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Google Cloud Python Client

Python idiomatic clients for Google Cloud Platform services.

Stability levels

The development status classifier on PyPI indicates the current stability of a package.

General Availability

GA (general availability) indicates that the client library for a particular service is stable, and that the code surface will not change in backwards-incompatible ways unless absolutely necessary (e.g., due to critical security issues) or with an extensive deprecation period. Issues and requests against GA libraries are addressed with the highest priority.

GA libraries have a development status classifier of Development Status :: 5 - Production/Stable.

Note

Sub-components of GA libraries explicitly marked as beta in the import path (e.g., google.cloud.language_v1beta2) should be considered beta.

Beta Support

Beta indicates that the client library for a particular service is mostly stable and is being prepared for release. Issues and requests against beta libraries are addressed with a higher priority.

Beta libraries have a development status classifier of Development Status :: 4 - Beta.

Alpha Support

Alpha indicates that the client library for a particular service is still a work-in-progress and is more likely to receive backwards-incompatible updates. See `versioning`_ for more details.

Alpha libraries have a development status classifier of Development Status :: 3 - Alpha.

If you need support for other Google APIs, check out the Google APIs Python Client library.

Libraries

Client Release Level Version
AI Platform |stable| PyPI-google-cloud-aiplatform
App Engine Admin |stable| PyPI-google-cloud-appengine-admin
Asset Inventory |stable| PyPI-google-cloud-asset
AutoML |stable| PyPI-google-cloud-automl
BigQuery |stable| PyPI-google-cloud-bigquery
BigQuery Storage |stable| PyPI-google-cloud-bigquery-storage
Bigtable |stable| PyPI-google-cloud-bigtable
Binary Authorization |stable| PyPI-google-cloud-binary-authorization
Build |stable| PyPI-google-cloud-build
Common |stable| PyPI-google-cloud-common
Compute Engine |stable| PyPI-google-cloud-compute
Container Analysis |stable| PyPI-google-cloud-containeranalysis
Datastore |stable| PyPI-google-cloud-datastore
Filestore |stable| PyPI-google-cloud-filestore
Firestore |stable| PyPI-google-cloud-firestore
GKE Hub |stable| PyPI-google-cloud-gke-hub
Grafeas |stable| PyPI-grafeas
Identity and Access Management |stable| PyPI-grpc-google-iam-v1
Key Management Service |stable| PyPI-google-cloud-kms
Logging |stable| PyPI-google-cloud-logging
Monitoring Dashboards |stable| PyPI-google-cloud-monitoring-dashboards
NDB Client Library for Datastore |stable| PyPI-google-cloud-ndb
OS Login |stable| PyPI-google-cloud-os-login
Pandas Data Types for SQL systems (BigQuery, Spanner) |stable| PyPI-db-dtypes
Pub/Sub |stable| PyPI-google-cloud-pubsub
Pub/Sub Lite |stable| PyPI-google-cloud-pubsublite
Service Management |stable| PyPI-google-cloud-service-management
Spanner |stable| PyPI-google-cloud-spanner
Spanner Django |stable| PyPI-django-google-spanner
Speech |stable| PyPI-google-cloud-speech
Stackdriver Monitoring |stable| PyPI-google-cloud-monitoring
Storage |stable| PyPI-google-cloud-storage
Trace |stable| PyPI-google-cloud-trace
Translation |stable| PyPI-google-cloud-translate
Vision |stable| PyPI-google-cloud-vision
A unified Python API in BigQuery |preview| PyPI-bigframes
Analytics Admin |preview| PyPI-google-analytics-admin
Analytics Data |preview| PyPI-google-analytics-data
Audit Log |preview| PyPI-google-cloud-audit-log
BigQuery connector for pandas |preview| PyPI-pandas-gbq
DNS |preview| PyPI-google-cloud-dns
Dataflow |preview| PyPI-google-cloud-dataflow-client
Document AI Toolbox |preview| PyPI-google-cloud-documentai-toolbox
Error Reporting |preview| PyPI-google-cloud-error-reporting
Run |preview| PyPI-google-cloud-run
Runtime Configurator |preview| PyPI-google-cloud-runtimeconfig
SQLAlchemy dialect for BigQuery |preview| PyPI-sqlalchemy-bigquery

Introduction

Google Cloud Platform (GCP) offers a wide array of services for building, deploying, and managing applications and services. The Google Cloud Python Client provides Python idiomatic clients for various GCP services, making it easier for developers to integrate GCP into their Python applications.

Stability Levels

The Google Cloud Python Client libraries are classified into different stability levels to indicate their current status and support level:

  • GA (General Availability): Libraries marked as GA are considered stable, with no expected backwards-incompatible changes unless absolutely necessary. They receive the highest priority for issue resolution and support.
  • Beta Support: Beta libraries are mostly stable but are still undergoing final testing and refinement before their official release. Issues and requests against beta libraries are addressed with a higher priority compared to alpha libraries.
  • Alpha Support: Alpha libraries are still in active development and are more likely to undergo backwards-incompatible updates. They are considered works-in-progress and are suitable for experimentation but not recommended for production use.

Libraries

The Google Cloud Python Client includes libraries for various GCP services. Here are some of the key libraries available:

  • AI Platform: Provides Python clients for working with Google Cloud AI Platform.
  • App Engine Admin: Allows managing Google App Engine applications programmatically.
  • Asset Inventory: Offers Python clients for accessing the Asset Inventory API.
  • AutoML: Provides Python idiomatic clients for Google Cloud AutoML.
  • BigQuery: Includes Python clients for working with Google BigQuery.
  • BigQuery Storage: Provides Python clients for accessing BigQuery Storage.
  • Bigtable: Allows interacting with Google Cloud Bigtable using Python.
  • Binary Authorization: Offers Python clients for the Binary Authorization API.
  • Build: Provides Python clients for Google Cloud Build.
  • Common: Contains common utilities and tools used across multiple Google Cloud services.
  • Compute Engine: Offers Python clients for managing Google Compute Engine resources.
  • Container Analysis: Provides Python clients for the Container Analysis API.
  • Datastore: Includes Python clients for working with Google Cloud Datastore.
  • Filestore: Allows interacting with Google Cloud Filestore using Python.
  • Firestore: Provides Python clients for Google Cloud Firestore.
  • GKE Hub: Offers Python clients for the GKE Hub API.
  • Grafeas: Provides Python clients for interacting with the Grafeas API.
  • Identity and Access Management: Allows managing IAM policies and permissions programmatically.
  • Key Management Service: Provides Python clients for Google Cloud Key Management Service.
  • Logging: Includes Python clients for accessing and managing Google Cloud Logging.
  • Monitoring Dashboards: Provides Python clients for working with Google Cloud Monitoring Dashboards.
  • NDB Client Library for Datastore: Offers an NDB client library for Google Cloud Datastore.
  • OS Login: Allows managing OS login configurations programmatically.
  • Pandas Data Types for SQL systems: Provides pandas data types for SQL systems like BigQuery and Spanner.
  • Pub/Sub: Includes Python clients for Google Cloud Pub/Sub.
  • Pub/Sub Lite: Provides Python clients for Google Cloud Pub/Sub Lite.
  • Service Management: Allows managing Google Cloud services programmatically.
  • Spanner: Includes Python clients for Google Cloud Spanner.
  • Spanner Django: Offers Django integration with Google Cloud Spanner.
  • Speech: Provides Python clients for Google Cloud Speech-to-Text and Text-to-Speech.
  • Stackdriver Monitoring: Includes Python clients for Stackdriver Monitoring.
  • Storage: Offers Python clients for working with Google Cloud Storage.
  • Trace: Provides Python clients for Google Cloud Trace.
  • Translation: Includes Python clients for Google Cloud Translation.
  • Vision: Provides Python clients for Google Cloud Vision.
  • BigQuery Dataframes: Offers a unified Python API for working with BigQuery.
  • Analytics Admin: Provides Python clients for Google Analytics Admin API.
  • Analytics Data: Offers Python clients for Google Analytics Data API.
  • Audit Log: Provides Python clients for accessing Google Cloud Audit Logs.
  • BigQuery connector for pandas: Allows using pandas with BigQuery.
  • DNS: Offers Python clients for working with Google Cloud DNS.
  • Dataflow: Provides Python clients for Google Cloud Dataflow.
  • Document AI Toolbox: Includes Python clients for Google Cloud Document AI Toolbox.
  • Error Reporting: Provides Python clients for Google Cloud Error Reporting.
  • Run: Allows interacting with Google Cloud Run using Python.
  • Runtime Configurator: Provides Python clients for Google Cloud Runtime Configurator.
  • SQLAlchemy dialect for BigQuery: Allows using SQLAlchemy with BigQuery.

Each library has its own GitHub repository where you can find detailed documentation, examples, and installation instructions.

Conclusion

The Google Cloud Python Client libraries offer a convenient way to interact with various Google Cloud services using Python. Whether you're working with data analytics, machine learning, or cloud infrastructure, these libraries provide a Pythonic interface to access GCP services efficiently. Choose the appropriate library based on your project's requirements and start building scalable and reliable applications on Google Cloud Platform.

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