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Merge pull request #3134 from freqtrade/backtesting_memory
Backtesting memory and dataframe
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@ -149,8 +149,8 @@ class Backtesting:
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# To avoid using data from future, we use buy/sell signals shifted
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# from the previous candle
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df_analyzed.loc[:, 'buy'] = df_analyzed['buy'].shift(1)
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df_analyzed.loc[:, 'sell'] = df_analyzed['sell'].shift(1)
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df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
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df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
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df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
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@ -467,8 +467,11 @@ class IStrategy(ABC):
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"""
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Creates a dataframe and populates indicators for given candle (OHLCV) data
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Used by optimize operations only, not during dry / live runs.
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Using .copy() to get a fresh copy of the dataframe for every strategy run.
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Has positive effects on memory usage for whatever reason - also when
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using only one strategy.
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"""
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return {pair: self.advise_indicators(pair_data, {'pair': pair})
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return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair})
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for pair, pair_data in data.items()}
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def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@ -168,6 +168,19 @@ def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
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assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
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def test_ohlcvdata_to_dataframe_copy(mocker, default_conf, testdatadir) -> None:
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default_conf.update({'strategy': 'DefaultStrategy'})
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strategy = StrategyResolver.load_strategy(default_conf)
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aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
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timerange = TimeRange.parse_timerange('1510694220-1510700340')
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data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
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fill_up_missing=True)
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strategy.ohlcvdata_to_dataframe(data)
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assert aimock.call_count == 1
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# Ensure that a copy of the dataframe is passed to advice_indicators
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assert aimock.call_args_list[0][0][0] is not data
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def test_min_roi_reached(default_conf, fee) -> None:
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# Use list to confirm sequence does not matter
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