jorisvandenbossche commented on code in PR #13199:
URL: https://github.com/apache/arrow/pull/13199#discussion_r881414255
##########
python/pyarrow/dataset.py:
##########
@@ -622,26 +624,75 @@ def dataset(source, schema=None, format=None,
filesystem=None,
Examples
--------
+ Creating an example Table:
+
+ >>> import pyarrow as pa
+ >>> import pyarrow.parquet as pq
+ >>> table = pa.table({'year': [2020, 2022, 2021, 2022, 2019, 2021],
+ ... 'n_legs': [2, 2, 4, 4, 5, 100],
+ ... 'animal': ["Flamingo", "Parrot", "Dog", "Horse",
+ ... "Brittle stars", "Centipede"]})
+ >>> pq.write_table(table, "file.parquet")
+
Opening a single file:
- >>> dataset("path/to/file.parquet", format="parquet")
+ >>> import pyarrow.dataset as ds
+ >>> dataset = ds.dataset("file.parquet", format="parquet")
+ >>> dataset.to_table()
+ pyarrow.Table
+ year: int64
+ n_legs: int64
+ animal: string
+ ----
+ year: [[2020,2022,2021,2022,2019,2021]]
+ n_legs: [[2,2,4,4,5,100]]
+ animal: [["Flamingo","Parrot","Dog","Horse","Brittle stars","Centipede"]]
Opening a single file with an explicit schema:
- >>> dataset("path/to/file.parquet", schema=myschema, format="parquet")
+ >>> myschema = pa.schema([
+ ... ('n_legs', pa.int64()),
+ ... ('animal', pa.string())])
+ >>> dataset = ds.dataset("file.parquet", schema=myschema, format="parquet")
+ >>> dataset.to_table()
+ pyarrow.Table
+ n_legs: int64
+ animal: string
+ ----
+ n_legs: [[2,2,4,4,5,100]]
+ animal: [["Flamingo","Parrot","Dog","Horse","Brittle stars","Centipede"]]
Opening a dataset for a single directory:
- >>> dataset("path/to/nyc-taxi/", format="parquet")
- >>> dataset("s3://mybucket/nyc-taxi/", format="parquet")
+ >>> ds.write_dataset(table, "partitioned_dataset", format="parquet",
+ ... partitioning=['year'])
+ >>> dataset = ds.dataset("partitioned_dataset", format="parquet")
+ >>> dataset.to_table()
+ pyarrow.Table
+ n_legs: int64
+ animal: string
+ ----
+ n_legs: [[5],[2],[4,100],[2,4]]
+ animal: [["Brittle stars"],["Flamingo"],...["Parrot","Horse"]]
+
+ For a single directory from a S3 bucket:
+
+ >>> ds.dataset("s3://mybucket/nyc-taxi/", format="parquet")# doctest: +SKIP
Review Comment:
```suggestion
>>> ds.dataset("s3://mybucket/nyc-taxi/", format="parquet") # doctest:
+SKIP
```
##########
python/pyarrow/dataset.py:
##########
@@ -155,18 +155,21 @@ def partitioning(schema=None, field_names=None,
flavor=None,
Specify the Schema for paths like "/2009/June":
- >>> partitioning(pa.schema([("year", pa.int16()), ("month", pa.string())]))
+ >>> import pyarrow as pa
+ >>> import pyarrow.dataset as ds
+ >>> part = ds.partitioning(pa.schema([("year", pa.int16()),
+ ... ("month", pa.string())]))
Review Comment:
```suggestion
>>> part = ds.partitioning(pa.schema([("year", pa.int16()),
... ("month", pa.string())]))
```
##########
python/pyarrow/conftest.py:
##########
@@ -0,0 +1,226 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import pytest
+from pyarrow import Codec
+
+groups = [
+ 'brotli',
+ 'bz2',
+ 'cython',
+ 'dataset',
+ 'hypothesis',
+ 'fastparquet',
+ 'gandiva',
+ 'gdb',
+ 'gzip',
+ 'hdfs',
+ 'large_memory',
+ 'lz4',
+ 'memory_leak',
+ 'nopandas',
+ 'orc',
+ 'pandas',
+ 'parquet',
+ 'parquet_encryption',
+ 'plasma',
+ 's3',
+ 'snappy',
+ 'substrait',
+ 'tensorflow',
+ 'flight',
+ 'slow',
+ 'requires_testing_data',
+ 'zstd',
+]
+
+defaults = {
+ 'brotli': Codec.is_available('brotli'),
+ 'bz2': Codec.is_available('bz2'),
+ 'cython': False,
+ 'dataset': False,
+ 'fastparquet': False,
+ 'flight': False,
+ 'gandiva': False,
+ 'gdb': True,
+ 'gzip': Codec.is_available('gzip'),
+ 'hdfs': False,
+ 'hypothesis': False,
+ 'large_memory': False,
+ 'lz4': Codec.is_available('lz4'),
+ 'memory_leak': False,
+ 'nopandas': False,
+ 'orc': False,
+ 'pandas': False,
+ 'parquet': False,
+ 'parquet_encryption': False,
+ 'plasma': False,
+ 'requires_testing_data': True,
+ 's3': False,
+ 'slow': False,
+ 'snappy': Codec.is_available('snappy'),
+ 'substrait': False,
+ 'tensorflow': False,
+ 'zstd': Codec.is_available('zstd'),
+}
+
+try:
+ import cython # noqa
+ defaults['cython'] = True
+except ImportError:
+ pass
+
+try:
+ import fastparquet # noqa
+ defaults['fastparquet'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.gandiva # noqa
+ defaults['gandiva'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.dataset # noqa
+ defaults['dataset'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.orc # noqa
+ defaults['orc'] = True
+except ImportError:
+ pass
+
+try:
+ import pandas # noqa
+ defaults['pandas'] = True
+except ImportError:
+ defaults['nopandas'] = True
+
+try:
+ import pyarrow.parquet # noqa
+ defaults['parquet'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.parquet.encryption # noqa
+ defaults['parquet_encryption'] = True
+except ImportError:
+ pass
+
+
+try:
+ import pyarrow.plasma # noqa
+ defaults['plasma'] = True
+except ImportError:
+ pass
+
+try:
+ import tensorflow # noqa
+ defaults['tensorflow'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.flight # noqa
+ defaults['flight'] = True
+except ImportError:
+ pass
+
+try:
+ from pyarrow.fs import S3FileSystem # noqa
+ defaults['s3'] = True
+except ImportError:
+ pass
+
+try:
+ from pyarrow.fs import HadoopFileSystem # noqa
+ defaults['hdfs'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.substrait # noqa
+ defaults['substrait'] = True
+except ImportError:
+ pass
+
+
+# Doctest should ignore files for the modules that are not built
+def pytest_ignore_collect(path, config):
+ if config.option.doctestmodules:
+ # don't try to run doctests on the /tests directory
+ if "/pyarrow/tests/" in str(path):
+ return True
+
+ doctest_groups = [
+ 'dataset',
+ 'orc',
+ 'parquet',
+ 'plasma',
+ 'flight',
+ ]
+
+ # handle cuda, flight, etc
+ for group in doctest_groups:
+ if 'pyarrow/{}'.format(group) in str(path) and \
+ not defaults[group]:
+ return True
Review Comment:
```suggestion
if 'pyarrow/{}'.format(group) in str(path):
if not defaults[group]:
return True
```
Possible alternative formatting (which avoids the `\` and the strange
indentation)
##########
python/pyarrow/conftest.py:
##########
@@ -0,0 +1,226 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import pytest
+from pyarrow import Codec
+
+groups = [
+ 'brotli',
+ 'bz2',
+ 'cython',
+ 'dataset',
+ 'hypothesis',
+ 'fastparquet',
+ 'gandiva',
+ 'gdb',
+ 'gzip',
+ 'hdfs',
+ 'large_memory',
+ 'lz4',
+ 'memory_leak',
+ 'nopandas',
+ 'orc',
+ 'pandas',
+ 'parquet',
+ 'parquet_encryption',
+ 'plasma',
+ 's3',
+ 'snappy',
+ 'substrait',
+ 'tensorflow',
+ 'flight',
+ 'slow',
+ 'requires_testing_data',
+ 'zstd',
+]
+
+defaults = {
+ 'brotli': Codec.is_available('brotli'),
+ 'bz2': Codec.is_available('bz2'),
+ 'cython': False,
+ 'dataset': False,
+ 'fastparquet': False,
+ 'flight': False,
+ 'gandiva': False,
+ 'gdb': True,
+ 'gzip': Codec.is_available('gzip'),
+ 'hdfs': False,
+ 'hypothesis': False,
+ 'large_memory': False,
+ 'lz4': Codec.is_available('lz4'),
+ 'memory_leak': False,
+ 'nopandas': False,
+ 'orc': False,
+ 'pandas': False,
+ 'parquet': False,
+ 'parquet_encryption': False,
+ 'plasma': False,
+ 'requires_testing_data': True,
+ 's3': False,
+ 'slow': False,
+ 'snappy': Codec.is_available('snappy'),
+ 'substrait': False,
+ 'tensorflow': False,
+ 'zstd': Codec.is_available('zstd'),
+}
+
+try:
+ import cython # noqa
+ defaults['cython'] = True
+except ImportError:
+ pass
+
+try:
+ import fastparquet # noqa
+ defaults['fastparquet'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.gandiva # noqa
+ defaults['gandiva'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.dataset # noqa
+ defaults['dataset'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.orc # noqa
+ defaults['orc'] = True
+except ImportError:
+ pass
+
+try:
+ import pandas # noqa
+ defaults['pandas'] = True
+except ImportError:
+ defaults['nopandas'] = True
+
+try:
+ import pyarrow.parquet # noqa
+ defaults['parquet'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.parquet.encryption # noqa
+ defaults['parquet_encryption'] = True
+except ImportError:
+ pass
+
+
+try:
+ import pyarrow.plasma # noqa
+ defaults['plasma'] = True
+except ImportError:
+ pass
+
+try:
+ import tensorflow # noqa
+ defaults['tensorflow'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.flight # noqa
+ defaults['flight'] = True
+except ImportError:
+ pass
+
+try:
+ from pyarrow.fs import S3FileSystem # noqa
+ defaults['s3'] = True
+except ImportError:
+ pass
+
+try:
+ from pyarrow.fs import HadoopFileSystem # noqa
+ defaults['hdfs'] = True
+except ImportError:
+ pass
+
+try:
+ import pyarrow.substrait # noqa
+ defaults['substrait'] = True
+except ImportError:
+ pass
+
+
+# Doctest should ignore files for the modules that are not built
+def pytest_ignore_collect(path, config):
+ if config.option.doctestmodules:
+ # don't try to run doctests on the /tests directory
+ if "/pyarrow/tests/" in str(path):
+ return True
+
+ doctest_groups = [
+ 'dataset',
+ 'orc',
+ 'parquet',
+ 'plasma',
+ 'flight',
+ ]
+
+ # handle cuda, flight, etc
+ for group in doctest_groups:
+ if 'pyarrow/{}'.format(group) in str(path) and \
+ not defaults[group]:
+ return True
+
+ if 'pyarrow/parquet/encryption' in str(path) and \
+ not defaults['parquet_encryption']:
+ return True
+
+ if 'pyarrow/cuda' in str(path):
+ try:
+ import pyarrow.cuda # noqa
+ return False
+ except ImportError:
+ return True
+
+ if 'pyarrow/fs' in str(path):
+ try:
+ from pyarrow.fs import S3FileSystem # noqa
+ return False
+ except ImportError:
+ return True
+
+ return False
+
+
+# Save output files from doctest examples into temp dir
[email protected](autouse=True)
+def _docdir(request):
+
+ # Trigger ONLY for the doctests.
+ doctest_plugin = request.config.pluginmanager.getplugin("doctest")
Review Comment:
Would `request.config.option.doctestmodules` work here as well? (to keep it
similar as how we checked for it above)
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