fix(python): Fix interchange protocol data buffer dtype (#10787)

Author: stinodego

py-polars/polars/interchange/column.py

@@ -157,11 +157,7 @@ def get_buffers(self) -> ColumnBuffers:
     def _get_data_buffer(self) -> tuple[PolarsBuffer, Dtype]:
         s = self._col._get_buffer(0)
         buffer = PolarsBuffer(s, allow_copy=self._allow_copy)
-
-        dtype = self.dtype
-        if dtype[0] == DtypeKind.CATEGORICAL:
-            dtype = (DtypeKind.UINT, 32, "I", Endianness.NATIVE)
-
+        dtype = polars_dtype_to_dtype(s.dtype)
         return buffer, dtype
 
     def _get_validity_buffer(self) -> tuple[PolarsBuffer, Dtype] | None:

py-polars/tests/unit/interchange/test_column.py

@@ -206,7 +206,7 @@ def test_get_buffers_with_validity_and_offsets() -> None:
     data_buffer, data_dtype = out["data"]
     expected = pl.Series([97, 98, 99, 195, 169, 195, 162, 195, 167], dtype=pl.UInt8)
     assert_series_equal(data_buffer._data, expected)
-    assert data_dtype == (DtypeKind.STRING, 8, "U", "=")
+    assert data_dtype == (DtypeKind.UINT, 8, "C", "=")
 
     validity = out["validity"]
     assert validity is not None
@@ -260,14 +260,14 @@ def test_get_buffers_chunked_zero_copy_fails() -> None:
         (
             pl.Series(["a", "bc", None, "éâç"], dtype=pl.String),
             pl.Series([97, 98, 99, 195, 169, 195, 162, 195, 167], dtype=pl.UInt8),
-            (DtypeKind.STRING, 8, "U", "="),
+            (DtypeKind.UINT, 8, "C", "="),
         ),
         (
             pl.Series(
                 [datetime(1988, 1, 2), None, datetime(2022, 12, 3)], dtype=pl.Datetime
             ),
             pl.Series([568080000000000, 0, 1670025600000000], dtype=pl.Int64),
-            (DtypeKind.DATETIME, 64, "tsu:", "="),
+            (DtypeKind.INT, 64, "l", "="),
         ),
         (
             pl.Series(["a", "b", None, "a"], dtype=pl.Categorical),

py-polars/tests/unit/interchange/test_roundtrip.py

@@ -57,6 +57,10 @@ def test_to_dataframe_pyarrow_zero_copy_parametric(df: pl.DataFrame) -> None:
     assert_frame_equal(result, df, categorical_as_str=True)
 
 
+@pytest.mark.skipif(
+    sys.version_info < (3, 9),
+    reason="The correct `from_dataframe` implementation for pandas is not available before Python 3.9",
+)
 @pytest.mark.filterwarnings(
     "ignore:.*PEP3118 format string that does not match its itemsize:RuntimeWarning"
 )
@@ -68,6 +72,10 @@ def test_to_dataframe_pandas_parametric(df: pl.DataFrame) -> None:
     assert_frame_equal(result, df, categorical_as_str=True)
 
 
+@pytest.mark.skipif(
+    sys.version_info < (3, 9),
+    reason="The correct `from_dataframe` implementation for pandas is not available before Python 3.9",
+)
 @pytest.mark.filterwarnings(
     "ignore:.*PEP3118 format string that does not match its itemsize:RuntimeWarning"
 )