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overload populate_indicators to work with and without pair argumen 

all while not breaking users strategies
This commit is contained in:
Matthias 2018-07-22 17:39:35 +02:00
parent 98665dcef4
commit f286ba6b87
5 changed files with 82 additions and 65 deletions
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6
freqtrade/strategy/default_strategy.py
View File

@ -28,7 +28,7 @@ class DefaultStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def advise_indicators(self, dataframe: DataFrame, pair: str) -> 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 advise_buy(self, dataframe: DataFrame, pair: str) -> 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
@ -218,7 +218,7 @@ class DefaultStrategy(IStrategy):
return dataframe
def advise_sell(self, dataframe: DataFrame, pair: str) -> 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

53
freqtrade/strategy/interface.py
View File

@ -3,7 +3,7 @@ IStrategy interface
This module defines the interface to apply for strategies
"""
import logging
from abc import ABC
from abc import ABC, abstractmethod
from datetime import datetime
from enum import Enum
from typing import Dict, List, NamedTuple, Tuple
@ -70,37 +70,32 @@ class IStrategy(ABC):
def __init__(self, config: dict) -> None:
self.config = config
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
@abstractmethod
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()
:param pair: Pair currently analyzed
:return: a Dataframe with all mandatory indicators for the strategies
"""
warnings.warn("deprecated - please replace this method with advise_indicators!",
DeprecationWarning)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
@abstractmethod
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
:param pair: Pair currently analyzed
:return: DataFrame with buy column
"""
warnings.warn("deprecated - please replace this method with advise_buy!",
DeprecationWarning)
dataframe.loc[(), 'buy'] = 0
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
@abstractmethod
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
:param pair: Pair currently analyzed
:return: DataFrame with sell column
"""
warnings.warn("deprecated - please replace this method with advise_sell!",
DeprecationWarning)
dataframe.loc[(), 'sell'] = 0
return dataframe
def get_strategy_name(self) -> str:
"""
@ -283,30 +278,44 @@ class IStrategy(ABC):
def advise_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Populate indicators that will be used in the Buy and Sell strategy
If not overridden, calls the legacy method `populate_indicators to keep strategies working
This method should not be overridden.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:param pair: The currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
return self.populate_indicators(dataframe)
if len(self.populate_indicators.__annotations__) == 2:
warnings.warn("deprecated - check out the Sample strategy to see "
"the current function headers!", DeprecationWarning)
return self.populate_indicators(dataframe) # type: ignore
else:
return self.populate_indicators(dataframe, pair)
def advise_buy(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
If not overridden, calls the legacy method `populate_buy_trend to keep strategies working
This method should not be overridden.
:param dataframe: DataFrame
:param pair: The currently traded pair
:return: DataFrame with buy column
"""
return self.populate_buy_trend(dataframe)
if len(self.populate_buy_trend.__annotations__) == 2:
warnings.warn("deprecated - check out the Sample strategy to see "
"the current function headers!", DeprecationWarning)
return self.populate_buy_trend(dataframe) # type: ignore
else:
return self.populate_buy_trend(dataframe, pair)
def advise_sell(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
If not overridden, calls the legacy method `populate_sell_trend to keep strategies working
This method should not be overridden.
:param dataframe: DataFrame
:param pair: The currently traded pair
:return: DataFrame with sell column
"""
return self.populate_sell_trend(dataframe)
if len(self.populate_sell_trend.__annotations__) == 2:
warnings.warn("deprecated - check out the Sample strategy to see "
"the current function headers!", DeprecationWarning)
return self.populate_sell_trend(dataframe) # type: ignore
else:
return self.populate_sell_trend(dataframe, pair)

7
freqtrade/tests/strategy/test_default_strategy.py
View File

@ -25,10 +25,11 @@ def test_default_strategy_structure():
def test_default_strategy(result):
strategy = DefaultStrategy({})
pair = 'ETH/BTC'
assert type(strategy.minimal_roi) is dict
assert type(strategy.stoploss) is float
assert type(strategy.ticker_interval) is str
indicators = strategy.populate_indicators(result)
indicators = strategy.populate_indicators(result, pair)
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, pair)) is DataFrame
assert type(strategy.populate_sell_trend(indicators, pair)) is DataFrame

75
freqtrade/tests/strategy/test_strategy.py
View File

@ -1,10 +1,10 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import logging
from os import path
from unittest.mock import MagicMock
import warnings
import pytest
from pandas import DataFrame
from freqtrade.strategy import import_strategy
from freqtrade.strategy.default_strategy import DefaultStrategy
@ -60,6 +60,9 @@ def test_search_strategy():
def test_load_strategy(result):
resolver = StrategyResolver({'strategy': 'TestStrategy'})
pair = 'ETH/BTC'
assert len(resolver.strategy.populate_indicators.__annotations__) == 3
assert 'dataframe' in resolver.strategy.populate_indicators.__annotations__
assert 'pair' in resolver.strategy.populate_indicators.__annotations__
assert 'adx' in resolver.strategy.advise_indicators(result, pair=pair)
@ -158,39 +161,35 @@ def test_strategy_override_ticker_interval(caplog):
def test_deprecate_populate_indicators(result):
resolver = StrategyResolver({'strategy': 'TestStrategy'})
default_location = path.join(path.dirname(path.realpath(__file__)))
resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
'strategy_path': default_location})
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
resolver.strategy.populate_indicators(result)
indicators = resolver.strategy.advise_indicators(result, 'ETH/BTC')
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - please replace this method with advise_indicators!" in str(
w[-1].message)
assert "deprecated - check out the Sample strategy to see the current function headers!" \
in str(w[-1].message)
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
resolver.strategy.advise_buy(indicators, 'ETH/BTC')
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - check out the Sample strategy to see the current function headers!" \
in str(w[-1].message)
def test_deprecate_populate_buy_trend(result):
resolver = StrategyResolver({'strategy': 'TestStrategy'})
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
resolver.strategy.populate_buy_trend(result)
resolver.strategy.advise_sell(indicators, 'ETH_BTC')
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - please replace this method with advise_buy!" in str(
w[-1].message)
def test_deprecate_populate_sell_trend(result):
resolver = StrategyResolver({'strategy': 'TestStrategy'})
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
resolver.strategy.populate_sell_trend(result)
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - please replace this method with advise_sell!" in str(
w[-1].message)
assert "deprecated - check out the Sample strategy to see the current function headers!" \
in str(w[-1].message)
def test_call_deprecated_function(result, monkeypatch):
@ -198,18 +197,26 @@ def test_call_deprecated_function(result, monkeypatch):
resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
'strategy_path': default_location})
pair = 'ETH/BTC'
indicators_mock = MagicMock()
buy_trend_mock = MagicMock()
sell_trend_mock = MagicMock()
monkeypatch.setattr(resolver.strategy, 'populate_indicators', indicators_mock)
resolver.strategy.advise_indicators(result, pair=pair)
assert indicators_mock.call_count == 1
# Make sure we are using a legacy function
assert len(resolver.strategy.populate_indicators.__annotations__) == 2
assert 'dataframe' in resolver.strategy.populate_indicators.__annotations__
assert 'pair' not in resolver.strategy.populate_indicators.__annotations__
assert len(resolver.strategy.populate_buy_trend.__annotations__) == 2
assert 'dataframe' in resolver.strategy.populate_buy_trend.__annotations__
assert 'pair' not in resolver.strategy.populate_buy_trend.__annotations__
assert len(resolver.strategy.populate_sell_trend.__annotations__) == 2
assert 'dataframe' in resolver.strategy.populate_sell_trend.__annotations__
assert 'pair' not in resolver.strategy.populate_sell_trend.__annotations__
monkeypatch.setattr(resolver.strategy, 'populate_buy_trend', buy_trend_mock)
resolver.strategy.advise_buy(result, pair=pair)
assert buy_trend_mock.call_count == 1
indicator_df = resolver.strategy.advise_indicators(result, pair=pair)
assert type(indicator_df) is DataFrame
assert 'adx' in indicator_df.columns
monkeypatch.setattr(resolver.strategy, 'populate_sell_trend', sell_trend_mock)
resolver.strategy.advise_sell(result, pair=pair)
assert sell_trend_mock.call_count == 1
buydf = resolver.strategy.advise_buy(result, pair=pair)
assert type(buydf) is DataFrame
assert 'buy' in buydf.columns
selldf = resolver.strategy.advise_sell(result, pair=pair)
assert type(selldf) is DataFrame
assert 'sell' in selldf

6
user_data/strategies/test_strategy.py
View File

@ -44,7 +44,7 @@ class TestStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def advise_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
@ -211,7 +211,7 @@ class TestStrategy(IStrategy):
return dataframe
def advise_buy(self, dataframe: DataFrame, pair: str) -> 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 populated with indicators
@ -228,7 +228,7 @@ class TestStrategy(IStrategy):
return dataframe
def advise_sell(self, dataframe: DataFrame, pair: str) -> 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 populated with indicators