chore: update pylance dependency to v4.0.0b12

pyproject.toml

@@ -24,7 +24,7 @@ classifiers = [
 
 dependencies = [
     "ray[data]>=2.41.0",
-    "pylance>=2.0.0",
+    "pylance>=4.0.0b12",
     "lance-namespace",
     "pyarrow>=17.0.0",
     "more_itertools>=2.6.0; python_version<'3.12'",

tests/test_blob.py

@@ -344,10 +344,7 @@ def test_stream_copy_basic_local(temp_dir):
     assert src.schema == dst.schema
 
     src_df = (
-        ray.data.from_arrow(table)
-        .to_pandas()
-        .sort_values("id")
-        .reset_index(drop=True)
+        ray.data.from_arrow(table).to_pandas().sort_values("id").reset_index(drop=True)
     )
     dst_df = (
         lr.read_lance(str(dst_path))
@@ -367,7 +364,9 @@ def test_stream_copy_resume_local(temp_dir):
     # Legacy blob schema
     schema = pa.schema(
         [
-            pa.field("blob", pa.large_binary(), metadata={"lance-encoding:blob": "true"}),
+            pa.field(
+                "blob", pa.large_binary(), metadata={"lance-encoding:blob": "true"}
+            ),
             pa.field("id", pa.int64()),
             pa.field("name", pa.string()),
             pa.field("val", pa.float64()),
@@ -402,10 +401,7 @@ def test_stream_copy_resume_local(temp_dir):
     )
 
     src_df = (
-        ray.data.from_arrow(table)
-        .to_pandas()
-        .sort_values("id")
-        .reset_index(drop=True)
+        ray.data.from_arrow(table).to_pandas().sort_values("id").reset_index(drop=True)
     )
     dst_df = (
         lr.read_lance(str(dst_path))

tests/test_distributed_indexing.py

@@ -465,9 +465,13 @@ def test_scalar_index_on_mixed_schema_list_indices(self, temp_dir):
         )
 
         indices = updated_dataset.list_indices()
-        assert len(indices) >= 1, "list_indices should return at least the new scalar index"
+        assert len(indices) >= 1, (
+            "list_indices should return at least the new scalar index"
+        )
         names = [idx["name"] for idx in indices]
-        assert index_name in names, f"Expected index name {index_name!r} in list_indices: {names}"
+        assert index_name in names, (
+            f"Expected index name {index_name!r} in list_indices: {names}"
+        )
 
         label_index = next(idx for idx in indices if idx["name"] == index_name)
         assert label_index["type"] == "BTree", (
@@ -1018,7 +1022,9 @@ def test_optimize_indices_success_with_uri(self, multi_fragment_lance_dataset):
         assert result.count_rows() == lance.LanceDataset(dataset_uri).count_rows()
 
         indices = result.list_indices()
-        assert len(indices) >= 1, "list_indices should include at least the existing index"
+        assert len(indices) >= 1, (
+            "list_indices should include at least the existing index"
+        )
         names = [idx["name"] for idx in indices]
         assert "text_idx" in names, f"Expected 'text_idx' in list_indices: {names}"
 
@@ -1029,9 +1035,10 @@ def test_optimize_indices_runtime_error_when_api_missing(self, temp_dir):
         lr.write_lance(ray.data.from_pandas(df), str(path))
         ds = lance.LanceDataset(str(path))
 
-        if getattr(ds, "optimize_indices", None) is not None or getattr(
-            ds, "optimize", None
-        ) is not None:
+        if (
+            getattr(ds, "optimize_indices", None) is not None
+            or getattr(ds, "optimize", None) is not None
+        ):
             pytest.skip(
                 "This lance version exposes optimize_indices/optimize; "
                 "cannot test RuntimeError path."