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Switch from pair(str) to metadata(dict)

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Matthias
2018-07-29 20:36:03 +02:00
parent 941879dc19
commit 787d6042de
7 changed files with 64 additions and 57 deletions
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28
docs/bot-optimization.md
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@@ -39,7 +39,6 @@ A strategy file contains all the information needed to build a good strategy:
- Sell strategy rules
- Minimal ROI recommended
- Stoploss recommended
- Hyperopt parameter
The bot also include a sample strategy called `TestStrategy` you can update: `user_data/strategies/test_strategy.py`.
You can test it with the parameter: `--strategy TestStrategy`
@@ -61,17 +60,16 @@ file as reference.**
### Buy strategy
Edit the method `populate_buy_trend()` into your strategy file to
update your buy strategy.
Edit the method `populate_buy_trend()` into your strategy file to update your buy strategy.
Sample from `user_data/strategies/test_strategy.py`:
```python
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
def populate_buy_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
:param pair: Pair currently analyzed
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
@@ -93,11 +91,11 @@ Please note that the sell-signal is only used if `use_sell_signal` is set to tru
Sample from `user_data/strategies/test_strategy.py`:
```python
def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param pair: Pair currently analyzed
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
@@ -110,7 +108,7 @@ def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
return dataframe
```
## Add more Indicator
## Add more Indicators
As you have seen, 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.
@@ -119,9 +117,16 @@ You should only add the indicators used in either `populate_buy_trend()`, `popul
Sample:
```python
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
dataframe['sar'] = ta.SAR(dataframe)
dataframe['adx'] = ta.ADX(dataframe)
@@ -152,6 +157,11 @@ def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
return dataframe
```
### Metadata dict
The metadata-dict (available for `populate_buy_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`.
### Want more indicator examples
Look into the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py).