Merge branch 'freqtrade:develop' into develop
This commit is contained in:
smarmau
GitHub
commit
a17c32577f
BIN
docs/assets/binance_futures_settings.png
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docs/assets/binance_futures_settings.png
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@ -60,11 +60,18 @@ Binance supports [time_in_force](configuration.md#understand-order_time_in_force
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Binance supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
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On futures, Binance supports both `stop-limit` as well as `stop-market` orders. You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type to use.
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### Binance Blacklist
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### Binance Blacklist recommendation
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For Binance, it is suggested to add `"BNB/<STAKE>"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `BNB` on the account or unless you're willing to disable using `BNB` for fees.
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Binance accounts may use `BNB` for fees, and if a trade happens to be on `BNB`, further trades may consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore.
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### Binance sites
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Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
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* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`.
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* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`.
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### Binance Futures
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Binance has specific (unfortunately complex) [Futures Trading Quantitative Rules](https://www.binance.com/en/support/faq/4f462ebe6ff445d4a170be7d9e897272) which need to be followed, and which prohibit a too low stake-amount (among others) for too many orders.
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@ -87,12 +94,14 @@ When trading on Binance Futures market, orderbook must be used because there is
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},
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```
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### Binance sites
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#### Binance futures settings
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Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
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Users will also have to have the futures-setting "Position Mode" set to "One-way Mode", and "Asset Mode" set to "Single-Asset Mode".
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These settings will be checked on startup, and freqtrade will show an error if this setting is wrong.
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* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`.
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* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`.
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Freqtrade will not attempt to change these settings.
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## Kraken
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@ -27,8 +27,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
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||||
| `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)). <br> **Datatype:** Positive float (typically < 1).
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| `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `populate_any_indicators()` for indicator creation. `FreqAI` uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN <br> **Datatype:** Positive integer.
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| `indicator_periods_candles` | Time periods to calculate indicators for. The indicators are added to the base indicator dataset. <br> **Datatype:** List of positive integers.
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| `stratify_training_data` | Split the feature set into training and testing datasets. For example, `stratify_training_data: 2` would set every 2nd data point into a separate dataset to be pulled from during training/testing. See details about how it works [here](freqai-running.md#data-stratification-for-training-and-testing-the-model). <br> **Datatype:** Positive integer.
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| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis) <br> **Datatype:** Boolean. defaults to `false`.
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| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis) <br> **Datatype:** Boolean. defaults to `False`.
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| `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features.<br> **Datatype:** Integer, defaults to `0`.
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| `DI_threshold` | Activates the use of the Dissimilarity Index for outlier detection when set to > 0. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di). <br> **Datatype:** Positive float (typically < 1).
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| `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training dataset, as well as from incoming data points. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm). <br> **Datatype:** Boolean.
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@ -41,7 +40,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
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||||
| | **Data split parameters**
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||||
| `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). <br> **Datatype:** Dictionary.
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||||
| `test_size` | The fraction of data that should be used for testing instead of training. <br> **Datatype:** Positive float < 1.
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| `shuffle` | Shuffle the training data points during training. Typically, for time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean.
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||||
| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Defaut: `False`.
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| | **Model training parameters**
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||||
| `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If you select a different model, this dictionary can contain any parameter from that model. <br> **Datatype:** Dictionary.
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| `n_estimators` | The number of boosted trees to fit in regression. <br> **Datatype:** Integer.
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@ -105,23 +105,6 @@ During dry/live mode, FreqAI trains each coin pair sequentially (on separate thr
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In the presented example config, the user will only allow predictions on models that are less than 1/2 hours old.
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## Data stratification for training and testing the model
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||||
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You can stratify (group) the training/testing data using:
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||||
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||||
```json
|
||||
"freqai": {
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||||
"feature_parameters" : {
|
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"stratify_training_data": 3
|
||||
}
|
||||
}
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```
|
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This will split the data chronologically so that every Xth data point is used to test the model after training. In the example above, the user is asking for every third data point in the dataframe to be used for
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testing; the other points are used for training.
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The test data is used to evaluate the performance of the model after training. If the test score is high, the model is able to capture the behavior of the data well. If the test score is low, either the model does not capture the complexity of the data, the test data is significantly different from the train data, or a different type of model should be used.
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## Controlling the model learning process
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Model training parameters are unique to the selected machine learning library. FreqAI allows you to set any parameter for any library using the `model_training_parameters` dictionary in the config. The example config (found in `config_examples/config_freqai.example.json`) shows some of the example parameters associated with `Catboost` and `LightGBM`, but you can add any parameters available in those libraries or any other machine learning library you choose to implement.
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@ -22,6 +22,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
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* [`StaticPairList`](#static-pair-list) (default, if not configured differently)
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* [`VolumePairList`](#volume-pair-list)
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* [`ProducerPairList`](#producerpairlist)
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* [`AgeFilter`](#agefilter)
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* [`OffsetFilter`](#offsetfilter)
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* [`PerformanceFilter`](#performancefilter)
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@ -84,7 +85,7 @@ Filtering instances (not the first position in the list) will not apply any cach
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You can define a minimum volume with `min_value` - which will filter out pairs with a volume lower than the specified value in the specified timerange.
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### VolumePairList Advanced mode
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##### VolumePairList Advanced mode
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`VolumePairList` can also operate in an advanced mode to build volume over a given timerange of specified candle size. It utilizes exchange historical candle data, builds a typical price (calculated by (open+high+low)/3) and multiplies the typical price with every candle's volume. The sum is the `quoteVolume` over the given range. This allows different scenarios, for a more smoothened volume, when using longer ranges with larger candle sizes, or the opposite when using a short range with small candles.
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@ -146,6 +147,32 @@ More sophisticated approach can be used, by using `lookback_timeframe` for candl
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!!! Note
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`VolumePairList` does not support backtesting mode.
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#### ProducerPairList
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With `ProducerPairList`, you can reuse the pairlist from a [Producer](producer-consumer.md) without explicitly defining the pairlist on each consumer.
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[Consumer mode](producer-consumer.md) is required for this pairlist to work.
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The pairlist will perform a check on active pairs against the current exchange configuration to avoid attempting to trade on invalid markets.
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You can limit the length of the pairlist with the optional parameter `number_assets`. Using `"number_assets"=0` or omitting this key will result in the reuse of all producer pairs valid for the current setup.
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```json
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"pairlists": [
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{
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"method": "ProducerPairList",
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||||
"number_assets": 5,
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"producer_name": "default",
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}
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],
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```
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!!! Tip "Combining pairlists"
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This pairlist can be combined with all other pairlists and filters for further pairlist reduction, and can also act as an "additional" pairlist, on top of already defined pairs.
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`ProducerPairList` can also be used multiple times in sequence, combining the pairs from multiple producers.
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Obviously in complex such configurations, the Producer may not provide data for all pairs, so the strategy must be fit for this.
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#### AgeFilter
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Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity).
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@ -643,7 +643,7 @@ This callback is **not** called when there is an open order (either buy or sell)
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Additional Buys are ignored once you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits.
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Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade. Modifications to leverage are not possible.
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Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade. Modifications to leverage are not possible, and the stake-amount is assumed to be before applying leverage.
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!!! Note "About stake size"
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Using fixed stake size means it will be the amount used for the first order, just like without position adjustment.
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@ -37,3 +37,12 @@ pip install -e .
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# Ensure freqUI is at the latest version
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freqtrade install-ui
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```
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### Problems updating
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||||
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Update-problems usually come missing dependencies (you didn't follow the above instructions) - or from updated dependencies, which fail to install (for example TA-lib).
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Please refer to the corresponding installation sections (common problems linked below)
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|
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Common problems and their solutions:
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||||
|
||||
* [ta-lib update on windows](windows_installation.md#2-install-ta-lib)
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@ -34,7 +34,7 @@ python -m venv .env
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.env\Scripts\activate.ps1
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# optionally install ta-lib from wheel
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# Eventually adjust the below filename to match the downloaded wheel
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pip install --find-links build_helpers\ TA-Lib
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pip install --find-links build_helpers\ TA-Lib -U
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pip install -r requirements.txt
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pip install -e .
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freqtrade
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@ -31,7 +31,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
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'CalmarHyperOptLoss',
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'MaxDrawDownHyperOptLoss', 'MaxDrawDownRelativeHyperOptLoss',
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'ProfitDrawDownHyperOptLoss']
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AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
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AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'ProducerPairList',
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'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
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'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
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'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
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@ -568,6 +568,7 @@ CONF_SCHEMA = {
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"properties": {
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"test_size": {"type": "number"},
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"random_state": {"type": "integer"},
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"shuffle": {"type": "boolean", "default": False}
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},
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},
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"model_training_parameters": {
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@ -47,8 +47,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
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def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *,
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fill_missing: bool = True,
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drop_incomplete: bool = True) -> DataFrame:
|
||||
fill_missing: bool, drop_incomplete: bool) -> DataFrame:
|
||||
"""
|
||||
Cleanse a OHLCV dataframe by
|
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* Grouping it by date (removes duplicate tics)
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|
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@ -26,7 +26,7 @@ def load_pair_history(pair: str,
|
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datadir: Path, *,
|
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timerange: Optional[TimeRange] = None,
|
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fill_up_missing: bool = True,
|
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drop_incomplete: bool = True,
|
||||
drop_incomplete: bool = False,
|
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startup_candles: int = 0,
|
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data_format: str = None,
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data_handler: IDataHandler = None,
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|
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@ -275,7 +275,7 @@ class IDataHandler(ABC):
|
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candle_type: CandleType, *,
|
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timerange: Optional[TimeRange] = None,
|
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fill_missing: bool = True,
|
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drop_incomplete: bool = True,
|
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drop_incomplete: bool = False,
|
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startup_candles: int = 0,
|
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warn_no_data: bool = True,
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) -> DataFrame:
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@ -68,6 +68,37 @@ class Binance(Exchange):
|
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tickers = deep_merge_dicts(bidsasks, tickers, allow_null_overrides=False)
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return tickers
|
||||
|
||||
@retrier
|
||||
def additional_exchange_init(self) -> None:
|
||||
"""
|
||||
Additional exchange initialization logic.
|
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.api will be available at this point.
|
||||
Must be overridden in child methods if required.
|
||||
"""
|
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try:
|
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if self.trading_mode == TradingMode.FUTURES and not self._config['dry_run']:
|
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position_side = self._api.fapiPrivateGetPositionsideDual()
|
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self._log_exchange_response('position_side_setting', position_side)
|
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assets_margin = self._api.fapiPrivateGetMultiAssetsMargin()
|
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self._log_exchange_response('multi_asset_margin', assets_margin)
|
||||
msg = ""
|
||||
if position_side.get('dualSidePosition') is True:
|
||||
msg += (
|
||||
"\nHedge Mode is not supported by freqtrade. "
|
||||
"Please change 'Position Mode' on your binance futures account.")
|
||||
if assets_margin.get('multiAssetsMargin') is True:
|
||||
msg += ("\nMulti-Asset Mode is not supported by freqtrade. "
|
||||
"Please change 'Asset Mode' on your binance futures account.")
|
||||
if msg:
|
||||
raise OperationalException(msg)
|
||||
except ccxt.DDoSProtection as e:
|
||||
raise DDosProtection(e) from e
|
||||
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
|
||||
raise TemporaryError(
|
||||
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
|
||||
except ccxt.BaseError as e:
|
||||
raise OperationalException(e) from e
|
||||
|
||||
@retrier
|
||||
def _set_leverage(
|
||||
self,
|
||||
|
||||
@ -1292,7 +1292,7 @@ class Exchange:
|
||||
order = self.fetch_order(order_id, pair)
|
||||
except InvalidOrderException:
|
||||
logger.warning(f"Could not fetch cancelled order {order_id}.")
|
||||
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
|
||||
order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
|
||||
|
||||
return order
|
||||
|
||||
|
||||
@ -78,7 +78,8 @@ class Okx(Exchange):
|
||||
raise DDosProtection(e) from e
|
||||
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
|
||||
raise TemporaryError(
|
||||
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
|
||||
f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}'
|
||||
) from e
|
||||
except ccxt.BaseError as e:
|
||||
raise OperationalException(e) from e
|
||||
|
||||
|
||||
@ -92,7 +92,7 @@ class BaseClassifierModel(IFreqaiModel):
|
||||
filtered_df = dk.normalize_data_from_metadata(filtered_df)
|
||||
dk.data_dictionary["prediction_features"] = filtered_df
|
||||
|
||||
self.data_cleaning_predict(dk, filtered_df)
|
||||
self.data_cleaning_predict(dk)
|
||||
|
||||
predictions = self.model.predict(dk.data_dictionary["prediction_features"])
|
||||
pred_df = DataFrame(predictions, columns=dk.label_list)
|
||||
|
||||
@ -92,7 +92,7 @@ class BaseRegressionModel(IFreqaiModel):
|
||||
dk.data_dictionary["prediction_features"] = filtered_df
|
||||
|
||||
# optional additional data cleaning/analysis
|
||||
self.data_cleaning_predict(dk, filtered_df)
|
||||
self.data_cleaning_predict(dk)
|
||||
|
||||
predictions = self.model.predict(dk.data_dictionary["prediction_features"])
|
||||
pred_df = DataFrame(predictions, columns=dk.label_list)
|
||||
|
||||
@ -423,7 +423,7 @@ class FreqaiDataDrawer:
|
||||
|
||||
dk.data["data_path"] = str(dk.data_path)
|
||||
dk.data["model_filename"] = str(dk.model_filename)
|
||||
dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns)
|
||||
dk.data["training_features_list"] = dk.training_features_list
|
||||
dk.data["label_list"] = dk.label_list
|
||||
# store the metadata
|
||||
with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:
|
||||
|
||||
@ -134,20 +134,15 @@ class FreqaiDataKitchen:
|
||||
"""
|
||||
feat_dict = self.freqai_config["feature_parameters"]
|
||||
|
||||
if 'shuffle' not in self.freqai_config['data_split_parameters']:
|
||||
self.freqai_config["data_split_parameters"].update({'shuffle': False})
|
||||
|
||||
weights: npt.ArrayLike
|
||||
if feat_dict.get("weight_factor", 0) > 0:
|
||||
weights = self.set_weights_higher_recent(len(filtered_dataframe))
|
||||
else:
|
||||
weights = np.ones(len(filtered_dataframe))
|
||||
|
||||
if feat_dict.get("stratify_training_data", 0) > 0:
|
||||
stratification = np.zeros(len(filtered_dataframe))
|
||||
for i in range(1, len(stratification)):
|
||||
if i % feat_dict.get("stratify_training_data", 0) == 0:
|
||||
stratification[i] = 1
|
||||
else:
|
||||
stratification = None
|
||||
|
||||
if self.freqai_config.get('data_split_parameters', {}).get('test_size', 0.1) != 0:
|
||||
(
|
||||
train_features,
|
||||
@ -160,7 +155,6 @@ class FreqaiDataKitchen:
|
||||
filtered_dataframe[: filtered_dataframe.shape[0]],
|
||||
labels,
|
||||
weights,
|
||||
stratify=stratification,
|
||||
**self.config["freqai"]["data_split_parameters"],
|
||||
)
|
||||
else:
|
||||
@ -210,7 +204,7 @@ class FreqaiDataKitchen:
|
||||
filtered_df = unfiltered_df.filter(training_feature_list, axis=1)
|
||||
filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan)
|
||||
|
||||
drop_index = pd.isnull(filtered_df).any(1) # get the rows that have NaNs,
|
||||
drop_index = pd.isnull(filtered_df).any(axis=1) # get the rows that have NaNs,
|
||||
drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement.
|
||||
if (training_filter):
|
||||
const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index)
|
||||
@ -221,7 +215,7 @@ class FreqaiDataKitchen:
|
||||
# about removing any row with NaNs
|
||||
# if labels has multiple columns (user wants to train multiple modelEs), we detect here
|
||||
labels = unfiltered_df.filter(label_list, axis=1)
|
||||
drop_index_labels = pd.isnull(labels).any(1)
|
||||
drop_index_labels = pd.isnull(labels).any(axis=1)
|
||||
drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0)
|
||||
dates = unfiltered_df['date']
|
||||
filtered_df = filtered_df[
|
||||
@ -249,7 +243,7 @@ class FreqaiDataKitchen:
|
||||
else:
|
||||
# we are backtesting so we need to preserve row number to send back to strategy,
|
||||
# so now we use do_predict to avoid any prediction based on a NaN
|
||||
drop_index = pd.isnull(filtered_df).any(1)
|
||||
drop_index = pd.isnull(filtered_df).any(axis=1)
|
||||
self.data["filter_drop_index_prediction"] = drop_index
|
||||
filtered_df.fillna(0, inplace=True)
|
||||
# replacing all NaNs with zeros to avoid issues in 'prediction', but any prediction
|
||||
@ -808,7 +802,7 @@ class FreqaiDataKitchen:
|
||||
:, :no_prev_pts
|
||||
]
|
||||
distances = distances.replace([np.inf, -np.inf], np.nan)
|
||||
drop_index = pd.isnull(distances).any(1)
|
||||
drop_index = pd.isnull(distances).any(axis=1)
|
||||
distances = distances[drop_index == 0]
|
||||
|
||||
inliers = pd.DataFrame(index=distances.index)
|
||||
@ -881,6 +875,7 @@ class FreqaiDataKitchen:
|
||||
"""
|
||||
column_names = dataframe.columns
|
||||
features = [c for c in column_names if "%" in c]
|
||||
|
||||
if not features:
|
||||
raise OperationalException("Could not find any features!")
|
||||
|
||||
|
||||
@ -275,7 +275,8 @@ class IFreqaiModel(ABC):
|
||||
|
||||
if dk.check_if_backtest_prediction_exists():
|
||||
self.dd.load_metadata(dk)
|
||||
self.check_if_feature_list_matches_strategy(dataframe_train, dk)
|
||||
dk.find_features(dataframe_train)
|
||||
self.check_if_feature_list_matches_strategy(dk)
|
||||
append_df = dk.get_backtesting_prediction()
|
||||
dk.append_predictions(append_df)
|
||||
else:
|
||||
@ -296,7 +297,6 @@ class IFreqaiModel(ABC):
|
||||
else:
|
||||
self.model = self.dd.load_data(pair, dk)
|
||||
|
||||
# self.check_if_feature_list_matches_strategy(dataframe_train, dk)
|
||||
pred_df, do_preds = self.predict(dataframe_backtest, dk)
|
||||
append_df = dk.get_predictions_to_append(pred_df, do_preds)
|
||||
dk.append_predictions(append_df)
|
||||
@ -420,7 +420,7 @@ class IFreqaiModel(ABC):
|
||||
return
|
||||
|
||||
def check_if_feature_list_matches_strategy(
|
||||
self, dataframe: DataFrame, dk: FreqaiDataKitchen
|
||||
self, dk: FreqaiDataKitchen
|
||||
) -> None:
|
||||
"""
|
||||
Ensure user is passing the proper feature set if they are reusing an `identifier` pointing
|
||||
@ -429,11 +429,12 @@ class IFreqaiModel(ABC):
|
||||
:param dk: FreqaiDataKitchen = non-persistent data container/analyzer for
|
||||
current coin/bot loop
|
||||
"""
|
||||
dk.find_features(dataframe)
|
||||
|
||||
if "training_features_list_raw" in dk.data:
|
||||
feature_list = dk.data["training_features_list_raw"]
|
||||
else:
|
||||
feature_list = dk.data['training_features_list']
|
||||
|
||||
if dk.training_features_list != feature_list:
|
||||
raise OperationalException(
|
||||
"Trying to access pretrained model with `identifier` "
|
||||
@ -481,13 +482,16 @@ class IFreqaiModel(ABC):
|
||||
if self.freqai_info["feature_parameters"].get('noise_standard_deviation', 0):
|
||||
dk.add_noise_to_training_features()
|
||||
|
||||
def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
|
||||
def data_cleaning_predict(self, dk: FreqaiDataKitchen) -> None:
|
||||
"""
|
||||
Base data cleaning method for predict.
|
||||
Functions here are complementary to the functions of data_cleaning_train.
|
||||
"""
|
||||
ft_params = self.freqai_info["feature_parameters"]
|
||||
|
||||
# ensure user is feeding the correct indicators to the model
|
||||
self.check_if_feature_list_matches_strategy(dk)
|
||||
|
||||
if ft_params.get('inlier_metric_window', 0):
|
||||
dk.compute_inlier_metric(set_='predict')
|
||||
|
||||
@ -505,9 +509,6 @@ class IFreqaiModel(ABC):
|
||||
if ft_params.get("use_DBSCAN_to_remove_outliers", False):
|
||||
dk.use_DBSCAN_to_remove_outliers(predict=True)
|
||||
|
||||
# ensure user is feeding the correct indicators to the model
|
||||
self.check_if_feature_list_matches_strategy(dk.data_dictionary['prediction_features'], dk)
|
||||
|
||||
def model_exists(self, dk: FreqaiDataKitchen) -> bool:
|
||||
"""
|
||||
Given a pair and path, check if a model already exists
|
||||
|
||||
@ -82,7 +82,10 @@ class FreqtradeBot(LoggingMixin):
|
||||
# Keep this at the end of this initialization method.
|
||||
self.rpc: RPCManager = RPCManager(self)
|
||||
|
||||
self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists, self.rpc)
|
||||
self.dataprovider = DataProvider(self.config, self.exchange, rpc=self.rpc)
|
||||
self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider)
|
||||
|
||||
self.dataprovider.add_pairlisthandler(self.pairlists)
|
||||
|
||||
# Attach Dataprovider to strategy instance
|
||||
self.strategy.dp = self.dataprovider
|
||||
@ -597,7 +600,7 @@ class FreqtradeBot(LoggingMixin):
|
||||
# We should decrease our position
|
||||
amount = self.exchange.amount_to_contract_precision(
|
||||
trade.pair,
|
||||
abs(float(FtPrecise(stake_amount) / FtPrecise(current_exit_rate))))
|
||||
abs(float(FtPrecise(stake_amount * trade.leverage) / FtPrecise(current_exit_rate))))
|
||||
if amount > trade.amount:
|
||||
# This is currently ineffective as remaining would become < min tradable
|
||||
# Fixing this would require checking for 0.0 there -
|
||||
@ -1340,11 +1343,12 @@ class FreqtradeBot(LoggingMixin):
|
||||
replacing: Optional[bool] = False
|
||||
) -> bool:
|
||||
"""
|
||||
Buy cancel - cancel order
|
||||
entry cancel - cancel order
|
||||
:param replacing: Replacing order - prevent trade deletion.
|
||||
:return: True if order was fully cancelled
|
||||
:return: True if trade was fully cancelled
|
||||
"""
|
||||
was_trade_fully_canceled = False
|
||||
side = trade.entry_side.capitalize()
|
||||
|
||||
# Cancelled orders may have the status of 'canceled' or 'closed'
|
||||
if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES:
|
||||
@ -1371,7 +1375,6 @@ class FreqtradeBot(LoggingMixin):
|
||||
corder = order
|
||||
reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
|
||||
|
||||
side = trade.entry_side.capitalize()
|
||||
logger.info('%s order %s for %s.', side, reason, trade)
|
||||
|
||||
# Using filled to determine the filled amount
|
||||
@ -1385,24 +1388,13 @@ class FreqtradeBot(LoggingMixin):
|
||||
was_trade_fully_canceled = True
|
||||
reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}"
|
||||
else:
|
||||
# FIXME TODO: This could possibly reworked to not duplicate the code 15 lines below.
|
||||
self.update_trade_state(trade, trade.open_order_id, corder)
|
||||
trade.open_order_id = None
|
||||
logger.info(f'{side} Order timeout for {trade}.')
|
||||
else:
|
||||
# if trade is partially complete, edit the stake details for the trade
|
||||
# and close the order
|
||||
# cancel_order may not contain the full order dict, so we need to fallback
|
||||
# to the order dict acquired before cancelling.
|
||||
# we need to fall back to the values from order if corder does not contain these keys.
|
||||
trade.amount = filled_amount
|
||||
# * Check edge cases, we don't want to make leverage > 1.0 if we don't have to
|
||||
# * (for leverage modes which aren't isolated futures)
|
||||
|
||||
trade.stake_amount = trade.amount * trade.open_rate / trade.leverage
|
||||
# update_trade_state (and subsequently recalc_trade_from_orders) will handle updates
|
||||
# to the trade object
|
||||
self.update_trade_state(trade, trade.open_order_id, corder)
|
||||
|
||||
trade.open_order_id = None
|
||||
logger.info(f'Partial {trade.entry_side} order timeout for {trade}.')
|
||||
reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}"
|
||||
|
||||
@ -1439,8 +1431,6 @@ class FreqtradeBot(LoggingMixin):
|
||||
trade.close_rate_requested = None
|
||||
trade.close_profit = None
|
||||
trade.close_profit_abs = None
|
||||
trade.close_date = None
|
||||
trade.is_open = True
|
||||
trade.open_order_id = None
|
||||
trade.exit_reason = None
|
||||
cancelled = True
|
||||
@ -1700,11 +1690,6 @@ class FreqtradeBot(LoggingMixin):
|
||||
'stake_amount': trade.stake_amount,
|
||||
}
|
||||
|
||||
if 'fiat_display_currency' in self.config:
|
||||
msg.update({
|
||||
'fiat_currency': self.config['fiat_display_currency'],
|
||||
})
|
||||
|
||||
# Send the message
|
||||
self.rpc.send_msg(msg)
|
||||
|
||||
|
||||
@ -110,7 +110,7 @@ class Backtesting:
|
||||
self.timeframe = str(self.config.get('timeframe'))
|
||||
self.timeframe_min = timeframe_to_minutes(self.timeframe)
|
||||
self.init_backtest_detail()
|
||||
self.pairlists = PairListManager(self.exchange, self.config)
|
||||
self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider)
|
||||
if 'VolumePairList' in self.pairlists.name_list:
|
||||
raise OperationalException("VolumePairList not allowed for backtesting. "
|
||||
"Please use StaticPairList instead.")
|
||||
@ -540,7 +540,7 @@ class Backtesting:
|
||||
|
||||
if stake_amount is not None and stake_amount < 0.0:
|
||||
amount = amount_to_contract_precision(
|
||||
abs(stake_amount) / current_rate, trade.amount_precision,
|
||||
abs(stake_amount * trade.leverage) / current_rate, trade.amount_precision,
|
||||
self.precision_mode, trade.contract_size)
|
||||
if amount == 0.0:
|
||||
return trade
|
||||
|
||||
90
freqtrade/plugins/pairlist/ProducerPairList.py
Normal file
90
freqtrade/plugins/pairlist/ProducerPairList.py
Normal file
@ -0,0 +1,90 @@
|
||||
"""
|
||||
External Pair List provider
|
||||
|
||||
Provides pair list from Leader data
|
||||
"""
|
||||
import logging
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.plugins.pairlist.IPairList import IPairList
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class ProducerPairList(IPairList):
|
||||
"""
|
||||
PairList plugin for use with external_message_consumer.
|
||||
Will use pairs given from leader data.
|
||||
|
||||
Usage:
|
||||
"pairlists": [
|
||||
{
|
||||
"method": "ProducerPairList",
|
||||
"number_assets": 5,
|
||||
"producer_name": "default",
|
||||
}
|
||||
],
|
||||
"""
|
||||
|
||||
def __init__(self, exchange, pairlistmanager,
|
||||
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
|
||||
pairlist_pos: int) -> None:
|
||||
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
|
||||
|
||||
self._num_assets: int = self._pairlistconfig.get('number_assets', 0)
|
||||
self._producer_name = self._pairlistconfig.get('producer_name', 'default')
|
||||
if not config.get('external_message_consumer', {}).get('enabled'):
|
||||
raise OperationalException(
|
||||
"ProducerPairList requires external_message_consumer to be enabled.")
|
||||
|
||||
@property
|
||||
def needstickers(self) -> bool:
|
||||
"""
|
||||
Boolean property defining if tickers are necessary.
|
||||
If no Pairlist requires tickers, an empty Dict is passed
|
||||
as tickers argument to filter_pairlist
|
||||
"""
|
||||
return False
|
||||
|
||||
def short_desc(self) -> str:
|
||||
"""
|
||||
Short whitelist method description - used for startup-messages
|
||||
-> Please overwrite in subclasses
|
||||
"""
|
||||
return f"{self.name} - {self._producer_name}"
|
||||
|
||||
def _filter_pairlist(self, pairlist: Optional[List[str]]):
|
||||
upstream_pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(
|
||||
self._producer_name)
|
||||
|
||||
if pairlist is None:
|
||||
pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(self._producer_name)
|
||||
|
||||
pairs = list(dict.fromkeys(pairlist + upstream_pairlist))
|
||||
if self._num_assets:
|
||||
pairs = pairs[:self._num_assets]
|
||||
|
||||
return pairs
|
||||
|
||||
def gen_pairlist(self, tickers: Dict) -> List[str]:
|
||||
"""
|
||||
Generate the pairlist
|
||||
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
|
||||
:return: List of pairs
|
||||
"""
|
||||
pairs = self._filter_pairlist(None)
|
||||
self.log_once(f"Received pairs: {pairs}", logger.debug)
|
||||
pairs = self._whitelist_for_active_markets(self.verify_whitelist(pairs, logger.info))
|
||||
return pairs
|
||||
|
||||
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
|
||||
"""
|
||||
Filters and sorts pairlist and returns the whitelist again.
|
||||
Called on each bot iteration - please use internal caching if necessary
|
||||
:param pairlist: pairlist to filter or sort
|
||||
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
|
||||
:return: new whitelist
|
||||
"""
|
||||
return self._filter_pairlist(pairlist)
|
||||
@ -232,6 +232,4 @@ class VolumePairList(IPairList):
|
||||
# Limit pairlist to the requested number of pairs
|
||||
pairs = pairs[:self._number_pairs]
|
||||
|
||||
self.log_once(f"Searching {self._number_pairs} pairs: {pairs}", logger.info)
|
||||
|
||||
return pairs
|
||||
|
||||
@ -3,11 +3,12 @@ PairList manager class
|
||||
"""
|
||||
import logging
|
||||
from functools import partial
|
||||
from typing import Dict, List
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from cachetools import TTLCache, cached
|
||||
|
||||
from freqtrade.constants import Config, ListPairsWithTimeframes
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
from freqtrade.enums import CandleType
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.mixins import LoggingMixin
|
||||
@ -21,13 +22,14 @@ logger = logging.getLogger(__name__)
|
||||
|
||||
class PairListManager(LoggingMixin):
|
||||
|
||||
def __init__(self, exchange, config: Config) -> None:
|
||||
def __init__(self, exchange, config: Config, dataprovider: DataProvider = None) -> None:
|
||||
self._exchange = exchange
|
||||
self._config = config
|
||||
self._whitelist = self._config['exchange'].get('pair_whitelist')
|
||||
self._blacklist = self._config['exchange'].get('pair_blacklist', [])
|
||||
self._pairlist_handlers: List[IPairList] = []
|
||||
self._tickers_needed = False
|
||||
self._dataprovider: Optional[DataProvider] = dataprovider
|
||||
for pairlist_handler_config in self._config.get('pairlists', []):
|
||||
pairlist_handler = PairListResolver.load_pairlist(
|
||||
pairlist_handler_config['method'],
|
||||
@ -96,6 +98,8 @@ class PairListManager(LoggingMixin):
|
||||
# to ensure blacklist is respected.
|
||||
pairlist = self.verify_blacklist(pairlist, logger.warning)
|
||||
|
||||
self.log_once(f"Whitelist with {len(pairlist)} pairs: {pairlist}", logger.info)
|
||||
|
||||
self._whitelist = pairlist
|
||||
|
||||
def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]:
|
||||
|
||||
@ -198,8 +198,10 @@ class ApiServer(RPCHandler):
|
||||
logger.debug(f"Found message of type: {message.get('type')}")
|
||||
# Broadcast it
|
||||
await self._ws_channel_manager.broadcast(message)
|
||||
# Sleep, make this configurable?
|
||||
await asyncio.sleep(0.1)
|
||||
# Limit messages per sec.
|
||||
# Could cause problems with queue size if too low, and
|
||||
# problems with network traffik if too high.
|
||||
await asyncio.sleep(0.001)
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
|
||||
@ -30,9 +30,9 @@ class Discord(Webhook):
|
||||
pass
|
||||
|
||||
def send_msg(self, msg) -> None:
|
||||
logger.info(f"Sending discord message: {msg}")
|
||||
|
||||
if msg['type'].value in self.config['discord']:
|
||||
logger.info(f"Sending discord message: {msg}")
|
||||
|
||||
msg['strategy'] = self.strategy
|
||||
msg['timeframe'] = self.timeframe
|
||||
|
||||
@ -61,6 +61,14 @@ class Webhook(RPCHandler):
|
||||
RPCMessageType.STARTUP,
|
||||
RPCMessageType.WARNING):
|
||||
valuedict = whconfig.get('webhookstatus')
|
||||
elif msg['type'] in (
|
||||
RPCMessageType.PROTECTION_TRIGGER,
|
||||
RPCMessageType.PROTECTION_TRIGGER_GLOBAL,
|
||||
RPCMessageType.WHITELIST,
|
||||
RPCMessageType.ANALYZED_DF,
|
||||
RPCMessageType.STRATEGY_MSG):
|
||||
# Don't fail for non-implemented types
|
||||
return
|
||||
else:
|
||||
raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
|
||||
if not valuedict:
|
||||
|
||||
2
setup.py
2
setup.py
@ -72,7 +72,7 @@ setup(
|
||||
'pandas',
|
||||
'tables',
|
||||
'blosc',
|
||||
'joblib',
|
||||
'joblib>=1.2.0',
|
||||
'pyarrow; platform_machine != "armv7l"',
|
||||
'fastapi',
|
||||
'uvicorn',
|
||||
|
||||
@ -200,6 +200,8 @@ def patch_freqtradebot(mocker, config) -> None:
|
||||
mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
|
||||
mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
|
||||
patch_whitelist(mocker, config)
|
||||
mocker.patch('freqtrade.freqtradebot.ExternalMessageConsumer')
|
||||
mocker.patch('freqtrade.configuration.config_validation._validate_consumers')
|
||||
|
||||
|
||||
def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
|
||||
|
||||
@ -235,7 +235,7 @@ def test_calculate_market_change(testdatadir):
|
||||
data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
|
||||
result = calculate_market_change(data)
|
||||
assert isinstance(result, float)
|
||||
assert pytest.approx(result) == 0.00955514
|
||||
assert pytest.approx(result) == 0.01100002
|
||||
|
||||
|
||||
def test_combine_dataframes_with_mean(testdatadir):
|
||||
|
||||
@ -139,10 +139,10 @@ def test_jsondatahandler_ohlcv_purge(mocker, testdatadir):
|
||||
def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
|
||||
dh = JsonDataHandler(testdatadir)
|
||||
df = dh.ohlcv_load('XRP/ETH', '5m', 'spot')
|
||||
assert len(df) == 711
|
||||
assert len(df) == 712
|
||||
|
||||
df_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', candle_type="mark")
|
||||
assert len(df_mark) == 99
|
||||
assert len(df_mark) == 100
|
||||
|
||||
df_no_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', 'spot')
|
||||
assert len(df_no_mark) == 0
|
||||
|
||||
@ -124,8 +124,8 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp
|
||||
assert '0' in captured.out
|
||||
assert '0.01616' in captured.out
|
||||
assert '34.049' in captured.out
|
||||
assert '0.104104' in captured.out
|
||||
assert '47.0996' in captured.out
|
||||
assert '0.104411' in captured.out
|
||||
assert '52.8292' in captured.out
|
||||
|
||||
# test group 1
|
||||
args = get_args(base_args + ['--analysis-groups', "1"])
|
||||
|
||||
@ -377,8 +377,8 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
|
||||
td = ((end - start).total_seconds() // 60 // 5) + 1
|
||||
assert td != len(data['UNITTEST/BTC'])
|
||||
|
||||
# Shift endtime with +5 - as last candle is dropped (partial candle)
|
||||
end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
|
||||
# Shift endtime with +5
|
||||
end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0])
|
||||
assert log_has(f'UNITTEST/BTC, spot, 5m, '
|
||||
f'data ends at {end_real.strftime(DATETIME_PRINT_FORMAT)}',
|
||||
caplog)
|
||||
@ -447,7 +447,7 @@ def test_get_timerange(default_conf, mocker, testdatadir) -> None:
|
||||
)
|
||||
min_date, max_date = get_timerange(data)
|
||||
assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
|
||||
assert max_date.isoformat() == '2017-11-14T22:58:00+00:00'
|
||||
assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'
|
||||
|
||||
|
||||
def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir) -> None:
|
||||
@ -470,7 +470,7 @@ def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir)
|
||||
min_date, max_date, timeframe_to_minutes('1m'))
|
||||
assert len(caplog.record_tuples) == 1
|
||||
assert log_has(
|
||||
"UNITTEST/BTC has missing frames: expected 14396, got 13680, that's 716 missing values",
|
||||
"UNITTEST/BTC has missing frames: expected 14397, got 13681, that's 716 missing values",
|
||||
caplog)
|
||||
|
||||
|
||||
|
||||
@ -501,6 +501,24 @@ def test_fill_leverage_tiers_binance_dryrun(default_conf, mocker, leverage_tiers
|
||||
assert len(v) == len(value)
|
||||
|
||||
|
||||
def test_additional_exchange_init_binance(default_conf, mocker):
|
||||
api_mock = MagicMock()
|
||||
api_mock.fapiPrivateGetPositionsideDual = MagicMock(return_value={"dualSidePosition": True})
|
||||
api_mock.fapiPrivateGetMultiAssetsMargin = MagicMock(return_value={"multiAssetsMargin": True})
|
||||
default_conf['dry_run'] = False
|
||||
default_conf['trading_mode'] = TradingMode.FUTURES
|
||||
default_conf['margin_mode'] = MarginMode.ISOLATED
|
||||
with pytest.raises(OperationalException,
|
||||
match=r"Hedge Mode is not supported.*\nMulti-Asset Mode is not supported.*"):
|
||||
get_patched_exchange(mocker, default_conf, id="binance", api_mock=api_mock)
|
||||
api_mock.fapiPrivateGetPositionsideDual = MagicMock(return_value={"dualSidePosition": False})
|
||||
api_mock.fapiPrivateGetMultiAssetsMargin = MagicMock(return_value={"multiAssetsMargin": False})
|
||||
exchange = get_patched_exchange(mocker, default_conf, id="binance", api_mock=api_mock)
|
||||
assert exchange
|
||||
ccxt_exceptionhandlers(mocker, default_conf, api_mock, 'binance',
|
||||
"additional_exchange_init", "fapiPrivateGetPositionsideDual")
|
||||
|
||||
|
||||
def test__set_leverage_binance(mocker, default_conf):
|
||||
|
||||
api_mock = MagicMock()
|
||||
|
||||
@ -137,6 +137,7 @@ def exchange_futures(request, exchange_conf, class_mocker):
|
||||
'freqtrade.exchange.binance.Binance.fill_leverage_tiers')
|
||||
class_mocker.patch('freqtrade.exchange.exchange.Exchange.fetch_trading_fees')
|
||||
class_mocker.patch('freqtrade.exchange.okx.Okx.additional_exchange_init')
|
||||
class_mocker.patch('freqtrade.exchange.binance.Binance.additional_exchange_init')
|
||||
class_mocker.patch('freqtrade.exchange.exchange.Exchange.load_cached_leverage_tiers',
|
||||
return_value=None)
|
||||
class_mocker.patch('freqtrade.exchange.exchange.Exchange.cache_leverage_tiers')
|
||||
|
||||
@ -86,7 +86,7 @@ def test_use_SVM_to_remove_outliers_and_outlier_protection(mocker, freqai_conf,
|
||||
freqai_conf['freqai']['feature_parameters'].update({"outlier_protection_percentage": 0.1})
|
||||
freqai.dk.use_SVM_to_remove_outliers(predict=False)
|
||||
assert log_has_re(
|
||||
"SVM detected 8.09%",
|
||||
"SVM detected 8.66%",
|
||||
caplog,
|
||||
)
|
||||
|
||||
|
||||
@ -80,7 +80,7 @@ def load_data_test(what, testdatadir):
|
||||
data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base
|
||||
|
||||
return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC',
|
||||
fill_missing=True)}
|
||||
fill_missing=True, drop_incomplete=True)}
|
||||
|
||||
|
||||
# FIX: fixturize this?
|
||||
@ -323,7 +323,7 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
|
||||
backtesting = Backtesting(default_conf)
|
||||
backtesting._set_strategy(backtesting.strategylist[0])
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
assert len(processed['UNITTEST/BTC']) == 102
|
||||
assert len(processed['UNITTEST/BTC']) == 103
|
||||
|
||||
# Load strategy to compare the result between Backtesting function and strategy are the same
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
@ -1165,9 +1165,9 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
|
||||
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2017-11-14 20:57:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Parameter --enable-position-stacking detected ...'
|
||||
]
|
||||
|
||||
@ -1244,9 +1244,9 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
|
||||
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2017-11-14 20:57:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Parameter --enable-position-stacking detected ...',
|
||||
f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
|
||||
'Running backtesting for Strategy StrategyTestV2',
|
||||
@ -1355,9 +1355,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
|
||||
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2017-11-14 20:57:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Parameter --enable-position-stacking detected ...',
|
||||
f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
|
||||
'Running backtesting for Strategy StrategyTestV2',
|
||||
@ -1371,7 +1371,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
|
||||
assert 'EXIT REASON STATS' in captured.out
|
||||
assert 'DAY BREAKDOWN' in captured.out
|
||||
assert 'LEFT OPEN TRADES REPORT' in captured.out
|
||||
assert '2017-11-14 21:17:00 -> 2017-11-14 22:58:00 | Max open trades : 1' in captured.out
|
||||
assert '2017-11-14 21:17:00 -> 2017-11-14 22:59:00 | Max open trades : 1' in captured.out
|
||||
assert 'STRATEGY SUMMARY' in captured.out
|
||||
|
||||
|
||||
@ -1503,9 +1503,9 @@ def test_backtest_start_nomock_futures(default_conf_usdt, mocker,
|
||||
'Parameter -i/--timeframe detected ... Using timeframe: 1h ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2021-11-17 01:00:00 '
|
||||
'up to 2021-11-21 03:00:00 (4 days).',
|
||||
'up to 2021-11-21 04:00:00 (4 days).',
|
||||
'Backtesting with data from 2021-11-17 21:00:00 '
|
||||
'up to 2021-11-21 03:00:00 (3 days).',
|
||||
'up to 2021-11-21 04:00:00 (3 days).',
|
||||
'XRP/USDT, funding_rate, 8h, data starts at 2021-11-18 00:00:00',
|
||||
'XRP/USDT, mark, 8h, data starts at 2021-11-18 00:00:00',
|
||||
f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
|
||||
@ -1616,9 +1616,9 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
|
||||
'Parameter --timeframe-detail detected, using 1m for intra-candle backtesting ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2019-10-11 00:00:00 '
|
||||
'up to 2019-10-13 11:10:00 (2 days).',
|
||||
'up to 2019-10-13 11:15:00 (2 days).',
|
||||
'Backtesting with data from 2019-10-11 01:40:00 '
|
||||
'up to 2019-10-13 11:10:00 (2 days).',
|
||||
'up to 2019-10-13 11:15:00 (2 days).',
|
||||
f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
|
||||
]
|
||||
|
||||
@ -1719,7 +1719,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda
|
||||
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
||||
f'Using data directory: {testdatadir} ...',
|
||||
'Loading data from 2017-11-14 20:57:00 '
|
||||
'up to 2017-11-14 22:58:00 (0 days).',
|
||||
'up to 2017-11-14 22:59:00 (0 days).',
|
||||
'Parameter --enable-position-stacking detected ...',
|
||||
]
|
||||
|
||||
@ -1732,7 +1732,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda
|
||||
'Running backtesting for Strategy StrategyTestV2',
|
||||
'Running backtesting for Strategy StrategyTestV3',
|
||||
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:59:00 (0 days).',
|
||||
]
|
||||
elif run_id == '2' and min_backtest_date < start_time:
|
||||
assert backtestmock.call_count == 0
|
||||
@ -1745,7 +1745,7 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda
|
||||
'Reusing result of previous backtest for StrategyTestV2',
|
||||
'Running backtesting for Strategy StrategyTestV3',
|
||||
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).',
|
||||
'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:59:00 (0 days).',
|
||||
]
|
||||
assert backtestmock.call_count == 1
|
||||
|
||||
|
||||
@ -93,11 +93,16 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
|
||||
t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
|
||||
|
||||
|
||||
def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> None:
|
||||
@pytest.mark.parametrize('leverage', [
|
||||
1, 2
|
||||
])
|
||||
def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, leverage) -> None:
|
||||
default_conf['use_exit_signal'] = False
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=10)
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=10)
|
||||
|
||||
patch_exchange(mocker)
|
||||
default_conf.update({
|
||||
"stake_amount": 100.0,
|
||||
@ -105,6 +110,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
"strategy": "StrategyTestV3"
|
||||
})
|
||||
backtesting = Backtesting(default_conf)
|
||||
backtesting._can_short = True
|
||||
backtesting._set_strategy(backtesting.strategylist[0])
|
||||
pair = 'XRP/USDT'
|
||||
row = [
|
||||
@ -120,18 +126,19 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
'', # enter_tag
|
||||
'', # exit_tag
|
||||
]
|
||||
backtesting.strategy.leverage = MagicMock(return_value=leverage)
|
||||
trade = backtesting._enter_trade(pair, row=row, direction='long')
|
||||
trade.orders[0].close_bt_order(row[0], trade)
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 100.0
|
||||
assert pytest.approx(trade.amount) == 47.61904762
|
||||
assert pytest.approx(trade.amount) == 47.61904762 * leverage
|
||||
assert len(trade.orders) == 1
|
||||
backtesting.strategy.adjust_trade_position = MagicMock(return_value=None)
|
||||
|
||||
trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 100.0
|
||||
assert pytest.approx(trade.amount) == 47.61904762
|
||||
assert pytest.approx(trade.amount) == 47.61904762 * leverage
|
||||
assert len(trade.orders) == 1
|
||||
# Increase position by 100
|
||||
backtesting.strategy.adjust_trade_position = MagicMock(return_value=100)
|
||||
@ -140,7 +147,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 200.0
|
||||
assert pytest.approx(trade.amount) == 95.23809524
|
||||
assert pytest.approx(trade.amount) == 95.23809524 * leverage
|
||||
assert len(trade.orders) == 2
|
||||
|
||||
# Reduce by more than amount - no change to trade.
|
||||
@ -150,7 +157,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 200.0
|
||||
assert pytest.approx(trade.amount) == 95.23809524
|
||||
assert pytest.approx(trade.amount) == 95.23809524 * leverage
|
||||
assert len(trade.orders) == 2
|
||||
assert trade.nr_of_successful_entries == 2
|
||||
|
||||
@ -160,7 +167,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 100.0
|
||||
assert pytest.approx(trade.amount) == 47.61904762
|
||||
assert pytest.approx(trade.amount) == 47.61904762 * leverage
|
||||
assert len(trade.orders) == 3
|
||||
assert trade.nr_of_successful_entries == 2
|
||||
assert trade.nr_of_successful_exits == 1
|
||||
@ -171,7 +178,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> Non
|
||||
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 100.0
|
||||
assert pytest.approx(trade.amount) == 47.61904762
|
||||
assert pytest.approx(trade.amount) == 47.61904762 * leverage
|
||||
assert len(trade.orders) == 3
|
||||
assert trade.nr_of_successful_entries == 2
|
||||
assert trade.nr_of_successful_exits == 1
|
||||
|
||||
@ -9,6 +9,7 @@ import pytest
|
||||
import time_machine
|
||||
|
||||
from freqtrade.constants import AVAILABLE_PAIRLISTS
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
from freqtrade.enums import CandleType, RunMode
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.persistence import Trade
|
||||
@ -40,6 +41,12 @@ def whitelist_conf(default_conf):
|
||||
"sort_key": "quoteVolume",
|
||||
},
|
||||
]
|
||||
default_conf.update({
|
||||
"external_message_consumer": {
|
||||
"enabled": True,
|
||||
"producers": [],
|
||||
}
|
||||
})
|
||||
return default_conf
|
||||
|
||||
|
||||
@ -126,7 +133,7 @@ def test_log_cached(mocker, static_pl_conf, markets, tickers):
|
||||
def test_load_pairlist_noexist(mocker, markets, default_conf):
|
||||
freqtrade = get_patched_freqtradebot(mocker, default_conf)
|
||||
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
|
||||
plm = PairListManager(freqtrade.exchange, default_conf)
|
||||
plm = PairListManager(freqtrade.exchange, default_conf, MagicMock())
|
||||
with pytest.raises(OperationalException,
|
||||
match=r"Impossible to load Pairlist 'NonexistingPairList'. "
|
||||
r"This class does not exist or contains Python code errors."):
|
||||
@ -137,7 +144,7 @@ def test_load_pairlist_noexist(mocker, markets, default_conf):
|
||||
def test_load_pairlist_verify_multi(mocker, markets_static, default_conf):
|
||||
freqtrade = get_patched_freqtradebot(mocker, default_conf)
|
||||
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_static))
|
||||
plm = PairListManager(freqtrade.exchange, default_conf)
|
||||
plm = PairListManager(freqtrade.exchange, default_conf, MagicMock())
|
||||
# Call different versions one after the other, should always consider what was passed in
|
||||
# and have no side-effects (therefore the same check multiple times)
|
||||
assert plm.verify_whitelist(['ETH/BTC', 'XRP/BTC', ], print) == ['ETH/BTC', 'XRP/BTC']
|
||||
@ -269,7 +276,7 @@ def test_refresh_pairlist_dynamic(mocker, shitcoinmarkets, tickers, whitelist_co
|
||||
with pytest.raises(OperationalException,
|
||||
match=r'`number_assets` not specified. Please check your configuration '
|
||||
r'for "pairlist.config.number_assets"'):
|
||||
PairListManager(freqtrade.exchange, whitelist_conf)
|
||||
PairListManager(freqtrade.exchange, whitelist_conf, MagicMock())
|
||||
|
||||
|
||||
def test_refresh_pairlist_dynamic_2(mocker, shitcoinmarkets, tickers, whitelist_conf_2):
|
||||
@ -694,7 +701,7 @@ def test_PrecisionFilter_error(mocker, whitelist_conf) -> None:
|
||||
|
||||
with pytest.raises(OperationalException,
|
||||
match=r"PrecisionFilter can only work with stoploss defined\..*"):
|
||||
PairListManager(MagicMock, whitelist_conf)
|
||||
PairListManager(MagicMock, whitelist_conf, MagicMock())
|
||||
|
||||
|
||||
def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None:
|
||||
@ -703,7 +710,7 @@ def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None:
|
||||
del Trade.query
|
||||
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
|
||||
exchange = get_patched_exchange(mocker, whitelist_conf)
|
||||
pm = PairListManager(exchange, whitelist_conf)
|
||||
pm = PairListManager(exchange, whitelist_conf, MagicMock())
|
||||
pm.refresh_pairlist()
|
||||
|
||||
assert log_has("PerformanceFilter is not available in this mode.", caplog)
|
||||
@ -1167,6 +1174,10 @@ def test_spreadfilter_invalid_data(mocker, default_conf, markets, tickers, caplo
|
||||
"[{'OffsetFilter': 'OffsetFilter - Taking 10 Pairs, starting from 5.'}]",
|
||||
None
|
||||
),
|
||||
({"method": "ProducerPairList"},
|
||||
"[{'ProducerPairList': 'ProducerPairList - default'}]",
|
||||
None
|
||||
),
|
||||
])
|
||||
def test_pricefilter_desc(mocker, whitelist_conf, markets, pairlistconfig,
|
||||
desc_expected, exception_expected):
|
||||
@ -1341,3 +1352,77 @@ def test_expand_pairlist_keep_invalid(wildcardlist, pairs, expected):
|
||||
expand_pairlist(wildcardlist, pairs, keep_invalid=True)
|
||||
else:
|
||||
assert sorted(expand_pairlist(wildcardlist, pairs, keep_invalid=True)) == sorted(expected)
|
||||
|
||||
|
||||
def test_ProducerPairlist_no_emc(mocker, whitelist_conf):
|
||||
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
|
||||
|
||||
whitelist_conf['pairlists'] = [
|
||||
{
|
||||
"method": "ProducerPairList",
|
||||
"number_assets": 10,
|
||||
"producer_name": "hello_world",
|
||||
}
|
||||
]
|
||||
del whitelist_conf['external_message_consumer']
|
||||
|
||||
with pytest.raises(OperationalException,
|
||||
match=r"ProducerPairList requires external_message_consumer to be enabled."):
|
||||
get_patched_freqtradebot(mocker, whitelist_conf)
|
||||
|
||||
|
||||
def test_ProducerPairlist(mocker, whitelist_conf, markets):
|
||||
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
|
||||
mocker.patch.multiple('freqtrade.exchange.Exchange',
|
||||
markets=PropertyMock(return_value=markets),
|
||||
exchange_has=MagicMock(return_value=True),
|
||||
)
|
||||
whitelist_conf['pairlists'] = [
|
||||
{
|
||||
"method": "ProducerPairList",
|
||||
"number_assets": 2,
|
||||
"producer_name": "hello_world",
|
||||
}
|
||||
]
|
||||
whitelist_conf.update({
|
||||
"external_message_consumer": {
|
||||
"enabled": True,
|
||||
"producers": [
|
||||
{
|
||||
"name": "hello_world",
|
||||
"host": "null",
|
||||
"port": 9891,
|
||||
"ws_token": "dummy",
|
||||
}
|
||||
]
|
||||
}
|
||||
})
|
||||
|
||||
exchange = get_patched_exchange(mocker, whitelist_conf)
|
||||
dp = DataProvider(whitelist_conf, exchange, None)
|
||||
pairs = ['ETH/BTC', 'LTC/BTC', 'XRP/BTC']
|
||||
# different producer
|
||||
dp._set_producer_pairs(pairs + ['MEEP/USDT'], 'default')
|
||||
pm = PairListManager(exchange, whitelist_conf, dp)
|
||||
pm.refresh_pairlist()
|
||||
assert pm.whitelist == []
|
||||
# proper producer
|
||||
dp._set_producer_pairs(pairs, 'hello_world')
|
||||
pm.refresh_pairlist()
|
||||
|
||||
# Pairlist reduced to 2
|
||||
assert pm.whitelist == pairs[:2]
|
||||
assert len(pm.whitelist) == 2
|
||||
whitelist_conf['exchange']['pair_whitelist'] = ['TKN/BTC']
|
||||
|
||||
whitelist_conf['pairlists'] = [
|
||||
{"method": "StaticPairList"},
|
||||
{
|
||||
"method": "ProducerPairList",
|
||||
"producer_name": "hello_world",
|
||||
}
|
||||
]
|
||||
pm = PairListManager(exchange, whitelist_conf, dp)
|
||||
pm.refresh_pairlist()
|
||||
assert len(pm.whitelist) == 4
|
||||
assert pm.whitelist == ['TKN/BTC'] + pairs
|
||||
|
||||
@ -207,10 +207,13 @@ async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker):
|
||||
})
|
||||
|
||||
dp = DataProvider(default_conf, None, None, None)
|
||||
# Handle start explicitly to avoid messing with threading in tests
|
||||
mocker.patch("freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start",)
|
||||
emc = ExternalMessageConsumer(default_conf, dp)
|
||||
|
||||
try:
|
||||
await asyncio.sleep(0.01)
|
||||
emc._running = True
|
||||
await emc._create_connection(emc.producers[0], asyncio.Lock())
|
||||
assert log_has_re(r".+ is an invalid WebSocket URL .+", caplog)
|
||||
finally:
|
||||
emc.shutdown()
|
||||
|
||||
@ -365,6 +365,14 @@ def test_exception_send_msg(default_conf, mocker, caplog):
|
||||
with pytest.raises(NotImplementedError):
|
||||
webhook.send_msg(msg)
|
||||
|
||||
# Test no failure for not implemented but known messagetypes
|
||||
for e in RPCMessageType:
|
||||
msg = {
|
||||
'type': e,
|
||||
'status': 'whatever'
|
||||
}
|
||||
webhook.send_msg(msg)
|
||||
|
||||
|
||||
def test__send_msg(default_conf, mocker, caplog):
|
||||
default_conf["webhook"] = get_webhook_dict()
|
||||
|
||||
@ -288,7 +288,7 @@ def test_advise_all_indicators(default_conf, testdatadir) -> None:
|
||||
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
|
||||
fill_up_missing=True)
|
||||
processed = strategy.advise_all_indicators(data)
|
||||
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
|
||||
assert len(processed['UNITTEST/BTC']) == 103
|
||||
|
||||
|
||||
def test_populate_any_indicators(default_conf, testdatadir) -> None:
|
||||
@ -300,7 +300,7 @@ def test_populate_any_indicators(default_conf, testdatadir) -> None:
|
||||
processed = strategy.populate_any_indicators('UNITTEST/BTC', data, '5m')
|
||||
assert processed == data
|
||||
assert id(processed) == id(data)
|
||||
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
|
||||
assert len(processed['UNITTEST/BTC']) == 103
|
||||
|
||||
|
||||
def test_freqai_not_initialized(default_conf) -> None:
|
||||
|
||||
@ -28,6 +28,7 @@ from tests.conftest import (create_mock_trades, create_mock_trades_usdt, get_pat
|
||||
from tests.conftest_trades import (MOCK_TRADE_COUNT, entry_side, exit_side, mock_order_1,
|
||||
mock_order_2, mock_order_2_sell, mock_order_3, mock_order_3_sell,
|
||||
mock_order_4, mock_order_5_stoploss, mock_order_6_sell)
|
||||
from tests.conftest_trades_usdt import mock_trade_usdt_4
|
||||
|
||||
|
||||
def patch_RPCManager(mocker) -> MagicMock:
|
||||
@ -1060,6 +1061,7 @@ def test_add_stoploss_on_exchange(mocker, default_conf_usdt, limit_order, is_sho
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.is_short = is_short
|
||||
trade.open_order_id = None
|
||||
@ -1101,6 +1103,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_
|
||||
# First case: when stoploss is not yet set but the order is open
|
||||
# should get the stoploss order id immediately
|
||||
# and should return false as no trade actually happened
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.is_short = is_short
|
||||
trade.is_open = True
|
||||
@ -1879,6 +1882,7 @@ def test_exit_positions(mocker, default_conf_usdt, limit_order, is_short, caplog
|
||||
return_value=limit_order[entry_side(is_short)])
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.is_short = is_short
|
||||
trade.open_order_id = '123'
|
||||
@ -1902,6 +1906,7 @@ def test_exit_positions_exception(mocker, default_conf_usdt, limit_order, caplog
|
||||
order = limit_order[entry_side(is_short)]
|
||||
mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.is_short = is_short
|
||||
trade.open_order_id = None
|
||||
@ -2042,6 +2047,7 @@ def test_update_trade_state_exception(mocker, default_conf_usdt, is_short, limit
|
||||
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
|
||||
mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.open_order_id = '123'
|
||||
trade.amount = 123
|
||||
@ -2060,6 +2066,7 @@ def test_update_trade_state_orderexception(mocker, default_conf_usdt, caplog) ->
|
||||
mocker.patch('freqtrade.exchange.Exchange.fetch_order',
|
||||
MagicMock(side_effect=InvalidOrderException))
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
trade.open_order_id = '123'
|
||||
|
||||
@ -2661,6 +2668,7 @@ def test_manage_open_orders_exit_usercustom(
|
||||
rpc_mock = patch_RPCManager(mocker)
|
||||
cancel_order_mock = MagicMock()
|
||||
patch_exchange(mocker)
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=0.0)
|
||||
et_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit')
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
@ -2673,7 +2681,6 @@ def test_manage_open_orders_exit_usercustom(
|
||||
open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
|
||||
open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
|
||||
open_trade_usdt.close_profit_abs = 0.001
|
||||
open_trade_usdt.is_open = False
|
||||
|
||||
Trade.query.session.add(open_trade_usdt)
|
||||
Trade.commit()
|
||||
@ -2687,7 +2694,6 @@ def test_manage_open_orders_exit_usercustom(
|
||||
freqtrade.manage_open_orders()
|
||||
assert cancel_order_mock.call_count == 0
|
||||
assert rpc_mock.call_count == 1
|
||||
assert open_trade_usdt.is_open is False
|
||||
assert freqtrade.strategy.check_exit_timeout.call_count == 1
|
||||
assert freqtrade.strategy.check_entry_timeout.call_count == 0
|
||||
|
||||
@ -2697,7 +2703,6 @@ def test_manage_open_orders_exit_usercustom(
|
||||
freqtrade.manage_open_orders()
|
||||
assert cancel_order_mock.call_count == 0
|
||||
assert rpc_mock.call_count == 1
|
||||
assert open_trade_usdt.is_open is False
|
||||
assert freqtrade.strategy.check_exit_timeout.call_count == 1
|
||||
assert freqtrade.strategy.check_entry_timeout.call_count == 0
|
||||
|
||||
@ -2707,7 +2712,6 @@ def test_manage_open_orders_exit_usercustom(
|
||||
freqtrade.manage_open_orders()
|
||||
assert cancel_order_mock.call_count == 1
|
||||
assert rpc_mock.call_count == 2
|
||||
assert open_trade_usdt.is_open is True
|
||||
assert freqtrade.strategy.check_exit_timeout.call_count == 1
|
||||
assert freqtrade.strategy.check_entry_timeout.call_count == 0
|
||||
|
||||
@ -2748,14 +2752,14 @@ def test_manage_open_orders_exit(
|
||||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=ticker_usdt,
|
||||
fetch_order=MagicMock(return_value=limit_sell_order_old),
|
||||
cancel_order=cancel_order_mock
|
||||
cancel_order=cancel_order_mock,
|
||||
get_min_pair_stake_amount=MagicMock(return_value=0),
|
||||
)
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
|
||||
open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
|
||||
open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
|
||||
open_trade_usdt.close_profit_abs = 0.001
|
||||
open_trade_usdt.is_open = False
|
||||
open_trade_usdt.is_short = is_short
|
||||
|
||||
Trade.query.session.add(open_trade_usdt)
|
||||
@ -2796,7 +2800,6 @@ def test_check_handle_cancelled_exit(
|
||||
|
||||
open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
|
||||
open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
|
||||
open_trade_usdt.is_open = False
|
||||
open_trade_usdt.is_short = is_short
|
||||
|
||||
Trade.query.session.add(open_trade_usdt)
|
||||
@ -2984,7 +2987,7 @@ def test_manage_open_orders_exception(default_conf_usdt, ticker_usdt, open_trade
|
||||
|
||||
|
||||
@pytest.mark.parametrize("is_short", [False, True])
|
||||
def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_short) -> None:
|
||||
def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_short, fee) -> None:
|
||||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
l_order = limit_order[entry_side(is_short)]
|
||||
@ -2998,15 +3001,12 @@ def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
freqtrade._notify_enter_cancel = MagicMock()
|
||||
|
||||
# TODO: Convert to real trade
|
||||
trade = MagicMock()
|
||||
trade.pair = 'LTC/USDT'
|
||||
trade.open_rate = 200
|
||||
trade.is_short = False
|
||||
trade.entry_side = "buy"
|
||||
trade = mock_trade_usdt_4(fee, is_short)
|
||||
Trade.query.session.add(trade)
|
||||
Trade.commit()
|
||||
|
||||
l_order['filled'] = 0.0
|
||||
l_order['status'] = 'open'
|
||||
trade.nr_of_successful_entries = 0
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
assert freqtrade.handle_cancel_enter(trade, l_order, reason)
|
||||
assert cancel_order_mock.call_count == 1
|
||||
@ -3038,7 +3038,7 @@ def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_
|
||||
@pytest.mark.parametrize("is_short", [False, True])
|
||||
@pytest.mark.parametrize("limit_buy_order_canceled_empty", ['binance', 'ftx', 'kraken', 'bittrex'],
|
||||
indirect=['limit_buy_order_canceled_empty'])
|
||||
def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_short,
|
||||
def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_short, fee,
|
||||
limit_buy_order_canceled_empty) -> None:
|
||||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
@ -3049,11 +3049,10 @@ def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_sho
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
# TODO: Convert to real trade
|
||||
trade = MagicMock()
|
||||
trade.nr_of_successful_entries = 0
|
||||
trade.pair = 'LTC/ETH'
|
||||
trade.entry_side = "sell" if is_short else "buy"
|
||||
|
||||
trade = mock_trade_usdt_4(fee, is_short)
|
||||
Trade.query.session.add(trade)
|
||||
Trade.commit()
|
||||
assert freqtrade.handle_cancel_enter(trade, limit_buy_order_canceled_empty, reason)
|
||||
assert cancel_order_mock.call_count == 0
|
||||
assert log_has_re(
|
||||
@ -3071,7 +3070,7 @@ def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_sho
|
||||
'String Return value',
|
||||
123
|
||||
])
|
||||
def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order, is_short,
|
||||
def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order, is_short, fee,
|
||||
cancelorder) -> None:
|
||||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
@ -3079,19 +3078,15 @@ def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order
|
||||
cancel_order_mock = MagicMock(return_value=cancelorder)
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
cancel_order=cancel_order_mock
|
||||
cancel_order=cancel_order_mock,
|
||||
fetch_order=MagicMock(side_effect=InvalidOrderException)
|
||||
)
|
||||
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
freqtrade._notify_enter_cancel = MagicMock()
|
||||
# TODO: Convert to real trade
|
||||
trade = MagicMock()
|
||||
trade.pair = 'LTC/USDT'
|
||||
trade.entry_side = "buy"
|
||||
trade.open_rate = 200
|
||||
trade.entry_side = "buy"
|
||||
trade.open_order_id = "open_order_noop"
|
||||
trade.nr_of_successful_entries = 0
|
||||
trade = mock_trade_usdt_4(fee, is_short)
|
||||
Trade.query.session.add(trade)
|
||||
Trade.commit()
|
||||
l_order['filled'] = 0.0
|
||||
l_order['status'] = 'open'
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
@ -3121,20 +3116,21 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
|
||||
amount=2,
|
||||
exchange='binance',
|
||||
open_rate=0.245441,
|
||||
open_order_id="123456",
|
||||
open_order_id="sell_123456",
|
||||
open_date=arrow.utcnow().shift(days=-2).datetime,
|
||||
fee_open=fee.return_value,
|
||||
fee_close=fee.return_value,
|
||||
close_rate=0.555,
|
||||
close_date=arrow.utcnow().datetime,
|
||||
exit_reason="sell_reason_whatever",
|
||||
stake_amount=0.245441 * 2,
|
||||
)
|
||||
trade.orders = [
|
||||
Order(
|
||||
Order(
|
||||
ft_order_side='buy',
|
||||
ft_pair=trade.pair,
|
||||
ft_is_open=True,
|
||||
order_id='123456',
|
||||
ft_is_open=False,
|
||||
order_id='buy_123456',
|
||||
status="closed",
|
||||
symbol=trade.pair,
|
||||
order_type="market",
|
||||
@ -3147,15 +3143,33 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
|
||||
order_date=trade.open_date,
|
||||
order_filled_date=trade.open_date,
|
||||
),
|
||||
Order(
|
||||
ft_order_side='sell',
|
||||
ft_pair=trade.pair,
|
||||
ft_is_open=True,
|
||||
order_id='sell_123456',
|
||||
status="open",
|
||||
symbol=trade.pair,
|
||||
order_type="limit",
|
||||
side="sell",
|
||||
price=trade.open_rate,
|
||||
average=trade.open_rate,
|
||||
filled=0.0,
|
||||
remaining=trade.amount,
|
||||
cost=trade.open_rate * trade.amount,
|
||||
order_date=trade.open_date,
|
||||
order_filled_date=trade.open_date,
|
||||
),
|
||||
]
|
||||
order = {'id': "123456",
|
||||
order = {'id': "sell_123456",
|
||||
'remaining': 1,
|
||||
'amount': 1,
|
||||
'status': "open"}
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
send_msg_mock.reset_mock()
|
||||
assert freqtrade.handle_cancel_exit(trade, order, reason)
|
||||
assert cancel_order_mock.call_count == 1
|
||||
assert send_msg_mock.call_count == 2
|
||||
assert send_msg_mock.call_count == 1
|
||||
assert trade.close_rate is None
|
||||
assert trade.exit_reason is None
|
||||
|
||||
@ -3181,11 +3195,13 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
|
||||
def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None:
|
||||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
mocker.patch(
|
||||
'freqtrade.exchange.Exchange.cancel_order_with_result', side_effect=InvalidOrderException())
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=0.0)
|
||||
mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result',
|
||||
side_effect=InvalidOrderException())
|
||||
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
|
||||
# TODO: should not be magicmock
|
||||
trade = MagicMock()
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
order = {'remaining': 1,
|
||||
|
||||
@ -2,7 +2,7 @@ from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
from freqtrade.enums import ExitCheckTuple, ExitType
|
||||
from freqtrade.enums import ExitCheckTuple, ExitType, TradingMode
|
||||
from freqtrade.persistence import Trade
|
||||
from freqtrade.persistence.models import Order
|
||||
from freqtrade.rpc.rpc import RPC
|
||||
@ -455,10 +455,12 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
|
||||
assert pytest.approx(trade.orders[-1].amount) == 61.538461232
|
||||
|
||||
|
||||
def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> None:
|
||||
@pytest.mark.parametrize('leverage', [1, 2])
|
||||
def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog, leverage) -> None:
|
||||
default_conf_usdt['position_adjustment_enable'] = True
|
||||
|
||||
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
|
||||
freqtrade.trading_mode = TradingMode.FUTURES
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=ticker_usdt,
|
||||
@ -467,15 +469,17 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non
|
||||
price_to_precision=lambda s, x, y: y,
|
||||
get_min_pair_stake_amount=MagicMock(return_value=10),
|
||||
)
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=10)
|
||||
|
||||
patch_get_signal(freqtrade)
|
||||
freqtrade.strategy.leverage = MagicMock(return_value=leverage)
|
||||
freqtrade.enter_positions()
|
||||
|
||||
assert len(Trade.get_trades().all()) == 1
|
||||
trade = Trade.get_trades().first()
|
||||
assert len(trade.orders) == 1
|
||||
assert pytest.approx(trade.stake_amount) == 60
|
||||
assert pytest.approx(trade.amount) == 30.0
|
||||
assert pytest.approx(trade.amount) == 30.0 * leverage
|
||||
assert trade.open_rate == 2.0
|
||||
|
||||
# Too small size
|
||||
@ -484,8 +488,9 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non
|
||||
trade = Trade.get_trades().first()
|
||||
assert len(trade.orders) == 1
|
||||
assert pytest.approx(trade.stake_amount) == 60
|
||||
assert pytest.approx(trade.amount) == 30.0
|
||||
assert log_has_re("Remaining amount of 1.6.* would be smaller than the minimum of 10.", caplog)
|
||||
assert pytest.approx(trade.amount) == 30.0 * leverage
|
||||
assert log_has_re(
|
||||
r"Remaining amount of \d\.\d+.* would be smaller than the minimum of 10.", caplog)
|
||||
|
||||
freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-20)
|
||||
|
||||
@ -494,7 +499,7 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non
|
||||
assert len(trade.orders) == 2
|
||||
assert trade.orders[-1].ft_order_side == 'sell'
|
||||
assert pytest.approx(trade.stake_amount) == 40.198
|
||||
assert pytest.approx(trade.amount) == 20.099
|
||||
assert pytest.approx(trade.amount) == 20.099 * leverage
|
||||
assert trade.open_rate == 2.0
|
||||
assert trade.is_open
|
||||
caplog.clear()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user