""" Dataprovider Responsible to provide data to the bot including ticker and orderbook data, live and historical candle (OHLCV) data Common Interface for bot and strategy to access data. """ import logging from datetime import datetime, timezone from typing import Any, Dict, List, Optional, Tuple from pandas import DataFrame from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe from freqtrade.data.history import load_pair_history from freqtrade.exceptions import ExchangeError, OperationalException from freqtrade.exchange import Exchange from freqtrade.state import RunMode logger = logging.getLogger(__name__) NO_EXCHANGE_EXCEPTION = 'Exchange is not available to DataProvider.' MAX_DATAFRAME_CANDLES = 1000 class DataProvider: def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None: self._config = config self._exchange = exchange self._pairlists = pairlists self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} self.__slice_index: Optional[int] = None def _set_dataframe_max_index(self, limit_index: int): """ Limit analyzed dataframe to max specified index. :param limit_index: dataframe index. """ self.__slice_index = limit_index def _set_cached_df(self, pair: str, timeframe: str, dataframe: DataFrame) -> None: """ Store cached Dataframe. Using private method as this should never be used by a user (but the class is exposed via `self.dp` to the strategy) :param pair: pair to get the data for :param timeframe: Timeframe to get data for :param dataframe: analyzed dataframe """ self.__cached_pairs[(pair, timeframe)] = (dataframe, datetime.now(timezone.utc)) def add_pairlisthandler(self, pairlists) -> None: """ Allow adding pairlisthandler after initialization """ self._pairlists = pairlists def historic_ohlcv(self, pair: str, timeframe: str = None) -> DataFrame: """ Get stored historical candle (OHLCV) data :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') ) def get_pair_dataframe(self, pair: str, timeframe: str = None) -> DataFrame: """ Return pair candle (OHLCV) data, either live or cached historical -- depending on the runmode. :param pair: pair to get the data for :param timeframe: timeframe to get data for :return: Dataframe for this pair """ if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): # Get live OHLCV data. data = self.ohlcv(pair=pair, timeframe=timeframe) else: # Get historical OHLCV data (cached on disk). data = self.historic_ohlcv(pair=pair, timeframe=timeframe) if len(data) == 0: logger.warning(f"No data found for ({pair}, {timeframe}).") return data def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]: """ Retrieve the analyzed dataframe. Returns the full dataframe in trade mode (live / dry), and the last 1000 candles (up to the time evaluated at this moment) in all other modes. :param pair: pair to get the data for :param timeframe: timeframe to get data for :return: Tuple of (Analyzed Dataframe, lastrefreshed) for the requested pair / timeframe combination. Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached. """ pair_key = (pair, timeframe) if pair_key in self.__cached_pairs: if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): df, date = self.__cached_pairs[pair_key] else: df, date = self.__cached_pairs[pair_key] if self.__slice_index is not None: max_index = self.__slice_index df = df.iloc[max(0, max_index - MAX_DATAFRAME_CANDLES):max_index] return df, date else: return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc)) @property def runmode(self) -> RunMode: """ Get runmode of the bot can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other". """ return RunMode(self._config.get('runmode', RunMode.OTHER)) def current_whitelist(self) -> List[str]: """ fetch latest available whitelist. Useful when you have a large whitelist and need to call each pair as an informative pair. As available pairs does not show whitelist until after informative pairs have been cached. :return: list of pairs in whitelist """ if self._pairlists: return self._pairlists.whitelist.copy() else: raise OperationalException("Dataprovider was not initialized with a pairlist provider.") def clear_cache(self): """ Clear pair dataframe cache. """ self.__cached_pairs = {} # Exchange functions def refresh(self, pairlist: ListPairsWithTimeframes, helping_pairs: ListPairsWithTimeframes = None) -> None: """ Refresh data, called with each cycle """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) if helping_pairs: self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs) else: self._exchange.refresh_latest_ohlcv(pairlist) @property def available_pairs(self) -> ListPairsWithTimeframes: """ Return a list of tuples containing (pair, timeframe) for which data is currently cached. Should be whitelist + open trades. """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) return list(self._exchange._klines.keys()) def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame: """ Get candle (OHLCV) data for the given pair as DataFrame Please use the `available_pairs` method to verify which pairs are currently cached. :param pair: pair to get the data for :param timeframe: Timeframe to get data for :param copy: copy dataframe before returning if True. Use False only for read-only operations (where the dataframe is not modified) """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE): return self._exchange.klines((pair, timeframe or self._config['timeframe']), copy=copy) else: return DataFrame() def market(self, pair: str) -> Optional[Dict[str, Any]]: """ Return market data for the pair :param pair: Pair to get the data for :return: Market data dict from ccxt or None if market info is not available for the pair """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) return self._exchange.markets.get(pair) def ticker(self, pair: str): """ Return last ticker data from exchange :param pair: Pair to get the data for :return: Ticker dict from exchange or empty dict if ticker is not available for the pair """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) try: return self._exchange.fetch_ticker(pair) except ExchangeError: return {} def orderbook(self, pair: str, maximum: int) -> Dict[str, List]: """ Fetch latest l2 orderbook data Warning: Does a network request - so use with common sense. :param pair: pair to get the data for :param maximum: Maximum number of orderbook entries to query :return: dict including bids/asks with a total of `maximum` entries. """ if self._exchange is None: raise OperationalException(NO_EXCHANGE_EXCEPTION) return self._exchange.fetch_l2_order_book(pair, maximum)