github.io/ta-lib/)
|
||||
* [pandas-ta](https://twopirllc.github.io/pandas-ta/)
|
||||
* [technical](https://github.com/freqtrade/technical/)
|
||||
- [ta-lib](https://ta-lib.github.io/ta-lib-python/)
|
||||
- [pandas-ta](https://twopirllc.github.io/pandas-ta/)
|
||||
- [technical](https://github.com/freqtrade/technical/)
|
||||
|
||||
Additional technical libraries can be installed as necessary, or custom indicators may be written / invented by the strategy author.
|
||||
|
||||
|
|
@ -1009,8 +1009,8 @@ This is a common pain-point, which can cause huge differences between backtestin
|
|||
|
||||
The following lists some common patterns which should be avoided to prevent frustration:
|
||||
|
||||
- don't use `shift(-1)`. This uses data from the future, which is not available.
|
||||
- don't use `.iloc[-1]` or any other absolute position in the dataframe, this will be different between dry-run and backtesting.
|
||||
- don't use `shift(-1)` or other negative values. This uses data from the future in backtesting, which is not available in dry or live modes.
|
||||
- don't use `.iloc[-1]` or any other absolute position in the dataframe within `populate_` functions, as this will be different between dry-run and backtesting. Absolute `iloc` indexing is safe to use in callbacks however - see [Strategy Callbacks](strategy-callbacks.md).
|
||||
- don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
|
||||
- don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
|
||||
|
||||
|
|
|
|||
|
|
@ -22,7 +22,7 @@ git clone https://github.com/freqtrade/freqtrade.git
|
|||
|
||||
### 2. Install ta-lib
|
||||
|
||||
Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
|
||||
Install ta-lib according to the [ta-lib documentation](https://github.com/TA-Lib/ta-lib-python#windows).
|
||||
|
||||
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), Freqtrade provides these dependencies (in the binary wheel format) for the latest 3 Python versions (3.9, 3.10 and 3.11) and for 64bit Windows.
|
||||
These Wheels are also used by CI running on windows, and are therefore tested together with freqtrade.
|
||||
|
|
|
|||
|
|
@ -219,27 +219,35 @@ class Arguments:
|
|||
)
|
||||
|
||||
# Add trade subcommand
|
||||
trade_cmd = subparsers.add_parser('trade', help='Trade module.',
|
||||
parents=[_common_parser, _strategy_parser])
|
||||
trade_cmd = subparsers.add_parser(
|
||||
'trade',
|
||||
help='Trade module.',
|
||||
parents=[_common_parser, _strategy_parser]
|
||||
)
|
||||
trade_cmd.set_defaults(func=start_trading)
|
||||
self._build_args(optionlist=ARGS_TRADE, parser=trade_cmd)
|
||||
|
||||
# add create-userdir subcommand
|
||||
create_userdir_cmd = subparsers.add_parser('create-userdir',
|
||||
help="Create user-data directory.",
|
||||
)
|
||||
create_userdir_cmd = subparsers.add_parser(
|
||||
'create-userdir',
|
||||
help="Create user-data directory.",
|
||||
)
|
||||
create_userdir_cmd.set_defaults(func=start_create_userdir)
|
||||
self._build_args(optionlist=ARGS_CREATE_USERDIR, parser=create_userdir_cmd)
|
||||
|
||||
# add new-config subcommand
|
||||
build_config_cmd = subparsers.add_parser('new-config',
|
||||
help="Create new config")
|
||||
build_config_cmd = subparsers.add_parser(
|
||||
'new-config',
|
||||
help="Create new config",
|
||||
)
|
||||
build_config_cmd.set_defaults(func=start_new_config)
|
||||
self._build_args(optionlist=ARGS_BUILD_CONFIG, parser=build_config_cmd)
|
||||
|
||||
# add new-strategy subcommand
|
||||
build_strategy_cmd = subparsers.add_parser('new-strategy',
|
||||
help="Create new strategy")
|
||||
build_strategy_cmd = subparsers.add_parser(
|
||||
'new-strategy',
|
||||
help="Create new strategy",
|
||||
)
|
||||
build_strategy_cmd.set_defaults(func=start_new_strategy)
|
||||
self._build_args(optionlist=ARGS_BUILD_STRATEGY, parser=build_strategy_cmd)
|
||||
|
||||
|
|
@ -289,8 +297,11 @@ class Arguments:
|
|||
self._build_args(optionlist=ARGS_LIST_DATA, parser=list_data_cmd)
|
||||
|
||||
# Add backtesting subcommand
|
||||
backtesting_cmd = subparsers.add_parser('backtesting', help='Backtesting module.',
|
||||
parents=[_common_parser, _strategy_parser])
|
||||
backtesting_cmd = subparsers.add_parser(
|
||||
'backtesting',
|
||||
help='Backtesting module.',
|
||||
parents=[_common_parser, _strategy_parser]
|
||||
)
|
||||
backtesting_cmd.set_defaults(func=start_backtesting)
|
||||
self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
|
||||
|
||||
|
|
@ -304,22 +315,29 @@ class Arguments:
|
|||
self._build_args(optionlist=ARGS_BACKTEST_SHOW, parser=backtesting_show_cmd)
|
||||
|
||||
# Add backtesting analysis subcommand
|
||||
analysis_cmd = subparsers.add_parser('backtesting-analysis',
|
||||
help='Backtest Analysis module.',
|
||||
parents=[_common_parser])
|
||||
analysis_cmd = subparsers.add_parser(
|
||||
'backtesting-analysis',
|
||||
help='Backtest Analysis module.',
|
||||
parents=[_common_parser]
|
||||
)
|
||||
analysis_cmd.set_defaults(func=start_analysis_entries_exits)
|
||||
self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd)
|
||||
|
||||
# Add edge subcommand
|
||||
edge_cmd = subparsers.add_parser('edge', help='Edge module.',
|
||||
parents=[_common_parser, _strategy_parser])
|
||||
edge_cmd = subparsers.add_parser(
|
||||
'edge',
|
||||
help='Edge module.',
|
||||
parents=[_common_parser, _strategy_parser]
|
||||
)
|
||||
edge_cmd.set_defaults(func=start_edge)
|
||||
self._build_args(optionlist=ARGS_EDGE, parser=edge_cmd)
|
||||
|
||||
# Add hyperopt subcommand
|
||||
hyperopt_cmd = subparsers.add_parser('hyperopt', help='Hyperopt module.',
|
||||
parents=[_common_parser, _strategy_parser],
|
||||
)
|
||||
hyperopt_cmd = subparsers.add_parser(
|
||||
'hyperopt',
|
||||
help='Hyperopt module.',
|
||||
parents=[_common_parser, _strategy_parser],
|
||||
)
|
||||
hyperopt_cmd.set_defaults(func=start_hyperopt)
|
||||
self._build_args(optionlist=ARGS_HYPEROPT, parser=hyperopt_cmd)
|
||||
|
||||
|
|
@ -447,16 +465,20 @@ class Arguments:
|
|||
self._build_args(optionlist=ARGS_PLOT_PROFIT, parser=plot_profit_cmd)
|
||||
|
||||
# Add webserver subcommand
|
||||
webserver_cmd = subparsers.add_parser('webserver', help='Webserver module.',
|
||||
parents=[_common_parser])
|
||||
webserver_cmd = subparsers.add_parser(
|
||||
'webserver',
|
||||
help='Webserver module.',
|
||||
parents=[_common_parser]
|
||||
)
|
||||
webserver_cmd.set_defaults(func=start_webserver)
|
||||
self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)
|
||||
|
||||
# Add strategy_updater subcommand
|
||||
strategy_updater_cmd = subparsers.add_parser('strategy-updater',
|
||||
help='updates outdated strategy'
|
||||
'files to the current version',
|
||||
parents=[_common_parser])
|
||||
strategy_updater_cmd = subparsers.add_parser(
|
||||
'strategy-updater',
|
||||
help='updates outdated strategy files to the current version',
|
||||
parents=[_common_parser]
|
||||
)
|
||||
strategy_updater_cmd.set_defaults(func=start_strategy_update)
|
||||
self._build_args(optionlist=ARGS_STRATEGY_UPDATER, parser=strategy_updater_cmd)
|
||||
|
||||
|
|
@ -464,8 +486,8 @@ class Arguments:
|
|||
lookahead_analayis_cmd = subparsers.add_parser(
|
||||
'lookahead-analysis',
|
||||
help="Check for potential look ahead bias.",
|
||||
parents=[_common_parser, _strategy_parser])
|
||||
|
||||
parents=[_common_parser, _strategy_parser]
|
||||
)
|
||||
lookahead_analayis_cmd.set_defaults(func=start_lookahead_analysis)
|
||||
|
||||
self._build_args(optionlist=ARGS_LOOKAHEAD_ANALYSIS,
|
||||
|
|
@ -475,8 +497,8 @@ class Arguments:
|
|||
recursive_analayis_cmd = subparsers.add_parser(
|
||||
'recursive-analysis',
|
||||
help="Check for potential recursive formula issue.",
|
||||
parents=[_common_parser, _strategy_parser])
|
||||
|
||||
parents=[_common_parser, _strategy_parser]
|
||||
)
|
||||
recursive_analayis_cmd.set_defaults(func=start_recursive_analysis)
|
||||
|
||||
self._build_args(optionlist=ARGS_RECURSIVE_ANALYSIS,
|
||||
|
|
|
|||
|
|
@ -109,7 +109,7 @@ def ask_user_config() -> Dict[str, Any]:
|
|||
"binance",
|
||||
"binanceus",
|
||||
"gate",
|
||||
"huobi",
|
||||
"htx",
|
||||
"kraken",
|
||||
"kucoin",
|
||||
"okx",
|
||||
|
|
|
|||
|
|
@ -134,10 +134,10 @@ def start_list_data(args: Dict[str, Any]) -> None:
|
|||
print(tabulate([
|
||||
(pair, timeframe, candle_type,
|
||||
start.strftime(DATETIME_PRINT_FORMAT),
|
||||
end.strftime(DATETIME_PRINT_FORMAT))
|
||||
for pair, timeframe, candle_type, start, end in sorted(
|
||||
end.strftime(DATETIME_PRINT_FORMAT), length)
|
||||
for pair, timeframe, candle_type, start, end, length in sorted(
|
||||
paircombs1,
|
||||
key=lambda x: (x[0], timeframe_to_minutes(x[1]), x[2]))
|
||||
],
|
||||
headers=("Pair", "Timeframe", "Type", 'From', 'To'),
|
||||
headers=("Pair", "Timeframe", "Type", 'From', 'To', 'Candles'),
|
||||
tablefmt='psql', stralign='right'))
|
||||
|
|
|
|||
|
|
@ -15,6 +15,7 @@ def start_test_pairlist(args: Dict[str, Any]) -> None:
|
|||
"""
|
||||
Test Pairlist configuration
|
||||
"""
|
||||
from freqtrade.persistence import FtNoDBContext
|
||||
from freqtrade.plugins.pairlistmanager import PairListManager
|
||||
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
|
||||
|
||||
|
|
@ -24,11 +25,12 @@ def start_test_pairlist(args: Dict[str, Any]) -> None:
|
|||
if not quote_currencies:
|
||||
quote_currencies = [config.get('stake_currency')]
|
||||
results = {}
|
||||
for curr in quote_currencies:
|
||||
config['stake_currency'] = curr
|
||||
pairlists = PairListManager(exchange, config)
|
||||
pairlists.refresh_pairlist()
|
||||
results[curr] = pairlists.whitelist
|
||||
with FtNoDBContext():
|
||||
for curr in quote_currencies:
|
||||
config['stake_currency'] = curr
|
||||
pairlists = PairListManager(exchange, config)
|
||||
pairlists.refresh_pairlist()
|
||||
results[curr] = pairlists.whitelist
|
||||
|
||||
for curr, pairlist in results.items():
|
||||
if not args.get('print_one_column', False) and not args.get('list_pairs_print_json', False):
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@ import logging
|
|||
import warnings
|
||||
from copy import deepcopy
|
||||
from pathlib import Path
|
||||
from typing import Any, Callable, Dict, List, Optional
|
||||
from typing import Any, Callable, Dict, List, Optional, Tuple
|
||||
|
||||
from freqtrade import constants
|
||||
from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
|
||||
|
|
@ -68,8 +68,10 @@ class Configuration:
|
|||
config: Config = load_from_files(self.args.get("config", []))
|
||||
|
||||
# Load environment variables
|
||||
env_data = enironment_vars_to_dict()
|
||||
config = deep_merge_dicts(env_data, config)
|
||||
from freqtrade.commands.arguments import NO_CONF_ALLOWED
|
||||
if self.args.get('command') not in NO_CONF_ALLOWED:
|
||||
env_data = enironment_vars_to_dict()
|
||||
config = deep_merge_dicts(env_data, config)
|
||||
|
||||
# Normalize config
|
||||
if 'internals' not in config:
|
||||
|
|
@ -233,54 +235,37 @@ class Configuration:
|
|||
except ValueError:
|
||||
pass
|
||||
|
||||
self._args_to_config(config, argname='timeframe_detail',
|
||||
logstring='Parameter --timeframe-detail detected, '
|
||||
'using {} for intra-candle backtesting ...')
|
||||
configurations = [
|
||||
('timeframe_detail',
|
||||
'Parameter --timeframe-detail detected, using {} for intra-candle backtesting ...'),
|
||||
('backtest_show_pair_list', 'Parameter --show-pair-list detected.'),
|
||||
('stake_amount',
|
||||
'Parameter --stake-amount detected, overriding stake_amount to: {} ...'),
|
||||
('dry_run_wallet',
|
||||
'Parameter --dry-run-wallet detected, overriding dry_run_wallet to: {} ...'),
|
||||
('fee', 'Parameter --fee detected, setting fee to: {} ...'),
|
||||
('timerange', 'Parameter --timerange detected: {} ...'),
|
||||
]
|
||||
|
||||
self._args_to_config(config, argname='backtest_show_pair_list',
|
||||
logstring='Parameter --show-pair-list detected.')
|
||||
|
||||
self._args_to_config(config, argname='stake_amount',
|
||||
logstring='Parameter --stake-amount detected, '
|
||||
'overriding stake_amount to: {} ...')
|
||||
self._args_to_config(config, argname='dry_run_wallet',
|
||||
logstring='Parameter --dry-run-wallet detected, '
|
||||
'overriding dry_run_wallet to: {} ...')
|
||||
self._args_to_config(config, argname='fee',
|
||||
logstring='Parameter --fee detected, '
|
||||
'setting fee to: {} ...')
|
||||
|
||||
self._args_to_config(config, argname='timerange',
|
||||
logstring='Parameter --timerange detected: {} ...')
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
self._process_datadir_options(config)
|
||||
|
||||
self._args_to_config(config, argname='strategy_list',
|
||||
logstring='Using strategy list of {} strategies', logfun=len)
|
||||
|
||||
self._args_to_config(
|
||||
config,
|
||||
argname='recursive_strategy_search',
|
||||
logstring='Recursively searching for a strategy in the strategies folder.',
|
||||
)
|
||||
|
||||
self._args_to_config(config, argname='timeframe',
|
||||
logstring='Overriding timeframe with Command line argument')
|
||||
|
||||
self._args_to_config(config, argname='export',
|
||||
logstring='Parameter --export detected: {} ...')
|
||||
|
||||
self._args_to_config(config, argname='backtest_breakdown',
|
||||
logstring='Parameter --breakdown detected ...')
|
||||
|
||||
self._args_to_config(config, argname='backtest_cache',
|
||||
logstring='Parameter --cache={} detected ...')
|
||||
|
||||
self._args_to_config(config, argname='disableparamexport',
|
||||
logstring='Parameter --disableparamexport detected: {} ...')
|
||||
|
||||
self._args_to_config(config, argname='freqai_backtest_live_models',
|
||||
logstring='Parameter --freqai-backtest-live-models detected ...')
|
||||
configurations = [
|
||||
('recursive_strategy_search',
|
||||
'Recursively searching for a strategy in the strategies folder.'),
|
||||
('timeframe', 'Overriding timeframe with Command line argument'),
|
||||
('export', 'Parameter --export detected: {} ...'),
|
||||
('backtest_breakdown', 'Parameter --breakdown detected ...'),
|
||||
('backtest_cache', 'Parameter --cache={} detected ...'),
|
||||
('disableparamexport', 'Parameter --disableparamexport detected: {} ...'),
|
||||
('freqai_backtest_live_models',
|
||||
'Parameter --freqai-backtest-live-models detected ...'),
|
||||
]
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
# Edge section:
|
||||
if 'stoploss_range' in self.args and self.args["stoploss_range"]:
|
||||
|
|
@ -291,31 +276,18 @@ class Configuration:
|
|||
logger.info('Parameter --stoplosses detected: %s ...', self.args["stoploss_range"])
|
||||
|
||||
# Hyperopt section
|
||||
self._args_to_config(config, argname='hyperopt',
|
||||
logstring='Using Hyperopt class name: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_path',
|
||||
logstring='Using additional Hyperopt lookup path: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperoptexportfilename',
|
||||
logstring='Using hyperopt file: {}')
|
||||
|
||||
self._args_to_config(config, argname='lookahead_analysis_exportfilename',
|
||||
logstring='Saving lookahead analysis results into {} ...')
|
||||
|
||||
self._args_to_config(config, argname='epochs',
|
||||
logstring='Parameter --epochs detected ... '
|
||||
'Will run Hyperopt with for {} epochs ...'
|
||||
)
|
||||
|
||||
self._args_to_config(config, argname='spaces',
|
||||
logstring='Parameter -s/--spaces detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='analyze_per_epoch',
|
||||
logstring='Parameter --analyze-per-epoch detected.')
|
||||
|
||||
self._args_to_config(config, argname='print_all',
|
||||
logstring='Parameter --print-all detected ...')
|
||||
configurations = [
|
||||
('hyperopt', 'Using Hyperopt class name: {}'),
|
||||
('hyperopt_path', 'Using additional Hyperopt lookup path: {}'),
|
||||
('hyperoptexportfilename', 'Using hyperopt file: {}'),
|
||||
('lookahead_analysis_exportfilename', 'Saving lookahead analysis results into {} ...'),
|
||||
('epochs', 'Parameter --epochs detected ... Will run Hyperopt with for {} epochs ...'),
|
||||
('spaces', 'Parameter -s/--spaces detected: {}'),
|
||||
('analyze_per_epoch', 'Parameter --analyze-per-epoch detected.'),
|
||||
('print_all', 'Parameter --print-all detected ...'),
|
||||
]
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
if 'print_colorized' in self.args and not self.args["print_colorized"]:
|
||||
logger.info('Parameter --no-color detected ...')
|
||||
|
|
@ -323,123 +295,55 @@ class Configuration:
|
|||
else:
|
||||
config.update({'print_colorized': True})
|
||||
|
||||
self._args_to_config(config, argname='print_json',
|
||||
logstring='Parameter --print-json detected ...')
|
||||
configurations = [
|
||||
('print_json', 'Parameter --print-json detected ...'),
|
||||
('export_csv', 'Parameter --export-csv detected: {}'),
|
||||
('hyperopt_jobs', 'Parameter -j/--job-workers detected: {}'),
|
||||
('hyperopt_random_state', 'Parameter --random-state detected: {}'),
|
||||
('hyperopt_min_trades', 'Parameter --min-trades detected: {}'),
|
||||
('hyperopt_loss', 'Using Hyperopt loss class name: {}'),
|
||||
('hyperopt_show_index', 'Parameter -n/--index detected: {}'),
|
||||
('hyperopt_list_best', 'Parameter --best detected: {}'),
|
||||
('hyperopt_list_profitable', 'Parameter --profitable detected: {}'),
|
||||
('hyperopt_list_min_trades', 'Parameter --min-trades detected: {}'),
|
||||
('hyperopt_list_max_trades', 'Parameter --max-trades detected: {}'),
|
||||
('hyperopt_list_min_avg_time', 'Parameter --min-avg-time detected: {}'),
|
||||
('hyperopt_list_max_avg_time', 'Parameter --max-avg-time detected: {}'),
|
||||
('hyperopt_list_min_avg_profit', 'Parameter --min-avg-profit detected: {}'),
|
||||
('hyperopt_list_max_avg_profit', 'Parameter --max-avg-profit detected: {}'),
|
||||
('hyperopt_list_min_total_profit', 'Parameter --min-total-profit detected: {}'),
|
||||
('hyperopt_list_max_total_profit', 'Parameter --max-total-profit detected: {}'),
|
||||
('hyperopt_list_min_objective', 'Parameter --min-objective detected: {}'),
|
||||
('hyperopt_list_max_objective', 'Parameter --max-objective detected: {}'),
|
||||
('hyperopt_list_no_details', 'Parameter --no-details detected: {}'),
|
||||
('hyperopt_show_no_header', 'Parameter --no-header detected: {}'),
|
||||
('hyperopt_ignore_missing_space', 'Paramter --ignore-missing-space detected: {}'),
|
||||
]
|
||||
|
||||
self._args_to_config(config, argname='export_csv',
|
||||
logstring='Parameter --export-csv detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_jobs',
|
||||
logstring='Parameter -j/--job-workers detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_random_state',
|
||||
logstring='Parameter --random-state detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_min_trades',
|
||||
logstring='Parameter --min-trades detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_loss',
|
||||
logstring='Using Hyperopt loss class name: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_show_index',
|
||||
logstring='Parameter -n/--index detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_best',
|
||||
logstring='Parameter --best detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_profitable',
|
||||
logstring='Parameter --profitable detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_min_trades',
|
||||
logstring='Parameter --min-trades detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_max_trades',
|
||||
logstring='Parameter --max-trades detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_min_avg_time',
|
||||
logstring='Parameter --min-avg-time detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_max_avg_time',
|
||||
logstring='Parameter --max-avg-time detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_min_avg_profit',
|
||||
logstring='Parameter --min-avg-profit detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_max_avg_profit',
|
||||
logstring='Parameter --max-avg-profit detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_min_total_profit',
|
||||
logstring='Parameter --min-total-profit detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_max_total_profit',
|
||||
logstring='Parameter --max-total-profit detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_min_objective',
|
||||
logstring='Parameter --min-objective detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_max_objective',
|
||||
logstring='Parameter --max-objective detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_list_no_details',
|
||||
logstring='Parameter --no-details detected: {}')
|
||||
|
||||
self._args_to_config(config, argname='hyperopt_show_no_header',
|
||||
logstring='Parameter --no-header detected: {}')
|
||||
|
||||
self._args_to_config(config, argname="hyperopt_ignore_missing_space",
|
||||
logstring="Paramter --ignore-missing-space detected: {}")
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
def _process_plot_options(self, config: Config) -> None:
|
||||
|
||||
self._args_to_config(config, argname='pairs',
|
||||
logstring='Using pairs {}')
|
||||
|
||||
self._args_to_config(config, argname='indicators1',
|
||||
logstring='Using indicators1: {}')
|
||||
|
||||
self._args_to_config(config, argname='indicators2',
|
||||
logstring='Using indicators2: {}')
|
||||
|
||||
self._args_to_config(config, argname='trade_ids',
|
||||
logstring='Filtering on trade_ids: {}')
|
||||
|
||||
self._args_to_config(config, argname='plot_limit',
|
||||
logstring='Limiting plot to: {}')
|
||||
|
||||
self._args_to_config(config, argname='plot_auto_open',
|
||||
logstring='Parameter --auto-open detected.')
|
||||
|
||||
self._args_to_config(config, argname='trade_source',
|
||||
logstring='Using trades from: {}')
|
||||
|
||||
self._args_to_config(config, argname='prepend_data',
|
||||
logstring='Prepend detected. Allowing data prepending.')
|
||||
self._args_to_config(config, argname='erase',
|
||||
logstring='Erase detected. Deleting existing data.')
|
||||
|
||||
self._args_to_config(config, argname='no_trades',
|
||||
logstring='Parameter --no-trades detected.')
|
||||
|
||||
self._args_to_config(config, argname='timeframes',
|
||||
logstring='timeframes --timeframes: {}')
|
||||
|
||||
self._args_to_config(config, argname='days',
|
||||
logstring='Detected --days: {}')
|
||||
|
||||
self._args_to_config(config, argname='include_inactive',
|
||||
logstring='Detected --include-inactive-pairs: {}')
|
||||
|
||||
self._args_to_config(config, argname='download_trades',
|
||||
logstring='Detected --dl-trades: {}')
|
||||
|
||||
self._args_to_config(config, argname='dataformat_ohlcv',
|
||||
logstring='Using "{}" to store OHLCV data.')
|
||||
|
||||
self._args_to_config(config, argname='dataformat_trades',
|
||||
logstring='Using "{}" to store trades data.')
|
||||
|
||||
self._args_to_config(config, argname='show_timerange',
|
||||
logstring='Detected --show-timerange')
|
||||
configurations = [
|
||||
('pairs', 'Using pairs {}'),
|
||||
('indicators1', 'Using indicators1: {}'),
|
||||
('indicators2', 'Using indicators2: {}'),
|
||||
('trade_ids', 'Filtering on trade_ids: {}'),
|
||||
('plot_limit', 'Limiting plot to: {}'),
|
||||
('plot_auto_open', 'Parameter --auto-open detected.'),
|
||||
('trade_source', 'Using trades from: {}'),
|
||||
('prepend_data', 'Prepend detected. Allowing data prepending.'),
|
||||
('erase', 'Erase detected. Deleting existing data.'),
|
||||
('no_trades', 'Parameter --no-trades detected.'),
|
||||
('timeframes', 'timeframes --timeframes: {}'),
|
||||
('days', 'Detected --days: {}'),
|
||||
('include_inactive', 'Detected --include-inactive-pairs: {}'),
|
||||
('download_trades', 'Detected --dl-trades: {}'),
|
||||
('dataformat_ohlcv', 'Using "{}" to store OHLCV data.'),
|
||||
('dataformat_trades', 'Using "{}" to store trades data.'),
|
||||
('show_timerange', 'Detected --show-timerange'),
|
||||
]
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
def _process_data_options(self, config: Config) -> None:
|
||||
self._args_to_config(config, argname='new_pairs_days',
|
||||
|
|
@ -453,45 +357,27 @@ class Configuration:
|
|||
logstring='Detected --candle-types: {}')
|
||||
|
||||
def _process_analyze_options(self, config: Config) -> None:
|
||||
self._args_to_config(config, argname='analysis_groups',
|
||||
logstring='Analysis reason groups: {}')
|
||||
configurations = [
|
||||
('analysis_groups', 'Analysis reason groups: {}'),
|
||||
('enter_reason_list', 'Analysis enter tag list: {}'),
|
||||
('exit_reason_list', 'Analysis exit tag list: {}'),
|
||||
('indicator_list', 'Analysis indicator list: {}'),
|
||||
('timerange', 'Filter trades by timerange: {}'),
|
||||
('analysis_rejected', 'Analyse rejected signals: {}'),
|
||||
('analysis_to_csv', 'Store analysis tables to CSV: {}'),
|
||||
('analysis_csv_path', 'Path to store analysis CSVs: {}'),
|
||||
# Lookahead analysis results
|
||||
('targeted_trade_amount', 'Targeted Trade amount: {}'),
|
||||
('minimum_trade_amount', 'Minimum Trade amount: {}'),
|
||||
('lookahead_analysis_exportfilename', 'Path to store lookahead-analysis-results: {}'),
|
||||
('startup_candle', 'Startup candle to be used on recursive analysis: {}'),
|
||||
]
|
||||
self._args_to_config_loop(config, configurations)
|
||||
|
||||
self._args_to_config(config, argname='enter_reason_list',
|
||||
logstring='Analysis enter tag list: {}')
|
||||
def _args_to_config_loop(self, config, configurations: List[Tuple[str, str]]) -> None:
|
||||
|
||||
self._args_to_config(config, argname='exit_reason_list',
|
||||
logstring='Analysis exit tag list: {}')
|
||||
|
||||
self._args_to_config(config, argname='indicator_list',
|
||||
logstring='Analysis indicator list: {}')
|
||||
|
||||
self._args_to_config(config, argname='timerange',
|
||||
logstring='Filter trades by timerange: {}')
|
||||
|
||||
self._args_to_config(config, argname='analysis_rejected',
|
||||
logstring='Analyse rejected signals: {}')
|
||||
|
||||
self._args_to_config(config, argname='analysis_to_csv',
|
||||
logstring='Store analysis tables to CSV: {}')
|
||||
|
||||
self._args_to_config(config, argname='analysis_csv_path',
|
||||
logstring='Path to store analysis CSVs: {}')
|
||||
|
||||
self._args_to_config(config, argname='analysis_csv_path',
|
||||
logstring='Path to store analysis CSVs: {}')
|
||||
|
||||
# Lookahead analysis results
|
||||
self._args_to_config(config, argname='targeted_trade_amount',
|
||||
logstring='Targeted Trade amount: {}')
|
||||
|
||||
self._args_to_config(config, argname='minimum_trade_amount',
|
||||
logstring='Minimum Trade amount: {}')
|
||||
|
||||
self._args_to_config(config, argname='lookahead_analysis_exportfilename',
|
||||
logstring='Path to store lookahead-analysis-results: {}')
|
||||
|
||||
self._args_to_config(config, argname='startup_candle',
|
||||
logstring='Startup candle to be used on recursive analysis: {}')
|
||||
for argname, logstring in configurations:
|
||||
self._args_to_config(config, argname=argname, logstring=logstring)
|
||||
|
||||
def _process_runmode(self, config: Config) -> None:
|
||||
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ from freqtrade.misc import deep_merge_dicts
|
|||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def get_var_typed(val):
|
||||
def _get_var_typed(val):
|
||||
try:
|
||||
return int(val)
|
||||
except ValueError:
|
||||
|
|
@ -24,7 +24,7 @@ def get_var_typed(val):
|
|||
return val
|
||||
|
||||
|
||||
def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str, Any]:
|
||||
def _flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str, Any]:
|
||||
"""
|
||||
Environment variables must be prefixed with FREQTRADE.
|
||||
FREQTRADE__{section}__{key}
|
||||
|
|
@ -40,7 +40,7 @@ def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str,
|
|||
logger.info(f"Loading variable '{env_var}'")
|
||||
key = env_var.replace(prefix, '')
|
||||
for k in reversed(key.split('__')):
|
||||
val = {k.lower(): get_var_typed(val)
|
||||
val = {k.lower(): _get_var_typed(val)
|
||||
if not isinstance(val, dict) and k not in no_convert else val}
|
||||
relevant_vars = deep_merge_dicts(val, relevant_vars)
|
||||
return relevant_vars
|
||||
|
|
@ -52,4 +52,4 @@ def enironment_vars_to_dict() -> Dict[str, Any]:
|
|||
Relevant variables must follow the FREQTRADE__{section}__{key} pattern
|
||||
:return: Nested dict based on available and relevant variables.
|
||||
"""
|
||||
return flat_vars_to_nested_dict(os.environ.copy(), ENV_VAR_PREFIX)
|
||||
return _flat_vars_to_nested_dict(os.environ.copy(), ENV_VAR_PREFIX)
|
||||
|
|
|
|||
|
|
@ -357,10 +357,10 @@ def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataF
|
|||
:param timeframe: Timeframe used for backtest
|
||||
:return: dataframe with open-counts per time-period in timeframe
|
||||
"""
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
timeframe_min = timeframe_to_minutes(timeframe)
|
||||
from freqtrade.exchange import timeframe_to_resample_freq
|
||||
timeframe_freq = timeframe_to_resample_freq(timeframe)
|
||||
dates = [pd.Series(pd.date_range(row[1]['open_date'], row[1]['close_date'],
|
||||
freq=f"{timeframe_min}min"))
|
||||
freq=timeframe_freq))
|
||||
for row in results[['open_date', 'close_date']].iterrows()]
|
||||
deltas = [len(x) for x in dates]
|
||||
dates = pd.Series(pd.concat(dates).values, name='date')
|
||||
|
|
@ -368,7 +368,7 @@ def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataF
|
|||
|
||||
df2 = pd.concat([dates, df2], axis=1)
|
||||
df2 = df2.set_index('date')
|
||||
df_final = df2.resample(f"{timeframe_min}min")[['pair']].count()
|
||||
df_final = df2.resample(timeframe_freq)[['pair']].count()
|
||||
df_final = df_final.rename({'pair': 'open_trades'}, axis=1)
|
||||
return df_final
|
||||
|
||||
|
|
|
|||
|
|
@ -84,7 +84,7 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
|
|||
using the previous close as price for "open", "high" "low" and "close", volume is set to 0
|
||||
|
||||
"""
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
from freqtrade.exchange import timeframe_to_resample_freq
|
||||
|
||||
ohlcv_dict = {
|
||||
'open': 'first',
|
||||
|
|
@ -93,13 +93,7 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
|
|||
'close': 'last',
|
||||
'volume': 'sum'
|
||||
}
|
||||
timeframe_minutes = timeframe_to_minutes(timeframe)
|
||||
resample_interval = f'{timeframe_minutes}min'
|
||||
if timeframe_minutes >= 43200 and timeframe_minutes < 525600:
|
||||
# Monthly candles need special treatment to stick to the 1st of the month
|
||||
resample_interval = f'{timeframe}S'
|
||||
elif timeframe_minutes > 43200:
|
||||
resample_interval = timeframe
|
||||
resample_interval = timeframe_to_resample_freq(timeframe)
|
||||
# Resample to create "NAN" values
|
||||
df = dataframe.resample(resample_interval, on='date').agg(ohlcv_dict)
|
||||
|
||||
|
|
|
|||
|
|
@ -70,14 +70,13 @@ def trades_to_ohlcv(trades: DataFrame, timeframe: str) -> DataFrame:
|
|||
:return: OHLCV Dataframe.
|
||||
:raises: ValueError if no trades are provided
|
||||
"""
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
timeframe_minutes = timeframe_to_minutes(timeframe)
|
||||
from freqtrade.exchange import timeframe_to_resample_freq
|
||||
if trades.empty:
|
||||
raise ValueError('Trade-list empty.')
|
||||
df = trades.set_index('date', drop=True)
|
||||
|
||||
df_new = df['price'].resample(f'{timeframe_minutes}min').ohlc()
|
||||
df_new['volume'] = df['amount'].resample(f'{timeframe_minutes}min').sum()
|
||||
resample_interval = timeframe_to_resample_freq(timeframe)
|
||||
df_new = df['price'].resample(resample_interval).ohlc()
|
||||
df_new['volume'] = df['amount'].resample(resample_interval).sum()
|
||||
df_new['date'] = df_new.index
|
||||
# Drop 0 volume rows
|
||||
df_new = df_new.dropna()
|
||||
|
|
|
|||
|
|
@ -94,21 +94,22 @@ class IDataHandler(ABC):
|
|||
"""
|
||||
|
||||
def ohlcv_data_min_max(self, pair: str, timeframe: str,
|
||||
candle_type: CandleType) -> Tuple[datetime, datetime]:
|
||||
candle_type: CandleType) -> Tuple[datetime, datetime, int]:
|
||||
"""
|
||||
Returns the min and max timestamp for the given pair and timeframe.
|
||||
:param pair: Pair to get min/max for
|
||||
:param timeframe: Timeframe to get min/max for
|
||||
:param candle_type: Any of the enum CandleType (must match trading mode!)
|
||||
:return: (min, max)
|
||||
:return: (min, max, len)
|
||||
"""
|
||||
data = self._ohlcv_load(pair, timeframe, None, candle_type)
|
||||
if data.empty:
|
||||
df = self._ohlcv_load(pair, timeframe, None, candle_type)
|
||||
if df.empty:
|
||||
return (
|
||||
datetime.fromtimestamp(0, tz=timezone.utc),
|
||||
datetime.fromtimestamp(0, tz=timezone.utc)
|
||||
datetime.fromtimestamp(0, tz=timezone.utc),
|
||||
0,
|
||||
)
|
||||
return data.iloc[0]['date'].to_pydatetime(), data.iloc[-1]['date'].to_pydatetime()
|
||||
return df.iloc[0]['date'].to_pydatetime(), df.iloc[-1]['date'].to_pydatetime(), len(df)
|
||||
|
||||
@abstractmethod
|
||||
def _ohlcv_load(self, pair: str, timeframe: str, timerange: Optional[TimeRange],
|
||||
|
|
|
|||
|
|
@ -61,10 +61,10 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
|
|||
"""
|
||||
if len(trades) == 0:
|
||||
raise ValueError("Trade dataframe empty.")
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
timeframe_minutes = timeframe_to_minutes(timeframe)
|
||||
from freqtrade.exchange import timeframe_to_resample_freq
|
||||
timeframe_freq = timeframe_to_resample_freq(timeframe)
|
||||
# Resample to timeframe to make sure trades match candles
|
||||
_trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_date'
|
||||
_trades_sum = trades.resample(timeframe_freq, on='close_date'
|
||||
)[['profit_abs']].sum()
|
||||
df.loc[:, col_name] = _trades_sum['profit_abs'].cumsum()
|
||||
# Set first value to 0
|
||||
|
|
|
|||
|
|
@ -17,10 +17,11 @@ from freqtrade.exchange.exchange_utils import (ROUND_DOWN, ROUND_UP, amount_to_c
|
|||
market_is_active, price_to_precision,
|
||||
timeframe_to_minutes, timeframe_to_msecs,
|
||||
timeframe_to_next_date, timeframe_to_prev_date,
|
||||
timeframe_to_seconds, validate_exchange)
|
||||
timeframe_to_resample_freq, timeframe_to_seconds,
|
||||
validate_exchange)
|
||||
from freqtrade.exchange.gate import Gate
|
||||
from freqtrade.exchange.hitbtc import Hitbtc
|
||||
from freqtrade.exchange.huobi import Huobi
|
||||
from freqtrade.exchange.htx import Htx
|
||||
from freqtrade.exchange.kraken import Kraken
|
||||
from freqtrade.exchange.kucoin import Kucoin
|
||||
from freqtrade.exchange.okx import Okx
|
||||
|
|
|
|||
|
|
@ -48,13 +48,14 @@ MAP_EXCHANGE_CHILDCLASS = {
|
|||
'binanceusdm': 'binance',
|
||||
'okex': 'okx',
|
||||
'gateio': 'gate',
|
||||
'huboi': 'htx',
|
||||
}
|
||||
|
||||
SUPPORTED_EXCHANGES = [
|
||||
'binance',
|
||||
'bitmart',
|
||||
'gate',
|
||||
'huobi',
|
||||
'htx',
|
||||
'kraken',
|
||||
'okx',
|
||||
]
|
||||
|
|
|
|||
|
|
@ -2216,13 +2216,13 @@ class Exchange:
|
|||
@retrier_async
|
||||
async def _async_fetch_trades(self, pair: str,
|
||||
since: Optional[int] = None,
|
||||
params: Optional[dict] = None) -> List[List]:
|
||||
params: Optional[dict] = None) -> Tuple[List[List], Any]:
|
||||
"""
|
||||
Asyncronously gets trade history using fetch_trades.
|
||||
Handles exchange errors, does one call to the exchange.
|
||||
:param pair: Pair to fetch trade data for
|
||||
:param since: Since as integer timestamp in milliseconds
|
||||
returns: List of dicts containing trades
|
||||
returns: List of dicts containing trades, the next iteration value (new "since" or trade_id)
|
||||
"""
|
||||
try:
|
||||
# fetch trades asynchronously
|
||||
|
|
@ -2237,7 +2237,8 @@ class Exchange:
|
|||
)
|
||||
trades = await self._api_async.fetch_trades(pair, since=since, limit=1000)
|
||||
trades = self._trades_contracts_to_amount(trades)
|
||||
return trades_dict_to_list(trades)
|
||||
pagination_value = self._get_trade_pagination_next_value(trades)
|
||||
return trades_dict_to_list(trades), pagination_value
|
||||
except ccxt.NotSupported as e:
|
||||
raise OperationalException(
|
||||
f'Exchange {self._api.name} does not support fetching historical trade data.'
|
||||
|
|
@ -2250,6 +2251,25 @@ class Exchange:
|
|||
except ccxt.BaseError as e:
|
||||
raise OperationalException(f'Could not fetch trade data. Msg: {e}') from e
|
||||
|
||||
def _valid_trade_pagination_id(self, pair: str, from_id: str) -> bool:
|
||||
"""
|
||||
Verify trade-pagination id is valid.
|
||||
Workaround for odd Kraken issue where ID is sometimes wrong.
|
||||
"""
|
||||
return True
|
||||
|
||||
def _get_trade_pagination_next_value(self, trades: List[Dict]):
|
||||
"""
|
||||
Extract pagination id for the next "from_id" value
|
||||
Applies only to fetch_trade_history by id.
|
||||
"""
|
||||
if not trades:
|
||||
return None
|
||||
if self._trades_pagination == 'id':
|
||||
return trades[-1].get('id')
|
||||
else:
|
||||
return trades[-1].get('timestamp')
|
||||
|
||||
async def _async_get_trade_history_id(self, pair: str,
|
||||
until: int,
|
||||
since: Optional[int] = None,
|
||||
|
|
@ -2265,33 +2285,35 @@ class Exchange:
|
|||
"""
|
||||
|
||||
trades: List[List] = []
|
||||
# DEFAULT_TRADES_COLUMNS: 0 -> timestamp
|
||||
# DEFAULT_TRADES_COLUMNS: 1 -> id
|
||||
has_overlap = self._ft_has.get('trades_pagination_overlap', True)
|
||||
# Skip last trade by default since its the key for the next call
|
||||
x = slice(None, -1) if has_overlap else slice(None)
|
||||
|
||||
if not from_id:
|
||||
if not from_id or not self._valid_trade_pagination_id(pair, from_id):
|
||||
# Fetch first elements using timebased method to get an ID to paginate on
|
||||
# Depending on the Exchange, this can introduce a drift at the start of the interval
|
||||
# of up to an hour.
|
||||
# e.g. Binance returns the "last 1000" candles within a 1h time interval
|
||||
# - so we will miss the first trades.
|
||||
t = await self._async_fetch_trades(pair, since=since)
|
||||
# DEFAULT_TRADES_COLUMNS: 0 -> timestamp
|
||||
# DEFAULT_TRADES_COLUMNS: 1 -> id
|
||||
from_id = t[-1][1]
|
||||
trades.extend(t[:-1])
|
||||
t, from_id = await self._async_fetch_trades(pair, since=since)
|
||||
trades.extend(t[x])
|
||||
while True:
|
||||
try:
|
||||
t = await self._async_fetch_trades(pair,
|
||||
params={self._trades_pagination_arg: from_id})
|
||||
t, from_id_next = await self._async_fetch_trades(
|
||||
pair, params={self._trades_pagination_arg: from_id})
|
||||
if t:
|
||||
# Skip last id since its the key for the next call
|
||||
trades.extend(t[:-1])
|
||||
if from_id == t[-1][1] or t[-1][0] > until:
|
||||
trades.extend(t[x])
|
||||
if from_id == from_id_next or t[-1][0] > until:
|
||||
logger.debug(f"Stopping because from_id did not change. "
|
||||
f"Reached {t[-1][0]} > {until}")
|
||||
# Reached the end of the defined-download period - add last trade as well.
|
||||
trades.extend(t[-1:])
|
||||
if has_overlap:
|
||||
trades.extend(t[-1:])
|
||||
break
|
||||
|
||||
from_id = t[-1][1]
|
||||
from_id = from_id_next
|
||||
else:
|
||||
logger.debug("Stopping as no more trades were returned.")
|
||||
break
|
||||
|
|
@ -2317,19 +2339,19 @@ class Exchange:
|
|||
# DEFAULT_TRADES_COLUMNS: 1 -> id
|
||||
while True:
|
||||
try:
|
||||
t = await self._async_fetch_trades(pair, since=since)
|
||||
t, since_next = await self._async_fetch_trades(pair, since=since)
|
||||
if t:
|
||||
# No more trades to download available at the exchange,
|
||||
# So we repeatedly get the same trade over and over again.
|
||||
if since == t[-1][0] and len(t) == 1:
|
||||
if since == since_next and len(t) == 1:
|
||||
logger.debug("Stopping because no more trades are available.")
|
||||
break
|
||||
since = t[-1][0]
|
||||
since = since_next
|
||||
trades.extend(t)
|
||||
# Reached the end of the defined-download period
|
||||
if until and t[-1][0] > until:
|
||||
if until and since_next > until:
|
||||
logger.debug(
|
||||
f"Stopping because until was reached. {t[-1][0]} > {until}")
|
||||
f"Stopping because until was reached. {since_next} > {until}")
|
||||
break
|
||||
else:
|
||||
logger.debug("Stopping as no more trades were returned.")
|
||||
|
|
|
|||
|
|
@ -118,6 +118,27 @@ def timeframe_to_msecs(timeframe: str) -> int:
|
|||
return ccxt.Exchange.parse_timeframe(timeframe) * 1000
|
||||
|
||||
|
||||
def timeframe_to_resample_freq(timeframe: str) -> str:
|
||||
"""
|
||||
Translates the timeframe interval value written in the human readable
|
||||
form ('1m', '5m', '1h', '1d', '1w', etc.) to the resample frequency
|
||||
used by pandas ('1T', '5T', '1H', '1D', '1W', etc.)
|
||||
"""
|
||||
if timeframe == '1y':
|
||||
return '1YS'
|
||||
timeframe_seconds = timeframe_to_seconds(timeframe)
|
||||
timeframe_minutes = timeframe_seconds // 60
|
||||
resample_interval = f'{timeframe_seconds}s'
|
||||
if 10000 < timeframe_minutes < 43200:
|
||||
resample_interval = '1W-MON'
|
||||
elif timeframe_minutes >= 43200 and timeframe_minutes < 525600:
|
||||
# Monthly candles need special treatment to stick to the 1st of the month
|
||||
resample_interval = f'{timeframe}S'
|
||||
elif timeframe_minutes > 43200:
|
||||
resample_interval = timeframe
|
||||
return resample_interval
|
||||
|
||||
|
||||
def timeframe_to_prev_date(timeframe: str, date: Optional[datetime] = None) -> datetime:
|
||||
"""
|
||||
Use Timeframe and determine the candle start date for this date.
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
""" Huobi exchange subclass """
|
||||
""" HTX exchange subclass """
|
||||
import logging
|
||||
from typing import Dict
|
||||
|
||||
|
|
@ -9,9 +9,9 @@ from freqtrade.exchange import Exchange
|
|||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Huobi(Exchange):
|
||||
class Htx(Exchange):
|
||||
"""
|
||||
Huobi exchange class. Contains adjustments needed for Freqtrade to work
|
||||
HTX exchange class. Contains adjustments needed for Freqtrade to work
|
||||
with this exchange.
|
||||
"""
|
||||
|
||||
|
|
@ -8,11 +8,9 @@ from pandas import DataFrame
|
|||
|
||||
from freqtrade.constants import BuySell
|
||||
from freqtrade.enums import MarginMode, TradingMode
|
||||
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
|
||||
OperationalException, TemporaryError)
|
||||
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
|
||||
from freqtrade.exchange import Exchange
|
||||
from freqtrade.exchange.common import retrier
|
||||
from freqtrade.exchange.exchange_utils import ROUND_DOWN, ROUND_UP
|
||||
from freqtrade.exchange.types import Tickers
|
||||
|
||||
|
||||
|
|
@ -24,13 +22,15 @@ class Kraken(Exchange):
|
|||
_params: Dict = {"trading_agreement": "agree"}
|
||||
_ft_has: Dict = {
|
||||
"stoploss_on_exchange": True,
|
||||
"stop_price_param": "stopPrice",
|
||||
"stop_price_prop": "stopPrice",
|
||||
"stop_price_param": "stopLossPrice",
|
||||
"stop_price_prop": "stopLossPrice",
|
||||
"stoploss_order_types": {"limit": "limit", "market": "market"},
|
||||
"order_time_in_force": ["GTC", "IOC", "PO"],
|
||||
"ohlcv_candle_limit": 720,
|
||||
"ohlcv_has_history": False,
|
||||
"trades_pagination": "id",
|
||||
"trades_pagination_arg": "since",
|
||||
"trades_pagination_overlap": False,
|
||||
"mark_ohlcv_timeframe": "4h",
|
||||
}
|
||||
|
||||
|
|
@ -90,75 +90,6 @@ class Kraken(Exchange):
|
|||
except ccxt.BaseError as e:
|
||||
raise OperationalException(e) from e
|
||||
|
||||
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
|
||||
"""
|
||||
Verify stop_loss against stoploss-order value (limit or price)
|
||||
Returns True if adjustment is necessary.
|
||||
"""
|
||||
return (order['type'] in ('stop-loss', 'stop-loss-limit') and (
|
||||
(side == "sell" and stop_loss > float(order['price'])) or
|
||||
(side == "buy" and stop_loss < float(order['price']))
|
||||
))
|
||||
|
||||
@retrier(retries=0)
|
||||
def create_stoploss(self, pair: str, amount: float, stop_price: float,
|
||||
order_types: Dict, side: BuySell, leverage: float) -> Dict:
|
||||
"""
|
||||
Creates a stoploss market order.
|
||||
Stoploss market orders is the only stoploss type supported by kraken.
|
||||
TODO: investigate if this can be combined with generic implementation
|
||||
(careful, prices are reversed)
|
||||
"""
|
||||
params = self._params.copy()
|
||||
if self.trading_mode == TradingMode.FUTURES:
|
||||
params.update({'reduceOnly': True})
|
||||
|
||||
round_mode = ROUND_DOWN if side == 'buy' else ROUND_UP
|
||||
if order_types.get('stoploss', 'market') == 'limit':
|
||||
ordertype = "stop-loss-limit"
|
||||
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
|
||||
if side == "sell":
|
||||
limit_rate = stop_price * limit_price_pct
|
||||
else:
|
||||
limit_rate = stop_price * (2 - limit_price_pct)
|
||||
params['price2'] = self.price_to_precision(pair, limit_rate, rounding_mode=round_mode)
|
||||
else:
|
||||
ordertype = "stop-loss"
|
||||
|
||||
stop_price = self.price_to_precision(pair, stop_price, rounding_mode=round_mode)
|
||||
|
||||
if self._config['dry_run']:
|
||||
dry_order = self.create_dry_run_order(
|
||||
pair, ordertype, side, amount, stop_price, leverage, stop_loss=True)
|
||||
return dry_order
|
||||
|
||||
try:
|
||||
amount = self.amount_to_precision(pair, amount)
|
||||
|
||||
order = self._api.create_order(symbol=pair, type=ordertype, side=side,
|
||||
amount=amount, price=stop_price, params=params)
|
||||
self._log_exchange_response('create_stoploss_order', order)
|
||||
logger.info('stoploss order added for %s. '
|
||||
'stop price: %s.', pair, stop_price)
|
||||
return order
|
||||
except ccxt.InsufficientFunds as e:
|
||||
raise InsufficientFundsError(
|
||||
f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
|
||||
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
|
||||
f'Message: {e}') from e
|
||||
except ccxt.InvalidOrder as e:
|
||||
raise InvalidOrderException(
|
||||
f'Could not create {ordertype} {side} order on market {pair}. '
|
||||
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
|
||||
f'Message: {e}') from e
|
||||
except ccxt.DDoSProtection as e:
|
||||
raise DDosProtection(e) from e
|
||||
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
|
||||
raise TemporaryError(
|
||||
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
|
||||
except ccxt.BaseError as e:
|
||||
raise OperationalException(e) from e
|
||||
|
||||
def _set_leverage(
|
||||
self,
|
||||
leverage: float,
|
||||
|
|
@ -227,18 +158,30 @@ class Kraken(Exchange):
|
|||
|
||||
return fees if is_short else -fees
|
||||
|
||||
def _trades_contracts_to_amount(self, trades: List) -> List:
|
||||
def _get_trade_pagination_next_value(self, trades: List[Dict]):
|
||||
"""
|
||||
Fix "last" id issue for kraken data downloads
|
||||
This whole override can probably be removed once the following
|
||||
issue is closed in ccxt: https://github.com/ccxt/ccxt/issues/15827
|
||||
Extract pagination id for the next "from_id" value
|
||||
Applies only to fetch_trade_history by id.
|
||||
"""
|
||||
super()._trades_contracts_to_amount(trades)
|
||||
if (
|
||||
len(trades) > 0
|
||||
and isinstance(trades[-1].get('info'), list)
|
||||
and len(trades[-1].get('info', [])) > 7
|
||||
):
|
||||
if len(trades) > 0:
|
||||
if (
|
||||
isinstance(trades[-1].get('info'), list)
|
||||
and len(trades[-1].get('info', [])) > 7
|
||||
):
|
||||
# Trade response's "last" value.
|
||||
return trades[-1].get('info', [])[-1]
|
||||
# Fall back to timestamp if info is somehow empty.
|
||||
return trades[-1].get('timestamp')
|
||||
return None
|
||||
|
||||
trades[-1]['id'] = trades[-1].get('info', [])[-1]
|
||||
return trades
|
||||
def _valid_trade_pagination_id(self, pair: str, from_id: str) -> bool:
|
||||
"""
|
||||
Verify trade-pagination id is valid.
|
||||
Workaround for odd Kraken issue where ID is sometimes wrong.
|
||||
"""
|
||||
# Regular id's are in timestamp format 1705443695120072285
|
||||
# If the id is smaller than 19 characters, it's not a valid timestamp.
|
||||
if len(from_id) >= 19:
|
||||
return True
|
||||
logger.debug(f"{pair} - trade-pagination id is not valid. Fallback to timestamp.")
|
||||
return False
|
||||
|
|
|
|||
|
|
@ -255,7 +255,7 @@ class FreqaiDataKitchen:
|
|||
if (1 - len(filtered_df) / len(unfiltered_df)) > 0.1 and self.live:
|
||||
worst_indicator = str(unfiltered_df.count().idxmin())
|
||||
logger.warning(
|
||||
f" {(1 - len(filtered_df)/len(unfiltered_df)) * 100:.0f} percent "
|
||||
f" {(1 - len(filtered_df) / len(unfiltered_df)) * 100:.0f} percent "
|
||||
" of training data dropped due to NaNs, model may perform inconsistent "
|
||||
f"with expectations. Verify {worst_indicator}"
|
||||
)
|
||||
|
|
@ -432,8 +432,12 @@ class FreqaiDataKitchen:
|
|||
if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
|
||||
append_df["DI_values"] = self.DI_values
|
||||
|
||||
user_cols = [col for col in dataframe_backtest.columns if col.startswith("%%")]
|
||||
cols = ["date"]
|
||||
cols.extend(user_cols)
|
||||
|
||||
dataframe_backtest.reset_index(drop=True, inplace=True)
|
||||
merged_df = pd.concat([dataframe_backtest["date"], append_df], axis=1)
|
||||
merged_df = pd.concat([dataframe_backtest[cols], append_df], axis=1)
|
||||
return merged_df
|
||||
|
||||
def append_predictions(self, append_df: DataFrame) -> None:
|
||||
|
|
@ -451,7 +455,8 @@ class FreqaiDataKitchen:
|
|||
Back fill values to before the backtesting range so that the dataframe matches size
|
||||
when it goes back to the strategy. These rows are not included in the backtest.
|
||||
"""
|
||||
to_keep = [col for col in dataframe.columns if not col.startswith("&")]
|
||||
to_keep = [col for col in dataframe.columns if
|
||||
not col.startswith("&") and not col.startswith("%%")]
|
||||
self.return_dataframe = pd.merge(dataframe[to_keep],
|
||||
self.full_df, how='left', on='date')
|
||||
self.return_dataframe[self.full_df.columns] = (
|
||||
|
|
|
|||
|
|
@ -13,7 +13,6 @@ from freqtrade.data.dataprovider import DataProvider
|
|||
from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.exchange import timeframe_to_seconds
|
||||
from freqtrade.exchange.exchange import market_is_active
|
||||
from freqtrade.freqai.data_drawer import FreqaiDataDrawer
|
||||
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
|
||||
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
|
||||
|
|
@ -33,8 +32,11 @@ def download_all_data_for_training(dp: DataProvider, config: Config) -> None:
|
|||
|
||||
if dp._exchange is None:
|
||||
raise OperationalException('No exchange object found.')
|
||||
markets = [p for p, m in dp._exchange.markets.items() if market_is_active(m)
|
||||
or config.get('include_inactive')]
|
||||
markets = [
|
||||
p for p in dp._exchange.get_markets(
|
||||
tradable_only=True, active_only=not config.get('include_inactive')
|
||||
).keys()
|
||||
]
|
||||
|
||||
all_pairs = dynamic_expand_pairlist(config, markets)
|
||||
|
||||
|
|
|
|||
|
|
@ -1424,11 +1424,11 @@ class FreqtradeBot(LoggingMixin):
|
|||
# New candle
|
||||
proposed_rate = self.exchange.get_rate(
|
||||
trade.pair, side='entry', is_short=trade.is_short, refresh=True)
|
||||
adjusted_entry_price = strategy_safe_wrapper(self.strategy.adjust_entry_price,
|
||||
default_retval=order_obj.price)(
|
||||
adjusted_entry_price = strategy_safe_wrapper(
|
||||
self.strategy.adjust_entry_price, default_retval=order_obj.safe_placement_price)(
|
||||
trade=trade, order=order_obj, pair=trade.pair,
|
||||
current_time=datetime.now(timezone.utc), proposed_rate=proposed_rate,
|
||||
current_order_rate=order_obj.safe_price, entry_tag=trade.enter_tag,
|
||||
current_order_rate=order_obj.safe_placement_price, entry_tag=trade.enter_tag,
|
||||
side=trade.trade_direction)
|
||||
|
||||
replacing = True
|
||||
|
|
@ -1436,7 +1436,7 @@ class FreqtradeBot(LoggingMixin):
|
|||
if not adjusted_entry_price:
|
||||
replacing = False
|
||||
cancel_reason = constants.CANCEL_REASON['USER_CANCEL']
|
||||
if order_obj.price != adjusted_entry_price:
|
||||
if order_obj.safe_placement_price != adjusted_entry_price:
|
||||
# cancel existing order if new price is supplied or None
|
||||
res = self.handle_cancel_enter(trade, order, order_obj, cancel_reason,
|
||||
replacing=replacing)
|
||||
|
|
|
|||
|
|
@ -33,7 +33,8 @@ from freqtrade.optimize.optimize_reports import (generate_backtest_stats, genera
|
|||
show_backtest_results,
|
||||
store_backtest_analysis_results,
|
||||
store_backtest_stats)
|
||||
from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
|
||||
from freqtrade.persistence import (LocalTrade, Order, PairLocks, Trade, disable_database_use,
|
||||
enable_database_use)
|
||||
from freqtrade.plugins.pairlistmanager import PairListManager
|
||||
from freqtrade.plugins.protectionmanager import ProtectionManager
|
||||
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
|
||||
|
|
@ -116,8 +117,9 @@ class Backtesting:
|
|||
raise OperationalException("Timeframe needs to be set in either "
|
||||
"configuration or as cli argument `--timeframe 5m`")
|
||||
self.timeframe = str(self.config.get('timeframe'))
|
||||
self.disable_database_use()
|
||||
self.timeframe_min = timeframe_to_minutes(self.timeframe)
|
||||
self.timeframe_td = timedelta(minutes=self.timeframe_min)
|
||||
self.disable_database_use()
|
||||
self.init_backtest_detail()
|
||||
self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider)
|
||||
self._validate_pairlists_for_backtesting()
|
||||
|
|
@ -177,8 +179,7 @@ class Backtesting:
|
|||
@staticmethod
|
||||
def cleanup():
|
||||
LoggingMixin.show_output = True
|
||||
PairLocks.use_db = True
|
||||
Trade.use_db = True
|
||||
enable_database_use()
|
||||
|
||||
def init_backtest_detail(self) -> None:
|
||||
# Load detail timeframe if specified
|
||||
|
|
@ -325,9 +326,7 @@ class Backtesting:
|
|||
self.futures_data = {}
|
||||
|
||||
def disable_database_use(self):
|
||||
PairLocks.use_db = False
|
||||
PairLocks.timeframe = self.timeframe
|
||||
Trade.use_db = False
|
||||
disable_database_use(self.timeframe)
|
||||
|
||||
def prepare_backtest(self, enable_protections):
|
||||
"""
|
||||
|
|
@ -1207,10 +1206,10 @@ class Backtesting:
|
|||
|
||||
# Indexes per pair, so some pairs are allowed to have a missing start.
|
||||
indexes: Dict = defaultdict(int)
|
||||
current_time = start_date + timedelta(minutes=self.timeframe_min)
|
||||
current_time = start_date + self.timeframe_td
|
||||
|
||||
self.progress.init_step(BacktestState.BACKTEST, int(
|
||||
(end_date - start_date) / timedelta(minutes=self.timeframe_min)))
|
||||
(end_date - start_date) / self.timeframe_td))
|
||||
# Loop timerange and get candle for each pair at that point in time
|
||||
while current_time <= end_date:
|
||||
open_trade_count_start = LocalTrade.bt_open_open_trade_count
|
||||
|
|
@ -1237,7 +1236,7 @@ class Backtesting:
|
|||
# Spread out into detail timeframe.
|
||||
# Should only happen when we are either in a trade for this pair
|
||||
# or when we got the signal for a new trade.
|
||||
exit_candle_end = current_detail_time + timedelta(minutes=self.timeframe_min)
|
||||
exit_candle_end = current_detail_time + self.timeframe_td
|
||||
|
||||
detail_data = self.detail_data[pair]
|
||||
detail_data = detail_data.loc[
|
||||
|
|
@ -1273,7 +1272,7 @@ class Backtesting:
|
|||
|
||||
# Move time one configured time_interval ahead.
|
||||
self.progress.increment()
|
||||
current_time += timedelta(minutes=self.timeframe_min)
|
||||
current_time += self.timeframe_td
|
||||
|
||||
self.handle_left_open(LocalTrade.bt_trades_open_pp, data=data)
|
||||
self.wallets.update()
|
||||
|
|
|
|||
|
|
@ -54,7 +54,7 @@ class BaseAnalysis:
|
|||
self.full_varHolder.from_dt = parsed_timerange.startdt
|
||||
|
||||
if parsed_timerange.stopdt is None:
|
||||
self.full_varHolder.to_dt = datetime.utcnow()
|
||||
self.full_varHolder.to_dt = datetime.now(timezone.utc)
|
||||
else:
|
||||
self.full_varHolder.to_dt = parsed_timerange.stopdt
|
||||
|
||||
|
|
|
|||
|
|
@ -4,3 +4,5 @@ from freqtrade.persistence.key_value_store import KeyStoreKeys, KeyValueStore
|
|||
from freqtrade.persistence.models import init_db
|
||||
from freqtrade.persistence.pairlock_middleware import PairLocks
|
||||
from freqtrade.persistence.trade_model import LocalTrade, Order, Trade
|
||||
from freqtrade.persistence.usedb_context import (FtNoDBContext, disable_database_use,
|
||||
enable_database_use)
|
||||
|
|
|
|||
|
|
@ -106,6 +106,11 @@ class Order(ModelBase):
|
|||
def safe_amount(self) -> float:
|
||||
return self.amount or self.ft_amount
|
||||
|
||||
@property
|
||||
def safe_placement_price(self) -> float:
|
||||
"""Price at which the order was placed"""
|
||||
return self.price or self.stop_price or self.ft_price
|
||||
|
||||
@property
|
||||
def safe_price(self) -> float:
|
||||
return self.average or self.price or self.stop_price or self.ft_price
|
||||
|
|
@ -1637,7 +1642,7 @@ class Trade(ModelBase, LocalTrade):
|
|||
Retrieves total realized profit
|
||||
"""
|
||||
if Trade.use_db:
|
||||
total_profit: float = Trade.session.execute(
|
||||
total_profit = Trade.session.execute(
|
||||
select(func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False))
|
||||
).scalar_one()
|
||||
else:
|
||||
|
|
@ -1845,4 +1850,4 @@ class Trade(ModelBase, LocalTrade):
|
|||
Order.order_filled_date >= start_date,
|
||||
Order.status == 'closed'
|
||||
)).scalar_one()
|
||||
return trading_volume
|
||||
return trading_volume or 0.0
|
||||
|
|
|
|||
33
freqtrade/persistence/usedb_context.py
Normal file
33
freqtrade/persistence/usedb_context.py
Normal file
|
|
@ -0,0 +1,33 @@
|
|||
|
||||
from freqtrade.persistence.pairlock_middleware import PairLocks
|
||||
from freqtrade.persistence.trade_model import Trade
|
||||
|
||||
|
||||
def disable_database_use(timeframe: str) -> None:
|
||||
"""
|
||||
Disable database usage for PairLocks and Trade models.
|
||||
Used for backtesting, and some other utility commands.
|
||||
"""
|
||||
PairLocks.use_db = False
|
||||
PairLocks.timeframe = timeframe
|
||||
Trade.use_db = False
|
||||
|
||||
|
||||
def enable_database_use() -> None:
|
||||
"""
|
||||
Cleanup function to restore database usage.
|
||||
"""
|
||||
PairLocks.use_db = True
|
||||
PairLocks.timeframe = ''
|
||||
Trade.use_db = True
|
||||
|
||||
|
||||
class FtNoDBContext:
|
||||
def __init__(self, timeframe: str = ''):
|
||||
self.timeframe = timeframe
|
||||
|
||||
def __enter__(self):
|
||||
disable_database_use(self.timeframe)
|
||||
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
enable_database_use()
|
||||
|
|
@ -62,16 +62,16 @@ class VolumePairList(IPairList):
|
|||
|
||||
# get timeframe in minutes and seconds
|
||||
self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
|
||||
self._tf_in_sec = self._tf_in_min * 60
|
||||
_tf_in_sec = self._tf_in_min * 60
|
||||
|
||||
# wether to use range lookback or not
|
||||
self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)
|
||||
|
||||
if self._use_range & (self._refresh_period < self._tf_in_sec):
|
||||
if self._use_range & (self._refresh_period < _tf_in_sec):
|
||||
raise OperationalException(
|
||||
f'Refresh period of {self._refresh_period} seconds is smaller than one '
|
||||
f'timeframe of {self._lookback_timeframe}. Please adjust refresh_period '
|
||||
f'to at least {self._tf_in_sec} and restart the bot.'
|
||||
f'to at least {_tf_in_sec} and restart the bot.'
|
||||
)
|
||||
|
||||
if (not self._use_range and not (
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import logging
|
||||
import secrets
|
||||
from datetime import datetime, timedelta
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from typing import Any, Dict, Union
|
||||
|
||||
import jwt
|
||||
|
|
@ -88,14 +88,14 @@ async def validate_ws_token(
|
|||
def create_token(data: dict, secret_key: str, token_type: str = "access") -> str:
|
||||
to_encode = data.copy()
|
||||
if token_type == "access":
|
||||
expire = datetime.utcnow() + timedelta(minutes=15)
|
||||
expire = datetime.now(timezone.utc) + timedelta(minutes=15)
|
||||
elif token_type == "refresh":
|
||||
expire = datetime.utcnow() + timedelta(days=30)
|
||||
expire = datetime.now(timezone.utc) + timedelta(days=30)
|
||||
else:
|
||||
raise ValueError()
|
||||
to_encode.update({
|
||||
"exp": expire,
|
||||
"iat": datetime.utcnow(),
|
||||
"iat": datetime.now(timezone.utc),
|
||||
"type": token_type,
|
||||
})
|
||||
encoded_jwt = jwt.encode(to_encode, secret_key, algorithm=ALGORITHM)
|
||||
|
|
|
|||
|
|
@ -7,6 +7,7 @@ from fastapi.exceptions import HTTPException
|
|||
from freqtrade.constants import Config
|
||||
from freqtrade.enums import CandleType
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.persistence import FtNoDBContext
|
||||
from freqtrade.rpc.api_server.api_schemas import (BackgroundTaskStatus, BgJobStarted,
|
||||
ExchangeModePayloadMixin, PairListsPayload,
|
||||
PairListsResponse, WhitelistEvaluateResponse)
|
||||
|
|
@ -57,16 +58,16 @@ def __run_pairlist(job_id: str, config_loc: Config):
|
|||
|
||||
ApiBG.jobs[job_id]['is_running'] = True
|
||||
from freqtrade.plugins.pairlistmanager import PairListManager
|
||||
|
||||
exchange = get_exchange(config_loc)
|
||||
pairlists = PairListManager(exchange, config_loc)
|
||||
pairlists.refresh_pairlist()
|
||||
ApiBG.jobs[job_id]['result'] = {
|
||||
'method': pairlists.name_list,
|
||||
'length': len(pairlists.whitelist),
|
||||
'whitelist': pairlists.whitelist
|
||||
}
|
||||
ApiBG.jobs[job_id]['status'] = 'success'
|
||||
with FtNoDBContext():
|
||||
exchange = get_exchange(config_loc)
|
||||
pairlists = PairListManager(exchange, config_loc)
|
||||
pairlists.refresh_pairlist()
|
||||
ApiBG.jobs[job_id]['result'] = {
|
||||
'method': pairlists.name_list,
|
||||
'length': len(pairlists.whitelist),
|
||||
'whitelist': pairlists.whitelist
|
||||
}
|
||||
ApiBG.jobs[job_id]['status'] = 'success'
|
||||
except (OperationalException, Exception) as e:
|
||||
logger.exception(e)
|
||||
ApiBG.jobs[job_id]['error'] = str(e)
|
||||
|
|
|
|||
|
|
@ -107,7 +107,7 @@ class ApiServer(RPCHandler):
|
|||
ApiServer._message_stream.publish(msg)
|
||||
|
||||
def handle_rpc_exception(self, request, exc):
|
||||
logger.exception(f"API Error calling: {exc}")
|
||||
logger.error(f"API Error calling: {exc}")
|
||||
return JSONResponse(
|
||||
status_code=502,
|
||||
content={'error': f"Error querying {request.url.path}: {exc.message}"}
|
||||
|
|
|
|||
|
|
@ -1346,7 +1346,7 @@ class Telegram(RPCHandler):
|
|||
output = "<b>Performance:</b>\n"
|
||||
for i, trade in enumerate(trades):
|
||||
stat_line = (
|
||||
f"{i+1}.\t <code>{trade['pair']}\t"
|
||||
f"{i + 1}.\t <code>{trade['pair']}\t"
|
||||
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
|
||||
f"({trade['profit_ratio']:.2%}) "
|
||||
f"({trade['count']})</code>\n")
|
||||
|
|
@ -1378,7 +1378,7 @@ class Telegram(RPCHandler):
|
|||
output = "<b>Entry Tag Performance:</b>\n"
|
||||
for i, trade in enumerate(trades):
|
||||
stat_line = (
|
||||
f"{i+1}.\t <code>{trade['enter_tag']}\t"
|
||||
f"{i + 1}.\t <code>{trade['enter_tag']}\t"
|
||||
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
|
||||
f"({trade['profit_ratio']:.2%}) "
|
||||
f"({trade['count']})</code>\n")
|
||||
|
|
@ -1410,7 +1410,7 @@ class Telegram(RPCHandler):
|
|||
output = "<b>Exit Reason Performance:</b>\n"
|
||||
for i, trade in enumerate(trades):
|
||||
stat_line = (
|
||||
f"{i+1}.\t <code>{trade['exit_reason']}\t"
|
||||
f"{i + 1}.\t <code>{trade['exit_reason']}\t"
|
||||
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
|
||||
f"({trade['profit_ratio']:.2%}) "
|
||||
f"({trade['count']})</code>\n")
|
||||
|
|
@ -1442,7 +1442,7 @@ class Telegram(RPCHandler):
|
|||
output = "<b>Mix Tag Performance:</b>\n"
|
||||
for i, trade in enumerate(trades):
|
||||
stat_line = (
|
||||
f"{i+1}.\t <code>{trade['mix_tag']}\t"
|
||||
f"{i + 1}.\t <code>{trade['mix_tag']}\t"
|
||||
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
|
||||
f"({trade['profit_ratio']:.2%}) "
|
||||
f"({trade['count']})</code>\n")
|
||||
|
|
|
|||
|
|
@ -1004,7 +1004,7 @@ class IStrategy(ABC, HyperStrategyMixin):
|
|||
:param is_short: Indicating existing trade direction.
|
||||
:return: (enter, exit) A bool-tuple with enter / exit values.
|
||||
"""
|
||||
latest, latest_date = self.get_latest_candle(pair, timeframe, dataframe)
|
||||
latest, _latest_date = self.get_latest_candle(pair, timeframe, dataframe)
|
||||
if latest is None:
|
||||
return False, False, None
|
||||
|
||||
|
|
@ -1388,7 +1388,8 @@ class IStrategy(ABC, HyperStrategyMixin):
|
|||
"""
|
||||
|
||||
logger.debug(f"Populating enter signals for pair {metadata.get('pair')}.")
|
||||
|
||||
# Initialize column to work around Pandas bug #56503.
|
||||
dataframe.loc[:, 'enter_tag'] = ''
|
||||
df = self.populate_entry_trend(dataframe, metadata)
|
||||
if 'enter_long' not in df.columns:
|
||||
df = df.rename({'buy': 'enter_long', 'buy_tag': 'enter_tag'}, axis='columns')
|
||||
|
|
@ -1404,6 +1405,8 @@ class IStrategy(ABC, HyperStrategyMixin):
|
|||
currently traded pair
|
||||
:return: DataFrame with exit column
|
||||
"""
|
||||
# Initialize column to work around Pandas bug #56503.
|
||||
dataframe.loc[:, 'exit_tag'] = ''
|
||||
logger.debug(f"Populating exit signals for pair {metadata.get('pair')}.")
|
||||
df = self.populate_exit_trend(dataframe, metadata)
|
||||
if 'exit_long' not in df.columns:
|
||||
|
|
|
|||
|
|
@ -7,21 +7,21 @@
|
|||
-r docs/requirements-docs.txt
|
||||
|
||||
coveralls==3.3.1
|
||||
ruff==0.1.11
|
||||
ruff==0.1.14
|
||||
mypy==1.8.0
|
||||
pre-commit==3.6.0
|
||||
pytest==7.4.4
|
||||
pytest-asyncio==0.21.1
|
||||
pytest-cov==4.1.0
|
||||
pytest-mock==3.12.0
|
||||
pytest-random-order==1.1.0
|
||||
pytest-random-order==1.1.1
|
||||
pytest-xdist==3.5.0
|
||||
isort==5.13.2
|
||||
# For datetime mocking
|
||||
time-machine==2.13.0
|
||||
|
||||
# Convert jupyter notebooks to markdown documents
|
||||
nbconvert==7.14.0
|
||||
nbconvert==7.14.2
|
||||
|
||||
# mypy types
|
||||
types-cachetools==5.3.0.7
|
||||
|
|
|
|||
|
|
@ -2,10 +2,10 @@
|
|||
-r requirements-freqai.txt
|
||||
|
||||
# Required for freqai-rl
|
||||
torch==2.1.2
|
||||
torch==2.1.2; python_version < '3.12'
|
||||
#until these branches will be released we can use this
|
||||
gymnasium==0.29.1
|
||||
stable_baselines3==2.2.1
|
||||
sb3_contrib>=2.0.0a9
|
||||
gymnasium==0.29.1; python_version < '3.12'
|
||||
stable_baselines3==2.2.1; python_version < '3.12'
|
||||
sb3_contrib>=2.0.0a9; python_version < '3.12'
|
||||
# Progress bar for stable-baselines3 and sb3-contrib
|
||||
tqdm==4.66.1
|
||||
|
|
|
|||
|
|
@ -3,9 +3,9 @@
|
|||
-r requirements-plot.txt
|
||||
|
||||
# Required for freqai
|
||||
scikit-learn==1.3.2
|
||||
scikit-learn==1.4.0
|
||||
joblib==1.3.2
|
||||
catboost==1.2.2; 'arm' not in platform_machine
|
||||
catboost==1.2.2; 'arm' not in platform_machine and python_version < '3.12'
|
||||
lightgbm==4.2.0
|
||||
xgboost==2.0.3
|
||||
tensorboard==2.15.1
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@
|
|||
-r requirements.txt
|
||||
|
||||
# Required for hyperopt
|
||||
scipy==1.11.4
|
||||
scikit-learn==1.3.2
|
||||
scipy==1.12.0
|
||||
scikit-learn==1.4.0
|
||||
ft-scikit-optimize==0.9.2
|
||||
filelock==3.13.1
|
||||
|
|
|
|||
|
|
@ -2,10 +2,10 @@ numpy==1.26.3
|
|||
pandas==2.1.4
|
||||
pandas-ta==0.3.14b
|
||||
|
||||
ccxt==4.2.9
|
||||
ccxt==4.2.21
|
||||
cryptography==41.0.7
|
||||
aiohttp==3.9.1
|
||||
SQLAlchemy==2.0.23
|
||||
SQLAlchemy==2.0.25
|
||||
python-telegram-bot==20.7
|
||||
# can't be hard-pinned due to telegram-bot pinning httpx with ~
|
||||
httpx>=0.24.1
|
||||
|
|
@ -13,16 +13,16 @@ arrow==1.3.0
|
|||
cachetools==5.3.2
|
||||
requests==2.31.0
|
||||
urllib3==2.1.0
|
||||
jsonschema==4.20.0
|
||||
jsonschema==4.21.1
|
||||
TA-Lib==0.4.28
|
||||
technical==1.4.2
|
||||
tabulate==0.9.0
|
||||
pycoingecko==3.1.0
|
||||
jinja2==3.1.2
|
||||
jinja2==3.1.3
|
||||
tables==3.9.1
|
||||
joblib==1.3.2
|
||||
rich==13.7.0
|
||||
pyarrow==14.0.2; platform_machine != 'armv7l'
|
||||
pyarrow==15.0.0; platform_machine != 'armv7l'
|
||||
|
||||
# find first, C search in arrays
|
||||
py_find_1st==1.1.6
|
||||
|
|
@ -30,18 +30,18 @@ py_find_1st==1.1.6
|
|||
# Load ticker files 30% faster
|
||||
python-rapidjson==1.14
|
||||
# Properly format api responses
|
||||
orjson==3.9.10
|
||||
orjson==3.9.12
|
||||
|
||||
# Notify systemd
|
||||
sdnotify==0.3.2
|
||||
|
||||
# API Server
|
||||
fastapi==0.108.0
|
||||
fastapi==0.109.0
|
||||
pydantic==2.5.3
|
||||
uvicorn==0.25.0
|
||||
uvicorn==0.26.0
|
||||
pyjwt==2.8.0
|
||||
aiofiles==23.2.1
|
||||
psutil==5.9.7
|
||||
psutil==5.9.8
|
||||
|
||||
# Support for colorized terminal output
|
||||
colorama==0.4.6
|
||||
|
|
|
|||
2
setup.py
2
setup.py
|
|
@ -70,7 +70,7 @@ setup(
|
|||
],
|
||||
install_requires=[
|
||||
# from requirements.txt
|
||||
'ccxt>=4.0.0',
|
||||
'ccxt>=4.2.15',
|
||||
'SQLAlchemy>=2.0.6',
|
||||
'python-telegram-bot>=20.1',
|
||||
'arrow>=1.0.0',
|
||||
|
|
|
|||
|
|
@ -1445,12 +1445,13 @@ def test_start_list_data(testdatadir, capsys):
|
|||
start_list_data(pargs)
|
||||
captured = capsys.readouterr()
|
||||
assert "Found 2 pair / timeframe combinations." in captured.out
|
||||
assert ("\n| Pair | Timeframe | Type | From | To |\n"
|
||||
in captured.out)
|
||||
assert (
|
||||
"\n| Pair | Timeframe | Type "
|
||||
"| From | To | Candles |\n") in captured.out
|
||||
assert "UNITTEST/BTC" not in captured.out
|
||||
assert (
|
||||
"\n| XRP/ETH | 1m | spot | 2019-10-11 00:00:00 | 2019-10-13 11:19:00 |\n"
|
||||
in captured.out)
|
||||
"\n| XRP/ETH | 1m | spot | "
|
||||
"2019-10-11 00:00:00 | 2019-10-13 11:19:00 | 2469 |\n") in captured.out
|
||||
|
||||
|
||||
@pytest.mark.usefixtures("init_persistence")
|
||||
|
|
@ -1508,7 +1509,7 @@ def test_backtesting_show(mocker, testdatadir, capsys):
|
|||
pargs['config'] = None
|
||||
start_backtesting_show(pargs)
|
||||
assert sbr.call_count == 1
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert "Pairs for Strategy" in out
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ import json
|
|||
import logging
|
||||
import re
|
||||
from copy import deepcopy
|
||||
from datetime import timedelta
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
from unittest.mock import MagicMock, Mock, PropertyMock
|
||||
|
|
@ -18,13 +18,11 @@ from freqtrade.commands import Arguments
|
|||
from freqtrade.data.converter import ohlcv_to_dataframe, trades_list_to_df
|
||||
from freqtrade.edge import PairInfo
|
||||
from freqtrade.enums import CandleType, MarginMode, RunMode, SignalDirection, TradingMode
|
||||
from freqtrade.exchange import Exchange
|
||||
from freqtrade.exchange.exchange import timeframe_to_minutes
|
||||
from freqtrade.exchange import Exchange, timeframe_to_minutes, timeframe_to_seconds
|
||||
from freqtrade.freqtradebot import FreqtradeBot
|
||||
from freqtrade.persistence import LocalTrade, Order, Trade, init_db
|
||||
from freqtrade.resolvers import ExchangeResolver
|
||||
from freqtrade.util import dt_ts
|
||||
from freqtrade.util.datetime_helpers import dt_now
|
||||
from freqtrade.util import dt_now, dt_ts
|
||||
from freqtrade.worker import Worker
|
||||
from tests.conftest_trades import (leverage_trade, mock_trade_1, mock_trade_2, mock_trade_3,
|
||||
mock_trade_4, mock_trade_5, mock_trade_6, short_trade)
|
||||
|
|
@ -107,17 +105,62 @@ def get_args(args):
|
|||
return Arguments(args).get_parsed_arg()
|
||||
|
||||
|
||||
def generate_trades_history(n_rows, start_date: Optional[datetime] = None, days=5):
|
||||
np.random.seed(42)
|
||||
if not start_date:
|
||||
start_date = datetime(2020, 1, 1, tzinfo=timezone.utc)
|
||||
|
||||
# Generate random data
|
||||
end_date = start_date + timedelta(days=days)
|
||||
_start_timestamp = start_date.timestamp()
|
||||
_end_timestamp = pd.to_datetime(end_date).timestamp()
|
||||
|
||||
random_timestamps_in_seconds = np.random.uniform(_start_timestamp, _end_timestamp, n_rows)
|
||||
timestamp = pd.to_datetime(random_timestamps_in_seconds, unit='s')
|
||||
|
||||
id = [
|
||||
f'a{np.random.randint(1e6, 1e7 - 1)}cd{np.random.randint(100, 999)}'
|
||||
for _ in range(n_rows)
|
||||
]
|
||||
|
||||
side = np.random.choice(['buy', 'sell'], n_rows)
|
||||
|
||||
# Initial price and subsequent changes
|
||||
initial_price = 0.019626
|
||||
price_changes = np.random.normal(0, initial_price * 0.05, n_rows)
|
||||
price = np.cumsum(np.concatenate(([initial_price], price_changes)))[:n_rows]
|
||||
|
||||
amount = np.random.uniform(0.011, 20, n_rows)
|
||||
cost = price * amount
|
||||
|
||||
# Create DataFrame
|
||||
df = pd.DataFrame({'timestamp': timestamp, 'id': id, 'type': None, 'side': side,
|
||||
'price': price, 'amount': amount, 'cost': cost})
|
||||
df['date'] = pd.to_datetime(df['timestamp'], unit='ms', utc=True)
|
||||
df = df.sort_values('timestamp').reset_index(drop=True)
|
||||
assert list(df.columns) == constants.DEFAULT_TRADES_COLUMNS + ['date']
|
||||
return df
|
||||
|
||||
|
||||
def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
|
||||
np.random.seed(42)
|
||||
|
||||
base = np.random.normal(20, 2, size=size)
|
||||
if timeframe == '1M':
|
||||
if timeframe == '1y':
|
||||
date = pd.date_range(start, periods=size, freq='1YS', tz='UTC')
|
||||
elif timeframe == '1M':
|
||||
date = pd.date_range(start, periods=size, freq='1MS', tz='UTC')
|
||||
elif timeframe == '1w':
|
||||
elif timeframe == '3M':
|
||||
date = pd.date_range(start, periods=size, freq='3MS', tz='UTC')
|
||||
elif timeframe == '1w' or timeframe == '7d':
|
||||
date = pd.date_range(start, periods=size, freq='1W-MON', tz='UTC')
|
||||
else:
|
||||
tf_mins = timeframe_to_minutes(timeframe)
|
||||
date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
|
||||
if tf_mins >= 1:
|
||||
date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
|
||||
else:
|
||||
tf_secs = timeframe_to_seconds(timeframe)
|
||||
date = pd.date_range(start, periods=size, freq=f'{tf_secs}s', tz='UTC')
|
||||
df = pd.DataFrame({
|
||||
'date': date,
|
||||
'open': base,
|
||||
|
|
@ -2386,14 +2429,7 @@ def trades_history_df(trades_history):
|
|||
|
||||
@pytest.fixture(scope="function")
|
||||
def fetch_trades_result():
|
||||
return [{'info': {'a': 126181329,
|
||||
'p': '0.01962700',
|
||||
'q': '0.04000000',
|
||||
'f': 138604155,
|
||||
'l': 138604155,
|
||||
'T': 1565798399463,
|
||||
'm': False,
|
||||
'M': True},
|
||||
return [{'info': ['0.01962700', '0.04000000', '1565798399.4631551', 'b', 'm', '', '126181329'],
|
||||
'timestamp': 1565798399463,
|
||||
'datetime': '2019-08-14T15:59:59.463Z',
|
||||
'symbol': 'ETH/BTC',
|
||||
|
|
@ -2406,14 +2442,7 @@ def fetch_trades_result():
|
|||
'amount': 0.04,
|
||||
'cost': 0.00078508,
|
||||
'fee': None},
|
||||
{'info': {'a': 126181330,
|
||||
'p': '0.01962700',
|
||||
'q': '0.24400000',
|
||||
'f': 138604156,
|
||||
'l': 138604156,
|
||||
'T': 1565798399629,
|
||||
'm': False,
|
||||
'M': True},
|
||||
{'info': ['0.01962700', '0.24400000', '1565798399.6291551', 'b', 'm', '', '126181330'],
|
||||
'timestamp': 1565798399629,
|
||||
'datetime': '2019-08-14T15:59:59.629Z',
|
||||
'symbol': 'ETH/BTC',
|
||||
|
|
@ -2426,14 +2455,7 @@ def fetch_trades_result():
|
|||
'amount': 0.244,
|
||||
'cost': 0.004788987999999999,
|
||||
'fee': None},
|
||||
{'info': {'a': 126181331,
|
||||
'p': '0.01962600',
|
||||
'q': '0.01100000',
|
||||
'f': 138604157,
|
||||
'l': 138604157,
|
||||
'T': 1565798399752,
|
||||
'm': True,
|
||||
'M': True},
|
||||
{'info': ['0.01962600', '0.01100000', '1565798399.7521551', 's', 'm', '', '126181331'],
|
||||
'timestamp': 1565798399752,
|
||||
'datetime': '2019-08-14T15:59:59.752Z',
|
||||
'symbol': 'ETH/BTC',
|
||||
|
|
@ -2446,14 +2468,7 @@ def fetch_trades_result():
|
|||
'amount': 0.011,
|
||||
'cost': 0.00021588599999999999,
|
||||
'fee': None},
|
||||
{'info': {'a': 126181332,
|
||||
'p': '0.01962600',
|
||||
'q': '0.01100000',
|
||||
'f': 138604158,
|
||||
'l': 138604158,
|
||||
'T': 1565798399862,
|
||||
'm': True,
|
||||
'M': True},
|
||||
{'info': ['0.01962600', '0.01100000', '1565798399.8621551', 's', 'm', '', '126181332'],
|
||||
'timestamp': 1565798399862,
|
||||
'datetime': '2019-08-14T15:59:59.862Z',
|
||||
'symbol': 'ETH/BTC',
|
||||
|
|
@ -2466,14 +2481,8 @@ def fetch_trades_result():
|
|||
'amount': 0.011,
|
||||
'cost': 0.00021588599999999999,
|
||||
'fee': None},
|
||||
{'info': {'a': 126181333,
|
||||
'p': '0.01952600',
|
||||
'q': '0.01200000',
|
||||
'f': 138604158,
|
||||
'l': 138604158,
|
||||
'T': 1565798399872,
|
||||
'm': True,
|
||||
'M': True},
|
||||
{'info': ['0.01952600', '0.01200000', '1565798399.8721551', 's', 'm', '', '126181333',
|
||||
1565798399872512133],
|
||||
'timestamp': 1565798399872,
|
||||
'datetime': '2019-08-14T15:59:59.872Z',
|
||||
'symbol': 'ETH/BTC',
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ from freqtrade.data.history import (get_timerange, load_data, load_pair_history,
|
|||
validate_backtest_data)
|
||||
from freqtrade.data.history.idatahandler import IDataHandler
|
||||
from freqtrade.enums import CandleType
|
||||
from tests.conftest import generate_test_data, log_has, log_has_re
|
||||
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
|
||||
from tests.conftest import generate_test_data, generate_trades_history, log_has, log_has_re
|
||||
from tests.data.test_history import _clean_test_file
|
||||
|
||||
|
||||
|
|
@ -51,6 +52,49 @@ def test_trades_to_ohlcv(trades_history_df, caplog):
|
|||
assert 'close' in df.columns
|
||||
assert df.iloc[0, :]['high'] == 0.019627
|
||||
assert df.iloc[0, :]['low'] == 0.019626
|
||||
assert df.iloc[0, :]['date'] == pd.Timestamp('2019-08-14 15:59:00+0000')
|
||||
|
||||
df_1h = trades_to_ohlcv(trades_history_df, '1h')
|
||||
assert len(df_1h) == 1
|
||||
assert df_1h.iloc[0, :]['high'] == 0.019627
|
||||
assert df_1h.iloc[0, :]['low'] == 0.019626
|
||||
assert df_1h.iloc[0, :]['date'] == pd.Timestamp('2019-08-14 15:00:00+0000')
|
||||
|
||||
df_1s = trades_to_ohlcv(trades_history_df, '1s')
|
||||
assert len(df_1s) == 2
|
||||
assert df_1s.iloc[0, :]['high'] == 0.019627
|
||||
assert df_1s.iloc[0, :]['low'] == 0.019627
|
||||
assert df_1s.iloc[0, :]['date'] == pd.Timestamp('2019-08-14 15:59:49+0000')
|
||||
assert df_1s.iloc[-1, :]['date'] == pd.Timestamp('2019-08-14 15:59:59+0000')
|
||||
|
||||
|
||||
@pytest.mark.parametrize('timeframe,rows,days,candles,start,end,weekday', [
|
||||
('1s', 20_000, 5, 19522, '2020-01-01 00:00:05', '2020-01-05 23:59:27', None),
|
||||
('1m', 20_000, 5, 6745, '2020-01-01 00:00:00', '2020-01-05 23:59:00', None),
|
||||
('5m', 20_000, 5, 1440, '2020-01-01 00:00:00', '2020-01-05 23:55:00', None),
|
||||
('15m', 20_000, 5, 480, '2020-01-01 00:00:00', '2020-01-05 23:45:00', None),
|
||||
('1h', 20_000, 5, 120, '2020-01-01 00:00:00', '2020-01-05 23:00:00', None),
|
||||
('2h', 20_000, 5, 60, '2020-01-01 00:00:00', '2020-01-05 22:00:00', None),
|
||||
('4h', 20_000, 5, 30, '2020-01-01 00:00:00', '2020-01-05 20:00:00', None),
|
||||
('8h', 20_000, 5, 15, '2020-01-01 00:00:00', '2020-01-05 16:00:00', None),
|
||||
('12h', 20_000, 5, 10, '2020-01-01 00:00:00', '2020-01-05 12:00:00', None),
|
||||
('1d', 20_000, 5, 5, '2020-01-01 00:00:00', '2020-01-05 00:00:00', 'Sunday'),
|
||||
('7d', 20_000, 37, 6, '2020-01-06 00:00:00', '2020-02-10 00:00:00', 'Monday'),
|
||||
('1w', 20_000, 37, 6, '2020-01-06 00:00:00', '2020-02-10 00:00:00', 'Monday'),
|
||||
('1M', 20_000, 74, 3, '2020-01-01 00:00:00', '2020-03-01 00:00:00', None),
|
||||
('3M', 20_000, 100, 2, '2020-01-01 00:00:00', '2020-04-01 00:00:00', None),
|
||||
('1y', 20_000, 1000, 3, '2020-01-01 00:00:00', '2022-01-01 00:00:00', None),
|
||||
])
|
||||
def test_trades_to_ohlcv_multi(timeframe, rows, days, candles, start, end, weekday):
|
||||
trades_history = generate_trades_history(n_rows=rows, days=days)
|
||||
df = trades_to_ohlcv(trades_history, timeframe)
|
||||
assert not df.empty
|
||||
assert len(df) == candles
|
||||
assert df.iloc[0, :]['date'] == pd.Timestamp(f'{start}+0000')
|
||||
assert df.iloc[-1, :]['date'] == pd.Timestamp(f'{end}+0000')
|
||||
if weekday:
|
||||
# Weekday is only relevant for daily and weekly candles.
|
||||
assert df.iloc[-1, :]['date'].day_name() == weekday
|
||||
|
||||
|
||||
def test_ohlcv_fill_up_missing_data(testdatadir, caplog):
|
||||
|
|
@ -132,6 +176,45 @@ def test_ohlcv_fill_up_missing_data2(caplog):
|
|||
f"{len(data)} - after: {len(data2)}.*", caplog)
|
||||
|
||||
|
||||
@pytest.mark.parametrize('timeframe', [
|
||||
'1s', '1m', '5m', '15m', '1h', '2h', '4h', '8h', '12h', '1d', '7d', '1w', '1M', '3M', '1y'
|
||||
])
|
||||
def test_ohlcv_to_dataframe_multi(timeframe):
|
||||
data = generate_test_data(timeframe, 180)
|
||||
assert len(data) == 180
|
||||
df = ohlcv_to_dataframe(data, timeframe, 'UNITTEST/USDT')
|
||||
assert len(df) == len(data) - 1
|
||||
df1 = ohlcv_to_dataframe(data, timeframe, 'UNITTEST/USDT', drop_incomplete=False)
|
||||
assert len(df1) == len(data)
|
||||
assert data.equals(df1)
|
||||
|
||||
data1 = data.copy()
|
||||
if timeframe in ('1M', '3M', '1y'):
|
||||
data1.loc[:, 'date'] = data1.loc[:, 'date'] + pd.to_timedelta('1w')
|
||||
else:
|
||||
# Shift by half a timeframe
|
||||
data1.loc[:, 'date'] = data1.loc[:, 'date'] + (pd.to_timedelta(timeframe) / 2)
|
||||
df2 = ohlcv_to_dataframe(data1, timeframe, 'UNITTEST/USDT')
|
||||
|
||||
assert len(df2) == len(data) - 1
|
||||
tfs = timeframe_to_seconds(timeframe)
|
||||
tfm = timeframe_to_minutes(timeframe)
|
||||
if 1 <= tfm < 10000:
|
||||
# minute based resampling does not work on timeframes >= 1 week
|
||||
ohlcv_dict = {
|
||||
'open': 'first',
|
||||
'high': 'max',
|
||||
'low': 'min',
|
||||
'close': 'last',
|
||||
'volume': 'sum'
|
||||
}
|
||||
dfs = data1.resample(f"{tfs}s", on='date').agg(ohlcv_dict).reset_index(drop=False)
|
||||
dfm = data1.resample(f"{tfm}min", on='date').agg(ohlcv_dict).reset_index(drop=False)
|
||||
|
||||
assert dfs.equals(dfm)
|
||||
assert dfs.equals(df1)
|
||||
|
||||
|
||||
def test_ohlcv_to_dataframe_1M():
|
||||
|
||||
# Monthly ticks from 2019-09-01 to 2023-07-01
|
||||
|
|
|
|||
|
|
@ -148,19 +148,25 @@ def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
|
|||
def test_datahandler_ohlcv_data_min_max(testdatadir):
|
||||
dh = JsonDataHandler(testdatadir)
|
||||
min_max = dh.ohlcv_data_min_max('UNITTEST/BTC', '5m', 'spot')
|
||||
assert len(min_max) == 2
|
||||
assert len(min_max) == 3
|
||||
|
||||
# Empty pair
|
||||
min_max = dh.ohlcv_data_min_max('UNITTEST/BTC', '8m', 'spot')
|
||||
assert len(min_max) == 2
|
||||
assert len(min_max) == 3
|
||||
assert min_max[0] == datetime.fromtimestamp(0, tz=timezone.utc)
|
||||
assert min_max[0] == min_max[1]
|
||||
# Empty pair2
|
||||
min_max = dh.ohlcv_data_min_max('NOPAIR/XXX', '4m', 'spot')
|
||||
assert len(min_max) == 2
|
||||
min_max = dh.ohlcv_data_min_max('NOPAIR/XXX', '41m', 'spot')
|
||||
assert len(min_max) == 3
|
||||
assert min_max[0] == datetime.fromtimestamp(0, tz=timezone.utc)
|
||||
assert min_max[0] == min_max[1]
|
||||
|
||||
# Existing pair ...
|
||||
min_max = dh.ohlcv_data_min_max('UNITTEST/BTC', '1m', 'spot')
|
||||
assert len(min_max) == 3
|
||||
assert min_max[0] == datetime(2017, 11, 4, 23, 2, tzinfo=timezone.utc)
|
||||
assert min_max[1] == datetime(2017, 11, 14, 22, 59, tzinfo=timezone.utc)
|
||||
|
||||
|
||||
def test_datahandler__check_empty_df(testdatadir, caplog):
|
||||
dh = JsonDataHandler(testdatadir)
|
||||
|
|
|
|||
|
|
@ -194,7 +194,7 @@ def test_get_producer_df(default_conf):
|
|||
assert la == empty_la
|
||||
|
||||
# non existent timeframe, empty dataframe
|
||||
datframe, la = dataprovider.get_producer_df(pair, timeframe='1h')
|
||||
_dataframe, la = dataprovider.get_producer_df(pair, timeframe='1h')
|
||||
assert dataframe.empty
|
||||
assert la == empty_la
|
||||
|
||||
|
|
|
|||
|
|
@ -2844,10 +2844,17 @@ async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
|
|||
exchange._api_async.fetch_trades = get_mock_coro(fetch_trades_result)
|
||||
|
||||
pair = 'ETH/BTC'
|
||||
res = await exchange._async_fetch_trades(pair, since=None, params=None)
|
||||
res, pagid = await exchange._async_fetch_trades(pair, since=None, params=None)
|
||||
assert isinstance(res, list)
|
||||
assert isinstance(res[0], list)
|
||||
assert isinstance(res[1], list)
|
||||
if exchange._trades_pagination == 'id':
|
||||
if exchange_name == 'kraken':
|
||||
assert pagid == 1565798399872512133
|
||||
else:
|
||||
assert pagid == '126181333'
|
||||
else:
|
||||
assert pagid == 1565798399872
|
||||
|
||||
assert exchange._api_async.fetch_trades.call_count == 1
|
||||
assert exchange._api_async.fetch_trades.call_args[0][0] == pair
|
||||
|
|
@ -2856,11 +2863,20 @@ async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
|
|||
assert log_has_re(f"Fetching trades for pair {pair}, since .*", caplog)
|
||||
caplog.clear()
|
||||
exchange._api_async.fetch_trades.reset_mock()
|
||||
res = await exchange._async_fetch_trades(pair, since=None, params={'from': '123'})
|
||||
res, pagid = await exchange._async_fetch_trades(pair, since=None, params={'from': '123'})
|
||||
assert exchange._api_async.fetch_trades.call_count == 1
|
||||
assert exchange._api_async.fetch_trades.call_args[0][0] == pair
|
||||
assert exchange._api_async.fetch_trades.call_args[1]['limit'] == 1000
|
||||
assert exchange._api_async.fetch_trades.call_args[1]['params'] == {'from': '123'}
|
||||
|
||||
if exchange._trades_pagination == 'id':
|
||||
if exchange_name == 'kraken':
|
||||
assert pagid == 1565798399872512133
|
||||
else:
|
||||
assert pagid == '126181333'
|
||||
else:
|
||||
assert pagid == 1565798399872
|
||||
|
||||
assert log_has_re(f"Fetching trades for pair {pair}, params: .*", caplog)
|
||||
exchange.close()
|
||||
|
||||
|
|
@ -2915,8 +2931,9 @@ async def test__async_fetch_trades_contract_size(default_conf, mocker, caplog, e
|
|||
)
|
||||
|
||||
pair = 'ETH/USDT:USDT'
|
||||
res = await exchange._async_fetch_trades(pair, since=None, params=None)
|
||||
res, pagid = await exchange._async_fetch_trades(pair, since=None, params=None)
|
||||
assert res[0][5] == 300
|
||||
assert pagid is not None
|
||||
exchange.close()
|
||||
|
||||
|
||||
|
|
@ -2926,13 +2943,17 @@ async def test__async_get_trade_history_id(default_conf, mocker, exchange_name,
|
|||
fetch_trades_result):
|
||||
|
||||
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
|
||||
if exchange._trades_pagination != 'id':
|
||||
exchange.close()
|
||||
pytest.skip("Exchange does not support pagination by trade id")
|
||||
pagination_arg = exchange._trades_pagination_arg
|
||||
|
||||
async def mock_get_trade_hist(pair, *args, **kwargs):
|
||||
if 'since' in kwargs:
|
||||
# Return first 3
|
||||
return fetch_trades_result[:-2]
|
||||
elif kwargs.get('params', {}).get(pagination_arg) == fetch_trades_result[-3]['id']:
|
||||
elif kwargs.get('params', {}).get(pagination_arg) in (
|
||||
fetch_trades_result[-3]['id'], 1565798399752):
|
||||
# Return 2
|
||||
return fetch_trades_result[-3:-1]
|
||||
else:
|
||||
|
|
@ -2948,7 +2969,8 @@ async def test__async_get_trade_history_id(default_conf, mocker, exchange_name,
|
|||
assert isinstance(ret, tuple)
|
||||
assert ret[0] == pair
|
||||
assert isinstance(ret[1], list)
|
||||
assert len(ret[1]) == len(fetch_trades_result)
|
||||
if exchange_name != 'kraken':
|
||||
assert len(ret[1]) == len(fetch_trades_result)
|
||||
assert exchange._api_async.fetch_trades.call_count == 3
|
||||
fetch_trades_cal = exchange._api_async.fetch_trades.call_args_list
|
||||
# first call (using since, not fromId)
|
||||
|
|
@ -2961,6 +2983,21 @@ async def test__async_get_trade_history_id(default_conf, mocker, exchange_name,
|
|||
assert exchange._ft_has['trades_pagination_arg'] in fetch_trades_cal[1][1]['params']
|
||||
|
||||
|
||||
@pytest.mark.parametrize('trade_id, expected', [
|
||||
('1234', True),
|
||||
('170544369512007228', True),
|
||||
('1705443695120072285', True),
|
||||
('170544369512007228555', True),
|
||||
])
|
||||
@pytest.mark.parametrize("exchange_name", EXCHANGES)
|
||||
def test__valid_trade_pagination_id(mocker, default_conf_usdt, exchange_name, trade_id, expected):
|
||||
if exchange_name == 'kraken':
|
||||
pytest.skip("Kraken has a different pagination id format, and an explicit test.")
|
||||
exchange = get_patched_exchange(mocker, default_conf_usdt, id=exchange_name)
|
||||
|
||||
assert exchange._valid_trade_pagination_id('XRP/USDT', trade_id) == expected
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("exchange_name", EXCHANGES)
|
||||
async def test__async_get_trade_history_time(default_conf, mocker, caplog, exchange_name,
|
||||
|
|
@ -2976,6 +3013,9 @@ async def test__async_get_trade_history_time(default_conf, mocker, caplog, excha
|
|||
|
||||
caplog.set_level(logging.DEBUG)
|
||||
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
|
||||
if exchange._trades_pagination != 'time':
|
||||
exchange.close()
|
||||
pytest.skip("Exchange does not support pagination by timestamp")
|
||||
# Monkey-patch async function
|
||||
exchange._api_async.fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
|
||||
pair = 'ETH/BTC'
|
||||
|
|
@ -3008,9 +3048,9 @@ async def test__async_get_trade_history_time_empty(default_conf, mocker, caplog,
|
|||
|
||||
async def mock_get_trade_hist(pair, *args, **kwargs):
|
||||
if kwargs['since'] == trades_history[0][0]:
|
||||
return trades_history[:-1]
|
||||
return trades_history[:-1], trades_history[:-1][-1][0]
|
||||
else:
|
||||
return []
|
||||
return [], None
|
||||
|
||||
caplog.set_level(logging.DEBUG)
|
||||
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
|
||||
|
|
@ -5312,3 +5352,4 @@ def test_price_to_precision_with_default_conf(default_conf, mocker):
|
|||
patched_ex = get_patched_exchange(mocker, conf)
|
||||
prec_price = patched_ex.price_to_precision("XRP/USDT", 1.0000000101)
|
||||
assert prec_price == 1.00000001
|
||||
assert prec_price == 1.00000001
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ from freqtrade.exceptions import OperationalException
|
|||
from freqtrade.exchange import (amount_to_contract_precision, amount_to_precision,
|
||||
date_minus_candles, price_to_precision, timeframe_to_minutes,
|
||||
timeframe_to_msecs, timeframe_to_next_date, timeframe_to_prev_date,
|
||||
timeframe_to_seconds)
|
||||
timeframe_to_resample_freq, timeframe_to_seconds)
|
||||
from freqtrade.exchange.check_exchange import check_exchange
|
||||
from tests.conftest import log_has_re
|
||||
|
||||
|
|
@ -124,6 +124,21 @@ def test_timeframe_to_msecs():
|
|||
assert timeframe_to_msecs("1d") == 86400000
|
||||
|
||||
|
||||
@pytest.mark.parametrize("timeframe,expected", [
|
||||
("1s", '1s'),
|
||||
("15s", '15s'),
|
||||
("5m", '300s'),
|
||||
("10m", '600s'),
|
||||
("1h", '3600s'),
|
||||
("1d", '86400s'),
|
||||
("1w", '1W-MON'),
|
||||
("1M", '1MS'),
|
||||
("1y", '1YS'),
|
||||
])
|
||||
def test_timeframe_to_resample_freq(timeframe, expected):
|
||||
assert timeframe_to_resample_freq(timeframe) == expected
|
||||
|
||||
|
||||
def test_timeframe_to_prev_date():
|
||||
# 2019-08-12 13:22:08
|
||||
date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ from tests.exchange.test_exchange import ccxt_exceptionhandlers
|
|||
(0.99, 220 * 0.99, "sell"),
|
||||
(0.98, 220 * 0.98, "sell"),
|
||||
])
|
||||
def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected, side):
|
||||
def test_create_stoploss_order_htx(default_conf, mocker, limitratio, expected, side):
|
||||
api_mock = MagicMock()
|
||||
order_id = f'test_prod_buy_{randint(0, 10 ** 6)}'
|
||||
order_type = 'stop-limit'
|
||||
|
|
@ -29,7 +29,7 @@ def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected,
|
|||
mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
|
||||
mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
|
||||
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'htx')
|
||||
|
||||
with pytest.raises(InvalidOrderException):
|
||||
order = exchange.create_stoploss(pair='ETH/BTC', amount=1, stop_price=190,
|
||||
|
|
@ -58,7 +58,7 @@ def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected,
|
|||
# test exception handling
|
||||
with pytest.raises(DependencyException):
|
||||
api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'htx')
|
||||
exchange.create_stoploss(pair='ETH/BTC', amount=1, stop_price=220,
|
||||
order_types={}, side=side, leverage=1.0)
|
||||
|
||||
|
|
@ -69,20 +69,20 @@ def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected,
|
|||
exchange.create_stoploss(pair='ETH/BTC', amount=1, stop_price=220,
|
||||
order_types={}, side=side, leverage=1.0)
|
||||
|
||||
ccxt_exceptionhandlers(mocker, default_conf, api_mock, "huobi",
|
||||
ccxt_exceptionhandlers(mocker, default_conf, api_mock, "htx",
|
||||
"create_stoploss", "create_order", retries=1,
|
||||
pair='ETH/BTC', amount=1, stop_price=220, order_types={},
|
||||
side=side, leverage=1.0)
|
||||
|
||||
|
||||
def test_create_stoploss_order_dry_run_huobi(default_conf, mocker):
|
||||
def test_create_stoploss_order_dry_run_htx(default_conf, mocker):
|
||||
api_mock = MagicMock()
|
||||
order_type = 'stop-limit'
|
||||
default_conf['dry_run'] = True
|
||||
mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
|
||||
mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
|
||||
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'htx')
|
||||
|
||||
with pytest.raises(InvalidOrderException):
|
||||
order = exchange.create_stoploss(pair='ETH/BTC', amount=1, stop_price=190,
|
||||
|
|
@ -103,8 +103,8 @@ def test_create_stoploss_order_dry_run_huobi(default_conf, mocker):
|
|||
assert order['amount'] == 1
|
||||
|
||||
|
||||
def test_stoploss_adjust_huobi(mocker, default_conf):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id='huobi')
|
||||
def test_stoploss_adjust_htx(mocker, default_conf):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id='htx')
|
||||
order = {
|
||||
'type': 'stop',
|
||||
'price': 1500,
|
||||
|
|
@ -183,19 +183,17 @@ def test_create_stoploss_order_kraken(default_conf, mocker, ordertype, side, adj
|
|||
assert 'info' in order
|
||||
assert order['id'] == order_id
|
||||
assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
|
||||
if ordertype == 'limit':
|
||||
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_LIMIT_ORDERTYPE
|
||||
assert api_mock.create_order.call_args_list[0][1]['params'] == {
|
||||
'trading_agreement': 'agree',
|
||||
'price2': adjustedprice
|
||||
}
|
||||
else:
|
||||
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
|
||||
assert api_mock.create_order.call_args_list[0][1]['params'] == {
|
||||
'trading_agreement': 'agree'}
|
||||
assert api_mock.create_order.call_args_list[0][1]['type'] == ordertype
|
||||
assert api_mock.create_order.call_args_list[0][1]['params'] == {
|
||||
'trading_agreement': 'agree',
|
||||
'stopLossPrice': 220
|
||||
}
|
||||
assert api_mock.create_order.call_args_list[0][1]['side'] == side
|
||||
assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
|
||||
assert api_mock.create_order.call_args_list[0][1]['price'] == 220
|
||||
if ordertype == 'limit':
|
||||
assert api_mock.create_order.call_args_list[0][1]['price'] == adjustedprice
|
||||
else:
|
||||
assert api_mock.create_order.call_args_list[0][1]['price'] is None
|
||||
|
||||
# test exception handling
|
||||
with pytest.raises(DependencyException):
|
||||
|
|
@ -253,7 +251,7 @@ def test_create_stoploss_order_dry_run_kraken(default_conf, mocker, side):
|
|||
assert 'info' in order
|
||||
assert 'type' in order
|
||||
|
||||
assert order['type'] == STOPLOSS_ORDERTYPE
|
||||
assert order['type'] == 'market'
|
||||
assert order['price'] == 220
|
||||
assert order['amount'] == 1
|
||||
|
||||
|
|
@ -265,11 +263,22 @@ def test_create_stoploss_order_dry_run_kraken(default_conf, mocker, side):
|
|||
def test_stoploss_adjust_kraken(mocker, default_conf, sl1, sl2, sl3, side):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id='kraken')
|
||||
order = {
|
||||
'type': STOPLOSS_ORDERTYPE,
|
||||
'price': 1500,
|
||||
'type': 'market',
|
||||
'stopLossPrice': 1500,
|
||||
}
|
||||
assert exchange.stoploss_adjust(sl1, order, side=side)
|
||||
assert not exchange.stoploss_adjust(sl2, order, side=side)
|
||||
# Test with invalid order case ...
|
||||
order['type'] = 'stop_loss_limit'
|
||||
assert not exchange.stoploss_adjust(sl3, order, side=side)
|
||||
# diff. order type ...
|
||||
order['type'] = 'limit'
|
||||
assert exchange.stoploss_adjust(sl3, order, side=side)
|
||||
|
||||
|
||||
@pytest.mark.parametrize('trade_id, expected', [
|
||||
('1234', False),
|
||||
('170544369512007228', False),
|
||||
('1705443695120072285', True),
|
||||
('170544369512007228555', True),
|
||||
])
|
||||
def test__valid_trade_pagination_id_kraken(mocker, default_conf_usdt, trade_id, expected):
|
||||
exchange = get_patched_exchange(mocker, default_conf_usdt, id='kraken')
|
||||
assert exchange._valid_trade_pagination_id('XRP/USDT', trade_id) == expected
|
||||
|
|
|
|||
|
|
@ -247,7 +247,7 @@ EXCHANGES = {
|
|||
'timeframe': '1h',
|
||||
'orderbook_max_entries': 50,
|
||||
},
|
||||
'huobi': {
|
||||
'htx': {
|
||||
'pair': 'ETH/BTC',
|
||||
'stake_currency': 'BTC',
|
||||
'hasQuoteVolume': True,
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import platform
|
||||
import sys
|
||||
from copy import deepcopy
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict
|
||||
|
|
@ -15,6 +16,10 @@ from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
|
|||
from tests.conftest import get_patched_exchange
|
||||
|
||||
|
||||
def is_py12() -> bool:
|
||||
return sys.version_info >= (3, 12)
|
||||
|
||||
|
||||
def is_mac() -> bool:
|
||||
machine = platform.system()
|
||||
return "Darwin" in machine
|
||||
|
|
@ -31,7 +36,7 @@ def patch_torch_initlogs(mocker) -> None:
|
|||
module_name = 'torch'
|
||||
mocked_module = types.ModuleType(module_name)
|
||||
sys.modules[module_name] = mocked_module
|
||||
else:
|
||||
elif not is_py12():
|
||||
mocker.patch("torch._logging._init_logs")
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -76,7 +76,7 @@ def test_filter_features(mocker, freqai_conf):
|
|||
freqai, unfiltered_dataframe = make_unfiltered_dataframe(mocker, freqai_conf)
|
||||
freqai.dk.find_features(unfiltered_dataframe)
|
||||
|
||||
filtered_df, labels = freqai.dk.filter_features(
|
||||
filtered_df, _labels = freqai.dk.filter_features(
|
||||
unfiltered_dataframe,
|
||||
freqai.dk.training_features_list,
|
||||
freqai.dk.label_list,
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
import logging
|
||||
import platform
|
||||
import shutil
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
|
|
@ -16,24 +15,24 @@ from freqtrade.optimize.backtesting import Backtesting
|
|||
from freqtrade.persistence import Trade
|
||||
from freqtrade.plugins.pairlistmanager import PairListManager
|
||||
from tests.conftest import EXMS, create_mock_trades, get_patched_exchange, log_has_re
|
||||
from tests.freqai.conftest import (get_patched_freqai_strategy, is_mac, make_rl_config,
|
||||
from tests.freqai.conftest import (get_patched_freqai_strategy, is_mac, is_py12, make_rl_config,
|
||||
mock_pytorch_mlp_model_training_parameters)
|
||||
|
||||
|
||||
def is_py12() -> bool:
|
||||
return sys.version_info >= (3, 12)
|
||||
|
||||
|
||||
def is_arm() -> bool:
|
||||
machine = platform.machine()
|
||||
return "arm" in machine or "aarch64" in machine
|
||||
|
||||
|
||||
def can_run_model(model: str) -> None:
|
||||
is_pytorch_model = 'Reinforcement' in model or 'PyTorch' in model
|
||||
|
||||
if is_py12() and ("Catboost" in model or is_pytorch_model):
|
||||
pytest.skip("Model not supported on python 3.12 yet.")
|
||||
|
||||
if is_arm() and "Catboost" in model:
|
||||
pytest.skip("CatBoost is not supported on ARM.")
|
||||
|
||||
is_pytorch_model = 'Reinforcement' in model or 'PyTorch' in model
|
||||
if is_pytorch_model and is_mac() and not is_arm():
|
||||
pytest.skip("Reinforcement learning / PyTorch module not available on intel based Mac OS.")
|
||||
|
||||
|
|
|
|||
|
|
@ -734,7 +734,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
|
|||
'min_rate': [0.10370188, 0.10300000000000001],
|
||||
'max_rate': [0.10501, 0.1038888],
|
||||
'is_open': [False, False],
|
||||
'enter_tag': [None, None],
|
||||
'enter_tag': ['', ''],
|
||||
"leverage": [1.0, 1.0],
|
||||
"is_short": [False, False],
|
||||
'open_timestamp': [1517251200000, 1517283000000],
|
||||
|
|
|
|||
|
|
@ -72,7 +72,7 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
|
|||
'min_rate': [0.10370188, 0.10300000000000001],
|
||||
'max_rate': [0.10481985, 0.1038888],
|
||||
'is_open': [False, False],
|
||||
'enter_tag': [None, None],
|
||||
'enter_tag': ['', ''],
|
||||
'leverage': [1.0, 1.0],
|
||||
'is_short': [False, False],
|
||||
'open_timestamp': [1517251200000, 1517283000000],
|
||||
|
|
|
|||
|
|
@ -254,7 +254,7 @@ def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
|
|||
'is_best': True
|
||||
}
|
||||
)
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert all(x in out
|
||||
for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC (1.00%)", "00:20:00"])
|
||||
|
||||
|
|
@ -333,7 +333,7 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
||||
# Should be called for historical candle data
|
||||
assert dumper.call_count == 1
|
||||
|
|
@ -577,7 +577,7 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
result_str = (
|
||||
'{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
|
||||
':{},"stoploss":null,"trailing_stop":null,"max_open_trades":null}'
|
||||
|
|
@ -624,7 +624,7 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501
|
||||
# Should be called for historical candle data
|
||||
assert dumper.call_count == 1
|
||||
|
|
@ -666,7 +666,7 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert '{"minimal_roi":{},"stoploss":null}' in out
|
||||
|
||||
assert dumper.call_count == 1
|
||||
|
|
@ -704,7 +704,7 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
||||
assert dumper.call_count == 1
|
||||
assert dumper2.call_count == 1
|
||||
|
|
@ -777,7 +777,7 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
||||
assert dumper.called
|
||||
assert dumper.call_count == 1
|
||||
|
|
@ -819,7 +819,7 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
|
|||
|
||||
parallel.assert_called_once()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
||||
assert dumper.called
|
||||
assert dumper.call_count == 1
|
||||
|
|
@ -1051,7 +1051,7 @@ def test_max_open_trades_dump(mocker, hyperopt_conf, tmp_path, fee, capsys) -> N
|
|||
|
||||
hyperopt.start()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
|
||||
assert 'max_open_trades = -1' in out
|
||||
assert 'max_open_trades = inf' not in out
|
||||
|
|
@ -1070,7 +1070,7 @@ def test_max_open_trades_dump(mocker, hyperopt_conf, tmp_path, fee, capsys) -> N
|
|||
|
||||
hyperopt.start()
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
|
||||
assert '"max_open_trades":-1' in out
|
||||
|
||||
|
|
|
|||
|
|
@ -143,8 +143,8 @@ def test_lookahead_helper_text_table_lookahead_analysis_instances(lookahead_conf
|
|||
|
||||
instance = LookaheadAnalysis(lookahead_conf, strategy_obj)
|
||||
instance.current_analysis = analysis
|
||||
table, headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
_table, _headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
|
||||
# check row contents for a try that has too few signals
|
||||
assert data[0][0] == 'strategy_test_v3_with_lookahead_bias.py'
|
||||
|
|
@ -158,14 +158,14 @@ def test_lookahead_helper_text_table_lookahead_analysis_instances(lookahead_conf
|
|||
analysis.false_exit_signals = 10
|
||||
instance = LookaheadAnalysis(lookahead_conf, strategy_obj)
|
||||
instance.current_analysis = analysis
|
||||
table, headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
_table, _headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
assert data[0][2].__contains__("error")
|
||||
|
||||
# edit it into not showing an error
|
||||
instance.failed_bias_check = False
|
||||
table, headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
_table, _headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
assert data[0][0] == 'strategy_test_v3_with_lookahead_bias.py'
|
||||
assert data[0][1] == 'strategy_test_v3_with_lookahead_bias'
|
||||
assert data[0][2] # True
|
||||
|
|
@ -176,8 +176,8 @@ def test_lookahead_helper_text_table_lookahead_analysis_instances(lookahead_conf
|
|||
|
||||
analysis.false_indicators.append('falseIndicator1')
|
||||
analysis.false_indicators.append('falseIndicator2')
|
||||
table, headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
_table, _headers, data = (LookaheadAnalysisSubFunctions.
|
||||
text_table_lookahead_analysis_instances(lookahead_conf, [instance]))
|
||||
|
||||
assert data[0][6] == 'falseIndicator1, falseIndicator2'
|
||||
|
||||
|
|
@ -185,7 +185,7 @@ def test_lookahead_helper_text_table_lookahead_analysis_instances(lookahead_conf
|
|||
assert len(data) == 1
|
||||
|
||||
# check amount of multiple rows
|
||||
table, headers, data = (LookaheadAnalysisSubFunctions.text_table_lookahead_analysis_instances(
|
||||
_table, _headers, data = (LookaheadAnalysisSubFunctions.text_table_lookahead_analysis_instances(
|
||||
lookahead_conf, [instance, instance, instance]))
|
||||
assert len(data) == 3
|
||||
|
||||
|
|
|
|||
|
|
@ -513,7 +513,7 @@ def test_show_sorted_pairlist(testdatadir, default_conf, capsys):
|
|||
|
||||
show_sorted_pairlist(default_conf, bt_data)
|
||||
|
||||
out, err = capsys.readouterr()
|
||||
out, _err = capsys.readouterr()
|
||||
assert 'Pairs for Strategy StrategyTestV3: \n[' in out
|
||||
assert 'TOTAL' not in out
|
||||
assert '"ETH/BTC", // ' in out
|
||||
|
|
|
|||
|
|
@ -107,8 +107,8 @@ def test_recursive_helper_text_table_recursive_analysis_instances(recursive_conf
|
|||
|
||||
instance = RecursiveAnalysis(recursive_conf, strategy_obj)
|
||||
instance.dict_recursive = dict_diff
|
||||
table, headers, data = (RecursiveAnalysisSubFunctions.
|
||||
text_table_recursive_analysis_instances([instance]))
|
||||
_table, _headers, data = (RecursiveAnalysisSubFunctions.
|
||||
text_table_recursive_analysis_instances([instance]))
|
||||
|
||||
# check row contents for a try that has too few signals
|
||||
assert data[0][0] == 'rsi'
|
||||
|
|
@ -119,8 +119,8 @@ def test_recursive_helper_text_table_recursive_analysis_instances(recursive_conf
|
|||
dict_diff = dict()
|
||||
instance = RecursiveAnalysis(recursive_conf, strategy_obj)
|
||||
instance.dict_recursive = dict_diff
|
||||
table, headers, data = (RecursiveAnalysisSubFunctions.
|
||||
text_table_recursive_analysis_instances([instance]))
|
||||
_table, _headers, data = (RecursiveAnalysisSubFunctions.
|
||||
text_table_recursive_analysis_instances([instance]))
|
||||
assert len(data) == 0
|
||||
|
||||
|
||||
|
|
|
|||
24
tests/persistence/test_db_context.py
Normal file
24
tests/persistence/test_db_context.py
Normal file
|
|
@ -0,0 +1,24 @@
|
|||
import pytest
|
||||
|
||||
from freqtrade.persistence import FtNoDBContext, PairLocks, Trade
|
||||
|
||||
|
||||
@pytest.mark.parametrize('timeframe', ['', '5m', '1d'])
|
||||
def test_FtNoDBContext(timeframe):
|
||||
PairLocks.timeframe = ''
|
||||
assert Trade.use_db is True
|
||||
assert PairLocks.use_db is True
|
||||
assert PairLocks.timeframe == ''
|
||||
|
||||
with FtNoDBContext(timeframe):
|
||||
assert Trade.use_db is False
|
||||
assert PairLocks.use_db is False
|
||||
assert PairLocks.timeframe == timeframe
|
||||
|
||||
with FtNoDBContext():
|
||||
assert Trade.use_db is False
|
||||
assert PairLocks.use_db is False
|
||||
assert PairLocks.timeframe == ''
|
||||
|
||||
assert Trade.use_db is True
|
||||
assert PairLocks.use_db is True
|
||||
|
|
@ -108,7 +108,7 @@ def test_fetch_pairlist_timeout_keep_last_pairlist(mocker, rpl_config, caplog):
|
|||
|
||||
remote_pairlist._last_pairlist = ["BTC/USDT", "ETH/USDT", "LTC/USDT"]
|
||||
|
||||
pairs, time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
pairs, _time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
assert log_has(f"Was not able to fetch pairlist from: {remote_pairlist._pairlist_url}", caplog)
|
||||
assert log_has("Keeping last fetched pairlist", caplog)
|
||||
assert pairs == ["BTC/USDT", "ETH/USDT", "LTC/USDT"]
|
||||
|
|
@ -281,7 +281,7 @@ def test_remote_pairlist_blacklist(mocker, rpl_config, caplog, markets, tickers)
|
|||
remote_pairlist = RemotePairList(exchange, pairlistmanager, rpl_config,
|
||||
rpl_config["pairlists"][1], 1)
|
||||
|
||||
pairs, time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
pairs, _time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
|
||||
assert pairs == ["XRP/USDT"]
|
||||
|
||||
|
|
@ -334,7 +334,7 @@ def test_remote_pairlist_whitelist(mocker, rpl_config, processing_mode, markets,
|
|||
remote_pairlist = RemotePairList(exchange, pairlistmanager, rpl_config,
|
||||
rpl_config["pairlists"][1], 1)
|
||||
|
||||
pairs, time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
pairs, _time_elapsed = remote_pairlist.fetch_pairlist()
|
||||
|
||||
assert pairs == ["XRP/USDT"]
|
||||
|
||||
|
|
|
|||
|
|
@ -112,7 +112,7 @@ def assert_response(response, expected_code=200, needs_cors=True):
|
|||
|
||||
|
||||
def test_api_not_found(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/invalid_url")
|
||||
assert_response(rc, 404)
|
||||
|
|
@ -120,7 +120,7 @@ def test_api_not_found(botclient):
|
|||
|
||||
|
||||
def test_api_ui_fallback(botclient, mocker):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, "/favicon.ico")
|
||||
assert rc.status_code == 200
|
||||
|
|
@ -150,7 +150,7 @@ def test_api_ui_fallback(botclient, mocker):
|
|||
|
||||
|
||||
def test_api_ui_version(botclient, mocker):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
mocker.patch('freqtrade.commands.deploy_commands.read_ui_version', return_value='0.1.2')
|
||||
rc = client_get(client, "/ui_version")
|
||||
|
|
@ -230,7 +230,7 @@ def test_api_unauthorized(botclient):
|
|||
|
||||
|
||||
def test_api_token_login(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
rc = client.post(f"{BASE_URI}/token/login",
|
||||
data=None,
|
||||
headers={'Authorization': _basic_auth_str('WRONG_USER', 'WRONG_PASS'),
|
||||
|
|
@ -249,7 +249,7 @@ def test_api_token_login(botclient):
|
|||
|
||||
|
||||
def test_api_token_refresh(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
rc = client_post(client, f"{BASE_URI}/token/login")
|
||||
assert_response(rc)
|
||||
rc = client.post(f"{BASE_URI}/token/refresh",
|
||||
|
|
@ -541,7 +541,7 @@ def test_api_count(botclient, mocker, ticker, fee, markets, is_short):
|
|||
|
||||
|
||||
def test_api_locks(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/locks")
|
||||
assert_response(rc)
|
||||
|
|
@ -821,7 +821,7 @@ def test_api_trade_reload_trade(botclient, mocker, fee, markets, ticker, is_shor
|
|||
|
||||
|
||||
def test_api_logs(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
rc = client_get(client, f"{BASE_URI}/logs")
|
||||
assert_response(rc)
|
||||
assert len(rc.json()) == 2
|
||||
|
|
@ -1228,7 +1228,7 @@ def test_api_status(botclient, mocker, ticker, fee, markets, is_short,
|
|||
|
||||
|
||||
def test_api_version(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/version")
|
||||
assert_response(rc)
|
||||
|
|
@ -1236,7 +1236,7 @@ def test_api_version(botclient):
|
|||
|
||||
|
||||
def test_api_blacklist(botclient, mocker):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/blacklist")
|
||||
assert_response(rc)
|
||||
|
|
@ -1303,7 +1303,7 @@ def test_api_blacklist(botclient, mocker):
|
|||
|
||||
|
||||
def test_api_whitelist(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/whitelist")
|
||||
assert_response(rc)
|
||||
|
|
@ -1558,7 +1558,7 @@ def test_api_pair_candles(botclient, ohlcv_history):
|
|||
|
||||
|
||||
def test_api_pair_history(botclient, mocker):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
timeframe = '5m'
|
||||
lfm = mocker.patch('freqtrade.strategy.interface.IStrategy.load_freqAI_model')
|
||||
# No pair
|
||||
|
|
@ -1603,9 +1603,9 @@ def test_api_pair_history(botclient, mocker):
|
|||
assert 'data' in result
|
||||
data = result['data']
|
||||
assert len(data) == 289
|
||||
# analyed DF has 28 columns
|
||||
assert len(result['columns']) == 28
|
||||
assert len(data[0]) == 28
|
||||
# analyed DF has 30 columns
|
||||
assert len(result['columns']) == 30
|
||||
assert len(data[0]) == 30
|
||||
date_col_idx = [idx for idx, c in enumerate(result['columns']) if c == 'date'][0]
|
||||
rsi_col_idx = [idx for idx, c in enumerate(result['columns']) if c == 'rsi'][0]
|
||||
|
||||
|
|
@ -1698,7 +1698,7 @@ def test_api_strategies(botclient, tmp_path):
|
|||
|
||||
|
||||
def test_api_strategy(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/strategy/{CURRENT_TEST_STRATEGY}")
|
||||
|
||||
|
|
@ -1717,7 +1717,7 @@ def test_api_strategy(botclient):
|
|||
|
||||
|
||||
def test_api_exchanges(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/exchanges")
|
||||
assert_response(rc)
|
||||
|
|
@ -1954,7 +1954,7 @@ def test_list_available_pairs(botclient):
|
|||
|
||||
|
||||
def test_sysinfo(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/sysinfo")
|
||||
assert_response(rc)
|
||||
|
|
@ -2234,7 +2234,7 @@ def test_api_patch_backtest_history_entry(botclient, tmp_path: Path):
|
|||
|
||||
|
||||
def test_health(botclient):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
|
||||
rc = client_get(client, f"{BASE_URI}/health")
|
||||
|
||||
|
|
@ -2245,7 +2245,7 @@ def test_health(botclient):
|
|||
|
||||
|
||||
def test_api_ws_subscribe(botclient, mocker):
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}"
|
||||
|
||||
sub_mock = mocker.patch('freqtrade.rpc.api_server.ws.WebSocketChannel.set_subscriptions')
|
||||
|
|
@ -2268,7 +2268,7 @@ def test_api_ws_subscribe(botclient, mocker):
|
|||
def test_api_ws_requests(botclient, caplog):
|
||||
caplog.set_level(logging.DEBUG)
|
||||
|
||||
ftbot, client = botclient
|
||||
_ftbot, client = botclient
|
||||
ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}"
|
||||
|
||||
# Test whitelist request
|
||||
|
|
|
|||
|
|
@ -2,7 +2,6 @@
|
|||
Unit test file for rpc/external_message_consumer.py
|
||||
"""
|
||||
import asyncio
|
||||
import functools
|
||||
import logging
|
||||
from datetime import datetime, timezone
|
||||
from unittest.mock import MagicMock
|
||||
|
|
@ -302,19 +301,16 @@ async def test_emc_receive_messages_valid(default_conf, caplog, mocker):
|
|||
dp = DataProvider(default_conf, None, None, None)
|
||||
emc = ExternalMessageConsumer(default_conf, dp)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
def change_running(emc): emc._running = not emc._running
|
||||
|
||||
class TestChannel:
|
||||
async def recv(self, *args, **kwargs):
|
||||
emc._running = False
|
||||
return {"type": "whitelist", "data": ["BTC/USDT"]}
|
||||
|
||||
async def ping(self, *args, **kwargs):
|
||||
return asyncio.Future()
|
||||
|
||||
try:
|
||||
change_running(emc)
|
||||
loop.call_soon(functools.partial(change_running, emc=emc))
|
||||
emc._running = True
|
||||
await emc._receive_messages(TestChannel(), test_producer, lock)
|
||||
|
||||
assert log_has_re(r"Received message of type `whitelist`.+", caplog)
|
||||
|
|
@ -349,19 +345,16 @@ async def test_emc_receive_messages_invalid(default_conf, caplog, mocker):
|
|||
dp = DataProvider(default_conf, None, None, None)
|
||||
emc = ExternalMessageConsumer(default_conf, dp)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
def change_running(emc): emc._running = not emc._running
|
||||
|
||||
class TestChannel:
|
||||
async def recv(self, *args, **kwargs):
|
||||
emc._running = False
|
||||
return {"type": ["BTC/USDT"]}
|
||||
|
||||
async def ping(self, *args, **kwargs):
|
||||
return asyncio.Future()
|
||||
|
||||
try:
|
||||
change_running(emc)
|
||||
loop.call_soon(functools.partial(change_running, emc=emc))
|
||||
emc._running = True
|
||||
await emc._receive_messages(TestChannel(), test_producer, lock)
|
||||
|
||||
assert log_has_re(r"Invalid message from.+", caplog)
|
||||
|
|
@ -396,8 +389,8 @@ async def test_emc_receive_messages_timeout(default_conf, caplog, mocker):
|
|||
dp = DataProvider(default_conf, None, None, None)
|
||||
emc = ExternalMessageConsumer(default_conf, dp)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
def change_running(emc): emc._running = not emc._running
|
||||
def change_running():
|
||||
emc._running = not emc._running
|
||||
|
||||
class TestChannel:
|
||||
async def recv(self, *args, **kwargs):
|
||||
|
|
@ -407,8 +400,7 @@ async def test_emc_receive_messages_timeout(default_conf, caplog, mocker):
|
|||
return asyncio.Future()
|
||||
|
||||
try:
|
||||
change_running(emc)
|
||||
loop.call_soon(functools.partial(change_running, emc=emc))
|
||||
change_running()
|
||||
|
||||
with pytest.raises(asyncio.TimeoutError):
|
||||
await emc._receive_messages(TestChannel(), test_producer, lock)
|
||||
|
|
@ -447,19 +439,16 @@ async def test_emc_receive_messages_handle_error(default_conf, caplog, mocker):
|
|||
|
||||
emc.handle_producer_message = MagicMock(side_effect=Exception)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
def change_running(emc): emc._running = not emc._running
|
||||
|
||||
class TestChannel:
|
||||
async def recv(self, *args, **kwargs):
|
||||
emc._running = False
|
||||
return {"type": "whitelist", "data": ["BTC/USDT"]}
|
||||
|
||||
async def ping(self, *args, **kwargs):
|
||||
return asyncio.Future()
|
||||
|
||||
try:
|
||||
change_running(emc)
|
||||
loop.call_soon(functools.partial(change_running, emc=emc))
|
||||
emc._running = True
|
||||
await emc._receive_messages(TestChannel(), test_producer, lock)
|
||||
|
||||
assert log_has_re(r"Error handling producer message.+", caplog)
|
||||
|
|
|
|||
|
|
@ -599,7 +599,7 @@ async def test_daily_handle(default_conf_usdt, update, ticker, fee, mocker, time
|
|||
get_fee=fee,
|
||||
)
|
||||
|
||||
telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf_usdt)
|
||||
telegram, _freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf_usdt)
|
||||
|
||||
# Move date to within day
|
||||
time_machine.move_to('2022-06-11 08:00:00+00:00')
|
||||
|
|
@ -1480,7 +1480,7 @@ async def test_telegram_performance_handle(default_conf_usdt, update, ticker, fe
|
|||
fetch_ticker=ticker,
|
||||
get_fee=fee,
|
||||
)
|
||||
telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf_usdt)
|
||||
telegram, _freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf_usdt)
|
||||
|
||||
# Create some test data
|
||||
create_mock_trades_usdt(fee)
|
||||
|
|
@ -1655,7 +1655,7 @@ async def test_telegram_lock_handle(default_conf, update, ticker, fee, mocker) -
|
|||
|
||||
async def test_whitelist_static(default_conf, update, mocker) -> None:
|
||||
|
||||
telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
telegram, _freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
|
||||
await telegram._whitelist(update=update, context=MagicMock())
|
||||
assert msg_mock.call_count == 1
|
||||
|
|
@ -2647,7 +2647,7 @@ async def test__send_msg_keyboard(default_conf, mocker, caplog) -> None:
|
|||
|
||||
|
||||
async def test_change_market_direction(default_conf, mocker, update) -> None:
|
||||
telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
telegram, _, _msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
assert telegram._rpc._freqtrade.strategy.market_direction == MarketDirection.NONE
|
||||
context = MagicMock()
|
||||
context.args = ["long"]
|
||||
|
|
|
|||
|
|
@ -152,7 +152,7 @@ class StrategyTestV3(IStrategy):
|
|||
(
|
||||
qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
|
||||
),
|
||||
'enter_short'] = 1
|
||||
('enter_short', 'enter_tag')] = (1, 'short_Tag')
|
||||
|
||||
return dataframe
|
||||
|
||||
|
|
@ -176,7 +176,7 @@ class StrategyTestV3(IStrategy):
|
|||
(
|
||||
qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
|
||||
),
|
||||
'exit_short'] = 1
|
||||
('exit_short', 'exit_tag')] = (1, 'short_Tag')
|
||||
|
||||
return dataframe
|
||||
|
||||
|
|
|
|||
|
|
@ -105,7 +105,7 @@ def test_returns_latest_signal(ohlcv_history):
|
|||
_STRATEGY.config['trading_mode'] = 'spot'
|
||||
|
||||
|
||||
def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
|
||||
def test_analyze_pair_empty(mocker, caplog, ohlcv_history):
|
||||
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
|
|
@ -1019,3 +1019,30 @@ def test_auto_hyperopt_interface_loadparams(default_conf, mocker, caplog):
|
|||
|
||||
StrategyResolver.load_strategy(default_conf)
|
||||
assert log_has("Invalid parameter file format.", caplog)
|
||||
|
||||
|
||||
@pytest.mark.parametrize('function,raises', [
|
||||
('populate_entry_trend', True),
|
||||
('advise_entry', False),
|
||||
('populate_exit_trend', True),
|
||||
('advise_exit', False),
|
||||
])
|
||||
def test_pandas_warning_direct(ohlcv_history, function, raises):
|
||||
|
||||
df = _STRATEGY.populate_indicators(ohlcv_history, {'pair': 'ETH/BTC'})
|
||||
if raises:
|
||||
with pytest.warns(FutureWarning):
|
||||
# Test for Future warning
|
||||
# FutureWarning: Setting an item of incompatible dtype is
|
||||
# deprecated and will raise in a future error of pandas
|
||||
# https://github.com/pandas-dev/pandas/issues/56503
|
||||
getattr(_STRATEGY, function)(df, {'pair': 'ETH/BTC'})
|
||||
else:
|
||||
getattr(_STRATEGY, function)(df, {'pair': 'ETH/BTC'})
|
||||
|
||||
|
||||
def test_pandas_warning_through_analyze_pair(ohlcv_history, mocker, recwarn):
|
||||
|
||||
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
||||
_STRATEGY.analyze_pair('ETH/BTC')
|
||||
assert len(recwarn) == 0
|
||||
|
|
|
|||
|
|
@ -15,7 +15,7 @@ from freqtrade.configuration.deprecated_settings import (check_conflicting_setti
|
|||
process_deprecated_setting,
|
||||
process_removed_setting,
|
||||
process_temporary_deprecated_settings)
|
||||
from freqtrade.configuration.environment_vars import flat_vars_to_nested_dict
|
||||
from freqtrade.configuration.environment_vars import _flat_vars_to_nested_dict
|
||||
from freqtrade.configuration.load_config import (load_config_file, load_file, load_from_files,
|
||||
log_config_error_range)
|
||||
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL, ENV_VAR_PREFIX
|
||||
|
|
@ -1419,7 +1419,7 @@ def test_flat_vars_to_nested_dict(caplog):
|
|||
'chat_id': '2151'
|
||||
}
|
||||
}
|
||||
res = flat_vars_to_nested_dict(test_args, ENV_VAR_PREFIX)
|
||||
res = _flat_vars_to_nested_dict(test_args, ENV_VAR_PREFIX)
|
||||
assert res == expected
|
||||
|
||||
assert log_has("Loading variable 'FREQTRADE__EXCHANGE__SOME_SETTING'", caplog)
|
||||
|
|
|
|||
|
|
@ -627,15 +627,16 @@ def test_process_exchange_failures(default_conf_usdt, ticker_usdt, mocker) -> No
|
|||
mocker.patch.multiple(
|
||||
EXMS,
|
||||
fetch_ticker=ticker_usdt,
|
||||
create_order=MagicMock(side_effect=TemporaryError)
|
||||
reload_markets=MagicMock(side_effect=TemporaryError),
|
||||
create_order=MagicMock(side_effect=TemporaryError),
|
||||
)
|
||||
sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
|
||||
sleep_mock = mocker.patch('time.sleep')
|
||||
|
||||
worker = Worker(args=None, config=default_conf_usdt)
|
||||
patch_get_signal(worker.freqtrade)
|
||||
|
||||
worker._process_running()
|
||||
assert sleep_mock.has_calls()
|
||||
assert sleep_mock.called is True
|
||||
|
||||
|
||||
def test_process_operational_exception(default_conf_usdt, ticker_usdt, mocker) -> None:
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user