Merge branch 'main' into null-nums

Author: Linchin

docs/conf.py

@@ -24,9 +24,9 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys
 import os
 import shlex
+import sys
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the

docs/index.rst

@@ -23,8 +23,8 @@ Note:  The canonical version of this documentation can always be found on the
    `BigQuery sandbox <https://cloud.google.com/bigquery/docs/sandbox>`__ to
    try the service for free.
 
-   Also, consider using `BigQuery DataFrames
-   <https://cloud.google.com/bigquery/docs/bigquery-dataframes-introduction>`__
+   Also, consider using BigQuery DataFrames 
+   (`bit.ly/bigframes-intro <https://bit.ly/bigframes-intro>`__)
    to process large results with pandas compatible APIs with transparent SQL
    pushdown to BigQuery engine. This provides an opportunity to save on costs
    and improve performance.

docs/intro.rst

@@ -27,7 +27,7 @@ Reading data from BigQuery
 Use the :func:`pandas_gbq.read_gbq` function to run a BigQuery query and
 download the results as a :class:`pandas.DataFrame` object.
 
-.. literalinclude:: samples/snippets/read_gbq_simple.py
+.. literalinclude:: ../samples/snippets/read_gbq_simple.py
    :language: python
    :dedent: 4
    :start-after: [START bigquery_pandas_gbq_read_gbq_simple]
@@ -57,7 +57,7 @@ Writing data to BigQuery
 Use the :func:`pandas_gbq.to_gbq` function to write a
 :class:`pandas.DataFrame` object to a BigQuery table.
 
-.. literalinclude:: samples/snippets/to_gbq_simple.py
+.. literalinclude:: ../samples/snippets/to_gbq_simple.py
    :language: python
    :dedent: 4
    :start-after: [START bigquery_pandas_gbq_to_gbq_simple]

docs/reading.rst

@@ -6,7 +6,7 @@ Reading Tables
 Use the :func:`pandas_gbq.read_gbq` function to run a BigQuery query and
 download the results as a :class:`pandas.DataFrame` object.
 
-.. literalinclude:: samples/snippets/read_gbq_simple.py
+.. literalinclude:: ../samples/snippets/read_gbq_simple.py
    :language: python
    :dedent: 4
    :start-after: [START bigquery_pandas_gbq_read_gbq_simple]
@@ -37,7 +37,7 @@ The ``dialect`` argument can be used to indicate whether to use
 BigQuery's ``'legacy'`` SQL or BigQuery's ``'standard'`` SQL. The
 default value is ``'standard'``.
 
-.. literalinclude:: samples/snippets/read_gbq_legacy.py
+.. literalinclude:: ../samples/snippets/read_gbq_legacy.py
    :language: python
    :dedent: 4
    :start-after: [START bigquery_pandas_gbq_read_gbq_legacy]

docs/samples

@@ -6,7 +6,7 @@ Writing Tables
 Use the :func:`pandas_gbq.to_gbq` function to write a
 :class:`pandas.DataFrame` object to a BigQuery table.
 
-.. literalinclude:: samples/snippets/to_gbq_simple.py
+.. literalinclude:: ../samples/snippets/to_gbq_simple.py
    :language: python
    :dedent: 4
    :start-after: [START bigquery_pandas_gbq_to_gbq_simple]

docs/writing.rst

@@ -17,6 +17,7 @@
 # Generated by synthtool. DO NOT EDIT!
 
 from __future__ import absolute_import
+
 import os
 import pathlib
 import re

noxfile.py

@@ -55,7 +55,7 @@
         # creating clients, not the end user.
         "docs/multiprocessing.rst",
         "noxfile.py",
-	"README.rst",
+        "README.rst",
         # exclude .kokoro/build.sh which is customized due to support for conda
         ".kokoro/build.sh",
     ],
@@ -66,7 +66,9 @@
 # ----------------------------------------------------------------------------
 
 s.replace(
-    [".github/header-checker-lint.yml"], '"Google LLC"', '"pandas-gbq Authors"',
+    [".github/header-checker-lint.yml"],
+    '"Google LLC"',
+    '"pandas-gbq Authors"',
 )
 
 # ----------------------------------------------------------------------------
@@ -79,6 +81,6 @@
 # Final cleanup
 # ----------------------------------------------------------------------------
 
-s.shell.run(["nox", "-s", "blacken"], hide_output=False)
+s.shell.run(["nox", "-s", "format"], hide_output=False)
 for noxfile in REPO_ROOT.glob("samples/**/noxfile.py"):
-    s.shell.run(["nox", "-s", "blacken"], cwd=noxfile.parent, hide_output=False)
+    s.shell.run(["nox", "-s", "format"], cwd=noxfile.parent, hide_output=False)

owlbot.py

@@ -2,10 +2,10 @@
 # Use of this source code is governed by a BSD-style
 # license that can be found in the LICENSE file.
 
-from .gbq import to_gbq, read_gbq, Context, context  # noqa
-
 from pandas_gbq import version as pandas_gbq_version
 
+from .gbq import Context, context, read_gbq, to_gbq  # noqa
+
 __version__ = pandas_gbq_version.__version__
 
 __all__ = [

pandas_gbq/__init__.py

@@ -54,8 +54,8 @@ def bigquery_has_query_and_wait(self):
 
     @property
     def pandas_installed_version(self):
-        import pandas
         import packaging.version
+        import pandas
 
         if self._pandas_installed_version is not None:
             return self._pandas_installed_version

pandas_gbq/features.py

@@ -268,8 +268,8 @@ def __init__(
         client_secret=None,
     ):
         global context
-        from google.api_core.exceptions import GoogleAPIError
-        from google.api_core.exceptions import ClientError
+        from google.api_core.exceptions import ClientError, GoogleAPIError
+
         from pandas_gbq import auth
 
         self.http_error = (ClientError, GoogleAPIError)
@@ -493,8 +493,7 @@ def _download_results(
                 num_gib = num_bytes / pandas_gbq.constants.BYTES_IN_GIB
                 warnings.warn(
                     f"Recommendation: Your results are {num_gib:.1f} GiB. "
-                    "Consider using BigQuery DataFrames "
-                    "(https://cloud.google.com/bigquery/docs/bigquery-dataframes-introduction) "
+                    "Consider using BigQuery DataFrames (https://bit.ly/bigframes-intro)"
                     "to process large results with pandas compatible APIs with transparent SQL "
                     "pushdown to BigQuery engine. This provides an opportunity to save on costs "
                     "and improve performance. "
@@ -1245,8 +1244,7 @@ def __init__(
 
     def _table_ref(self, table_id):
         """Return a BigQuery client library table reference"""
-        from google.cloud.bigquery import DatasetReference
-        from google.cloud.bigquery import TableReference
+        from google.cloud.bigquery import DatasetReference, TableReference
 
         return TableReference(
             DatasetReference(self.project_id, self.dataset_id), table_id
@@ -1287,9 +1285,7 @@ def create(self, table_id, schema):
             Use the generate_bq_schema to generate your table schema from a
             dataframe.
         """
-        from google.cloud.bigquery import DatasetReference
-        from google.cloud.bigquery import Table
-        from google.cloud.bigquery import TableReference
+        from google.cloud.bigquery import DatasetReference, Table, TableReference
 
         if self.exists(table_id):
             raise TableCreationError("Table {0} already exists".format(table_id))

pandas_gbq/gbq.py

@@ -9,9 +9,9 @@
 from typing import Any, Callable, Dict, List, Optional
 
 import db_dtypes
+from google.cloud import bigquery
 import pandas
 import pyarrow.lib
-from google.cloud import bigquery
 
 from pandas_gbq import exceptions
 import pandas_gbq.schema

pandas_gbq/load.py

@@ -14,7 +14,6 @@
 
 import pandas_gbq.exceptions
 
-
 logger = logging.getLogger(__name__)
 
 

pandas_gbq/query.py

@@ -6,7 +6,6 @@
 
 import copy
 
-
 # API may return data types as legacy SQL, so maintain a mapping of aliases
 # from standard SQL to legacy data types.
 _TYPE_ALIASES = {

pandas_gbq/schema.py

@@ -6,7 +6,6 @@
 import pytest
 import test_utils.prefixer
 
-
 prefixer = test_utils.prefixer.Prefixer("python-bigquery-pandas", "samples/snippets")
 
 

samples/snippets/conftest.py

@@ -22,7 +22,6 @@
 
 import nox
 
-
 # WARNING - WARNING - WARNING - WARNING - WARNING
 # WARNING - WARNING - WARNING - WARNING - WARNING
 #           DO NOT EDIT THIS FILE EVER!

samples/snippets/noxfile.py

@@ -4,8 +4,7 @@
 
 """System tests for read_gbq code samples."""
 
-from . import read_gbq_legacy
-from . import read_gbq_simple
+from . import read_gbq_legacy, read_gbq_simple
 
 
 def test_read_gbq_legacy(project_id):

samples/snippets/read_gbq_test.py

@@ -14,7 +14,6 @@ def main(project_id, table_id):
 
     # TODO: Set project_id to your Google Cloud Platform project ID.
     # project_id = "my-project"
-
     # TODO: Set table_id to the full destination table ID (including the
     #       dataset ID).
     # table_id = 'my_dataset.my_table'

samples/snippets/to_gbq_simple.py

@@ -10,7 +10,6 @@
 
 import setuptools
 
-
 # Package metadata.
 
 name = "pandas-gbq"

setup.py

@@ -2,15 +2,14 @@
 # Use of this source code is governed by a BSD-style
 # license that can be found in the LICENSE file.
 
-import os
 import functools
+import os
 import pathlib
 
 from google.cloud import bigquery
 import pytest
 import test_utils.prefixer
 
-
 prefixer = test_utils.prefixer.Prefixer("python-bigquery-pandas", "tests/system")
 
 REPO_DIR = pathlib.Path(__file__).parent.parent.parent

tests/system/conftest.py

@@ -11,7 +11,6 @@
 
 from pandas_gbq import auth
 
-
 IS_RUNNING_ON_CI = "KOKORO_BUILD_ID" in os.environ
 
 

tests/system/test_auth.py

@@ -5,22 +5,20 @@
 # -*- coding: utf-8 -*-
 
 import datetime
-import packaging.version
 import sys
 
 import numpy as np
+import packaging.version
 import pandas
+from pandas import DataFrame
 import pandas.api.types
 import pandas.testing as tm
-from pandas import DataFrame
-
-import pytz
 import pytest
+import pytz
 
 from pandas_gbq import gbq
 import pandas_gbq.schema
 
-
 TABLE_ID = "new_test"
 PANDAS_VERSION = packaging.version.parse(pandas.__version__)
 

tests/system/test_gbq.py

@@ -5,18 +5,17 @@
 import collections
 import datetime
 import decimal
-import packaging.version
 import random
 
 import db_dtypes
 from google.cloud import bigquery
+import packaging.version
 import pandas
 import pandas.testing
 import pytest
 
 from pandas_gbq.features import FEATURES
 
-
 QueryTestCase = collections.namedtuple(
     "QueryTestCase",
     ["query", "expected", "use_bqstorage_apis"],

tests/system/test_read_gbq.py

@@ -9,7 +9,6 @@
 
 import pytest
 
-
 pytest.importorskip("google.cloud.bigquery", minversion="1.24.0")
 
 

tests/system/test_read_gbq_with_bqstorage.py

@@ -2,17 +2,16 @@
 # Use of this source code is governed by a BSD-style
 # license that can be found in the LICENSE file.
 
+import collections
 import datetime
 import decimal
-import collections
 import random
 
 import db_dtypes
 import pandas
 import pandas.testing
 import pytest
 
-
 pytest.importorskip("google.cloud.bigquery", minversion="1.24.0")
 
 

tests/system/test_to_gbq.py

@@ -28,9 +28,10 @@ def default_bigquery_client(mock_bigquery_client):
 
 @pytest.fixture(autouse=True)
 def mock_get_credentials(monkeypatch):
-    from pandas_gbq import auth
     import google.auth.credentials
 
+    from pandas_gbq import auth
+
     mock_credentials = mock.MagicMock(google.auth.credentials.Credentials)
     mock_get_credentials = mock.Mock()
     mock_get_credentials.return_value = (mock_credentials, "my-project")

tests/unit/test_context.py

@@ -25,7 +25,6 @@
 import pandas_gbq.features
 from pandas_gbq.features import FEATURES
 
-
 pytestmark = pytest.mark.filterwarnings("ignore:credentials from Google Cloud SDK")
 
 

tests/unit/test_gbq.py

@@ -15,8 +15,7 @@
 import pandas.testing
 import pytest
 
-from pandas_gbq import exceptions
-from pandas_gbq import load
+from pandas_gbq import exceptions, load
 
 
 def load_method(bqclient, api_method):

tests/unit/test_load.py

@@ -4,8 +4,8 @@
 
 from __future__ import annotations
 
-import datetime
 import concurrent.futures
+import datetime
 from unittest import mock
 
 import freezegun

tests/unit/test_query.py

@@ -6,7 +6,6 @@
 
 import pandas
 import pandas.testing
-
 import pytest
 
 

tests/unit/test_timestamp.py

@@ -2,8 +2,8 @@
 # Use of this source code is governed by a BSD-style
 # license that can be found in the LICENSE file.
 
-import google.cloud.bigquery
 import google.api_core.exceptions
+import google.cloud.bigquery
 from pandas import DataFrame
 import pytest