def __from_arrow__(
self, array: pyarrow.Array | pyarrow.ChunkedArray
) -> BaseMaskedArray:
"""
Construct IntegerArray/FloatingArray from pyarrow Array/ChunkedArray.
"""
import pyarrow
from pandas.core.arrays._arrow_utils import pyarrow_array_to_numpy_and_mask
array_class = self.construct_array_type()
pyarrow_type = pyarrow.from_numpy_dtype(self.type)
if not array.type.equals(pyarrow_type):
array = array.cast(pyarrow_type)
if isinstance(array, pyarrow.Array):
chunks = [array]
else:
# pyarrow.ChunkedArray
chunks = array.chunks
results = []
for arr in chunks:
data, mask = pyarrow_array_to_numpy_and_mask(arr, dtype=self.type)
num_arr = array_class(data.copy(), ~mask, copy=False)
results.append(num_arr)
if len(results) == 1:
# avoid additional copy in _concat_same_type
return results[0]
else:
return array_class._concat_same_type(results)
def __from_arrow__(
self, array: pyarrow.Array | pyarrow.ChunkedArray
) -> BaseMaskedArray:
"""
Construct IntegerArray/FloatingArray from pyarrow Array/ChunkedArray.
"""
import pyarrow
from pandas.core.arrays.arrow._arrow_utils import (
pyarrow_array_to_numpy_and_mask,
)
array_class = self.construct_array_type()
pyarrow_type = pyarrow.from_numpy_dtype(self.type)
if not array.type.equals(pyarrow_type):
# test_from_arrow_type_error raise for string, but allow
# through itemsize conversion GH#31896
rt_dtype = pandas_dtype(array.type.to_pandas_dtype())
if rt_dtype.kind not in ["i", "u", "f"]:
# Could allow "c" or potentially disallow float<->int conversion,
# but at the moment we specifically test that uint<->int works
raise TypeError(
f"Expected array of {self} type, got {array.type} instead"
)
array = array.cast(pyarrow_type)
if isinstance(array, pyarrow.Array):
chunks = [array]
else:
# pyarrow.ChunkedArray
chunks = array.chunks
results = []
for arr in chunks:
data, mask = pyarrow_array_to_numpy_and_mask(arr, dtype=self.numpy_dtype)
num_arr = array_class(data.copy(), ~mask, copy=False)
results.append(num_arr)
if not results:
return array_class(
np.array([], dtype=self.numpy_dtype), np.array([], dtype=np.bool_)
)
elif len(results) == 1:
# avoid additional copy in _concat_same_type
return results[0]
else:
return array_class._concat_same_type(results)