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feat: Remove redundant filtering, add tests for pyarrow trade filtering, use date utils for date to ts conversion

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This commit is contained in:
Maxime Pagnoulle
2025-08-24 11:59:56 +02:00
parent 82903cc567
commit f21c5ea88a
3 changed files with 71 additions and 19 deletions
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2
freqtrade/data/history/datahandlers/featherdatahandler.py
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@@ -143,7 +143,7 @@ class FeatherDataHandler(IDataHandler):
except (ImportError, AttributeError, ValueError) as e:
# Fallback: load entire file
logger.debug(f"Unable to use Arrow filtering, loading entire trades file: {e}")
logger.warning(f"Unable to use Arrow filtering, loading entire trades file: {e}")
tradesdata = read_feather(filename)
return tradesdata

21
freqtrade/strategy/interface.py
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@@ -41,7 +41,7 @@ from freqtrade.strategy.informative_decorator import (
)
from freqtrade.strategy.strategy_validation import StrategyResultValidator
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.util import dt_now
from freqtrade.util import dt_now, dt_ts
from freqtrade.wallets import Wallets
@@ -1770,29 +1770,14 @@ class IStrategy(ABC, HyperStrategyMixin):
pair = metadata["pair"]
# 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)
start_ts = dt_ts(dataframe["date"].iloc[0])
end_ts = dt_ts(dataframe["date"].iloc[-1])
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)
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