tadeja commented on code in PR #48619:
URL: https://github.com/apache/arrow/pull/48619#discussion_r2706020043
##########
docs/source/python/extending_types.rst:
##########
@@ -530,12 +548,14 @@ in the numpy ndarray:
>>> numpy_tensor
array([[[ 1., 2.],
[ 3., 4.]],
+ <BLANKLINE>
[[ 10., 20.],
[ 30., 40.]],
+ <BLANKLINE>
[[100., 200.],
- [300., 400.]]])
+ [300., 400.]]], dtype=float32)
>>> numpy_tensor.shape
- (3, 2, 2)
+ (3, 2, 2)
Review Comment:
```suggestion
[300., 400.]]], dtype=float32)
>>> numpy_tensor.shape
(3, 2, 2)
```
Useless nitpick - 4th leading space can be removed as main code lines above
seem to have 3 spaces.
##########
docs/source/python/dataset.rst:
##########
@@ -722,17 +799,35 @@ call. For simple datasets it may be possible to know
which files will be create
larger or partitioned datasets it is not so easy. The ``file_visitor``
keyword can be used
to supply a visitor that will be called as each file is created:
-.. ipython:: python
+.. code-block:: python
- def file_visitor(written_file):
- print(f"path={written_file.path}")
- print(f"size={written_file.size} bytes")
- print(f"metadata={written_file.metadata}")
+ >>> def file_visitor(written_file):
+ ... print(f"path={written_file.path}")
+ ... print(f"size={written_file.size} bytes")
+ ... print(f"metadata={written_file.metadata}")
-.. ipython:: python
+.. code-block:: python
- ds.write_dataset(table, "dataset_visited", format="parquet",
partitioning=part,
- file_visitor=file_visitor)
+ >>> ds.write_dataset(table, "dataset_visited", format="parquet",
partitioning=part,
+ ... file_visitor=file_visitor)
+ path=dataset_visited/c=.../part-0.parquet
+ size=824 bytes
+ metadata=<pyarrow._parquet.FileMetaData object at ...>
+ created_by: parquet-cpp-arrow version 23.0.0-SNAPSHOT
Review Comment:
```suggestion
size=... bytes
metadata=<pyarrow._parquet.FileMetaData object at ...>
created_by: parquet-cpp-arrow version ...
```
##########
docs/source/python/dataset.rst:
##########
@@ -722,17 +799,35 @@ call. For simple datasets it may be possible to know
which files will be create
larger or partitioned datasets it is not so easy. The ``file_visitor``
keyword can be used
to supply a visitor that will be called as each file is created:
-.. ipython:: python
+.. code-block:: python
- def file_visitor(written_file):
- print(f"path={written_file.path}")
- print(f"size={written_file.size} bytes")
- print(f"metadata={written_file.metadata}")
+ >>> def file_visitor(written_file):
+ ... print(f"path={written_file.path}")
+ ... print(f"size={written_file.size} bytes")
+ ... print(f"metadata={written_file.metadata}")
-.. ipython:: python
+.. code-block:: python
- ds.write_dataset(table, "dataset_visited", format="parquet",
partitioning=part,
- file_visitor=file_visitor)
+ >>> ds.write_dataset(table, "dataset_visited", format="parquet",
partitioning=part,
+ ... file_visitor=file_visitor)
+ path=dataset_visited/c=.../part-0.parquet
+ size=824 bytes
+ metadata=<pyarrow._parquet.FileMetaData object at ...>
+ created_by: parquet-cpp-arrow version 23.0.0-SNAPSHOT
+ num_columns: 2
+ num_rows: 5
+ num_row_groups: 1
+ format_version: 2.6
+ serialized_size: 0
+ path=dataset_visited/c=.../part-0.parquet
+ size=826 bytes
+ metadata=<pyarrow._parquet.FileMetaData object at ...>
+ created_by: parquet-cpp-arrow version 23.0.0-SNAPSHOT
Review Comment:
```suggestion
size=... bytes
metadata=<pyarrow._parquet.FileMetaData object at ...>
created_by: parquet-cpp-arrow version ...
```
##########
docs/source/python/extending_types.rst:
##########
@@ -530,12 +548,14 @@ in the numpy ndarray:
>>> numpy_tensor
array([[[ 1., 2.],
[ 3., 4.]],
+ <BLANKLINE>
[[ 10., 20.],
[ 30., 40.]],
+ <BLANKLINE>
[[100., 200.],
- [300., 400.]]])
+ [300., 400.]]], dtype=float32)
>>> numpy_tensor.shape
- (3, 2, 2)
+ (3, 2, 2)
Review Comment:
```suggestion
[300., 400.]]], dtype=float32)
>>> numpy_tensor.shape
(3, 2, 2)
```
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