Store tickers by pair / ticker_interval
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@ -6,7 +6,7 @@ Common Interface for bot and strategy to access data.
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"""
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import logging
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from pathlib import Path
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from typing import List
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from typing import List, Tuple
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from pandas import DataFrame
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@ -23,11 +23,11 @@ class DataProvider(object):
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self._config = config
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self._exchange = exchange
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def refresh(self, pairlist: List[str]) -> None:
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def refresh(self, pairlist: List[Tuple[str, str]]) -> None:
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"""
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Refresh data, called with each cycle
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"""
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self._exchange.refresh_latest_ohlcv(pairlist, self._config['ticker_interval'])
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self._exchange.refresh_latest_ohlcv(pairlist)
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@property
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def available_pairs(self) -> List[str]:
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@ -37,23 +37,31 @@ class DataProvider(object):
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"""
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return list(self._exchange._klines.keys())
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def ohlcv(self, pair: str, copy: bool = True) -> DataFrame:
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def ohlcv(self, pair: str, tick_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 check `available_pairs` to verify which pairs are currently cached.
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:param pair: pair to get the data for
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:param tick_interval: ticker_interval to get pair for
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:param copy: copy dataframe before returning.
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Use false only for RO operations (where the dataframe is not modified)
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"""
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# TODO: Should not be stored in exchange but in this class
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if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
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return self._exchange.klines(pair, copy)
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if tick_interval:
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pairtick = (pair, tick_interval)
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else:
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pairtick = (pair, self._config['ticker_interval'])
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return self._exchange.klines(pairtick, copy=copy)
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else:
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return DataFrame()
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def historic_ohlcv(self, pair: str, ticker_interval: str) -> DataFrame:
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"""
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get historic ohlcv data stored for backtesting
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:param pair: pair to get the data for
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:param tick_interval: ticker_interval to get pair for
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"""
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return load_pair_history(pair=pair,
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ticker_interval=ticker_interval,
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@ -83,7 +83,7 @@ class Exchange(object):
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self._pairs_last_refresh_time: Dict[str, int] = {}
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# Holds candles
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self._klines: Dict[str, DataFrame] = {}
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self._klines: Dict[Tuple[str, str], DataFrame] = {}
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# Holds all open sell orders for dry_run
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self._dry_run_open_orders: Dict[str, Any] = {}
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@ -158,9 +158,10 @@ class Exchange(object):
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"""exchange ccxt id"""
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return self._api.id
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def klines(self, pair: str, copy=True) -> DataFrame:
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if pair in self._klines:
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return self._klines[pair].copy() if copy else self._klines[pair]
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def klines(self, pair_interval: Tuple[str, str], copy=True) -> DataFrame:
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# create key tuple
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if pair_interval in self._klines:
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return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
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else:
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return DataFrame()
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@ -531,24 +532,24 @@ class Exchange(object):
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logger.info("downloaded %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[str],
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ticker_interval: str) -> List[Tuple[str, List]]:
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def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
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"""
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Refresh in-memory ohlcv asyncronously and set `_klines` with the result
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"""
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logger.debug("Refreshing ohlcv data for %d pairs", len(pair_list))
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# Calculating ticker interval in second
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interval_in_sec = constants.TICKER_INTERVAL_MINUTES[ticker_interval] * 60
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input_coroutines = []
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# Gather corotines to run
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for pair in pair_list:
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for pair, ticker_interval in pair_list:
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# Calculating ticker interval in second
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interval_in_sec = constants.TICKER_INTERVAL_MINUTES[ticker_interval] * 60
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if not (self._pairs_last_refresh_time.get(pair, 0) + interval_in_sec >=
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arrow.utcnow().timestamp and pair in self._klines):
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arrow.utcnow().timestamp and (pair, ticker_interval) in self._klines):
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input_coroutines.append(self._async_get_candle_history(pair, ticker_interval))
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else:
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logger.debug("Using cached ohlcv data for %s ...", pair)
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logger.debug("Using cached ohlcv data for %s, %s ...", pair, ticker_interval)
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tickers = asyncio.get_event_loop().run_until_complete(
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asyncio.gather(*input_coroutines, return_exceptions=True))
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@ -559,13 +560,14 @@ class Exchange(object):
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logger.warning("Async code raised an exception: %s", res.__class__.__name__)
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continue
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pair = res[0]
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tick_interval[1]
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tick_interval = res[1]
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ticks = res[2]
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# keeping last candle time as last refreshed time of the pair
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if ticks:
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self._pairs_last_refresh_time[pair] = ticks[-1][0] // 1000
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# keeping parsed dataframe in cache
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self._klines[pair] = parse_ticker_dataframe(ticks, tick_interval, fill_missing=True)
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self._klines[(pair, tick_interval)] = parse_ticker_dataframe(
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ticks, tick_interval, fill_missing=True)
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return tickers
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@retrier_async
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@ -170,8 +170,11 @@ class FreqtradeBot(object):
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self.active_pair_whitelist.extend([trade.pair for trade in trades
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if trade.pair not in self.active_pair_whitelist])
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# Create pair-whitelist tuple with (pair, ticker_interval)
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pair_whitelist = [(pair, self.config['ticker_interval'])
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for pair in self.active_pair_whitelist]
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# Refreshing candles
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self.dataprovider.refresh(self.active_pair_whitelist)
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self.dataprovider.refresh(pair_whitelist)
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# First process current opened trades
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for trade in trades:
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@ -321,7 +324,9 @@ class FreqtradeBot(object):
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# running get_signal on historical data fetched
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for _pair in whitelist:
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(buy, sell) = self.strategy.get_signal(_pair, interval, self.dataprovider.ohlcv(_pair))
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(buy, sell) = self.strategy.get_signal(
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_pair, interval, self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
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if buy and not sell:
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stake_amount = self._get_trade_stake_amount(_pair)
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if not stake_amount:
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@ -582,8 +587,9 @@ class FreqtradeBot(object):
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(buy, sell) = (False, False)
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experimental = self.config.get('experimental', {})
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if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
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(buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.ticker_interval,
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self.dataprovider.ohlcv(trade.pair))
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(buy, sell) = self.strategy.get_signal(
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trade.pair, self.strategy.ticker_interval,
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self.dataprovider.ohlcv(trade.pair, self.strategy.ticker_interval))
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config_ask_strategy = self.config.get('ask_strategy', {})
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if config_ask_strategy.get('use_order_book', False):
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@ -368,8 +368,9 @@ class Backtesting(object):
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if self.config.get('live'):
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logger.info('Downloading data for all pairs in whitelist ...')
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self.exchange.refresh_latest_ohlcv(pairs, self.ticker_interval)
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data = self.exchange._klines
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self.exchange.refresh_latest_ohlcv([(pair, self.ticker_interval) for pair in pairs])
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data = {key[0]: value for key, value in self.exchange._klines.items()}
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else:
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logger.info('Using local backtesting data (using whitelist in given config) ...')
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