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Adding the pair name when populating indicators allowing the strategy to have customized context for a pair

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This commit is contained in:
Jean-Baptiste LE STANG 2018-01-30 15:03:38 +01:00
parent 5f86c389b0
commit 26e288e655
14 changed files with 46 additions and 46 deletions
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6
docs/bot-optimization.md
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@ -51,7 +51,7 @@ update your buy strategy.
Sample from `user_data/strategies/test_strategy.py`:
```python
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair : str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
@ -74,7 +74,7 @@ update your sell strategy.
Sample from `user_data/strategies/test_strategy.py`:
```python
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, pair : str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
@ -97,7 +97,7 @@ the method `populate_indicators()` from your strategy file.
Sample:
```python
def populate_indicators(dataframe: DataFrame) -> DataFrame:
def populate_indicators(dataframe: DataFrame, pair : str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
"""

6
docs/hyperopt.md
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@ -42,7 +42,7 @@ If you have updated the buy strategy, means change the content of
As for an example if your `populate_buy_trend()` method is:
```python
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
dataframe.loc[
(dataframe['rsi'] < 35) &
(dataframe['adx'] > 65),
@ -81,7 +81,7 @@ space = {
...
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['adx']['enabled']:
@ -280,7 +280,7 @@ at `adx`-block, that translates to the following code block:
So translating your whole hyperopt result to as the new buy-signal
would be the following:
```
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 15.0) & # adx-value

22
freqtrade/analyze.py
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@ -37,7 +37,7 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
return frame
def populate_indicators(dataframe: DataFrame) -> DataFrame:
def populate_indicators(dataframe: DataFrame, pair: str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
@ -46,39 +46,39 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
"""
strategy = Strategy()
return strategy.populate_indicators(dataframe=dataframe)
return strategy.populate_indicators(dataframe=dataframe, pair=pair)
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
strategy = Strategy()
return strategy.populate_buy_trend(dataframe=dataframe)
return strategy.populate_buy_trend(dataframe=dataframe, pair=pair)
def populate_sell_trend(dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
strategy = Strategy()
return strategy.populate_sell_trend(dataframe=dataframe)
return strategy.populate_sell_trend(dataframe=dataframe, pair=pair)
def analyze_ticker(ticker_history: List[Dict]) -> DataFrame:
def analyze_ticker(ticker_history: List[Dict], pair: str) -> DataFrame:
"""
Parses the given ticker history and returns a populated DataFrame
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
dataframe = parse_ticker_dataframe(ticker_history)
dataframe = populate_indicators(dataframe)
dataframe = populate_buy_trend(dataframe)
dataframe = populate_sell_trend(dataframe)
dataframe = populate_indicators(dataframe, pair)
dataframe = populate_buy_trend(dataframe, pair)
dataframe = populate_sell_trend(dataframe, pair)
return dataframe
@ -96,7 +96,7 @@ def get_signal(pair: str, interval: int) -> (bool, bool):
return (False, False) # return False ?
try:
dataframe = analyze_ticker(ticker_hist)
dataframe = analyze_ticker(ticker_hist, pair)
except ValueError as ex:
logger.warning('Unable to analyze ticker for pair %s: %s', pair, str(ex))
return (False, False) # return False ?

2
freqtrade/optimize/__init__.py
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@ -91,7 +91,7 @@ def tickerdata_to_dataframe(data):
def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
"""Creates a dataframe and populates indicators for given ticker data"""
return {pair: populate_indicators(parse_ticker_dataframe(pair_data))
return {pair: populate_indicators(parse_ticker_dataframe(pair_data), pair)
for pair, pair_data in tickerdata.items()}

2
freqtrade/optimize/backtesting.py
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@ -117,7 +117,7 @@ def backtest(args) -> DataFrame:
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0
ticker = populate_sell_trend(populate_buy_trend(pair_data))
ticker = populate_sell_trend(populate_buy_trend(pair_data, pair), pair)
# for each buy point
lock_pair_until = None
headers = ['buy', 'open', 'close', 'date', 'sell']

4
freqtrade/optimize/hyperopt.py
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@ -61,7 +61,7 @@ TRIALS = Trials()
main._CONF = OPTIMIZE_CONFIG
def populate_indicators(dataframe: DataFrame) -> DataFrame:
def populate_indicators(dataframe: DataFrame, pair: str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
"""
@ -320,7 +320,7 @@ def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the buy strategy parameters to be used by hyperopt
"""
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if 'uptrend_long_ema' in params and params['uptrend_long_ema']['enabled']:

6
freqtrade/strategy/default_strategy.py
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@ -29,7 +29,7 @@ class DefaultStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = 5
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
@ -196,7 +196,7 @@ class DefaultStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
@ -217,7 +217,7 @@ class DefaultStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame

6
freqtrade/strategy/interface.py
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@ -19,7 +19,7 @@ class IStrategy(ABC):
"""
@abstractmethod
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Populate indicators that will be used in the Buy and Sell strategy
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
@ -27,7 +27,7 @@ class IStrategy(ABC):
"""
@abstractmethod
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
@ -36,7 +36,7 @@ class IStrategy(ABC):
"""
@abstractmethod
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame

12
freqtrade/strategy/strategy.py
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@ -143,27 +143,27 @@ class Strategy(object):
return path
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Populate indicators that will be used in the Buy and Sell strategy
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:return: a Dataframe with all mandatory indicators for the strategies
"""
return self.custom_strategy.populate_indicators(dataframe)
return self.custom_strategy.populate_indicators(dataframe, pair)
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
:return:
"""
return self.custom_strategy.populate_buy_trend(dataframe)
return self.custom_strategy.populate_buy_trend(dataframe, pair)
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
return self.custom_strategy.populate_sell_trend(dataframe)
return self.custom_strategy.populate_sell_trend(dataframe, pair)

6
freqtrade/tests/strategy/test_default_strategy.py
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@ -30,7 +30,7 @@ def test_default_strategy(result):
assert type(strategy.minimal_roi) is dict
assert type(strategy.stoploss) is float
assert type(strategy.ticker_interval) is int
indicators = strategy.populate_indicators(result)
indicators = strategy.populate_indicators(result, None)
assert type(indicators) is DataFrame
assert type(strategy.populate_buy_trend(indicators)) is DataFrame
assert type(strategy.populate_sell_trend(indicators)) is DataFrame
assert type(strategy.populate_buy_trend(indicators, None)) is DataFrame
assert type(strategy.populate_sell_trend(indicators, None)) is DataFrame

8
freqtrade/tests/strategy/test_strategy.py
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@ -37,7 +37,7 @@ def test_load_strategy(result):
assert not hasattr(Strategy, 'custom_strategy')
assert hasattr(strategy.custom_strategy, 'populate_indicators')
assert 'adx' in strategy.populate_indicators(result)
assert 'adx' in strategy.populate_indicators(result, None)
def test_strategy(result):
@ -51,14 +51,14 @@ def test_strategy(result):
assert strategy.stoploss == -0.10
assert hasattr(strategy.custom_strategy, 'populate_indicators')
assert 'adx' in strategy.populate_indicators(result)
assert 'adx' in strategy.populate_indicators(result, None)
assert hasattr(strategy.custom_strategy, 'populate_buy_trend')
dataframe = strategy.populate_buy_trend(strategy.populate_indicators(result))
dataframe = strategy.populate_buy_trend(strategy.populate_indicators(result, None), None)
assert 'buy' in dataframe.columns
assert hasattr(strategy.custom_strategy, 'populate_sell_trend')
dataframe = strategy.populate_sell_trend(strategy.populate_indicators(result))
dataframe = strategy.populate_sell_trend(strategy.populate_indicators(result, None), None)
assert 'sell' in dataframe.columns

4
freqtrade/tests/test_analyze.py
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@ -26,7 +26,7 @@ def test_populates_buy_trend(result):
# Load the default strategy for the unit test, because this logic is done in main.py
Strategy().init({'strategy': 'default_strategy'})
dataframe = populate_buy_trend(populate_indicators(result))
dataframe = populate_buy_trend(populate_indicators(result, None), None)
assert 'buy' in dataframe.columns
@ -34,7 +34,7 @@ def test_populates_sell_trend(result):
# Load the default strategy for the unit test, because this logic is done in main.py
Strategy().init({'strategy': 'default_strategy'})
dataframe = populate_sell_trend(populate_indicators(result))
dataframe = populate_sell_trend(populate_indicators(result, None), None)
assert 'sell' in dataframe.columns

2
freqtrade/tests/test_dataframe.py
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@ -12,7 +12,7 @@ def load_dataframe_pair(pairs):
assert isinstance(ld, dict)
assert isinstance(pairs[0], str)
dataframe = ld[pairs[0]]
dataframe = analyze.analyze_ticker(dataframe)
dataframe = analyze.analyze_ticker(dataframe, pairs[0])
return dataframe

6
user_data/strategies/test_strategy.py
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@ -47,7 +47,7 @@ class TestStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = 5
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
@ -214,7 +214,7 @@ class TestStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
@ -230,7 +230,7 @@ class TestStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame