Move dataframe validation to abstract class
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@ -10,6 +10,7 @@ from pathlib import Path
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from typing import Dict, List, Optional
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from datetime import datetime, timezone
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from pandas import DataFrame
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from freqtrade.data.converter import clean_ohlcv_dataframe, trim_dataframe
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from freqtrade.configuration import TimeRange
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from freqtrade.exchange import timeframe_to_seconds
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@ -47,15 +48,26 @@ class IDataHandler(ABC):
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timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
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pairdf = self._ohlcv_load(pair, timeframe,
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timerange=timerange_startup,
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fill_missing=fill_missing,
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drop_incomplete=drop_incomplete)
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timerange=timerange_startup)
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if pairdf.empty:
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logger.warning(
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f'No history data for pair: "{pair}", timeframe: {timeframe}. '
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'Use `freqtrade download-data` to download the data'
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)
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return pairdf
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return pairdf
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else:
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enddate = pairdf.iloc[-1]['date']
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if timerange_startup:
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self._validate_pairdata(pair, pairdf, timerange_startup)
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pairdf = trim_dataframe(pairdf, timerange_startup)
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# incomplete candles should only be dropped if we didn't trim the end beforehand.
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return clean_ohlcv_dataframe(pairdf, timeframe,
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pair=pair,
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fill_missing=fill_missing,
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drop_incomplete=(drop_incomplete and
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enddate == pairdf.iloc[-1]['date']))
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def _validate_pairdata(self, pair, pairdata: DataFrame, timerange: TimeRange):
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"""
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@ -7,7 +7,6 @@ from pandas import DataFrame, read_json, to_datetime
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from freqtrade import misc
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from freqtrade.configuration import TimeRange
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from freqtrade.data.converter import clean_ohlcv_dataframe, trim_dataframe
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from .idatahandler import IDataHandler
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@ -54,18 +53,14 @@ class JsonDataHandler(IDataHandler):
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def _ohlcv_load(self, pair: str, timeframe: str,
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timerange: Optional[TimeRange] = None,
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fill_missing: bool = True,
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drop_incomplete: bool = True,
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) -> DataFrame:
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"""
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Internal method used to load data for one pair from disk.
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Implements the loading and conversation to a Pandas dataframe.
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Timerange trimming and dataframe validation happens outside of this method.
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:param pair: Pair to load data
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:param timeframe: Ticker timeframe (e.g. "5m")
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:param timerange: Limit data to be loaded to this timerange
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:param fill_missing: Fill missing values with "No action"-candles
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:param drop_incomplete: Drop last candle assuming it may be incomplete.
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:param startup_candles: Additional candles to load at the start of the period
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:param timerange: Limit data to be loaded to this timerange.
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:return: DataFrame with ohlcv data, or empty DataFrame
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"""
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filename = self._pair_data_filename(self._datadir, pair, timeframe)
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@ -77,19 +72,7 @@ class JsonDataHandler(IDataHandler):
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unit='ms',
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utc=True,
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infer_datetime_format=True)
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enddate = pairdata.iloc[-1]['date']
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if timerange:
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self._validate_pairdata(pair, pairdata, timerange)
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pairdata = trim_dataframe(pairdata, timerange)
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# incomplete candles should only be dropped if we didn't trim the end beforehand.
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return clean_ohlcv_dataframe(pairdata, timeframe,
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pair=pair,
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fill_missing=fill_missing,
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drop_incomplete=(drop_incomplete and
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enddate == pairdata.iloc[-1]['date']))
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return pairdata
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def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
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"""
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