do date parsing while loading json, not later
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@ -4,7 +4,7 @@ from datetime import timedelta
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import arrow
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import talib.abstract as ta
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from pandas import DataFrame
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from pandas import DataFrame, to_datetime
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from qtpylib.indicators import awesome_oscillator, crossed_above
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from freqtrade import exchange
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@ -23,8 +23,9 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
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"""
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df = DataFrame(ticker) \
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.drop('BV', 1) \
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.rename(columns={'C':'close', 'V':'volume', 'O':'open', 'H':'high', 'L':'low', 'T':'date'}) \
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.sort_values('date')
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.rename(columns={'C':'close', 'V':'volume', 'O':'open', 'H':'high', 'L':'low', 'T':'date'})
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df['date'] = to_datetime(df['date'], utc=True, infer_datetime_format=True)
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df.sort_values('date', inplace=True)
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return df
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@ -56,12 +56,12 @@ def backtest(conf, pairs, mocker):
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for index, row in ticker[ticker.buy == 1].iterrows():
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trade = Trade(
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open_rate=row['close'],
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open_date=arrow.get(row['date']).datetime,
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open_date=row['date'],
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amount=1,
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)
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# calculate win/lose forwards from buy point
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for index2, row2 in ticker[index:].iterrows():
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if should_sell(trade, row2['close'], arrow.get(row2['date']).datetime):
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if should_sell(trade, row2['close'], row2['date']):
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current_profit = (row2['close'] - trade.open_rate) / trade.open_rate
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trades.append((pair, current_profit, index2 - index))
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