mohammadian7/freqtrade
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Further increase typehints in freqAI interface

Browse Source
This commit is contained in:
Matthias
2023-04-23 19:36:17 +02:00
parent c5dc21e80c
commit ad4996259e
5 changed files with 19 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docs/freqai-feature-engineering.md
+4 -4
View File
@@ -16,7 +16,7 @@ Meanwhile, high level feature engineering is handled within `"feature_parameters
It is advisable to start from the template `feature_engineering_*` functions in the source provided example strategy (found in `templates/FreqaiExampleStrategy.py`) to ensure that the feature definitions are following the correct conventions. Here is an example of how to set the indicators and labels in the strategy:
```python
def feature_engineering_expand_all(self, dataframe, period, metadata, **kwargs):
def feature_engineering_expand_all(self, dataframe: DataFrame, period, metadata, **kwargs) -> DataFrame:
"""
*Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined
@@ -67,7 +67,7 @@ It is advisable to start from the template `feature_engineering_*` functions in
return dataframe
def feature_engineering_expand_basic(self, dataframe, metadata, **kwargs):
def feature_engineering_expand_basic(self, dataframe: DataFrame, metadata, **kwargs) -> DataFrame:
"""
*Only functional with FreqAI enabled strategies*
This function will automatically expand the defined features on the config defined
@@ -96,7 +96,7 @@ It is advisable to start from the template `feature_engineering_*` functions in
dataframe["%-raw_price"] = dataframe["close"]
return dataframe
def feature_engineering_standard(self, dataframe, metadata, **kwargs):
def feature_engineering_standard(self, dataframe: DataFrame, metadata, **kwargs) -> DataFrame:
"""
*Only functional with FreqAI enabled strategies*
This optional function will be called once with the dataframe of the base timeframe.
@@ -122,7 +122,7 @@ It is advisable to start from the template `feature_engineering_*` functions in
dataframe["%-hour_of_day"] = (dataframe["date"].dt.hour + 1) / 25
return dataframe
def set_freqai_targets(self, dataframe, metadata, **kwargs):
def set_freqai_targets(self, dataframe: DataFrame, metadata, **kwargs) -> DataFrame:
"""
*Only functional with FreqAI enabled strategies*
Required function to set the targets for the model.