mirror of
https://github.com/freqtrade/freqtrade.git
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330 lines
13 KiB
Python
330 lines
13 KiB
Python
"""
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Percent Change PairList provider
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Provides dynamic pair list based on trade change
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sorted based on percentage change in price over a
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defined period or as coming from ticker
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"""
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import logging
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from datetime import timedelta
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from typing import Any, Optional
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from cachetools import TTLCache
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from pandas import DataFrame
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from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
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from freqtrade.exchange.exchange_types import Ticker, Tickers
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from freqtrade.plugins.pairlist.IPairList import IPairList, PairlistParameter, SupportsBacktesting
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from freqtrade.util import dt_now, format_ms_time
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logger = logging.getLogger(__name__)
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class PercentChangePairList(IPairList):
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is_pairlist_generator = True
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supports_backtesting = SupportsBacktesting.NO
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def __init__(self, *args, **kwargs) -> None:
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super().__init__(*args, **kwargs)
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if "number_assets" not in self._pairlistconfig:
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raise OperationalException(
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"`number_assets` not specified. Please check your configuration "
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'for "pairlist.config.number_assets"'
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)
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self._stake_currency = self._config["stake_currency"]
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self._number_pairs = self._pairlistconfig["number_assets"]
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self._min_value = self._pairlistconfig.get("min_value", None)
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self._max_value = self._pairlistconfig.get("max_value", None)
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self._refresh_period = self._pairlistconfig.get("refresh_period", 1800)
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self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period)
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self._lookback_days = self._pairlistconfig.get("lookback_days", 0)
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self._lookback_timeframe = self._pairlistconfig.get("lookback_timeframe", "1d")
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self._lookback_period = self._pairlistconfig.get("lookback_period", 0)
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self._sort_direction: Optional[str] = self._pairlistconfig.get("sort_direction", "desc")
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self._def_candletype = self._config["candle_type_def"]
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if (self._lookback_days > 0) & (self._lookback_period > 0):
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raise OperationalException(
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"Ambiguous configuration: lookback_days and lookback_period both set in pairlist "
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"config. Please set lookback_days only or lookback_period and lookback_timeframe "
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"and restart the bot."
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)
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# overwrite lookback timeframe and days when lookback_days is set
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if self._lookback_days > 0:
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self._lookback_timeframe = "1d"
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self._lookback_period = self._lookback_days
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# get timeframe in minutes and seconds
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self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
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_tf_in_sec = self._tf_in_min * 60
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# whether to use range lookback or not
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self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)
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if self._use_range & (self._refresh_period < _tf_in_sec):
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raise OperationalException(
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f"Refresh period of {self._refresh_period} seconds is smaller than one "
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f"timeframe of {self._lookback_timeframe}. Please adjust refresh_period "
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f"to at least {_tf_in_sec} and restart the bot."
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)
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if not self._use_range and not (
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self._exchange.exchange_has("fetchTickers")
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and self._exchange.get_option("tickers_have_percentage")
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):
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raise OperationalException(
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"Exchange does not support dynamic whitelist in this configuration. "
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"Please edit your config and either remove PercentChangePairList, "
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"or switch to using candles. and restart the bot."
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)
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candle_limit = self._exchange.ohlcv_candle_limit(
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self._lookback_timeframe, self._config["candle_type_def"]
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)
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if self._lookback_period > candle_limit:
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raise OperationalException(
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"ChangeFilter requires lookback_period to not "
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f"exceed exchange max request size ({candle_limit})"
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)
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@property
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def needstickers(self) -> bool:
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"""
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Boolean property defining if tickers are necessary.
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If no Pairlist requires tickers, an empty Dict is passed
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as tickers argument to filter_pairlist
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"""
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return not self._use_range
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def short_desc(self) -> str:
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"""
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Short whitelist method description - used for startup-messages
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"""
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return f"{self.name} - top {self._pairlistconfig['number_assets']} percent change pairs."
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@staticmethod
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def description() -> str:
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return "Provides dynamic pair list based on percentage change."
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@staticmethod
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def available_parameters() -> dict[str, PairlistParameter]:
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return {
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"number_assets": {
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"type": "number",
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"default": 30,
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"description": "Number of assets",
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"help": "Number of assets to use from the pairlist",
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},
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"min_value": {
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"type": "number",
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"default": None,
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"description": "Minimum value",
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"help": "Minimum value to use for filtering the pairlist.",
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},
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"max_value": {
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"type": "number",
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"default": None,
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"description": "Maximum value",
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"help": "Maximum value to use for filtering the pairlist.",
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},
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"sort_direction": {
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"type": "option",
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"default": "desc",
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"options": ["", "asc", "desc"],
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"description": "Sort pairlist",
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"help": "Sort Pairlist ascending or descending by rate of change.",
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},
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**IPairList.refresh_period_parameter(),
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"lookback_days": {
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"type": "number",
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"default": 0,
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"description": "Lookback Days",
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"help": "Number of days to look back at.",
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},
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"lookback_timeframe": {
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"type": "string",
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"default": "1d",
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"description": "Lookback Timeframe",
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"help": "Timeframe to use for lookback.",
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},
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"lookback_period": {
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"type": "number",
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"default": 0,
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"description": "Lookback Period",
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"help": "Number of periods to look back at.",
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},
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}
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def gen_pairlist(self, tickers: Tickers) -> list[str]:
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"""
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Generate the pairlist
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:param tickers: Tickers (from exchange.get_tickers). May be cached.
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:return: List of pairs
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"""
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pairlist = self._pair_cache.get("pairlist")
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if pairlist:
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# Item found - no refresh necessary
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return pairlist.copy()
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else:
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# Use fresh pairlist
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# Check if pair quote currency equals to the stake currency.
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_pairlist = [
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k
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for k in self._exchange.get_markets(
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quote_currencies=[self._stake_currency], tradable_only=True, active_only=True
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).keys()
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]
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# No point in testing for blacklisted pairs...
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_pairlist = self.verify_blacklist(_pairlist, logger.info)
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if not self._use_range:
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filtered_tickers = [
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v
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for k, v in tickers.items()
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if (
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self._exchange.get_pair_quote_currency(k) == self._stake_currency
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and (self._use_range or v.get("percentage") is not None)
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and v["symbol"] in _pairlist
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)
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]
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pairlist = [s["symbol"] for s in filtered_tickers]
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else:
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pairlist = _pairlist
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pairlist = self.filter_pairlist(pairlist, tickers)
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self._pair_cache["pairlist"] = pairlist.copy()
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return pairlist
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def filter_pairlist(self, pairlist: list[str], tickers: dict) -> list[str]:
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"""
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Filters and sorts pairlist and returns the whitelist again.
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Called on each bot iteration - please use internal caching if necessary
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:param pairlist: pairlist to filter or sort
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:param tickers: Tickers (from exchange.get_tickers). May be cached.
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:return: new whitelist
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"""
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filtered_tickers: list[dict[str, Any]] = [{"symbol": k} for k in pairlist]
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if self._use_range:
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# calculating using lookback_period
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self.fetch_percent_change_from_lookback_period(filtered_tickers)
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else:
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# Fetching 24h change by default from supported exchange tickers
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self.fetch_percent_change_from_tickers(filtered_tickers, tickers)
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if self._min_value is not None:
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filtered_tickers = [v for v in filtered_tickers if v["percentage"] > self._min_value]
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if self._max_value is not None:
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filtered_tickers = [v for v in filtered_tickers if v["percentage"] < self._max_value]
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sorted_tickers = sorted(
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filtered_tickers,
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reverse=self._sort_direction == "desc",
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key=lambda t: t["percentage"],
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)
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# Validate whitelist to only have active market pairs
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pairs = self._whitelist_for_active_markets([s["symbol"] for s in sorted_tickers])
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pairs = self.verify_blacklist(pairs, logmethod=logger.info)
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# Limit pairlist to the requested number of pairs
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pairs = pairs[: self._number_pairs]
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return pairs
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def fetch_candles_for_lookback_period(
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self, filtered_tickers: list[dict[str, str]]
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) -> dict[PairWithTimeframe, DataFrame]:
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since_ms = (
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int(
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timeframe_to_prev_date(
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self._lookback_timeframe,
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dt_now()
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+ timedelta(
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minutes=-(self._lookback_period * self._tf_in_min) - self._tf_in_min
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),
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).timestamp()
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)
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* 1000
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)
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to_ms = (
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int(
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timeframe_to_prev_date(
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self._lookback_timeframe, dt_now() - timedelta(minutes=self._tf_in_min)
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).timestamp()
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)
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* 1000
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)
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# todo: utc date output for starting date
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self.log_once(
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f"Using change range of {self._lookback_period} candles, timeframe: "
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f"{self._lookback_timeframe}, starting from {format_ms_time(since_ms)} "
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f"till {format_ms_time(to_ms)}",
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logger.info,
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)
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needed_pairs: ListPairsWithTimeframes = [
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(p, self._lookback_timeframe, self._def_candletype)
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for p in [s["symbol"] for s in filtered_tickers]
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if p not in self._pair_cache
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]
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candles = self._exchange.refresh_ohlcv_with_cache(needed_pairs, since_ms)
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return candles
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def fetch_percent_change_from_lookback_period(self, filtered_tickers: list[dict[str, Any]]):
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# get lookback period in ms, for exchange ohlcv fetch
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candles = self.fetch_candles_for_lookback_period(filtered_tickers)
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for i, p in enumerate(filtered_tickers):
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pair_candles = (
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candles[(p["symbol"], self._lookback_timeframe, self._def_candletype)]
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if (p["symbol"], self._lookback_timeframe, self._def_candletype) in candles
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else None
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)
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# in case of candle data calculate typical price and change for candle
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if pair_candles is not None and not pair_candles.empty:
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current_close = pair_candles["close"].iloc[-1]
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previous_close = pair_candles["close"].shift(self._lookback_period).iloc[-1]
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pct_change = (
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((current_close - previous_close) / previous_close) if previous_close > 0 else 0
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)
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# replace change with a range change sum calculated above
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filtered_tickers[i]["percentage"] = pct_change
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else:
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filtered_tickers[i]["percentage"] = 0
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def fetch_percent_change_from_tickers(self, filtered_tickers: list[dict[str, Any]], tickers):
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for i, p in enumerate(filtered_tickers):
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# Filter out assets
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if not self._validate_pair(
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p["symbol"], tickers[p["symbol"]] if p["symbol"] in tickers else None
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):
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filtered_tickers.remove(p)
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else:
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filtered_tickers[i]["percentage"] = tickers[p["symbol"]]["percentage"]
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def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool:
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"""
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Check if one price-step (pip) is > than a certain barrier.
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:param pair: Pair that's currently validated
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:param ticker: ticker dict as returned from ccxt.fetch_ticker
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:return: True if the pair can stay, false if it should be removed
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"""
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if not ticker or "percentage" not in ticker or ticker["percentage"] is None:
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self.log_once(
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f"Removed {pair} from whitelist, because "
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"ticker['percentage'] is empty (Usually no trade in the last 24h).",
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logger.info,
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)
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return False
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return True
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