# Copyright 2018 Google LLC
#
# Licensed 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.
"""IPython Magics
.. function:: %%bigquery
IPython cell magic to run a query and display the result as a DataFrame
.. code-block:: python
%%bigquery [<destination_var>] [--project <project>] [--use_legacy_sql]
[--verbose] [--params <params>]
<query>
Parameters:
* ``<destination_var>`` (optional, line argument):
variable to store the query results. The results are not displayed if
this parameter is used.
* ``--project <project>`` (optional, line argument):
Project to use for running the query. Defaults to the context
:attr:`~google.cloud.bigquery.magics.Context.project`.
* ``--use_bqstorage_api`` (optional, line argument):
Downloads the DataFrame using the BigQuery Storage API. To use this
option, install the ``google-cloud-bigquery-storage`` and ``fastavro``
packages, and `enable the BigQuery Storage API
<https://console.cloud.google.com/apis/library/bigquerystorage.googleapis.com>`_.
* ``--use_legacy_sql`` (optional, line argument):
Runs the query using Legacy SQL syntax. Defaults to Standard SQL if
this argument not used.
* ``--verbose`` (optional, line argument):
If this flag is used, information including the query job ID and the
amount of time for the query to complete will not be cleared after the
query is finished. By default, this information will be displayed but
will be cleared after the query is finished.
* ``--params <params>`` (optional, line argument):
If present, the argument following the ``--params`` flag must be
either:
* :class:`str` - A JSON string representation of a dictionary in the
format ``{"param_name": "param_value"}`` (ex. ``{"num": 17}``). Use
of the parameter in the query should be indicated with
``@param_name``. See ``In[5]`` in the Examples section below.
* :class:`dict` reference - A reference to a ``dict`` in the format
``{"param_name": "param_value"}``, where the value types must be JSON
serializable. The variable reference is indicated by a ``$`` before
the variable name (ex. ``$my_dict_var``). See ``In[6]`` and ``In[7]``
in the Examples section below.
* ``<query>`` (required, cell argument):
SQL query to run.
Returns:
A :class:`pandas.DataFrame` with the query results.
.. note::
All queries run using this magic will run using the context
:attr:`~google.cloud.bigquery.magics.Context.credentials`.
Examples:
The following examples can be run in an IPython notebook after loading
the bigquery IPython extension (see ``In[1]``) and setting up
Application Default Credentials.
.. code-block:: none
In [1]: %load_ext google.cloud.bigquery
In [2]: %%bigquery
...: SELECT name, SUM(number) as count
...: FROM `bigquery-public-data.usa_names.usa_1910_current`
...: GROUP BY name
...: ORDER BY count DESC
...: LIMIT 3
Out[2]: name count
...: -------------------
...: 0 James 4987296
...: 1 John 4866302
...: 2 Robert 4738204
In [3]: %%bigquery df --project my-alternate-project --verbose
...: SELECT name, SUM(number) as count
...: FROM `bigquery-public-data.usa_names.usa_1910_current`
...: WHERE gender = 'F'
...: GROUP BY name
...: ORDER BY count DESC
...: LIMIT 3
Executing query with job ID: bf633912-af2c-4780-b568-5d868058632b
Query executing: 2.61s
Query complete after 2.92s
In [4]: df
Out[4]: name count
...: ----------------------
...: 0 Mary 3736239
...: 1 Patricia 1568495
...: 2 Elizabeth 1519946
In [5]: %%bigquery --params {"num": 17}
...: SELECT @num AS num
Out[5]: num
...: -------
...: 0 17
In [6]: params = {"num": 17}
In [7]: %%bigquery --params $params
...: SELECT @num AS num
Out[7]: num
...: -------
...: 0 17
"""
from __future__ import print_function
import ast
import sys
import time
from concurrent import futures
try:
import IPython
from IPython import display
from IPython.core import magic_arguments
except ImportError: # pragma: NO COVER
raise ImportError("This module can only be loaded in IPython.")
from google.api_core import client_info
import google.auth
from google.cloud import bigquery
from google.cloud.bigquery.dbapi import _helpers
import six
IPYTHON_USER_AGENT = "ipython-{}".format(IPython.__version__)
[docs]class Context(object):
"""Storage for objects to be used throughout an IPython notebook session.
A Context object is initialized when the ``magics`` module is imported,
and can be found at ``google.cloud.bigquery.magics.context``.
"""
def __init__(self):
self._credentials = None
self._project = None
self._connection = None
self._use_bqstorage_api = None
self._default_query_job_config = bigquery.QueryJobConfig()
@property
def credentials(self):
"""google.auth.credentials.Credentials: Credentials to use for queries
performed through IPython magics
Note:
These credentials do not need to be explicitly defined if you are
using Application Default Credentials. If you are not using
Application Default Credentials, manually construct a
:class:`google.auth.credentials.Credentials` object and set it as
the context credentials as demonstrated in the example below. See
`auth docs`_ for more information on obtaining credentials.
Example:
Manually setting the context credentials:
>>> from google.cloud.bigquery import magics
>>> from google.oauth2 import service_account
>>> credentials = (service_account
... .Credentials.from_service_account_file(
... '/path/to/key.json'))
>>> magics.context.credentials = credentials
.. _auth docs: http://google-auth.readthedocs.io
/en/latest/user-guide.html#obtaining-credentials
"""
if self._credentials is None:
self._credentials, _ = google.auth.default()
return self._credentials
@credentials.setter
def credentials(self, value):
self._credentials = value
@property
def project(self):
"""str: Default project to use for queries performed through IPython
magics
Note:
The project does not need to be explicitly defined if you have an
environment default project set. If you do not have a default
project set in your environment, manually assign the project as
demonstrated in the example below.
Example:
Manually setting the context project:
>>> from google.cloud.bigquery import magics
>>> magics.context.project = 'my-project'
"""
if self._project is None:
_, self._project = google.auth.default()
return self._project
@project.setter
def project(self, value):
self._project = value
@property
def use_bqstorage_api(self):
"""bool: [Beta] Set to True to use the BigQuery Storage API to
download query results
To use this option, install the ``google-cloud-bigquery-storage`` and
``fastavro`` packages, and `enable the BigQuery Storage API
<https://console.cloud.google.com/apis/library/bigquerystorage.googleapis.com>`_.
"""
return self._use_bqstorage_api
@use_bqstorage_api.setter
def use_bqstorage_api(self, value):
self._use_bqstorage_api = value
@property
def default_query_job_config(self):
"""google.cloud.bigquery.job.QueryJobConfig: Default job
configuration for queries.
The context's :class:`~google.cloud.bigquery.job.QueryJobConfig` is
used for queries. Some properties can be overridden with arguments to
the magics.
Example:
Manually setting the default value for ``maximum_bytes_billed``
to 100 MB:
>>> from google.cloud.bigquery import magics
>>> magics.context.default_query_job_config.maximum_bytes_billed = 100000000
"""
return self._default_query_job_config
@default_query_job_config.setter
def default_query_job_config(self, value):
self._default_query_job_config = value
context = Context()
def _run_query(client, query, job_config=None):
"""Runs a query while printing status updates
Args:
client (google.cloud.bigquery.client.Client):
Client to bundle configuration needed for API requests.
query (str):
SQL query to be executed. Defaults to the standard SQL dialect.
Use the ``job_config`` parameter to change dialects.
job_config (google.cloud.bigquery.job.QueryJobConfig, optional):
Extra configuration options for the job.
Returns:
google.cloud.bigquery.job.QueryJob: the query job created
Example:
>>> client = bigquery.Client()
>>> _run_query(client, "SELECT 17")
Executing query with job ID: bf633912-af2c-4780-b568-5d868058632b
Query executing: 1.66s
Query complete after 2.07s
'bf633912-af2c-4780-b568-5d868058632b'
"""
start_time = time.time()
query_job = client.query(query, job_config=job_config)
if job_config and job_config.dry_run:
return query_job
print("Executing query with job ID: {}".format(query_job.job_id))
while True:
print("\rQuery executing: {:0.2f}s".format(time.time() - start_time), end="")
try:
query_job.result(timeout=0.5)
break
except futures.TimeoutError:
continue
print("\nQuery complete after {:0.2f}s".format(time.time() - start_time))
return query_job
@magic_arguments.magic_arguments()
@magic_arguments.argument(
"destination_var",
nargs="?",
help=("If provided, save the output to this variable instead of displaying it."),
)
@magic_arguments.argument(
"--project",
type=str,
default=None,
help=("Project to use for executing this query. Defaults to the context project."),
)
@magic_arguments.argument(
"--maximum_bytes_billed",
default=None,
help=(
"maximum_bytes_billed to use for executing this query. Defaults to "
"the context default_query_job_config.maximum_bytes_billed."
),
)
@magic_arguments.argument(
"--dry_run",
action="store_true",
default=False,
help=(
"Sets query to be a dry run to estimate costs. "
"Defaults to executing the query instead of dry run if this argument is not used."
),
)
@magic_arguments.argument(
"--use_legacy_sql",
action="store_true",
default=False,
help=(
"Sets query to use Legacy SQL instead of Standard SQL. Defaults to "
"Standard SQL if this argument is not used."
),
)
@magic_arguments.argument(
"--use_bqstorage_api",
action="store_true",
default=False,
help=(
"[Beta] Use the BigQuery Storage API to download large query results. "
"To use this option, install the google-cloud-bigquery-storage and "
"fastavro packages, and enable the BigQuery Storage API."
),
)
@magic_arguments.argument(
"--verbose",
action="store_true",
default=False,
help=(
"If set, print verbose output, including the query job ID and the "
"amount of time for the query to finish. By default, this "
"information will be displayed as the query runs, but will be "
"cleared after the query is finished."
),
)
@magic_arguments.argument(
"--params",
nargs="+",
default=None,
help=(
"Parameters to format the query string. If present, the --params "
"flag should be followed by a string representation of a dictionary "
"in the format {'param_name': 'param_value'} (ex. {\"num\": 17}), "
"or a reference to a dictionary in the same format. The dictionary "
"reference can be made by including a '$' before the variable "
"name (ex. $my_dict_var)."
),
)
def _cell_magic(line, query):
"""Underlying function for bigquery cell magic
Note:
This function contains the underlying logic for the 'bigquery' cell
magic. This function is not meant to be called directly.
Args:
line (str): "%%bigquery" followed by arguments as required
query (str): SQL query to run
Returns:
pandas.DataFrame: the query results.
"""
args = magic_arguments.parse_argstring(_cell_magic, line)
params = []
if args.params is not None:
try:
params = _helpers.to_query_parameters(
ast.literal_eval("".join(args.params))
)
except Exception:
raise SyntaxError(
"--params is not a correctly formatted JSON string or a JSON "
"serializable dictionary"
)
project = args.project or context.project
client = bigquery.Client(
project=project,
credentials=context.credentials,
default_query_job_config=context.default_query_job_config,
client_info=client_info.ClientInfo(user_agent=IPYTHON_USER_AGENT),
)
if context._connection:
client._connection = context._connection
bqstorage_client = _make_bqstorage_client(
args.use_bqstorage_api or context.use_bqstorage_api, context.credentials
)
job_config = bigquery.job.QueryJobConfig()
job_config.query_parameters = params
job_config.use_legacy_sql = args.use_legacy_sql
job_config.dry_run = args.dry_run
if args.maximum_bytes_billed == "None":
job_config.maximum_bytes_billed = 0
elif args.maximum_bytes_billed is not None:
value = int(args.maximum_bytes_billed)
job_config.maximum_bytes_billed = value
error = None
try:
query_job = _run_query(client, query, job_config)
except Exception as ex:
error = str(ex)
if not args.verbose:
display.clear_output()
if error:
if args.destination_var:
print(
"Could not save output to variable '{}'.".format(args.destination_var),
file=sys.stderr,
)
print("\nERROR:\n", error, file=sys.stderr)
return
if args.dry_run and args.destination_var:
IPython.get_ipython().push({args.destination_var: query_job})
return
elif args.dry_run:
print(
"Query validated. This query will process {} bytes.".format(
query_job.total_bytes_processed
)
)
return query_job
result = query_job.to_dataframe(bqstorage_client=bqstorage_client)
if args.destination_var:
IPython.get_ipython().push({args.destination_var: result})
else:
return result
def _make_bqstorage_client(use_bqstorage_api, credentials):
if not use_bqstorage_api:
return None
try:
from google.cloud import bigquery_storage_v1beta1
except ImportError as err:
customized_error = ImportError(
"Install the google-cloud-bigquery-storage and pyarrow packages "
"to use the BigQuery Storage API."
)
six.raise_from(customized_error, err)
try:
from google.api_core.gapic_v1 import client_info as gapic_client_info
except ImportError as err:
customized_error = ImportError(
"Install the grpcio package to use the BigQuery Storage API."
)
six.raise_from(customized_error, err)
return bigquery_storage_v1beta1.BigQueryStorageClient(
credentials=credentials,
client_info=gapic_client_info.ClientInfo(user_agent=IPYTHON_USER_AGENT),
)