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feat: Filter trades based on timerange

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This commit is contained in:
Maxime Pagnoulle
2025-08-23 20:25:26 +02:00
parent 0233c38711
commit 82903cc567
1 changed files with 25 additions and 2 deletions
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27
freqtrade/strategy/interface.py
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@@ -11,6 +11,7 @@ from math import isinf, isnan
from pandas import DataFrame
from pydantic import ValidationError
from freqtrade.configuration import TimeRange
from freqtrade.constants import CUSTOM_TAG_MAX_LENGTH, Config, IntOrInf, ListPairsWithTimeframes
from freqtrade.data.converter import populate_dataframe_with_trades
from freqtrade.data.converter.converter import reduce_dataframe_footprint
@@ -1767,9 +1768,31 @@ class IStrategy(ABC, HyperStrategyMixin):
use_public_trades = self.config.get("exchange", {}).get("use_public_trades", False)
if use_public_trades:
pair = metadata["pair"]
trades = self.dp.trades(pair=pair, copy=False)
# Build timerange from dataframe date column
if not dataframe.empty:
start_ts = int(dataframe["date"].iloc[0].timestamp() * 1000)
end_ts = int(dataframe["date"].iloc[-1].timestamp() * 1000)
timerange = TimeRange("date", "date", startts=start_ts, stopts=end_ts)
else:
timerange = None
trades = self.dp.trades(pair=pair, copy=False, timerange=timerange)
# Apply additional filtering with buffer for faster backtesting
if not trades.empty and not dataframe.empty and "timestamp" in trades.columns:
# Add timeframe buffer to ensure complete candle coverage
timeframe_buffer = timeframe_to_seconds(self.config["timeframe"]) * 1000
# Create time bounds with buffer
time_start = start_ts - timeframe_buffer
time_end = end_ts + timeframe_buffer
# Filter trades within buffered timerange
trades_mask = (trades["timestamp"] >= time_start) & (
trades["timestamp"] <= time_end
)
trades = trades.loc[trades_mask].reset_index(drop=True)
# TODO: slice trades to size of dataframe for faster backtesting
cached_grouped_trades: DataFrame | None = self._cached_grouped_trades_per_pair.get(pair)
dataframe, cached_grouped_trades = populate_dataframe_with_trades(
cached_grouped_trades, self.config, dataframe, trades