test_cffi.py

# -*- coding: utf-8 -*-
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# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

import contextlib
import ctypes
import gc

import pyarrow as pa
try:
    from pyarrow.cffi import ffi
except ImportError:
    ffi = None

import pytest

try:
    import pandas as pd
    import pandas.testing as tm
except ImportError:
    pd = tm = None


needs_cffi = pytest.mark.skipif(ffi is None,
                                reason="test needs cffi package installed")

assert_schema_released = pytest.raises(
    ValueError, match="Cannot import released ArrowSchema")

assert_array_released = pytest.raises(
    ValueError, match="Cannot import released ArrowArray")

assert_stream_released = pytest.raises(
    ValueError, match="Cannot import released Arrow Stream")


def PyCapsule_IsValid(capsule, name):
    return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1


@contextlib.contextmanager
def registered_extension_type(ext_type):
    pa.register_extension_type(ext_type)
    try:
        yield
    finally:
        pa.unregister_extension_type(ext_type.extension_name)


class ParamExtType(pa.ExtensionType):

    def __init__(self, width):
        self._width = width
        super().__init__(pa.binary(width),
                         "pyarrow.tests.test_cffi.ParamExtType")

    @property
    def width(self):
        return self._width

    def __arrow_ext_serialize__(self):
        return str(self.width).encode()

    @classmethod
    def __arrow_ext_deserialize__(cls, storage_type, serialized):
        width = int(serialized.decode())
        return cls(width)


def make_schema():
    return pa.schema([('ints', pa.list_(pa.int32()))],
                     metadata={b'key1': b'value1'})


def make_extension_schema():
    return pa.schema([('ext', ParamExtType(3))],
                     metadata={b'key1': b'value1'})


def make_extension_storage_schema():
    # Should be kept in sync with make_extension_schema
    return pa.schema([('ext', ParamExtType(3).storage_type)],
                     metadata={b'key1': b'value1'})


def make_batch():
    return pa.record_batch([[[1], [2, 42]]], make_schema())


def make_extension_batch():
    schema = make_extension_schema()
    ext_col = schema[0].type.wrap_array(pa.array([b"foo", b"bar"],
                                                 type=pa.binary(3)))
    return pa.record_batch([ext_col], schema)


def make_batches():
    schema = make_schema()
    return [
        pa.record_batch([[[1], [2, 42]]], schema),
        pa.record_batch([[None, [], [5, 6]]], schema),
    ]


def make_serialized(schema, batches):
    with pa.BufferOutputStream() as sink:
        with pa.ipc.new_stream(sink, schema) as out:
            for batch in batches:
                out.write(batch)
        return sink.getvalue()


@needs_cffi
def test_export_import_type():
    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    typ = pa.list_(pa.int32())
    typ._export_to_c(ptr_schema)
    assert pa.total_allocated_bytes() > old_allocated
    # Delete and recreate C++ object from exported pointer
    del typ
    assert pa.total_allocated_bytes() > old_allocated
    typ_new = pa.DataType._import_from_c(ptr_schema)
    assert typ_new == pa.list_(pa.int32())
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_schema_released:
        pa.DataType._import_from_c(ptr_schema)

    # Invalid format string
    pa.int32()._export_to_c(ptr_schema)
    bad_format = ffi.new("char[]", b"zzz")
    c_schema.format = bad_format
    with pytest.raises(ValueError,
                       match="Invalid or unsupported format string"):
        pa.DataType._import_from_c(ptr_schema)
    # Now released
    with assert_schema_released:
        pa.DataType._import_from_c(ptr_schema)


@needs_cffi
def test_export_import_field():
    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    field = pa.field("test", pa.list_(pa.int32()), nullable=True)
    field._export_to_c(ptr_schema)
    assert pa.total_allocated_bytes() > old_allocated
    # Delete and recreate C++ object from exported pointer
    del field
    assert pa.total_allocated_bytes() > old_allocated

    field_new = pa.Field._import_from_c(ptr_schema)
    assert field_new == pa.field("test", pa.list_(pa.int32()), nullable=True)
    assert pa.total_allocated_bytes() == old_allocated

    # Now released
    with assert_schema_released:
        pa.Field._import_from_c(ptr_schema)


def check_export_import_array(array_type, exporter, importer):
    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))
    c_array = ffi.new(f"struct {array_type}*")
    ptr_array = int(ffi.cast("uintptr_t", c_array))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    # Type is known up front
    typ = pa.list_(pa.int32())
    arr = pa.array([[1], [2, 42]], type=typ)
    py_value = arr.to_pylist()
    exporter(arr, ptr_array)
    assert pa.total_allocated_bytes() > old_allocated
    # Delete recreate C++ object from exported pointer
    del arr
    arr_new = importer(ptr_array, typ)
    assert arr_new.to_pylist() == py_value
    assert arr_new.type == pa.list_(pa.int32())
    assert pa.total_allocated_bytes() > old_allocated
    del arr_new, typ
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_array_released:
        importer(ptr_array, pa.list_(pa.int32()))

    # Type is exported and imported at the same time
    arr = pa.array([[1], [2, 42]], type=pa.list_(pa.int32()))
    py_value = arr.to_pylist()
    exporter(arr, ptr_array, ptr_schema)
    # Delete and recreate C++ objects from exported pointers
    del arr
    arr_new = importer(ptr_array, ptr_schema)
    assert arr_new.to_pylist() == py_value
    assert arr_new.type == pa.list_(pa.int32())
    assert pa.total_allocated_bytes() > old_allocated
    del arr_new
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_schema_released:
        importer(ptr_array, ptr_schema)


@needs_cffi
def test_export_import_array():
    check_export_import_array(
        "ArrowArray",
        pa.Array._export_to_c,
        pa.Array._import_from_c,
    )


@needs_cffi
def test_export_import_device_array():
    check_export_import_array(
        "ArrowDeviceArray",
        pa.Array._export_to_c_device,
        pa.Array._import_from_c_device,
    )

    # verify exported struct
    c_array = ffi.new("struct ArrowDeviceArray*")
    ptr_array = int(ffi.cast("uintptr_t", c_array))
    arr = pa.array([[1], [2, 42]], type=pa.list_(pa.int32()))
    arr._export_to_c_device(ptr_array)

    assert c_array.device_type == 1  # ARROW_DEVICE_CPU 1
    assert c_array.device_id == -1
    assert c_array.array.length == 2


def check_export_import_schema(schema_factory, expected_schema_factory=None):
    if expected_schema_factory is None:
        expected_schema_factory = schema_factory

    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    schema_factory()._export_to_c(ptr_schema)
    assert pa.total_allocated_bytes() > old_allocated
    # Delete and recreate C++ object from exported pointer
    schema_new = pa.Schema._import_from_c(ptr_schema)
    assert schema_new == expected_schema_factory()
    assert pa.total_allocated_bytes() == old_allocated
    del schema_new
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_schema_released:
        pa.Schema._import_from_c(ptr_schema)

    # Not a struct type
    pa.int32()._export_to_c(ptr_schema)
    with pytest.raises(ValueError,
                       match="ArrowSchema describes non-struct type"):
        pa.Schema._import_from_c(ptr_schema)
    # Now released
    with assert_schema_released:
        pa.Schema._import_from_c(ptr_schema)


@needs_cffi
def test_export_import_schema():
    check_export_import_schema(make_schema)


@needs_cffi
def test_export_import_schema_with_extension():
    # Extension type is unregistered => the storage type is imported
    check_export_import_schema(make_extension_schema,
                               make_extension_storage_schema)

    # Extension type is registered => the extension type is imported
    with registered_extension_type(ParamExtType(1)):
        check_export_import_schema(make_extension_schema)


@needs_cffi
def test_export_import_schema_float_pointer():
    # Previous versions of the R Arrow library used to pass pointer
    # values as a double.
    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))

    match = "Passing a pointer value as a float is unsafe"
    with pytest.warns(UserWarning, match=match):
        make_schema()._export_to_c(float(ptr_schema))
    with pytest.warns(UserWarning, match=match):
        schema_new = pa.Schema._import_from_c(float(ptr_schema))
    assert schema_new == make_schema()


def check_export_import_batch(array_type, exporter, importer, batch_factory):
    c_schema = ffi.new("struct ArrowSchema*")
    ptr_schema = int(ffi.cast("uintptr_t", c_schema))
    c_array = ffi.new(f"struct {array_type}*")
    ptr_array = int(ffi.cast("uintptr_t", c_array))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    # Schema is known up front
    batch = batch_factory()
    schema = batch.schema
    py_value = batch.to_pydict()
    exporter(batch, ptr_array)
    assert pa.total_allocated_bytes() > old_allocated
    # Delete and recreate C++ object from exported pointer
    del batch
    batch_new = importer(ptr_array, schema)
    assert batch_new.to_pydict() == py_value
    assert batch_new.schema == schema
    assert pa.total_allocated_bytes() > old_allocated
    del batch_new, schema
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_array_released:
        importer(ptr_array, make_schema())

    # Type is exported and imported at the same time
    batch = batch_factory()
    py_value = batch.to_pydict()
    batch._export_to_c(ptr_array, ptr_schema)
    # Delete and recreate C++ objects from exported pointers
    del batch
    batch_new = importer(ptr_array, ptr_schema)
    assert batch_new.to_pydict() == py_value
    assert batch_new.schema == batch_factory().schema
    assert pa.total_allocated_bytes() > old_allocated
    del batch_new
    assert pa.total_allocated_bytes() == old_allocated
    # Now released
    with assert_schema_released:
        importer(ptr_array, ptr_schema)

    # Not a struct type
    pa.int32()._export_to_c(ptr_schema)
    batch_factory()._export_to_c(ptr_array)
    with pytest.raises(ValueError,
                       match="ArrowSchema describes non-struct type"):
        importer(ptr_array, ptr_schema)
    # Now released
    with assert_schema_released:
        importer(ptr_array, ptr_schema)


@needs_cffi
def test_export_import_batch():
    check_export_import_batch(
        "ArrowArray",
        pa.RecordBatch._export_to_c,
        pa.RecordBatch._import_from_c,
        make_batch,
    )


@needs_cffi
def test_export_import_batch_with_extension():
    with registered_extension_type(ParamExtType(1)):
        check_export_import_batch(
            "ArrowArray",
            pa.RecordBatch._export_to_c,
            pa.RecordBatch._import_from_c,
            make_extension_batch,
        )


@needs_cffi
def test_export_import_device_batch():
    check_export_import_batch(
        "ArrowDeviceArray",
        pa.RecordBatch._export_to_c_device,
        pa.RecordBatch._import_from_c_device,
        make_batch,
    )

    # verify exported struct
    c_array = ffi.new("struct ArrowDeviceArray*")
    ptr_array = int(ffi.cast("uintptr_t", c_array))
    batch = make_batch()
    batch._export_to_c_device(ptr_array)
    assert c_array.device_type == 1  # ARROW_DEVICE_CPU 1
    assert c_array.device_id == -1
    assert c_array.array.length == 2


def _export_import_batch_reader(ptr_stream, reader_factory):
    # Prepare input
    batches = make_batches()
    schema = batches[0].schema

    reader = reader_factory(schema, batches)
    reader._export_to_c(ptr_stream)
    # Delete and recreate C++ object from exported pointer
    del reader, batches

    reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
    assert reader_new.schema == schema
    got_batches = list(reader_new)
    del reader_new
    assert got_batches == make_batches()

    # Test read_pandas()
    if pd is not None:
        batches = make_batches()
        schema = batches[0].schema
        expected_df = pa.Table.from_batches(batches).to_pandas()

        reader = reader_factory(schema, batches)
        reader._export_to_c(ptr_stream)
        del reader, batches

        reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
        got_df = reader_new.read_pandas()
        del reader_new
        tm.assert_frame_equal(expected_df, got_df)


def make_ipc_stream_reader(schema, batches):
    return pa.ipc.open_stream(make_serialized(schema, batches))


def make_py_record_batch_reader(schema, batches):
    return pa.RecordBatchReader.from_batches(schema, batches)


@needs_cffi
@pytest.mark.parametrize('reader_factory',
                         [make_ipc_stream_reader,
                          make_py_record_batch_reader])
def test_export_import_batch_reader(reader_factory):
    c_stream = ffi.new("struct ArrowArrayStream*")
    ptr_stream = int(ffi.cast("uintptr_t", c_stream))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    _export_import_batch_reader(ptr_stream, reader_factory)

    assert pa.total_allocated_bytes() == old_allocated

    # Now released
    with assert_stream_released:
        pa.RecordBatchReader._import_from_c(ptr_stream)


@needs_cffi
def test_export_import_exception_reader():
    # See: https://github.com/apache/arrow/issues/37164
    c_stream = ffi.new("struct ArrowArrayStream*")
    ptr_stream = int(ffi.cast("uintptr_t", c_stream))

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    def gen():
        if True:
            try:
                raise ValueError('foo')
            except ValueError as e:
                raise NotImplementedError('bar') from e
        else:
            yield from make_batches()

    original = pa.RecordBatchReader.from_batches(make_schema(), gen())
    original._export_to_c(ptr_stream)

    reader = pa.RecordBatchReader._import_from_c(ptr_stream)
    with pytest.raises(NotImplementedError) as exc_info:
        reader.read_next_batch()

    # inner *and* outer exception should be present
    assert 'ValueError: foo' in str(exc_info.value)
    assert 'NotImplementedError: bar' in str(exc_info.value)
    # Stacktrace containing line of the raise statement
    assert 'raise ValueError(\'foo\')' in str(exc_info.value)

    assert pa.total_allocated_bytes() == old_allocated


@needs_cffi
def test_imported_batch_reader_error():
    c_stream = ffi.new("struct ArrowArrayStream*")
    ptr_stream = int(ffi.cast("uintptr_t", c_stream))

    schema = pa.schema([('foo', pa.int32())])
    batches = [pa.record_batch([[1, 2, 3]], schema=schema),
               pa.record_batch([[4, 5, 6]], schema=schema)]
    buf = make_serialized(schema, batches)

    # Open a corrupt/incomplete stream and export it
    reader = pa.ipc.open_stream(buf[:-16])
    reader._export_to_c(ptr_stream)
    del reader

    reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
    batch = reader_new.read_next_batch()
    assert batch == batches[0]
    with pytest.raises(OSError,
                       match="Expected to be able to read 16 bytes "
                             "for message body, got 8"):
        reader_new.read_next_batch()

    # Again, but call read_all()
    reader = pa.ipc.open_stream(buf[:-16])
    reader._export_to_c(ptr_stream)
    del reader

    reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
    with pytest.raises(OSError,
                       match="Expected to be able to read 16 bytes "
                             "for message body, got 8"):
        reader_new.read_all()


@pytest.mark.parametrize('obj', [pa.int32(), pa.field('foo', pa.int32()),
                                 pa.schema({'foo': pa.int32()})],
                         ids=['type', 'field', 'schema'])
def test_roundtrip_schema_capsule(obj):
    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    capsule = obj.__arrow_c_schema__()
    assert PyCapsule_IsValid(capsule, b"arrow_schema") == 1
    assert pa.total_allocated_bytes() > old_allocated
    obj_out = type(obj)._import_from_c_capsule(capsule)
    assert obj_out == obj

    assert pa.total_allocated_bytes() == old_allocated

    capsule = obj.__arrow_c_schema__()

    assert pa.total_allocated_bytes() > old_allocated
    del capsule
    assert pa.total_allocated_bytes() == old_allocated


@pytest.mark.parametrize('arr,schema_accessor,bad_type,good_type', [
    (pa.array(['a', 'b', 'c']), lambda x: x.type, pa.int32(), pa.string()),
    (
        pa.record_batch([pa.array(['a', 'b', 'c'])], names=['x']),
        lambda x: x.schema,
        pa.schema({'x': pa.int32()}),
        pa.schema({'x': pa.string()})
    ),
], ids=['array', 'record_batch'])
def test_roundtrip_array_capsule(arr, schema_accessor, bad_type, good_type):
    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    import_array = type(arr)._import_from_c_capsule

    schema_capsule, capsule = arr.__arrow_c_array__()
    assert PyCapsule_IsValid(schema_capsule, b"arrow_schema") == 1
    assert PyCapsule_IsValid(capsule, b"arrow_array") == 1
    arr_out = import_array(schema_capsule, capsule)
    assert arr_out.equals(arr)

    assert pa.total_allocated_bytes() > old_allocated
    del arr_out

    assert pa.total_allocated_bytes() == old_allocated

    capsule = arr.__arrow_c_array__()

    assert pa.total_allocated_bytes() > old_allocated
    del capsule
    assert pa.total_allocated_bytes() == old_allocated

    with pytest.raises(ValueError,
                       match=r"Could not cast.* string to requested .* int32"):
        arr.__arrow_c_array__(bad_type.__arrow_c_schema__())

    schema_capsule, array_capsule = arr.__arrow_c_array__(
        good_type.__arrow_c_schema__())
    arr_out = import_array(schema_capsule, array_capsule)
    assert schema_accessor(arr_out) == good_type


@pytest.mark.parametrize('arr,schema_accessor,bad_type,good_type', [
    (pa.array(['a', 'b', 'c']), lambda x: x.type, pa.int32(), pa.string()),
    (
        pa.record_batch([pa.array(['a', 'b', 'c'])], names=['x']),
        lambda x: x.schema,
        pa.schema({'x': pa.int32()}),
        pa.schema({'x': pa.string()})
    ),
], ids=['array', 'record_batch'])
def test_roundtrip_device_array_capsule(arr, schema_accessor, bad_type, good_type):
    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    import_array = type(arr)._import_from_c_device_capsule

    schema_capsule, capsule = arr.__arrow_c_device_array__()
    assert PyCapsule_IsValid(schema_capsule, b"arrow_schema") == 1
    assert PyCapsule_IsValid(capsule, b"arrow_device_array") == 1
    arr_out = import_array(schema_capsule, capsule)
    assert arr_out.equals(arr)

    assert pa.total_allocated_bytes() > old_allocated
    del arr_out

    assert pa.total_allocated_bytes() == old_allocated

    capsule = arr.__arrow_c_array__()

    assert pa.total_allocated_bytes() > old_allocated
    del capsule
    assert pa.total_allocated_bytes() == old_allocated

    with pytest.raises(ValueError,
                       match=r"Could not cast.* string to requested .* int32"):
        arr.__arrow_c_device_array__(bad_type.__arrow_c_schema__())

    schema_capsule, array_capsule = arr.__arrow_c_device_array__(
        good_type.__arrow_c_schema__())
    arr_out = import_array(schema_capsule, array_capsule)
    assert schema_accessor(arr_out) == good_type


# TODO: implement requested_schema for stream
@pytest.mark.parametrize('constructor', [
    pa.RecordBatchReader.from_batches,
    # Use a lambda because we need to re-order the parameters
    lambda schema, batches: pa.Table.from_batches(batches, schema),
], ids=['recordbatchreader', 'table'])
def test_roundtrip_reader_capsule(constructor):
    batches = make_batches()
    schema = batches[0].schema

    gc.collect()  # Make sure no Arrow data dangles in a ref cycle
    old_allocated = pa.total_allocated_bytes()

    obj = constructor(schema, batches)

    capsule = obj.__arrow_c_stream__()
    assert PyCapsule_IsValid(capsule, b"arrow_array_stream") == 1
    imported_reader = pa.RecordBatchReader._import_from_c_capsule(capsule)
    assert imported_reader.schema == schema
    imported_batches = list(imported_reader)
    assert len(imported_batches) == len(batches)
    for batch, expected in zip(imported_batches, batches):
        assert batch.equals(expected)

    del obj, imported_reader, batch, expected, imported_batches

    assert pa.total_allocated_bytes() == old_allocated

    obj = constructor(schema, batches)

    bad_schema = pa.schema({'ints': pa.int32()})
    with pytest.raises(pa.lib.ArrowTypeError, match="Field 0 cannot be cast"):
        obj.__arrow_c_stream__(bad_schema.__arrow_c_schema__())

    # Can work with matching schema
    matching_schema = pa.schema({'ints': pa.list_(pa.int32())})
    capsule = obj.__arrow_c_stream__(matching_schema.__arrow_c_schema__())
    imported_reader = pa.RecordBatchReader._import_from_c_capsule(capsule)
    assert imported_reader.schema == matching_schema
    for batch, expected in zip(imported_reader, batches):
        assert batch.equals(expected)


def test_roundtrip_batch_reader_capsule_requested_schema():
    batch = make_batch()
    requested_schema = pa.schema([('ints', pa.list_(pa.int64()))])
    requested_capsule = requested_schema.__arrow_c_schema__()
    batch_as_requested = batch.cast(requested_schema)

    capsule = batch.__arrow_c_stream__(requested_capsule)
    assert PyCapsule_IsValid(capsule, b"arrow_array_stream") == 1
    imported_reader = pa.RecordBatchReader._import_from_c_capsule(capsule)
    assert imported_reader.schema == requested_schema
    assert imported_reader.read_next_batch().equals(batch_as_requested)
    with pytest.raises(StopIteration):
        imported_reader.read_next_batch()


def test_roundtrip_batch_reader_capsule():
    batch = make_batch()

    capsule = batch.__arrow_c_stream__()
    assert PyCapsule_IsValid(capsule, b"arrow_array_stream") == 1
    imported_reader = pa.RecordBatchReader._import_from_c_capsule(capsule)
    assert imported_reader.schema == batch.schema
    assert imported_reader.read_next_batch().equals(batch)
    with pytest.raises(StopIteration):
        imported_reader.read_next_batch()


def test_roundtrip_chunked_array_capsule():
    chunked = pa.chunked_array([pa.array(["a", "b", "c"])])

    capsule = chunked.__arrow_c_stream__()
    assert PyCapsule_IsValid(capsule, b"arrow_array_stream") == 1
    imported_chunked = pa.ChunkedArray._import_from_c_capsule(capsule)
    assert imported_chunked.type == chunked.type
    assert imported_chunked == chunked


def test_roundtrip_chunked_array_capsule_requested_schema():
    chunked = pa.chunked_array([pa.array(["a", "b", "c"])])

    # Requesting the same type should work
    requested_capsule = chunked.type.__arrow_c_schema__()
    capsule = chunked.__arrow_c_stream__(requested_capsule)
    imported_chunked = pa.ChunkedArray._import_from_c_capsule(capsule)
    assert imported_chunked == chunked

    # Casting to something else should error if not possible
    requested_type = pa.binary()
    requested_capsule = requested_type.__arrow_c_schema__()
    capsule = chunked.__arrow_c_stream__(requested_capsule)
    imported_chunked = pa.ChunkedArray._import_from_c_capsule(capsule)
    assert imported_chunked == chunked.cast(pa.binary())

    requested_type = pa.int64()
    requested_capsule = requested_type.__arrow_c_schema__()
    with pytest.raises(
        ValueError, match="Could not cast string to requested type int64"
    ):
        chunked.__arrow_c_stream__(requested_capsule)


@needs_cffi
def test_import_device_no_cuda():
    try:
        import pyarrow.cuda  # noqa
    except ImportError:
        pass
    else:
        pytest.skip("pyarrow.cuda is available")

    c_array = ffi.new("struct ArrowDeviceArray*")
    ptr_array = int(ffi.cast("uintptr_t", c_array))
    arr = pa.array([1, 2, 3], type=pa.int64())
    arr._export_to_c_device(ptr_array)

    # patch the device type of the struct, this results in an invalid ArrowDeviceArray
    # but this is just to test we raise am error before actually importing buffers
    c_array.device_type = 2  # ARROW_DEVICE_CUDA

    with pytest.raises(ImportError, match="Trying to import data on a CUDA device"):
        pa.Array._import_from_c_device(ptr_array, arr.type)