freqtrade_origin/freqtrade/plugins/pairlist/PercentVolumeChangePairList.py

"""
Change PairList provider

Provides dynamic pair list based on trade change
sorted based on percentage change in volume over a
defined period
"""

import logging
from datetime import timedelta
from typing import Any, Dict, List, Literal

from cachetools import TTLCache

from freqtrade.constants import ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
from freqtrade.exchange.types import Tickers
from freqtrade.plugins.pairlist.IPairList import IPairList, PairlistParameter, SupportsBacktesting
from freqtrade.util import dt_now, format_ms_time


logger = logging.getLogger(__name__)

SORT_VALUES = ["rolling_volume_change"]


class PercentVolumeChangePairList(IPairList):
    is_pairlist_generator = True
    supports_backtesting = SupportsBacktesting.NO

    def __init__(self, *args, **kwargs) -> None:
        super().__init__(*args, **kwargs)

        if "number_assets" not in self._pairlistconfig:
            raise OperationalException(
                "`number_assets` not specified. Please check your configuration "
                'for "pairlist.config.number_assets"'
            )

        self._stake_currency = self._config["stake_currency"]
        self._number_pairs = self._pairlistconfig["number_assets"]
        self._sort_key: Literal["rolling_volume_change"] = self._pairlistconfig.get(
            "sort_key", "rolling_volume_change"
        )
        self._min_value = self._pairlistconfig.get("min_value", 0)
        self._max_value = self._pairlistconfig.get("max_value", None)
        self._refresh_period = self._pairlistconfig.get("refresh_period", 1800)
        self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period)
        self._lookback_days = self._pairlistconfig.get("lookback_days", 0)
        self._lookback_timeframe = self._pairlistconfig.get("lookback_timeframe", "1d")
        self._lookback_period = self._pairlistconfig.get("lookback_period", 0)
        self._def_candletype = self._config["candle_type_def"]

        if (self._lookback_days > 0) & (self._lookback_period > 0):
            raise OperationalException(
                "Ambiguous configuration: lookback_days and lookback_period both set in pairlist "
                "config. Please set lookback_days only or lookback_period and lookback_timeframe "
                "and restart the bot."
            )

        # overwrite lookback timeframe and days when lookback_days is set
        if self._lookback_days > 0:
            self._lookback_timeframe = "1d"
            self._lookback_period = self._lookback_days

        # get timeframe in minutes and seconds
        self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
        _tf_in_sec = self._tf_in_min * 60

        # whether to use range lookback or not
        self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)

        if self._use_range & (self._refresh_period < _tf_in_sec):
            raise OperationalException(
                f"Refresh period of {self._refresh_period} seconds is smaller than one "
                f"timeframe of {self._lookback_timeframe}. Please adjust refresh_period "
                f"to at least {_tf_in_sec} and restart the bot."
            )

        if not self._use_range and not (
            self._exchange.exchange_has("fetchTickers")
            and self._exchange.get_option("tickers_have_change")
        ):
            raise OperationalException(
                "Exchange does not support dynamic whitelist in this configuration. "
                "Please edit your config and either remove PercentVolumeChangePairList, "
                "or switch to using candles. and restart the bot."
            )

        if not self._validate_keys(self._sort_key):
            raise OperationalException(f"key {self._sort_key} not in {SORT_VALUES}")

        candle_limit = self._exchange.ohlcv_candle_limit(
            self._lookback_timeframe, self._config["candle_type_def"]
        )
        if self._lookback_period < 4:
            raise OperationalException("ChangeFilter requires lookback_period to be >= 4")
        self.log_once(f"Candle limit is {candle_limit}", logger.info)
        if self._lookback_period > candle_limit:
            raise OperationalException(
                "ChangeFilter requires lookback_period to not "
                f"exceed exchange max request size ({candle_limit})"
            )

    @property
    def needstickers(self) -> bool:
        """
        Boolean property defining if tickers are necessary.
        If no Pairlist requires tickers, an empty Dict is passed
        as tickers argument to filter_pairlist
        """
        return not self._use_range

    def _validate_keys(self, key):
        return key in SORT_VALUES

    def short_desc(self) -> str:
        """
        Short whitelist method description - used for startup-messages
        """
        return (
            f"{self.name} - top {self._pairlistconfig['number_assets']} percent "
            f"volume change pairs."
        )

    @staticmethod
    def description() -> str:
        return "Provides dynamic pair list based on percentage volume change."

    @staticmethod
    def available_parameters() -> Dict[str, PairlistParameter]:
        return {
            "number_assets": {
                "type": "number",
                "default": 30,
                "description": "Number of assets",
                "help": "Number of assets to use from the pairlist",
            },
            "sort_key": {
                "type": "option",
                "default": "rolling_volume_change",
                "options": SORT_VALUES,
                "description": "Sort key",
                "help": "Sort key to use for sorting the pairlist.",
            },
            "min_value": {
                "type": "number",
                "default": 0,
                "description": "Minimum value",
                "help": "Minimum value to use for filtering the pairlist.",
            },
            "max_value": {
                "type": "number",
                "default": None,
                "description": "Maximum value",
                "help": "Maximum value to use for filtering the pairlist.",
            },
            "refresh_period": {
                "type": "number",
                "default": 1800,
                "description": "Refresh period",
                "help": "Refresh period in seconds",
            },
            "lookback_days": {
                "type": "number",
                "default": 0,
                "description": "Lookback Days",
                "help": "Number of days to look back at.",
            },
            "lookback_timeframe": {
                "type": "string",
                "default": "1d",
                "description": "Lookback Timeframe",
                "help": "Timeframe to use for lookback.",
            },
            "lookback_period": {
                "type": "number",
                "default": 0,
                "description": "Lookback Period",
                "help": "Number of periods to look back at.",
            },
        }

    def gen_pairlist(self, tickers: Tickers) -> List[str]:
        """
        Generate the pairlist
        :param tickers: Tickers (from exchange.get_tickers). May be cached.
        :return: List of pairs
        """
        # Generate dynamic whitelist
        # Must always run if this pairlist is not the first in the list.
        pairlist = self._pair_cache.get("pairlist")
        if pairlist:
            # Item found - no refresh necessary
            return pairlist.copy()
        else:
            # Use fresh pairlist
            # Check if pair quote currency equals to the stake currency.
            _pairlist = [
                k
                for k in self._exchange.get_markets(
                    quote_currencies=[self._stake_currency], tradable_only=True, active_only=True
                ).keys()
            ]

            # No point in testing for blacklisted pairs...
            _pairlist = self.verify_blacklist(_pairlist, logger.info)
            if not self._use_range:
                filtered_tickers = [
                    v
                    for k, v in tickers.items()
                    if (
                        self._exchange.get_pair_quote_currency(k) == self._stake_currency
                        and (self._use_range or v.get(self._sort_key) is not None)
                        and v["symbol"] in _pairlist
                    )
                ]
                pairlist = [s["symbol"] for s in filtered_tickers]
            else:
                pairlist = _pairlist

            pairlist = self.filter_pairlist(pairlist, tickers)
            self._pair_cache["pairlist"] = pairlist.copy()

        return pairlist

    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
        """
        Filters and sorts pairlist and returns the whitelist again.
        Called on each bot iteration - please use internal caching if necessary
        :param pairlist: pairlist to filter or sort
        :param tickers: Tickers (from exchange.get_tickers). May be cached.
        :return: new whitelist
        """
        self.log_once(f"Filter ticker is self use range {pairlist}", logger.warning)
        if self._use_range:
            filtered_tickers: List[Dict[str, Any]] = [{"symbol": k} for k in pairlist]

            # get lookback period in ms, for exchange ohlcv fetch
            since_ms = (
                int(
                    timeframe_to_prev_date(
                        self._lookback_timeframe,
                        dt_now()
                        + timedelta(
                            minutes=-(self._lookback_period * self._tf_in_min) - self._tf_in_min
                        ),
                    ).timestamp()
                )
                * 1000
            )

            to_ms = (
                int(
                    timeframe_to_prev_date(
                        self._lookback_timeframe, dt_now() - timedelta(minutes=self._tf_in_min)
                    ).timestamp()
                )
                * 1000
            )

            # todo: utc date output for starting date
            self.log_once(
                f"Using change range of {self._lookback_period} candles, timeframe: "
                f"{self._lookback_timeframe}, starting from {format_ms_time(since_ms)} "
                f"till {format_ms_time(to_ms)}",
                logger.info,
            )
            needed_pairs: ListPairsWithTimeframes = [
                (p, self._lookback_timeframe, self._def_candletype)
                for p in [s["symbol"] for s in filtered_tickers]
                if p not in self._pair_cache
            ]

            candles = self._exchange.refresh_ohlcv_with_cache(needed_pairs, since_ms)

            for i, p in enumerate(filtered_tickers):
                pair_candles = (
                    candles[(p["symbol"], self._lookback_timeframe, self._def_candletype)]
                    if (p["symbol"], self._lookback_timeframe, self._def_candletype) in candles
                    else None
                )

                # in case of candle data calculate typical price and change for candle
                if pair_candles is not None and not pair_candles.empty:
                    pair_candles["rolling_volume_sum"] = (
                        pair_candles["volume"].rolling(window=self._lookback_period).sum()
                    )
                    pair_candles["rolling_volume_change"] = (
                        pair_candles["rolling_volume_sum"].pct_change() * 100
                    )

                    # ensure that a rolling sum over the lookback_period is built
                    # if pair_candles contains more candles than lookback_period
                    rolling_volume_change = pair_candles["rolling_volume_change"].fillna(0).iloc[-1]

                    # replace change with a range change sum calculated above
                    filtered_tickers[i]["rolling_volume_change"] = rolling_volume_change
                    self.log_once(f"ticker {filtered_tickers[i]}", logger.info)
                else:
                    filtered_tickers[i]["rolling_volume_change"] = 0
        else:
            filtered_tickers = [v for k, v in tickers.items() if k in pairlist]

        filtered_tickers = [v for v in filtered_tickers if v[self._sort_key] > self._min_value]
        if self._max_value is not None:
            filtered_tickers = [v for v in filtered_tickers if v[self._sort_key] < self._max_value]

        sorted_tickers = sorted(filtered_tickers, reverse=True, key=lambda t: t[self._sort_key])

        self.log_once(f"Sorted Tickers {sorted_tickers}", logger.info)
        # Validate whitelist to only have active market pairs
        pairs = self._whitelist_for_active_markets([s["symbol"] for s in sorted_tickers])
        pairs = self.verify_blacklist(pairs, logmethod=logger.info)
        # Limit pairlist to the requested number of pairs
        pairs = pairs[: self._number_pairs]

        return pairs