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https://github.com/freqtrade/freqtrade.git
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chore: update usage of TTLCache to FtTTLCache
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@@ -16,7 +16,6 @@ from typing import Any, Literal, TypeGuard, TypeVar
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import ccxt
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import ccxt.pro as ccxt_pro
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from cachetools import TTLCache
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from ccxt import TICK_SIZE
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from dateutil import parser
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from pandas import DataFrame, concat
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@@ -107,9 +106,8 @@ from freqtrade.misc import (
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file_load_json,
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safe_value_fallback2,
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)
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from freqtrade.util import dt_from_ts, dt_now
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from freqtrade.util import FtTTLCache, PeriodicCache, dt_from_ts, dt_now
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from freqtrade.util.datetime_helpers import dt_humanize_delta, dt_ts, format_ms_time
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from freqtrade.util.periodic_cache import PeriodicCache
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logger = logging.getLogger(__name__)
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@@ -230,13 +228,13 @@ class Exchange:
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self._cache_lock = Lock()
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# Cache for 10 minutes ...
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self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=4, ttl=60 * 10)
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self._fetch_tickers_cache: FtTTLCache = FtTTLCache(maxsize=4, ttl=60 * 10)
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# Cache values for 300 to avoid frequent polling of the exchange for prices
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# Caching only applies to RPC methods, so prices for open trades are still
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# refreshed once every iteration.
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# Shouldn't be too high either, as it'll freeze UI updates in case of open orders.
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self._exit_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300)
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self._entry_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300)
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self._exit_rate_cache: FtTTLCache = FtTTLCache(maxsize=100, ttl=300)
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self._entry_rate_cache: FtTTLCache = FtTTLCache(maxsize=100, ttl=300)
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# Holds candles
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self._klines: dict[PairWithTimeframe, DataFrame] = {}
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@@ -2164,7 +2162,9 @@ class Exchange:
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name = side.capitalize()
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strat_name = "entry_pricing" if side == "entry" else "exit_pricing"
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cache_rate: TTLCache = self._entry_rate_cache if side == "entry" else self._exit_rate_cache
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cache_rate: FtTTLCache = (
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self._entry_rate_cache if side == "entry" else self._exit_rate_cache
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)
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if not refresh:
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with self._cache_lock:
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rate = cache_rate.get(pair)
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