As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Source code for google.cloud.bigquery.magics.magics

# 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

To use these magics, you must first register them. Run the ``%load_ext`` magic
in a Jupyter notebook cell.

.. code::

    %load_ext google.cloud.bigquery

This makes the ``%%bigquery`` magic available.

.. 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. If an error occurs during the query execution,
        the corresponding ``QueryJob`` instance (if available) is stored in
        the variable instead.
    * ``--destination_table`` (Optional[line argument]):
        A dataset and table to store the query results. If table does not exists,
        it will be created. If table already exists, its data will be overwritten.
        Variable should be in a format <dataset_id>.<table_id>.
    * ``--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]):
        [Deprecated] Not used anymore, as BigQuery Storage API is used by default.
    * ``--use_rest_api`` (Optional[line argument]):
        Use the BigQuery REST API instead of the Storage API.
    * ``--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. If the query does not contain any whitespace (aside
        from leading and trailing whitespace), it is assumed to represent a
        fully-qualified table ID, and the latter's data will be fetched.

    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 re
import ast
import copy
import functools
import sys
import time
import warnings
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
from google.api_core import client_options
from google.api_core.exceptions import NotFound
import google.auth
from google.cloud import bigquery
import google.cloud.bigquery.dataset
from google.cloud.bigquery.dbapi import _helpers
from google.cloud.bigquery.magics import line_arg_parser as lap


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._default_query_job_config = bigquery.QueryJobConfig() self._bigquery_client_options = client_options.ClientOptions() self._bqstorage_client_options = client_options.ClientOptions() self._progress_bar_type = "tqdm" @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 bigquery_client_options(self): """google.api_core.client_options.ClientOptions: client options to be used through IPython magics. Note:: The client options do not need to be explicitly defined if no special network connections are required. Normally you would be using the https://bigquery.googleapis.com/ end point. Example: Manually setting the endpoint: >>> from google.cloud.bigquery import magics >>> client_options = {} >>> client_options['api_endpoint'] = "https://some.special.url" >>> magics.context.bigquery_client_options = client_options """ return self._bigquery_client_options @bigquery_client_options.setter def bigquery_client_options(self, value): self._bigquery_client_options = value @property def bqstorage_client_options(self): """google.api_core.client_options.ClientOptions: client options to be used through IPython magics for the storage client. Note:: The client options do not need to be explicitly defined if no special network connections are required. Normally you would be using the https://bigquerystorage.googleapis.com/ end point. Example: Manually setting the endpoint: >>> from google.cloud.bigquery import magics >>> client_options = {} >>> client_options['api_endpoint'] = "https://some.special.url" >>> magics.context.bqstorage_client_options = client_options """ return self._bqstorage_client_options @bqstorage_client_options.setter def bqstorage_client_options(self, value): self._bqstorage_client_options = 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 @property def progress_bar_type(self): """str: Default progress bar type to use to display progress bar while executing queries through IPython magics. Note:: Install the ``tqdm`` package to use this feature. Example: Manually setting the progress_bar_type: >>> from google.cloud.bigquery import magics >>> magics.context.progress_bar_type = "tqdm" """ return self._progress_bar_type @progress_bar_type.setter def progress_bar_type(self, value): self._progress_bar_type = value
context = Context() def _handle_error(error, destination_var=None): """Process a query execution error. Args: error (Exception): An exception that ocurred during the query exectution. destination_var (Optional[str]): The name of the IPython session variable to store the query job. """ if destination_var: query_job = getattr(error, "query_job", None) if query_job is not None: IPython.get_ipython().push({destination_var: query_job}) else: # this is the case when previewing table rows by providing just # table ID to cell magic print( "Could not save output to variable '{}'.".format(destination_var), file=sys.stderr, ) print("\nERROR:\n", str(error), file=sys.stderr) 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 (Optional[google.cloud.bigquery.job.QueryJobConfig]): 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 def _create_dataset_if_necessary(client, dataset_id): """Create a dataset in the current project if it doesn't exist. Args: client (google.cloud.bigquery.client.Client): Client to bundle configuration needed for API requests. dataset_id (str): Dataset id. """ dataset_reference = bigquery.dataset.DatasetReference(client.project, dataset_id) try: dataset = client.get_dataset(dataset_reference) return except NotFound: pass dataset = bigquery.Dataset(dataset_reference) dataset.location = client.location print("Creating dataset: {}".format(dataset_id)) dataset = client.create_dataset(dataset) @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( "--destination_table", type=str, default=None, help=( "If provided, save the output of the query to a new BigQuery table. " "Variable should be in a format <dataset_id>.<table_id>. " "If table does not exists, it will be created. " "If table already exists, its data will be overwritten." ), ) @magic_arguments.argument( "--project", type=str, default=None, help=("Project to use for executing this query. Defaults to the context project."), ) @magic_arguments.argument( "--max_results", default=None, help=( "Maximum number of rows in dataframe returned from executing the query." "Defaults to returning all rows." ), ) @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( "--bigquery_api_endpoint", type=str, default=None, help=( "The desired API endpoint, e.g., bigquery.googlepis.com. Defaults to this " "option's value in the context bigquery_client_options." ), ) @magic_arguments.argument( "--bqstorage_api_endpoint", type=str, default=None, help=( "The desired API endpoint, e.g., bigquerystorage.googlepis.com. Defaults to " "this option's value in the context bqstorage_client_options." ), ) @magic_arguments.argument( "--use_bqstorage_api", action="store_true", default=None, help=( "[Deprecated] The BigQuery Storage API is already used by default to " "download large query results, and this option has no effect. " "If you want to switch to the classic REST API instead, use the " "--use_rest_api option." ), ) @magic_arguments.argument( "--use_rest_api", action="store_true", default=False, help=( "Use the classic REST API instead of the BigQuery Storage API to " "download query results." ), ) @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. $my_dict_var)." ), ) @magic_arguments.argument( "--progress_bar_type", type=str, default=None, help=( "Sets progress bar type to display a progress bar while executing the query." "Defaults to use tqdm. Install the ``tqdm`` package to use this feature." ), ) def _cell_magic(line, query): """Underlying function for bigquery cell magic Note: This function contains the underlying logic for the 'bigquery' cell magic. This function is not meant to be called directly. Args: line (str): "%%bigquery" followed by arguments as required query (str): SQL query to run Returns: pandas.DataFrame: the query results. """ # The built-in parser does not recognize Python structures such as dicts, thus # we extract the "--params" option and inteprpret it separately. try: params_option_value, rest_of_args = _split_args_line(line) except lap.exceptions.QueryParamsParseError as exc: rebranded_error = SyntaxError( "--params is not a correctly formatted JSON string or a JSON " "serializable dictionary" ) raise rebranded_error from exc except lap.exceptions.DuplicateQueryParamsError as exc: rebranded_error = ValueError("Duplicate --params option.") raise rebranded_error from exc except lap.exceptions.ParseError as exc: rebranded_error = ValueError( "Unrecognized input, are option values correct? " "Error details: {}".format(exc.args[0]) ) raise rebranded_error from exc args = magic_arguments.parse_argstring(_cell_magic, rest_of_args) if args.use_bqstorage_api is not None: warnings.warn( "Deprecated option --use_bqstorage_api, the BigQuery " "Storage API is already used by default.", category=DeprecationWarning, ) use_bqstorage_api = not args.use_rest_api params = [] if params_option_value: # A non-existing params variable is not expanded and ends up in the input # in its raw form, e.g. "$query_params". if params_option_value.startswith("$"): msg = 'Parameter expansion failed, undefined variable "{}".'.format( params_option_value[1:] ) raise NameError(msg) params = _helpers.to_query_parameters(ast.literal_eval(params_option_value), {}) project = args.project or context.project bigquery_client_options = copy.deepcopy(context.bigquery_client_options) if args.bigquery_api_endpoint: if isinstance(bigquery_client_options, dict): bigquery_client_options["api_endpoint"] = args.bigquery_api_endpoint else: bigquery_client_options.api_endpoint = args.bigquery_api_endpoint 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), client_options=bigquery_client_options, ) if context._connection: client._connection = context._connection bqstorage_client_options = copy.deepcopy(context.bqstorage_client_options) if args.bqstorage_api_endpoint: if isinstance(bqstorage_client_options, dict): bqstorage_client_options["api_endpoint"] = args.bqstorage_api_endpoint else: bqstorage_client_options.api_endpoint = args.bqstorage_api_endpoint bqstorage_client = _make_bqstorage_client( client, use_bqstorage_api, bqstorage_client_options, ) close_transports = functools.partial(_close_transports, client, bqstorage_client) try: if args.max_results: max_results = int(args.max_results) else: max_results = None query = query.strip() if not query: error = ValueError("Query is missing.") _handle_error(error, args.destination_var) return # Any query that does not contain whitespace (aside from leading and trailing whitespace) # is assumed to be a table id if not re.search(r"\s", query): try: rows = client.list_rows(query, max_results=max_results) except Exception as ex: _handle_error(ex, args.destination_var) return result = rows.to_dataframe( bqstorage_client=bqstorage_client, create_bqstorage_client=False, ) if args.destination_var: IPython.get_ipython().push({args.destination_var: result}) return else: return result 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.destination_table: split = args.destination_table.split(".") if len(split) != 2: raise ValueError( "--destination_table should be in a <dataset_id>.<table_id> format." ) dataset_id, table_id = split job_config.allow_large_results = True dataset_ref = bigquery.dataset.DatasetReference(client.project, dataset_id) destination_table_ref = dataset_ref.table(table_id) job_config.destination = destination_table_ref job_config.create_disposition = "CREATE_IF_NEEDED" job_config.write_disposition = "WRITE_TRUNCATE" _create_dataset_if_necessary(client, dataset_id) 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 try: query_job = _run_query(client, query, job_config=job_config) except Exception as ex: _handle_error(ex, args.destination_var) return if not args.verbose: display.clear_output() 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 progress_bar = context.progress_bar_type or args.progress_bar_type if max_results: result = query_job.result(max_results=max_results).to_dataframe( bqstorage_client=None, create_bqstorage_client=False, progress_bar_type=progress_bar, ) else: result = query_job.to_dataframe( bqstorage_client=bqstorage_client, create_bqstorage_client=False, progress_bar_type=progress_bar, ) if args.destination_var: IPython.get_ipython().push({args.destination_var: result}) else: return result finally: close_transports() def _split_args_line(line): """Split out the --params option value from the input line arguments. Args: line (str): The line arguments passed to the cell magic. Returns: Tuple[str, str] """ lexer = lap.Lexer(line) scanner = lap.Parser(lexer) tree = scanner.input_line() extractor = lap.QueryParamsExtractor() params_option_value, rest_of_args = extractor.visit(tree) return params_option_value, rest_of_args def _make_bqstorage_client(client, use_bqstorage_api, client_options): if not use_bqstorage_api: return None try: from google.cloud import bigquery_storage # noqa: F401 except ImportError as err: customized_error = ImportError( "The default BigQuery Storage API client cannot be used, install " "the missing google-cloud-bigquery-storage and pyarrow packages " "to use it. Alternatively, use the classic REST API by specifying " "the --use_rest_api magic option." ) raise customized_error from 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." ) raise customized_error from err return client._ensure_bqstorage_client( client_options=client_options, client_info=gapic_client_info.ClientInfo(user_agent=IPYTHON_USER_AGENT), ) def _close_transports(client, bqstorage_client): """Close the given clients' underlying transport channels. Closing the transport is needed to release system resources, namely open sockets. Args: client (:class:`~google.cloud.bigquery.client.Client`): bqstorage_client (Optional[:class:`~google.cloud.bigquery_storage.BigQueryReadClient`]): A client for the BigQuery Storage API. """ client.close() if bqstorage_client is not None: bqstorage_client._transport.grpc_channel.close()