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Apr 9, 2018
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ENH/DOC: update pandas-gbq signature and docstring #20564

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ea52387
DOC: intersphinx to pandas-gbq
tswast Mar 30, 2018
b1b1479
DOC: add detailed docs for read_gbq, to_gbq back.
tswast Apr 2, 2018
0429227
CLN: line lengths.
tswast Apr 2, 2018
bee847b
DOC: remove dead link to pandas.io.to_gbq
tswast Apr 2, 2018
2e5b148
DOC: update versionadded string for pandas-gbq
tswast Apr 2, 2018
cb178d9
Add pandas-gbq args to function signature directly.
tswast Apr 3, 2018
f09d38e
DOC: cross-reference to_gbq and read_gbq
tswast Apr 3, 2018
b6fdf37
Fix lint error.
tswast Apr 4, 2018
37b2a08
DOC: render BigQuery auth flows as links
tswast Apr 4, 2018
f6c38f0
DOC: pandas-gbq to whatsnew
tswast Apr 5, 2018
0889d6d
DOC: sync pandas-gbq changes from 0.4.0 (deprecate verbosity)
tswast Apr 5, 2018
aa99d47
DOC: clarify Pandas-GBQ version in whatsnew.
tswast Apr 5, 2018
1ab0934
move whatsnew
jorisvandenbossche Apr 9, 2018
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1 change: 1 addition & 0 deletions doc/source/conf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -350,6 +350,7 @@
intersphinx_mapping = {
'statsmodels': ('http://www.statsmodels.org/devel/', None),
'matplotlib': ('http://matplotlib.org/', None),
'pandas-gbq': ('https://pandas-gbq.readthedocs.io/en/latest/', None),
'python': ('https://docs.python.org/3/', None),
'numpy': ('https://docs.scipy.org/doc/numpy/', None),
'scipy': ('https://docs.scipy.org/doc/scipy/reference/', None),
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5 changes: 4 additions & 1 deletion doc/source/whatsnew/v0.23.0.txt
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Expand Up @@ -404,7 +404,10 @@ Other Enhancements
- :func:`read_html` now accepts a ``displayed_only`` keyword argument to controls whether or not hidden elements are parsed (``True`` by default) (:issue:`20027`)
- zip compression is supported via ``compression=zip`` in :func:`DataFrame.to_pickle`, :func:`Series.to_pickle`, :func:`DataFrame.to_csv`, :func:`Series.to_csv`, :func:`DataFrame.to_json`, :func:`Series.to_json`. (:issue:`17778`)
- :class:`DataFrame` and :class:`Series` now support matrix multiplication (```@```) operator (:issue:`10259`) for Python>=3.5

- Updated ``to_gbq`` and ``read_gbq`` signature and documentation to reflect changes from
the Pandas-GBQ library version 0.4.0. Adds intersphinx mapping to Pandas-GBQ
library. (:issue:`20564`)

.. _whatsnew_0230.api_breaking:

Backwards incompatible API changes
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100 changes: 65 additions & 35 deletions pandas/core/frame.py
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Expand Up @@ -1116,60 +1116,90 @@ def to_dict(self, orient='dict', into=dict):
else:
raise ValueError("orient '%s' not understood" % orient)

def to_gbq(self, destination_table, project_id, chunksize=10000,
verbose=True, reauth=False, if_exists='fail', private_key=None):
"""Write a DataFrame to a Google BigQuery table.

The main method a user calls to export pandas DataFrame contents to
Google BigQuery table.
def to_gbq(self, destination_table, project_id, chunksize=None,
verbose=None, reauth=False, if_exists='fail', private_key=None,
auth_local_webserver=False, table_schema=None):
"""
Write a DataFrame to a Google BigQuery table.

Google BigQuery API Client Library v2 for Python is used.
Documentation is available `here
<https://developers.google.com/api-client-library/python/apis/bigquery/v2>`__
This function requires the `pandas-gbq package
<https://pandas-gbq.readthedocs.io>`__.

Authentication to the Google BigQuery service is via OAuth 2.0.

- If "private_key" is not provided:
- If ``private_key`` is provided, the library loads the JSON service
account credentials and uses those to authenticate.

By default "application default credentials" are used.
- If no ``private_key`` is provided, the library tries `application
default credentials`_.

If default application credentials are not found or are restrictive,
user account credentials are used. In this case, you will be asked to
grant permissions for product name 'pandas GBQ'.
.. _application default credentials:
https://cloud.google.com/docs/authentication/production#providing_credentials_to_your_application

- If "private_key" is provided:

Service account credentials will be used to authenticate.
- If application default credentials are not found or cannot be used
with BigQuery, the library authenticates with user account
credentials. In this case, you will be asked to grant permissions
for product name 'pandas GBQ'.

Parameters
----------
dataframe : DataFrame
DataFrame to be written
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this needs to stay

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The validation script was complaining about this one. I think because this is a method of DataFrame, so there is no dataframe argument. (I also tried self and it complained about that, too.)

################################################################################
################################## Validation ##################################
################################################################################

Errors found:
	Errors in parameters section
		Unknown parameters {'dataframe'}
		Parameter "kwargs" description should finish with "."
	No returns section found
	Missing description for See Also "pandas_gbq.to_gbq" reference
	No examples section found

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oh don’t worry about that too much

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I think @tswast is correct that this should be removed. The method does not take a dataframe as input (it is writing self to gbq)

destination_table : string
Name of table to be written, in the form 'dataset.tablename'
destination_table : str
Name of table to be written, in the form 'dataset.tablename'.
project_id : str
Google BigQuery Account project ID.
chunksize : int (default 10000)
chunksize : int, optional
Number of rows to be inserted in each chunk from the dataframe.
verbose : boolean (default True)
Show percentage complete
reauth : boolean (default False)
Set to ``None`` to load the whole dataframe at once.
reauth : bool, default False
Force Google BigQuery to reauthenticate the user. This is useful
if multiple accounts are used.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
'fail': If table exists, do nothing.
'replace': If table exists, drop it, recreate it, and insert data.
'append': If table exists, insert data. Create if does not exist.
private_key : str (optional)
if_exists : str, default 'fail'
Behavior when the destination table exists. Value can be one of:

``'fail'``
If table exists, do nothing.
``'replace'``
If table exists, drop it, recreate it, and insert data.
``'append'``
If table exists, insert data. Create if does not exist.
private_key : str, optional
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)
"""
authentication (eg. Jupyter/IPython notebook on remote host).
auth_local_webserver : bool, default False
Use the `local webserver flow`_ instead of the `console flow`_
when getting user credentials.

.. _local webserver flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_local_server
.. _console flow:
http://google-auth-oauthlib.readthedocs.io/en/latest/reference/google_auth_oauthlib.flow.html#google_auth_oauthlib.flow.InstalledAppFlow.run_console

*New in version 0.2.0 of pandas-gbq*.
table_schema : list of dicts, optional
List of BigQuery table fields to which according DataFrame
columns conform to, e.g. ``[{'name': 'col1', 'type':
'STRING'},...]``. If schema is not provided, it will be
generated according to dtypes of DataFrame columns. See
BigQuery API documentation on available names of a field.

*New in version 0.3.1 of pandas-gbq*.
verbose : boolean, deprecated
*Deprecated in Pandas-GBQ 0.4.0.* Use the `logging module
to adjust verbosity instead
<https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.

See Also
--------
pandas_gbq.to_gbq : This function in the pandas-gbq library.
pandas.read_gbq : Read a DataFrame from Google BigQuery.
"""
from pandas.io import gbq
return gbq.to_gbq(self, destination_table, project_id=project_id,
chunksize=chunksize, verbose=verbose, reauth=reauth,
if_exists=if_exists, private_key=private_key)
return gbq.to_gbq(
self, destination_table, 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)

@classmethod
def from_records(cls, data, index=None, exclude=None, columns=None,
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73 changes: 42 additions & 31 deletions pandas/io/gbq.py
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Expand Up @@ -22,12 +22,10 @@ def _try_import():


def read_gbq(query, project_id=None, index_col=None, col_order=None,
reauth=False, verbose=True, private_key=None, dialect='legacy',
reauth=False, verbose=None, private_key=None, dialect='legacy',
**kwargs):
r"""Load data from Google BigQuery.

The main method a user calls to execute a Query in Google BigQuery
and read results into a pandas DataFrame.
"""
Load data from Google BigQuery.

This function requires the `pandas-gbq package
<https://pandas-gbq.readthedocs.io>`__.
Expand All @@ -49,32 +47,39 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
Parameters
----------
query : str
SQL-Like Query to return data values
SQL-Like Query to return data values.
project_id : str
Google BigQuery Account project ID.
index_col : str (optional)
Name of result column to use for index in results DataFrame
col_order : list(str) (optional)
index_col : str, optional
Name of result column to use for index in results DataFrame.
col_order : list(str), optional
List of BigQuery column names in the desired order for results
DataFrame
reauth : boolean (default False)
DataFrame.
reauth : boolean, default False
Force Google BigQuery to reauthenticate the user. This is useful
if multiple accounts are used.
verbose : boolean (default True)
Verbose output
private_key : str (optional)
private_key : str, optional
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)

dialect : {'legacy', 'standard'}, default 'legacy'
'legacy' : Use BigQuery's legacy SQL dialect.
'standard' : Use BigQuery's standard SQL, which is
compliant with the SQL 2011 standard. For more information
see `BigQuery SQL Reference
<https://cloud.google.com/bigquery/sql-reference/>`__

`**kwargs` : Arbitrary keyword arguments
authentication (eg. Jupyter/IPython notebook on remote host).
dialect : str, default 'legacy'
SQL syntax dialect to use. Value can be one of:

``'legacy'``
Use BigQuery's legacy SQL dialect. For more information see
`BigQuery Legacy SQL Reference
<https://cloud.google.com/bigquery/docs/reference/legacy-sql>`__.
``'standard'``
Use BigQuery's standard SQL, which is
compliant with the SQL 2011 standard. For more information
see `BigQuery Standard SQL Reference
<https://cloud.google.com/bigquery/docs/reference/standard-sql/>`__.
verbose : boolean, deprecated
*Deprecated in Pandas-GBQ 0.4.0.* Use the `logging module
to adjust verbosity instead
<https://pandas-gbq.readthedocs.io/en/latest/intro.html#logging>`__.
kwargs : dict
Arbitrary keyword arguments.
configuration (dict): query config parameters for job processing.
For example:

Expand All @@ -86,8 +91,12 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
Returns
-------
df: DataFrame
DataFrame representing results of query
DataFrame representing results of query.

See Also
--------
pandas_gbq.read_gbq : This function in the pandas-gbq library.
pandas.DataFrame.to_gbq : Write a DataFrame to Google BigQuery.
"""
pandas_gbq = _try_import()
return pandas_gbq.read_gbq(
Expand All @@ -99,10 +108,12 @@ def read_gbq(query, project_id=None, index_col=None, col_order=None,
**kwargs)


def to_gbq(dataframe, destination_table, project_id, chunksize=10000,
verbose=True, reauth=False, if_exists='fail', private_key=None):
def to_gbq(dataframe, destination_table, project_id, chunksize=None,
verbose=None, reauth=False, if_exists='fail', private_key=None,
auth_local_webserver=False, table_schema=None):
pandas_gbq = _try_import()
pandas_gbq.to_gbq(dataframe, destination_table, project_id,
chunksize=chunksize,
verbose=verbose, reauth=reauth,
if_exists=if_exists, private_key=private_key)
return pandas_gbq.to_gbq(
dataframe, destination_table, 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)