stable/freqtrade/data/dataprovider.py

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"""
Dataprovider
Responsible to provide data to the bot
including Klines, tickers, historic data
Common Interface for bot and strategy to access data.
"""
import logging
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from pathlib import Path
from typing import List, Tuple
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from pandas import DataFrame
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from freqtrade.data.history import load_pair_history
from freqtrade.exchange import Exchange
from freqtrade.state import RunMode
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logger = logging.getLogger(__name__)
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class DataProvider:
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def __init__(self, config: dict, exchange: Exchange) -> None:
self._config = config
self._exchange = exchange
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def refresh(self,
pairlist: List[Tuple[str, str]],
helping_pairs: List[Tuple[str, str]] = None) -> None:
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"""
Refresh data, called with each cycle
"""
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if helping_pairs:
self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
else:
self._exchange.refresh_latest_ohlcv(pairlist)
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@property
def available_pairs(self) -> List[Tuple[str, str]]:
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"""
Return a list of tuples containing pair, ticker_interval for which data is currently cached.
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Should be whitelist + open trades.
"""
return list(self._exchange._klines.keys())
def ohlcv(self, pair: str, ticker_interval: str = None, copy: bool = True) -> DataFrame:
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"""
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Get ohlcv data for the given pair as DataFrame
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Please use the `available_pairs` method to verify which pairs are currently cached.
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:param pair: pair to get the data for
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:param ticker_interval: ticker interval 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)
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"""
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
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return self._exchange.klines((pair, ticker_interval or self._config['ticker_interval']),
copy=copy)
else:
return DataFrame()
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def historic_ohlcv(self, pair: str, ticker_interval: str = None) -> DataFrame:
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"""
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Get stored historic ohlcv data
:param pair: pair to get the data for
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:param ticker_interval: ticker interval to get data for
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"""
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return load_pair_history(pair=pair,
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ticker_interval=ticker_interval or self._config['ticker_interval'],
datadir=Path(self._config['datadir'])
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)
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def get_pair_dataframe(self, pair: str, ticker_interval: str = None) -> DataFrame:
"""
Return pair ohlcv data, either live or cached historical -- depending
on the runmode.
:param pair: pair to get the data for
:param ticker_interval: ticker interval to get data for
"""
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
# Get live ohlcv data.
data = self.ohlcv(pair=pair, ticker_interval=ticker_interval)
else:
# Get historic ohlcv data (cached on disk).
data = self.historic_ohlcv(pair=pair, ticker_interval=ticker_interval)
if len(data) == 0:
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logger.warning(f"No data found for ({pair}, {ticker_interval}).")
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return data
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def market(self, pair: str):
"""
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
"""
return self._exchange.markets.get(pair)
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def ticker(self, pair: str):
"""
Return last ticker data
"""
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# TODO: Implement me
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pass
def orderbook(self, pair: str, maximum: int):
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"""
return latest orderbook data
: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.
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"""
return self._exchange.get_order_book(pair, maximum)
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@property
def runmode(self) -> RunMode:
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"""
Get runmode of the bot
can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other".
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"""
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return RunMode(self._config.get('runmode', RunMode.OTHER))