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Update populate_buy_trend to populate_entry_trend

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Matthias
2022-03-12 10:49:00 +01:00
parent 9d6d8043ee
commit 59791b0659
4 changed files with 17 additions and 17 deletions
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18
docs/strategy-customization.md
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@@ -101,7 +101,7 @@ With this section, you have a new column in your dataframe, which has `1` assign
Buy and sell strategies need indicators. You can add more indicators by extending the list contained in the method `populate_indicators()` from your strategy file.
You should only add the indicators used in either `populate_buy_trend()`, `populate_sell_trend()`, or to populate another indicator, otherwise performance may suffer.
You should only add the indicators used in either `populate_entry_trend()`, `populate_sell_trend()`, or to populate another indicator, otherwise performance may suffer.
It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
@@ -201,7 +201,7 @@ If this data is available, indicators will be calculated with this extended time
### Entry signal rules
Edit the method `populate_buy_trend()` in your strategy file to update your entry strategy.
Edit the method `populate_entry_trend()` in your strategy file to update your entry strategy.
It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
@@ -210,7 +210,7 @@ This method will also define a new column, `"enter_long"`, which needs to contai
Sample from `user_data/strategies/sample_strategy.py`:
```python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame populated with indicators
@@ -236,7 +236,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
Please make sure to set [`can_short`]() appropriately on your strategy if you intend to short.
```python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
@@ -397,7 +397,7 @@ Disabling of this will have short signals ignored (also in futures markets).
### Metadata dict
The metadata-dict (available for `populate_buy_trend`, `populate_sell_trend`, `populate_indicators`) contains additional information.
The metadata-dict (available for `populate_entry_trend`, `populate_sell_trend`, `populate_indicators`) contains additional information.
Currently this is `pair`, which can be accessed using `metadata['pair']` - and will return a pair in the format `XRP/BTC`.
The Metadata-dict should not be modified and does not persist information across multiple calls.
@@ -567,7 +567,7 @@ for more information.
Use string formatting when accessing informative dataframes of other pairs. This will allow easily changing stake currency in config without having to adjust strategy code.
``` python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
stake = self.config['stake_currency']
dataframe.loc[
(
@@ -782,7 +782,7 @@ class SampleStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
@@ -1050,11 +1050,11 @@ if self.config['runmode'].value in ('live', 'dry_run'):
## Print created dataframe
To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.
To inspect the created dataframe, you can issue a print-statement in either `populate_entry_trend()` or `populate_sell_trend()`.
You may also want to print the pair so it's clear what data is currently shown.
``` python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
#>> whatever condition<<<