structure saas with tools
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Davidson Gomes
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Metadata-Version: 2.1
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Name: google-cloud-bigquery
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Version: 3.31.0
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Summary: Google BigQuery API client library
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Author-email: Google LLC <googleapis-packages@google.com>
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License: Apache 2.0
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Project-URL: Repository, https://github.com/googleapis/python-bigquery
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: Apache Software License
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: Programming Language :: Python :: 3.13
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Classifier: Operating System :: OS Independent
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Classifier: Topic :: Internet
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Requires-Python: >=3.9
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Description-Content-Type: text/x-rst
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License-File: LICENSE
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Requires-Dist: google-api-core[grpc]<3.0.0,>=2.11.1
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Requires-Dist: google-auth<3.0.0,>=2.14.1
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Requires-Dist: google-cloud-core<3.0.0,>=2.4.1
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Requires-Dist: google-resumable-media<3.0.0,>=2.0.0
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Requires-Dist: packaging>=24.2.0
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Requires-Dist: python-dateutil<3.0.0,>=2.8.2
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Requires-Dist: requests<3.0.0,>=2.21.0
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Provides-Extra: all
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Requires-Dist: google-cloud-bigquery[bigquery_v2,bqstorage,geopandas,ipython,ipywidgets,opentelemetry,pandas,tqdm]; extra == "all"
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Provides-Extra: bigquery_v2
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Requires-Dist: proto-plus<2.0.0,>=1.22.3; extra == "bigquery-v2"
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Requires-Dist: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<7.0.0,>=3.20.2; extra == "bigquery-v2"
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Provides-Extra: bqstorage
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Requires-Dist: google-cloud-bigquery-storage<3.0.0,>=2.18.0; extra == "bqstorage"
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Requires-Dist: grpcio<2.0.0,>=1.47.0; extra == "bqstorage"
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Requires-Dist: pyarrow>=4.0.0; extra == "bqstorage"
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Requires-Dist: grpcio<2.0.0,>=1.49.1; python_version >= "3.11" and extra == "bqstorage"
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Provides-Extra: geopandas
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Requires-Dist: geopandas<2.0.0,>=0.9.0; extra == "geopandas"
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Requires-Dist: Shapely<3.0.0,>=1.8.4; extra == "geopandas"
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Provides-Extra: ipython
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Requires-Dist: ipython>=7.23.1; extra == "ipython"
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Requires-Dist: bigquery-magics>=0.6.0; extra == "ipython"
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Provides-Extra: ipywidgets
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Requires-Dist: ipywidgets>=7.7.1; extra == "ipywidgets"
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Requires-Dist: ipykernel>=6.2.0; extra == "ipywidgets"
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Provides-Extra: opentelemetry
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Requires-Dist: opentelemetry-api>=1.1.0; extra == "opentelemetry"
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Requires-Dist: opentelemetry-sdk>=1.1.0; extra == "opentelemetry"
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Requires-Dist: opentelemetry-instrumentation>=0.20b0; extra == "opentelemetry"
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Provides-Extra: pandas
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Requires-Dist: pandas>=1.1.4; extra == "pandas"
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Requires-Dist: pandas-gbq>=0.26.1; extra == "pandas"
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Requires-Dist: grpcio<2.0.0,>=1.47.0; extra == "pandas"
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Requires-Dist: pyarrow>=3.0.0; extra == "pandas"
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Requires-Dist: db-dtypes<2.0.0,>=1.0.4; extra == "pandas"
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Requires-Dist: grpcio<2.0.0,>=1.49.1; python_version >= "3.11" and extra == "pandas"
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Provides-Extra: tqdm
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Requires-Dist: tqdm<5.0.0,>=4.7.4; extra == "tqdm"
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Python Client for Google BigQuery
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=================================
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|GA| |pypi| |versions|
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Querying massive datasets can be time consuming and expensive without the
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right hardware and infrastructure. Google `BigQuery`_ solves this problem by
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enabling super-fast, SQL queries against append-mostly tables, using the
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processing power of Google's infrastructure.
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- `Client Library Documentation`_
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- `Product Documentation`_
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.. |GA| image:: https://img.shields.io/badge/support-GA-gold.svg
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:target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#general-availability
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.. |pypi| image:: https://img.shields.io/pypi/v/google-cloud-bigquery.svg
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:target: https://pypi.org/project/google-cloud-bigquery/
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.. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-bigquery.svg
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:target: https://pypi.org/project/google-cloud-bigquery/
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.. _BigQuery: https://cloud.google.com/bigquery/what-is-bigquery
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.. _Client Library Documentation: https://googleapis.dev/python/bigquery/latest
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.. _Product Documentation: https://cloud.google.com/bigquery/docs/reference/v2/
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Quick Start
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-----------
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In order to use this library, you first need to go through the following steps:
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1. `Select or create a Cloud Platform project.`_
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2. `Enable billing for your project.`_
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3. `Enable the Google Cloud BigQuery API.`_
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4. `Setup Authentication.`_
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.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project
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.. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project
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.. _Enable the Google Cloud BigQuery API.: https://cloud.google.com/bigquery
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.. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html
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Installation
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~~~~~~~~~~~~
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Install this library in a `virtualenv`_ using pip. `virtualenv`_ is a tool to
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create isolated Python environments. The basic problem it addresses is one of
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dependencies and versions, and indirectly permissions.
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With `virtualenv`_, it's possible to install this library without needing system
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install permissions, and without clashing with the installed system
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dependencies.
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.. _`virtualenv`: https://virtualenv.pypa.io/en/latest/
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Supported Python Versions
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^^^^^^^^^^^^^^^^^^^^^^^^^
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Python >= 3.9
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Unsupported Python Versions
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^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Python == 2.7, Python == 3.5, Python == 3.6, Python == 3.7, and Python == 3.8.
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The last version of this library compatible with Python 2.7 and 3.5 is
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`google-cloud-bigquery==1.28.0`.
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Mac/Linux
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^^^^^^^^^
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.. code-block:: console
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pip install virtualenv
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virtualenv <your-env>
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source <your-env>/bin/activate
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<your-env>/bin/pip install google-cloud-bigquery
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Windows
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^^^^^^^
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.. code-block:: console
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pip install virtualenv
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virtualenv <your-env>
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<your-env>\Scripts\activate
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<your-env>\Scripts\pip.exe install google-cloud-bigquery
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Example Usage
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-------------
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Perform a query
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~~~~~~~~~~~~~~~
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.. code:: python
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from google.cloud import bigquery
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client = bigquery.Client()
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# Perform a query.
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QUERY = (
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'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
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'WHERE state = "TX" '
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'LIMIT 100')
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query_job = client.query(QUERY) # API request
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rows = query_job.result() # Waits for query to finish
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for row in rows:
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print(row.name)
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Instrumenting With OpenTelemetry
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--------------------------------
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This application uses `OpenTelemetry`_ to output tracing data from
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API calls to BigQuery. To enable OpenTelemetry tracing in
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the BigQuery client the following PyPI packages need to be installed:
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.. _OpenTelemetry: https://opentelemetry.io
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.. code-block:: console
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pip install google-cloud-bigquery[opentelemetry] opentelemetry-exporter-gcp-trace
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After installation, OpenTelemetry can be used in the BigQuery
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client and in BigQuery jobs. First, however, an exporter must be
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specified for where the trace data will be outputted to. An
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example of this can be found here:
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.. code-block:: python
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from opentelemetry import trace
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.sdk.trace.export import BatchSpanProcessor
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from opentelemetry.exporter.cloud_trace import CloudTraceSpanExporter
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tracer_provider = TracerProvider()
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tracer_provider = BatchSpanProcessor(CloudTraceSpanExporter())
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trace.set_tracer_provider(TracerProvider())
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In this example all tracing data will be published to the Google
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`Cloud Trace`_ console. For more information on OpenTelemetry, please consult the `OpenTelemetry documentation`_.
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.. _OpenTelemetry documentation: https://opentelemetry-python.readthedocs.io
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.. _Cloud Trace: https://cloud.google.com/trace
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