fix: parse UTC metric timestamps on Python 3.10

Author: O2eg

src/pg_diag/metric_engine.py

@@ -1488,6 +1488,10 @@ def _chart_epoch_status(previous: dict[str, Any], current: dict[str, Any]) -> st
 
 
 def _seconds_between(start: str, end: str) -> float:
+    # json_safe serializes UTC datetimes with Z; Python 3.10 requires an
+    # explicit offset when parsing those source timestamps with fromisoformat.
+    start = start[:-1] + "+00:00" if start.endswith("Z") else start
+    end = end[:-1] + "+00:00" if end.endswith("Z") else end
     try:
         return max((datetime.fromisoformat(end) - datetime.fromisoformat(start)).total_seconds(), 0.0)
     except ValueError:

tests/README.md

@@ -281,3 +281,5 @@ counts and changing top-N wait groups must retain their diagnostic evidence.
 The pytest wrapper passes explicit test file paths for compatibility with Node
 18 and 22. Architecture tests also cover event metadata, writer-pressure counts,
 and wait-profile shares with unequal sample counts.
+`test_metric_engine.py` verifies that UTC timestamps emitted by `json_safe`
+produce valid delta and rate intervals on Python 3.10 as well as newer versions.

tests/unit/test_metric_engine.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 
 import pytest
@@ -15,6 +16,7 @@
     evaluate_metric_table_findings,
 )
 from pg_diag.planner import PlannedItem
+from pg_diag.security import json_safe
 from pg_diag.versioning import select_query_variant
 
 
@@ -43,6 +45,23 @@
 }
 
 
+@pytest.mark.parametrize(("transform", "expected"), [("delta", 120), ("rate", 4.0)])
+def test_chart_intervals_accept_serialized_utc_timestamps(transform: str, expected: float) -> None:
+    start = datetime(2026, 9, 5, tzinfo=timezone.utc)
+    samples = json_safe([
+        {"timestamp": start, "rows": [{"value": 10}]},
+        {"timestamp": start + timedelta(seconds=30), "rows": [{"value": 130}]},
+    ])
+    assert all(sample["timestamp"].endswith("Z") for sample in samples)
+    result = build_chart_result(
+        {"series": [{"name": "count", "value_ref": "value", "transform": transform}]},
+        samples,
+        {},
+    )
+    assert result["series"][0]["points"][-1]["value"] == expected
+    assert result["interval_coverage"]["comparable"] == 1
+
+
 @pytest.mark.parametrize("entry", [
     {"name": "rx", "sample_count": 2, "missing_count": -1},
     {"name": "rx", "sample_count": True, "missing_count": 0},