feat: Support for unbounded start and/or end in timerange filtering, added associated tests

freqtrade/data/history/datahandlers/featherdatahandler.py

@@ -112,6 +112,36 @@ class FeatherDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
+    def _build_arrow_time_filter(self, timerange: TimeRange | None):
+        """
+        Build Arrow predicate filter for timerange filtering.
+        Treats 0 as unbounded (no filter on that side).
+        :param timerange: TimeRange object with start/stop timestamps
+        :return: Arrow filter expression or None if fully unbounded
+        """
+        if not timerange:
+            return None
+
+        # Treat 0 as unbounded
+        start_set = bool(timerange.startts and timerange.startts > 0)
+        stop_set = bool(timerange.stopts and timerange.stopts > 0)
+
+        if not (start_set or stop_set):
+            return None
+
+        ts_field = dataset.field("timestamp")
+        exprs = []
+
+        if start_set:
+            exprs.append(ts_field >= timerange.startts)
+        if stop_set:
+            exprs.append(ts_field <= timerange.stopts)
+
+        if len(exprs) == 1:
+            return exprs[0]
+        else:
+            return exprs[0] & exprs[1]
+
     def _trades_load(
         self, pair: str, trading_mode: TradingMode, timerange: TimeRange | None = None
     ) -> DataFrame:
@@ -126,20 +156,22 @@ class FeatherDataHandler(IDataHandler):
         if not filename.exists():
             return DataFrame(columns=DEFAULT_TRADES_COLUMNS)
 
-        # Load trades data with optional timerange filtering
-        if timerange is None:
-            # No timerange filter - load entire file
-            logger.debug(f"Loading entire trades file for {pair}")
-            tradesdata = read_feather(filename)
-        else:
-            # Use Arrow dataset with predicate pushdown for efficient filtering
+        # Use Arrow dataset with optional timerange filtering, fallback to read_feather
         try:
             dataset_reader = dataset.dataset(filename, format="feather")
-                time_filter = (dataset.field("timestamp") >= timerange.startts) & (
-                    dataset.field("timestamp") <= timerange.stopts
-                )
+            time_filter = self._build_arrow_time_filter(timerange)
+
+            if time_filter is not None and timerange is not None:
                 tradesdata = dataset_reader.to_table(filter=time_filter).to_pandas()
-                logger.debug(f"Loaded {len(tradesdata)} trades for {pair}")
+                start_desc = timerange.startts if timerange.startts > 0 else "unbounded"
+                stop_desc = timerange.stopts if timerange.stopts > 0 else "unbounded"
+                logger.debug(
+                    f"Loaded {len(tradesdata)} trades for {pair} "
+                    f"(filtered start={start_desc}, stop={stop_desc})"
+                )
+            else:
+                tradesdata = dataset_reader.to_table().to_pandas()
+                logger.debug(f"Loaded {len(tradesdata)} trades for {pair} (unfiltered)")
 
         except (ImportError, AttributeError, ValueError) as e:
             # Fallback: load entire file

tests/data/test_datahandler.py

@@ -571,3 +571,72 @@ def test_feather_trades_timerange_pushdown_fallback(
         "Unable to use Arrow filtering, loading entire trades file" in r.message
         for r in caplog.records
     )
+
+
+def test_feather_trades_timerange_open_start(feather_dh, trades_full):
+    # Open start: stop timestamp but no start (startts=0)
+    stop_ts = int(trades_full["timestamp"].iloc[(2 * len(trades_full)) // 3])
+    tr = TimeRange(None, "date", startts=0, stopts=stop_ts)
+
+    filtered = feather_dh.trades_load("XRP/ETH", TradingMode.SPOT, timerange=tr)
+    assert 0 < len(filtered) < len(trades_full)
+    assert filtered["timestamp"].max() <= stop_ts
+    # First row should match full's first row
+    assert filtered.iloc[0]["timestamp"] == trades_full.iloc[0]["timestamp"]
+
+
+def test_feather_trades_timerange_open_end(feather_dh, trades_full):
+    # Open end: start timestamp but no stop (stopts=0)
+    start_ts = int(trades_full["timestamp"].iloc[len(trades_full) // 3])
+    tr = TimeRange("date", None, startts=start_ts, stopts=0)
+
+    filtered = feather_dh.trades_load("XRP/ETH", TradingMode.SPOT, timerange=tr)
+    assert 0 < len(filtered) < len(trades_full)
+    assert filtered["timestamp"].min() >= start_ts
+    # Last row should match full's last row
+    assert filtered.iloc[-1]["timestamp"] == trades_full.iloc[-1]["timestamp"]
+
+
+def test_feather_trades_timerange_fully_open(feather_dh, trades_full):
+    # Fully open: no start or stop bounds (both 0)
+    tr = TimeRange(None, None, startts=0, stopts=0)
+
+    filtered = feather_dh.trades_load("XRP/ETH", TradingMode.SPOT, timerange=tr)
+    # Should equal unfiltered load
+    assert_frame_equal(
+        trades_full.reset_index(drop=True), filtered.reset_index(drop=True), check_exact=True
+    )
+
+
+def test_feather_build_arrow_time_filter(feather_dh):
+    # None timerange should return None
+    assert feather_dh._build_arrow_time_filter(None) is None
+
+    # Fully open (both bounds 0) should return None
+    tr_fully_open = TimeRange(None, None, startts=0, stopts=0)
+    assert feather_dh._build_arrow_time_filter(tr_fully_open) is None
+
+    # Open start (startts=0) should return stop filter only
+    tr_open_start = TimeRange(None, "date", startts=0, stopts=1000)
+    filter_open_start = feather_dh._build_arrow_time_filter(tr_open_start)
+    assert filter_open_start is not None
+    # Should be a single expression (timestamp <= stopts)
+    assert str(filter_open_start).count("<=") == 1
+    assert str(filter_open_start).count(">=") == 0
+
+    # Open end (stopts=0) should return start filter only
+    tr_open_end = TimeRange("date", None, startts=500, stopts=0)
+    filter_open_end = feather_dh._build_arrow_time_filter(tr_open_end)
+    assert filter_open_end is not None
+    # Should be a single expression (timestamp >= startts)
+    assert str(filter_open_end).count(">=") == 1
+    assert str(filter_open_end).count("<=") == 0
+
+    # Closed range should return combined filter
+    tr_closed = TimeRange("date", "date", startts=500, stopts=1000)
+    filter_closed = feather_dh._build_arrow_time_filter(tr_closed)
+    assert filter_closed is not None
+    # Should contain both >= and <= (combined with &)
+    filter_str = str(filter_closed)
+    assert ">=" in filter_str
+    assert "<=" in filter_str