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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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12
user_data/strategies/test_strategy.py
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@@ -45,7 +45,7 @@ class TestStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
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
@@ -53,7 +53,7 @@ class TestStrategy(IStrategy):
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 pair: Pair currently analyzed
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
@@ -215,11 +215,11 @@ class TestStrategy(IStrategy):
return dataframe
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[
@@ -232,11 +232,11 @@ class TestStrategy(IStrategy):
return dataframe
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[