fix(chart): Bump deepnote-vegafusion to 2.1.1 for fractional-second timestamps

pyproject.toml

@@ -125,7 +125,7 @@ dependencies = [
     # NOTE: 1.7.0 is latest version of vl-convert which ships with Vega 5. In webapp we can't update to Vega 6 due to ESM-only issues
     # so we keep vl-convert version pinned as well
     "vl-convert-python==1.7.0",
-    "deepnote-vegafusion>=2.1.0,<3",
+    "deepnote-vegafusion>=2.1.1,<3",
     "matplotlib-inline>=0.1.7,<0.2.0; python_version <= '3.10'",  # 0.2.0 is not compatible with matplotlib 3.6.3 on Python <=3.10
     "matplotlib-inline>=0.2.1,<0.3.0; python_version >= '3.11'",
 

tests/unit/test_chart.py

@@ -246,6 +246,39 @@ def test_works_with_polars_uuid_object_column(self):
         spec = {"mark": "bar", "encoding": {"x": {"field": "id"}}}
         self._assert_chart_is_json_serializable(df, spec)
 
+    # Regression test: naive timestamp strings only parsed with 0 or 3 fractional digits.
+    @parameterized.expand(
+        [
+            ("no_fraction", "2024-01-01 10:00:00", "2024-01-01T10:00:00.000"),
+            ("tenths", "2024-01-01 10:00:00.1", "2024-01-01T10:00:00.100"),
+            ("milliseconds", "2024-01-01 10:00:00.123", "2024-01-01T10:00:00.123"),
+            ("microseconds", "2024-01-01 10:00:00.123456", "2024-01-01T10:00:00.123"),
+            (
+                "nanoseconds",
+                "2024-01-01 10:00:00.123456789",
+                "2024-01-01T10:00:00.123",
+            ),
+        ]
+    )
+    def test_timezone_naive_string_timestamps(self, _name, raw_timestamp, expected):
+        df = pd.DataFrame({"ts": [raw_timestamp], "value": [1]})
+        spec = {
+            "mark": "line",
+            "encoding": {
+                "x": {"field": "ts", "type": "temporal"},
+                "y": {"field": "value", "type": "quantitative"},
+            },
+        }
+
+        chart = DeepnoteChart(df, spec_dict=spec)
+
+        charted_rows = [
+            dataset["values"]
+            for dataset in chart.compiled_vega_spec_dict["data"]
+            if dataset.get("values") and "ts" in dataset["values"][0]
+        ]
+        self.assertEqual(charted_rows, [[{"ts": expected, "value": 1}]])
+
 
 class TestDeepnoteSanitizeDataframe(unittest.TestCase):
     def test_small_dataframe_remains_ordered_the_same(self):