enforce date column in backtesting freqai predictions files
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@ -1021,20 +1021,11 @@ class FreqaiDataKitchen:
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Back fill values to before the backtesting range so that the dataframe matches size
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when it goes back to the strategy. These rows are not included in the backtest.
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"""
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# len_filler = len(dataframe) - len(self.full_df.index) # startup_candle_count
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# filler_df = pd.DataFrame(
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# np.zeros((len_filler, len(self.full_df.columns))), columns=self.full_df.columns
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# )
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# self.full_df = pd.concat([filler_df, self.full_df], axis=0, ignore_index=True)
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to_keep = [col for col in dataframe.columns if not col.startswith("&")]
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# self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1)
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# self.full_df = DataFrame()
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self.return_dataframe = pd.merge(dataframe[to_keep],
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self.full_df, how='left', on='date')
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self.return_dataframe[self.full_df.columns] = (
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self.return_dataframe[self.full_df.columns].fillna(value=0))
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self.full_df = DataFrame()
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return
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@ -1368,12 +1359,13 @@ class FreqaiDataKitchen:
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if file_exists:
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append_df = self.get_backtesting_prediction()
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if len(append_df) == len_backtest_df:
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if len(append_df) == len_backtest_df and 'date' in append_df:
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logger.info(f"Found backtesting prediction file at {path_to_predictionfile}")
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return True
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else:
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logger.info("A new backtesting prediction file is required. "
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"(Number of predictions is different from dataframe length).")
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"(Number of predictions is different from dataframe length or "
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"old prediction file version).")
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return False
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else:
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logger.info(
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