rok commented on code in PR #50325:
URL: https://github.com/apache/arrow/pull/50325#discussion_r3528401021
##########
python/pyarrow/types.pxi:
##########
@@ -1969,6 +1969,11 @@ cdef class JsonType(BaseExtensionType):
return JsonScalar
+class _UuidPandasDtype:
+ def __from_arrow__(self, array):
+ return np.asarray(array.to_pylist(), dtype=object).reshape(1, -1)
Review Comment:
Wouldn't this make `UuidType.__from_arrow__` return a 2-D array to satisfy
old pandas `DataFrame` block construction, but the same hook is also used by
`Array.to_pandas()`, which expects 1-D data for pd.Series?
Perhaps a better fix is to keep `__from_arrow__` returning normal 1-D object
data, and handle the old pandas block-manager reshape only in the `DataFrame`
reconstruction path where 2-D block shape is
actually needed?
##########
python/pyarrow/tests/parquet/test_data_types.py:
##########
@@ -604,6 +604,27 @@ def test_uuid_extension_type():
store_schema=False)
[email protected]
+def test_uuid_roundtrip(tempdir):
+ import uuid
+ u1, u2 = uuid.uuid4(), uuid.uuid4()
+ df = pd.DataFrame({"id": [u1, None, u2]})
+ table = pa.Table.from_pandas(df)
+ assert table.column("id").type == pa.uuid()
+
+ path = tempdir / "uuid_pandas_roundtrip.parquet"
+ pq.write_table(table, path)
+ read_table = pq.read_table(path)
+ assert read_table.column("id").type == pa.uuid()
+
+ result_df = read_table.to_pandas()
+ assert isinstance(result_df.loc[0, "id"], uuid.UUID)
+ assert isinstance(result_df.loc[2, "id"], uuid.UUID)
+ assert result_df.loc[0, "id"] == u1
+ assert result_df.loc[2, "id"] == u2
+ assert pd.isna(result_df.loc[1, "id"])
+
+
Review Comment:
Would this test pass with the current proposal?
```suggestion
@pytest.mark.pandas
def test_uuid_array_to_pandas():
from uuid import uuid4
import pandas as pd
import pandas.testing as tm
values = [uuid4(), None, uuid4()]
arr = pa.array(values, type=pa.uuid())
result = arr.to_pandas()
expected = pd.Series(values, dtype=object)
tm.assert_series_equal(result, expected)
```
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