mirror of
https://github.com/freqtrade/freqtrade.git
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104 lines
4.0 KiB
Python
104 lines
4.0 KiB
Python
"""
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Abstract datahandler interface.
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It's subclasses handle and storing data from disk.
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"""
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import logging
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from abc import ABC, abstractmethod, abstractclassmethod
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from pathlib import Path
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from typing import Dict, List, Optional
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from copy import deepcopy
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from pandas import 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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from freqtrade.data.converter import parse_ticker_dataframe
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logger = logging.getLogger(__name__)
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class IDataHandler(ABC):
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def __init__(self, datadir: Path) -> None:
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self._datadir = datadir
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# TODO: create abstract interface
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def ohlcv_load(self, pair, timeframe: str,
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timerange: Optional[TimeRange] = None,
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fill_up_missing: bool = True,
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drop_incomplete: bool = True,
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startup_candles: int = 0,
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) -> DataFrame:
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"""
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Load cached ticker history for the given pair.
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:param pair: Pair to load data for
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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_up_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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:return: DataFrame with ohlcv data, or empty DataFrame
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"""
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# Fix startup period
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timerange_startup = deepcopy(timerange)
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if startup_candles > 0 and timerange_startup:
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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_up_missing,
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drop_incomplete=drop_incomplete)
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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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else:
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if timerange_startup:
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self._validate_pairdata(pair, pairdf, timerange_startup)
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return pairdf
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def _validate_pairdata(pair, pairdata: DataFrame, timerange: TimeRange):
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"""
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Validates pairdata for missing data at start end end and logs warnings.
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:param pairdata: Dataframe to validate
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:param timerange: Timerange specified for start and end dates
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"""
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if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
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logger.warning('Missing data at start for pair %s, data starts at %s',
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pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
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if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
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logger.warning('Missing data at end for pair %s, data ends at %s',
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pair, arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
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@staticmethod
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def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
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"""
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TODO: investigate if this is needed ... we can probably cover this in a dataframe
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Trim tickerlist based on given timerange
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"""
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if not tickerlist:
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return tickerlist
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start_index = 0
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stop_index = len(tickerlist)
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if timerange.starttype == 'date':
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while (start_index < len(tickerlist) and
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tickerlist[start_index][0] < timerange.startts * 1000):
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start_index += 1
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if timerange.stoptype == 'date':
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while (stop_index > 0 and
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tickerlist[stop_index-1][0] > timerange.stopts * 1000):
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stop_index -= 1
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if start_index > stop_index:
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raise ValueError(f'The timerange [{timerange.startts},{timerange.stopts}] is incorrect')
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return tickerlist[start_index:stop_index]
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