Introduce datatype for informative pairs
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72165a1926
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@ -9,11 +9,13 @@ from typing import Any, Dict, List, Optional, Tuple
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from pandas import DataFrame
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from freqtrade.data.common import ListPairsWithTimeframes
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from freqtrade.data.history import load_pair_history
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from freqtrade.exceptions import DependencyException, OperationalException
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from freqtrade.exchange import Exchange
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from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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@ -25,8 +27,8 @@ class DataProvider:
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self._pairlists = pairlists
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def refresh(self,
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pairlist: List[Tuple[str, str]],
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helping_pairs: List[Tuple[str, str]] = None) -> None:
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pairlist: ListPairsWithTimeframes,
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helping_pairs: ListPairsWithTimeframes = None) -> None:
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"""
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Refresh data, called with each cycle
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"""
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@ -36,7 +38,7 @@ class DataProvider:
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self._exchange.refresh_latest_ohlcv(pairlist)
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@property
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def available_pairs(self) -> List[Tuple[str, str]]:
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def available_pairs(self) -> ListPairsWithTimeframes:
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"""
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Return a list of tuples containing (pair, timeframe) for which data is currently cached.
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Should be whitelist + open trades.
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@ -18,6 +18,7 @@ from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE,
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TRUNCATE, decimal_to_precision)
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from pandas import DataFrame
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from freqtrade.data.common import ListPairsWithTimeframes
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from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
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from freqtrade.exceptions import (DependencyException, InvalidOrderException,
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OperationalException, TemporaryError)
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@ -676,7 +677,7 @@ class Exchange:
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logger.info("Downloaded data for %s with length %s.", pair, len(data))
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return data
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def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
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def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes) -> List[Tuple[str, List]]:
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"""
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Refresh in-memory OHLCV asynchronously and set `_klines` with the result
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Loops asynchronously over pair_list and downloads all pairs async (semi-parallel).
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@ -12,6 +12,7 @@ from typing import Dict, List, NamedTuple, Optional, Tuple
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import arrow
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from pandas import DataFrame
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from freqtrade.data.common import ListPairsWithTimeframes
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.exceptions import StrategyError
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from freqtrade.exchange import timeframe_to_minutes
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@ -185,7 +186,7 @@ class IStrategy(ABC):
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"""
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return False
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def informative_pairs(self) -> List[Tuple[str, str]]:
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def informative_pairs(self) -> ListPairsWithTimeframes:
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"""
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Define additional, informative pair/interval combinations to be cached from the exchange.
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These pair/interval combinations are non-tradeable, unless they are part
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