westonpace edited a comment on pull request #11014:
URL: https://github.com/apache/arrow/pull/11014#issuecomment-908595122
> What would be a use case? (I don't see any test where it is actually used
for something) I suppose as alternative for #11008, right?
@jorisvandenbossche
Yes, but not as an alternative, this would be to enable #11008. I don't
believe #11008 works today. `ds.partitioning(field_names=['a'])` returns a
partitioning factory and not a partitioning. It also returns an error when
specifying the hive format. A partitioning factory cannot be used for writing
datasets (only reading)...
```
>>> import pyarrow
>>> import pyarrow as pa
>>> import pyarrow.dataset as ds
>>> table = pa.Table.from_pydict({'a': [1, 2, 3], 'b': ['x', 'y', 'z']})
>>> ds.partitioning(field_names=['a'])
<pyarrow._dataset.PartitioningFactory object at 0x7f2410d4c170>
>>> part = ds.partitioning(field_names=['a'])
>>> ds.write_dataset(table, '/tmp/new_dataset', format='parquet',
partitioning=part)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File
"/home/pace/anaconda3/envs/arrow-release-5/lib/python3.9/site-packages/pyarrow/dataset.py",
line 791, in write_dataset
partitioning = _ensure_write_partitioning(partitioning)
File
"/home/pace/anaconda3/envs/arrow-release-5/lib/python3.9/site-packages/pyarrow/dataset.py",
line 686, in _ensure_write_partitioning
raise ValueError("partitioning needs to be actual Partitioning object")
ValueError: partitioning needs to be actual Partitioning object
```
I didn't add real world use cases (or python bindings) because I figured
those would be covered by #11008.
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