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MINOR: [Docs][Python] Mention explicit None partitioning options for pyarrow.parquet.read_table #45163

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MINOR: [Docs][Python] Mention explicit None partitioning options for pyarrow.parquet.read_table #45163

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4 changes: 2 additions & 2 deletions python/pyarrow/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -542,7 +542,7 @@ def parquet_dataset(metadata_path, schema=None, filesystem=None, format=None,
format : ParquetFileFormat
An instance of a ParquetFileFormat if special options needs to be
passed.
partitioning : Partitioning, PartitioningFactory, str, list of str
partitioning : Partitioning, PartitioningFactory, str, list of str, optional
The partitioning scheme specified with the ``partitioning()``
function. A flavor string can be used as shortcut, and with a list of
field names a DirectoryPartitioning will be inferred.
Expand Down Expand Up @@ -638,7 +638,7 @@ def dataset(source, schema=None, format=None, filesystem=None,
examples below.
Note that the URIs on Windows must follow 'file:///C:...' or
'file:/C:...' patterns.
partitioning : Partitioning, PartitioningFactory, str, list of str
partitioning : Partitioning, PartitioningFactory, str, list of str, optional
The partitioning scheme specified with the ``partitioning()``
function. A flavor string can be used as shortcut, and with a list of
field names a DirectoryPartitioning will be inferred.
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7 changes: 4 additions & 3 deletions python/pyarrow/parquet/core.py
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Expand Up @@ -1163,13 +1163,14 @@ def _get_pandas_index_columns(keyvalues):
buffer_size : int, default 0
If positive, perform read buffering when deserializing individual
column chunks. Otherwise IO calls are unbuffered.
partitioning : pyarrow.dataset.Partitioning or str or list of str, \
partitioning : pyarrow.dataset.Partitioning or str or list of str or None, \
default "hive"
The partitioning scheme for a partitioned dataset. The default of "hive"
assumes directory names with key=value pairs like "/year=2009/month=11".
In addition, a scheme like "/2009/11" is also supported, in which case
you need to specify the field names or a full schema. See the
``pyarrow.dataset.partitioning()`` function for more details."""
you need to specify the field names or a full schema. If no partitioning
is used, pass ``None``.
See the ``pyarrow.dataset.partitioning()`` function for more details."""


_parquet_dataset_example = """\
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