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Dataprovider caching and trimming to timerange of historical informative.

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This commit is contained in:
George Muravei-Alkhavoi 2021-07-19 00:25:24 +03:00
parent adef5d89f3
commit f705293353
1 changed files with 17 additions and 6 deletions
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23
freqtrade/data/dataprovider.py
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@ -14,7 +14,8 @@ from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
from freqtrade.data.history import load_pair_history
from freqtrade.enums import RunMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.exchange import Exchange
from freqtrade.exchange import Exchange, timeframe_to_seconds
from freqtrade.configuration import TimeRange
logger = logging.getLogger(__name__)
@ -31,6 +32,7 @@ class DataProvider:
self._pairlists = pairlists
self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
self.__slice_index: Optional[int] = None
self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
def _set_dataframe_max_index(self, limit_index: int):
"""
@ -62,11 +64,20 @@ class DataProvider:
:param pair: pair to get the data for
:param timeframe: timeframe to get data for
"""
return load_pair_history(pair=pair,
timeframe=timeframe or self._config['timeframe'],
datadir=self._config['datadir'],
data_format=self._config.get('dataformat_ohlcv', 'json')
)
saved_pair = (pair, timeframe)
if saved_pair not in self.__cached_pairs_backtesting:
timerange = TimeRange.parse_timerange(None if self._config.get(
'timerange') is None else str(self._config.get('timerange')))
# Move informative start time respecting startup_candle_count
timerange.subtract_start(timeframe_to_seconds(timeframe) * self._config.get('startup_candle_count', 0))
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
pair=pair,
timeframe=timeframe or self._config['timeframe'],
datadir=self._config['datadir'],
timerange=timerange,
data_format=self._config.get('dataformat_ohlcv', 'json')
)
return self.__cached_pairs_backtesting[saved_pair].copy()
def get_pair_dataframe(self, pair: str, timeframe: str = None) -> DataFrame:
"""