fix: use PyCapsule Interface instead of Dataframe Interchange Protocol

pyproject.toml

@@ -42,6 +42,7 @@ dev = [
     "mypy",
     "pandas-stubs",
     "pre-commit",
+    "pyarrow",
     "flit",
 ]
 docs = [

seaborn/_core/data.py

@@ -5,7 +5,6 @@
 
 from collections.abc import Mapping, Sized
 from typing import cast
-import warnings
 
 import pandas as pd
 from pandas import DataFrame
@@ -269,9 +268,9 @@ def _assign_variables(
 
 def handle_data_source(data: object) -> pd.DataFrame | Mapping | None:
     """Convert the data source object to a common union representation."""
-    if isinstance(data, pd.DataFrame) or hasattr(data, "__dataframe__"):
+    if isinstance(data, pd.DataFrame) or hasattr(data, "__arrow_c_stream__"):
         # Check for pd.DataFrame inheritance could be removed once
-        # minimal pandas version supports dataframe interchange (1.5.0).
+        # minimal pandas version supports PyCapsule Interface (2.2).
         data = convert_dataframe_to_pandas(data)
     elif data is not None and not isinstance(data, Mapping):
         err = f"Data source must be a DataFrame or Mapping, not {type(data)!r}."
@@ -285,35 +284,32 @@ def convert_dataframe_to_pandas(data: object) -> pd.DataFrame:
     if isinstance(data, pd.DataFrame):
         return data
 
-    if not hasattr(pd.api, "interchange"):
-        msg = (
-            "Support for non-pandas DataFrame objects requires a version of pandas "
-            "that implements the DataFrame interchange protocol. Please upgrade "
-            "your pandas version or coerce your data to pandas before passing "
-            "it to seaborn."
-        )
-        raise TypeError(msg)
-
-    if _version_predates(pd, "2.0.2"):
-        msg = (
-            "DataFrame interchange with pandas<2.0.2 has some known issues. "
-            f"You are using pandas {pd.__version__}. "
-            "Continuing, but it is recommended to carefully inspect the results and to "
-            "consider upgrading."
-        )
-        warnings.warn(msg, stacklevel=2)
-
-    try:
-        # This is going to convert all columns in the input dataframe, even though
-        # we may only need one or two of them. It would be more efficient to select
-        # the columns that are going to be used in the plot prior to interchange.
-        # Solving that in general is a hard problem, especially with the objects
-        # interface where variables passed in Plot() may only be referenced later
-        # in Plot.add(). But noting here in case this seems to be a bottleneck.
-        return pd.api.interchange.from_dataframe(data)
-    except Exception as err:
-        msg = (
-            "Encountered an exception when converting data source "
-            "to a pandas DataFrame. See traceback above for details."
-        )
-        raise RuntimeError(msg) from err
+    if hasattr(data, '__arrow_c_stream__'):
+        try:
+            import pyarrow
+        except ImportError as err:
+            msg = "PyArrow is required for non-pandas Dataframe support."
+            raise RuntimeError(msg) from err
+        if _version_predates(pyarrow, '14.0.0'):
+            msg = "PyArrow>=14.0.0 is required for non-pandas Dataframe support."
+            raise RuntimeError(msg)
+        try:
+            # This is going to convert all columns in the input dataframe, even though
+            # we may only need one or two of them. It would be more efficient to select
+            # the columns that are going to be used in the plot prior to interchange.
+            # Solving that in general is a hard problem, especially with the objects
+            # interface where variables passed in Plot() may only be referenced later
+            # in Plot.add(). But noting here in case this seems to be a bottleneck.
+            return pyarrow.table(data).to_pandas()
+        except Exception as err:
+            msg = (
+                "Encountered an exception when converting data source "
+                "to a pandas DataFrame. See traceback above for details."
+            )
+            raise RuntimeError(msg) from err
+
+    msg = (
+        "Expected object which implements '__arrow_c_stream__' from the "
+        f"PyCapsule Interface, got: {type(data)}"
+    )
+    raise TypeError(msg)

seaborn/_core/plot.py

@@ -349,7 +349,7 @@ def _resolve_positionals(
 
         if (
             isinstance(args[0], (abc.Mapping, pd.DataFrame))
-            or hasattr(args[0], "__dataframe__")
+            or hasattr(args[0], "__arrow_c_stream__")
         ):
             if data is not None:
                 raise TypeError("`data` given by both name and position.")

seaborn/_core/typing.py

@@ -17,9 +17,9 @@
 VariableSpec = Union[ColumnName, Vector, None]
 VariableSpecList = Union[List[VariableSpec], Index, None]
 
-# A DataSource can be an object implementing __dataframe__, or a Mapping
+# A DataSource can be an object implementing __arrow_c_stream__, or a Mapping
 # (and is optional in all contexts where it is used).
-# I don't think there's an abc for "has __dataframe__", so we type as object
+# I don't think there's an abc for "has __arrow_c_stream__", so we type as object
 # but keep the (slightly odd) Union alias for better user-facing annotations.
 DataSource = Union[object, Mapping, None]
 

tests/_core/test_data.py

@@ -1,6 +1,7 @@
 import functools
 import numpy as np
 import pandas as pd
+from seaborn.external.version import Version
 
 import pytest
 from numpy.testing import assert_array_equal
@@ -405,8 +406,8 @@ def test_bad_type(self, flat_list):
             PlotData(flat_list, {})
 
     @pytest.mark.skipif(
-        condition=not hasattr(pd.api, "interchange"),
-        reason="Tests behavior assuming support for dataframe interchange"
+        condition=not hasattr(pd.DataFrame, "__arrow_c_stream__"),
+        reason="Tests behavior assuming support for PyCapsule Interface"
     )
     def test_data_interchange(self, mock_long_df, long_df):
 
@@ -420,20 +421,21 @@ def test_data_interchange(self, mock_long_df, long_df):
             assert_vector_equal(p.frame[var], long_df[col])
 
     @pytest.mark.skipif(
-        condition=not hasattr(pd.api, "interchange"),
-        reason="Tests behavior assuming support for dataframe interchange"
+        condition=not hasattr(pd.DataFrame, "__arrow_c_stream__"),
+        reason="Tests behavior assuming support for PyCapsule Interface"
     )
     def test_data_interchange_failure(self, mock_long_df):
 
-        mock_long_df._data = None  # Break __dataframe__()
+        mock_long_df.__arrow_c_stream__ = lambda _x: 1 / 0  # Break __arrow_c_stream__()
         with pytest.raises(RuntimeError, match="Encountered an exception"):
             PlotData(mock_long_df, {"x": "x"})
 
-    @pytest.mark.skipif(
-        condition=hasattr(pd.api, "interchange"),
-        reason="Tests graceful failure without support for dataframe interchange"
-    )
     def test_data_interchange_support_test(self, mock_long_df):
+        pyarrow = pytest.importorskip('pyarrow')
+        if Version(pyarrow.__version__) >= Version('14.0.0'):
+            pytest.skip(
+                reason="Tests graceful failure without support for PyCapsule Interface"
+            )
 
         with pytest.raises(TypeError, match="Support for non-pandas DataFrame"):
             PlotData(mock_long_df, {"x": "x"})

tests/_core/test_plot.py

@@ -171,8 +171,8 @@ def test_positional_x(self, long_df):
         assert list(p._data.source_vars) == ["x"]
 
     @pytest.mark.skipif(
-        condition=not hasattr(pd.api, "interchange"),
-        reason="Tests behavior assuming support for dataframe interchange"
+        condition=not hasattr(pd.DataFrame, "__arrow_c_stream__"),
+        reason="Tests behavior assuming support for PyCapsule Interface"
     )
     def test_positional_interchangeable_dataframe(self, mock_long_df, long_df):
 

tests/conftest.py

@@ -188,11 +188,12 @@ class MockInterchangeableDataFrame:
     def __init__(self, data):
         self._data = data
 
-    def __dataframe__(self, *args, **kwargs):
-        return self._data.__dataframe__(*args, **kwargs)
+    def __arrow_c_stream__(self, *args, **kwargs):
+        return self._data.__arrow_c_stream__()
 
 
 @pytest.fixture
 def mock_long_df(long_df):
+    import pyarrow
 
-    return MockInterchangeableDataFrame(long_df)
+    return MockInterchangeableDataFrame(pyarrow.Table.from_pandas(long_df))

tests/test_axisgrid.py

@@ -709,8 +709,8 @@ def test_tick_params(self):
                     assert tick.get_pad() == pad
 
     @pytest.mark.skipif(
-        condition=not hasattr(pd.api, "interchange"),
-        reason="Tests behavior assuming support for dataframe interchange"
+        condition=not hasattr(pd.DataFrame, "__arrow_c_stream__"),
+        reason="Tests behavior assuming support for PyCapsule Interface"
     )
     def test_data_interchange(self, mock_long_df, long_df):
 
@@ -1478,8 +1478,8 @@ def test_tick_params(self):
                     assert tick.get_pad() == pad
 
     @pytest.mark.skipif(
-        condition=not hasattr(pd.api, "interchange"),
-        reason="Tests behavior assuming support for dataframe interchange"
+        condition=not hasattr(pd.DataFrame, "__arrow_c_stream__"),
+        reason="Tests behavior assuming support for PyCapsule Interface"
     )
     def test_data_interchange(self, mock_long_df, long_df):