ENH: update pandas-gbq to 0.8.0, adds credentials arg

doc/source/install.rst

@@ -286,7 +286,9 @@ Optional Dependencies
   `xsel <http://www.vergenet.net/~conrad/software/xsel/>`__, or
   `xclip <https://github.com/astrand/xclip/>`__: necessary to use
   :func:`~pandas.read_clipboard`. Most package managers on Linux distributions will have ``xclip`` and/or ``xsel`` immediately available for installation.
-* `pandas-gbq <https://pandas-gbq.readthedocs.io/en/latest/install.html#dependencies>`__: for Google BigQuery I/O.
+* `pandas-gbq
+  <https://pandas-gbq.readthedocs.io/en/latest/install.html#dependencies>`__:
+  for Google BigQuery I/O. (pandas-gbq >= 0.8.0)
 
 
 * `Backports.lzma <https://pypi.org/project/backports.lzma/>`__: Only for Python 2, for writing to and/or reading from an xz compressed DataFrame in CSV; Python 3 support is built into the standard library.

doc/source/whatsnew/v0.24.0.rst

@@ -218,9 +218,12 @@ Other Enhancements
 - :meth:`Series.droplevel` and :meth:`DataFrame.droplevel` are now implemented (:issue:`20342`)
 - Added support for reading from/writing to Google Cloud Storage via the ``gcsfs`` library (:issue:`19454`, :issue:`23094`)
 - :func:`to_gbq` and :func:`read_gbq` signature and documentation updated to
-  reflect changes from the `Pandas-GBQ library version 0.6.0
-  <https://pandas-gbq.readthedocs.io/en/latest/changelog.html#changelog-0-6-0>`__.
-  (:issue:`21627`, :issue:`22557`)
+  reflect changes from the `Pandas-GBQ library version 0.8.0
+  <https://pandas-gbq.readthedocs.io/en/latest/changelog.html#changelog-0-8-0>`__.
+  Adds a ``credentials`` argument, which enables the use of any kind of
+  `google-auth credentials
+  <https://google-auth.readthedocs.io/en/latest/>`__. (:issue:`21627`,
+  :issue:`22557`, :issue:`23662`)
 - New method :meth:`HDFStore.walk` will recursively walk the group hierarchy of an HDF5 file (:issue:`10932`)
 - :func:`read_html` copies cell data across ``colspan`` and ``rowspan``, and it treats all-``th`` table rows as headers if ``header`` kwarg is not given and there is no ``thead`` (:issue:`17054`)
 - :meth:`Series.nlargest`, :meth:`Series.nsmallest`, :meth:`DataFrame.nlargest`, and :meth:`DataFrame.nsmallest` now accept the value ``"all"`` for the ``keep`` argument. This keeps all ties for the nth largest/smallest value (:issue:`16818`)
@@ -271,17 +274,19 @@ If installed, we now require:
 +-----------------+-----------------+----------+
 | bottleneck      | 1.2.0           |          |
 +-----------------+-----------------+----------+
+| fastparquet     | 0.1.2           |          |
++-----------------+-----------------+----------+
 | matplotlib      | 2.0.0           |          |
 +-----------------+-----------------+----------+
 | numexpr         | 2.6.1           |          |
 +-----------------+-----------------+----------+
-| pytables        | 3.4.2           |          |
-+-----------------+-----------------+----------+
-| scipy           | 0.18.1          |          |
+| pandas-gbq      | 0.8.0           |          |
 +-----------------+-----------------+----------+
 | pyarrow         | 0.7.0           |          |
 +-----------------+-----------------+----------+
-| fastparquet     | 0.1.2           |          |
+| pytables        | 3.4.2           |          |
++-----------------+-----------------+----------+
+| scipy           | 0.18.1          |          |
 +-----------------+-----------------+----------+
 
 Additionally we no longer depend on `feather-format` for feather based storage

pandas/core/frame.py

@@ -1241,9 +1241,9 @@ def to_dict(self, orient='dict', into=dict):
             raise ValueError("orient '{o}' not understood".format(o=orient))
 
     def to_gbq(self, destination_table, project_id=None, chunksize=None,
-               reauth=False, if_exists='fail', private_key=None,
-               auth_local_webserver=False, table_schema=None, location=None,
-               progress_bar=True, verbose=None):
+               reauth=False, if_exists='fail', auth_local_webserver=False,
+               table_schema=None, location=None, progress_bar=True,
+               credentials=None, verbose=None, private_key=None):
         """
         Write a DataFrame to a Google BigQuery table.
 
@@ -1311,10 +1311,31 @@ def to_gbq(self, destination_table, project_id=None, chunksize=None,
             chunk by chunk.
 
             *New in version 0.5.0 of pandas-gbq*.
+        credentials : google.auth.credentials.Credentials, optional
+            Credentials for accessing Google APIs. Use this parameter to
+            override default credentials, such as to use Compute Engine
+            :class:`google.auth.compute_engine.Credentials` or Service
+            Account :class:`google.oauth2.service_account.Credentials`
+            directly.
+
+            *New in version 0.8.0 of pandas-gbq*.
+
+            .. versionadded:: 0.24.0
         verbose : bool, deprecated
-            Deprecated in Pandas-GBQ 0.4.0. Use the `logging module
+            Deprecated in pandas-gbq version 0.4.0. Use the `logging module
             to adjust verbosity instead
             <https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.
+        private_key : str, deprecated
+            Deprecated in pandas-gbq version 0.8.0. Use the ``credentials``
+            parameter and
+            :func:`google.oauth2.service_account.Credentials.from_service_account_info`
+            or
+            :func:`google.oauth2.service_account.Credentials.from_service_account_file`
+            instead.
+
+            Service account private key in JSON format. Can be file path
+            or string contents. This is useful for remote server
+            authentication (eg. Jupyter/IPython notebook on remote host).
 
         See Also
         --------
@@ -1324,11 +1345,11 @@ def to_gbq(self, destination_table, project_id=None, chunksize=None,
         from pandas.io import gbq
         return gbq.to_gbq(
             self, destination_table, project_id=project_id,
-            chunksize=chunksize, reauth=reauth,
-            if_exists=if_exists, private_key=private_key,
+            chunksize=chunksize, reauth=reauth, if_exists=if_exists,
             auth_local_webserver=auth_local_webserver,
             table_schema=table_schema, location=location,
-            progress_bar=progress_bar, verbose=verbose)
+            progress_bar=progress_bar, credentials=credentials,
+            verbose=verbose, private_key=private_key)
 
     @classmethod
     def from_records(cls, data, index=None, exclude=None, columns=None,

pandas/io/gbq.py

@@ -24,9 +24,9 @@ def _try_import():
 
 
 def read_gbq(query, project_id=None, index_col=None, col_order=None,
-             reauth=False, private_key=None, auth_local_webserver=False,
-             dialect=None, location=None, configuration=None,
-             verbose=None):
+             reauth=False, auth_local_webserver=False, dialect=None,
+             location=None, configuration=None, credentials=None,
+             private_key=None, verbose=None):
     """
     Load data from Google BigQuery.
 
@@ -98,10 +98,30 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
 
         For more information see `BigQuery REST API Reference
         <https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.query>`__.
+    credentials : google.auth.credentials.Credentials, optional
+        Credentials for accessing Google APIs. Use this parameter to override
+        default credentials, such as to use Compute Engine
+        :class:`google.auth.compute_engine.Credentials` or Service Account
+        :class:`google.oauth2.service_account.Credentials` directly.
+
+        *New in version 0.8.0 of pandas-gbq*.
+
+        .. versionadded:: 0.24.0
     verbose : None, deprecated
-        Deprecated in Pandas-GBQ 0.4.0. Use the `logging module
-        to adjust verbosity instead
+        Deprecated in pandas-gbq version 0.4.0. Use the `logging module to
+        adjust verbosity instead
         <https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.
+    private_key : str, deprecated
+        Deprecated in pandas-gbq version 0.8.0. Use the ``credentials``
+        parameter and
+        :func:`google.oauth2.service_account.Credentials.from_service_account_info`
+        or
+        :func:`google.oauth2.service_account.Credentials.from_service_account_file`
+        instead.
+
+        Service account private key in JSON format. Can be file path
+        or string contents. This is useful for remote server
+        authentication (eg. Jupyter/IPython notebook on remote host).
 
     Returns
     -------
@@ -127,20 +147,20 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
 
     return pandas_gbq.read_gbq(
         query, project_id=project_id, index_col=index_col,
-        col_order=col_order, reauth=reauth, verbose=verbose,
-        private_key=private_key, auth_local_webserver=auth_local_webserver,
-        dialect=dialect, location=location, configuration=configuration)
+        col_order=col_order, reauth=reauth,
+        auth_local_webserver=auth_local_webserver, dialect=dialect,
+        location=location, configuration=configuration,
+        credentials=credentials, verbose=verbose, private_key=private_key)
 
 
 def to_gbq(dataframe, destination_table, project_id=None, chunksize=None,
-           verbose=None, reauth=False, if_exists='fail', private_key=None,
-           auth_local_webserver=False, table_schema=None, location=None,
-           progress_bar=True):
+           reauth=False, if_exists='fail', auth_local_webserver=False,
+           table_schema=None, location=None, progress_bar=True,
+           credentials=None, verbose=None, private_key=None):
     pandas_gbq = _try_import()
     return pandas_gbq.to_gbq(
         dataframe, destination_table, project_id=project_id,
-        chunksize=chunksize, verbose=verbose, reauth=reauth,
-        if_exists=if_exists, private_key=private_key,
-        auth_local_webserver=auth_local_webserver,
-        table_schema=table_schema, location=location,
-        progress_bar=progress_bar)
+        chunksize=chunksize, reauth=reauth, if_exists=if_exists,
+        auth_local_webserver=auth_local_webserver, table_schema=table_schema,
+        location=location, progress_bar=progress_bar,
+        credentials=credentials, verbose=verbose, private_key=private_key)

pandas/tests/io/test_gbq.py

@@ -19,7 +19,7 @@
 api_exceptions = pytest.importorskip("google.api_core.exceptions")
 bigquery = pytest.importorskip("google.cloud.bigquery")
 service_account = pytest.importorskip("google.oauth2.service_account")
-pandas_gbq = pytest.importorskip('pandas_gbq')
+pandas_gbq = pytest.importorskip("pandas_gbq")
 
 PROJECT_ID = None
 PRIVATE_KEY_JSON_PATH = None
@@ -70,15 +70,16 @@ def _get_private_key_path():
     return private_key_path
 
 
-def _get_client():
-    project_id = _get_project_id()
-    credentials = None
-
+def _get_credentials():
     private_key_path = _get_private_key_path()
     if private_key_path:
-        credentials = service_account.Credentials.from_service_account_file(
+        return service_account.Credentials.from_service_account_file(
             private_key_path)
 
+
+def _get_client():
+    project_id = _get_project_id()
+    credentials = _get_credentials()
     return bigquery.Client(project=project_id, credentials=credentials)
 
 
@@ -144,11 +145,11 @@ def test_roundtrip(self):
         df = make_mixed_dataframe_v2(test_size)
 
         df.to_gbq(destination_table, _get_project_id(), chunksize=None,
-                  private_key=_get_private_key_path())
+                  credentials=_get_credentials())
 
         result = pd.read_gbq("SELECT COUNT(*) AS num_rows FROM {0}"
                              .format(destination_table),
                              project_id=_get_project_id(),
-                             private_key=_get_private_key_path(),
+                             credentials=_get_credentials(),
                              dialect="standard")
         assert result['num_rows'][0] == test_size