google-cloud-automl
Google Cloud Automl API client library
Decision gist · record as of 2026-08-14
Yes. This is the official, actively maintained client for a Google-managed ML service. Install it if you're building on Google Cloud and need to programmatically train or deploy custom models. Low install friction, permissive license, no vulnerabilities, and recent maintenance make it a straightforward dependency. Prerequisite: you must have a Google Cloud project with AutoML enabled and proper authentication configured.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Requires Google Cloud project setup, billing enabled, Cloud AutoML service enabled, and authentication credentials configured.
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing use in commercial and open-source projects with minimal restrictions beyond attribution and liability disclaimers.
last release 2026-06-03 (72 days) · last repo commit 2026-08-14 · 5,371 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 76,019,197 downloads/mo, #446 on PyPI
Alternatives
Verify before relying
pip install google-cloud-automl
from google.cloud import automl_v1
client = automl_v1.AutoMlClient()
# Use client to interact with Cloud AutoML service- Specific AutoML capabilities supported (image classification, text, tabular, etc.) beyond the generic client library interface
- Whether the library supports all current Cloud AutoML API versions or has version constraints
- Real-world latency and throughput characteristics for model training and prediction workflows
What it is and what it does
google-cloud-automl is the official Python client for Google Cloud's AutoML service, a managed machine learning platform that abstracts away much of the complexity of building custom models. It provides programmatic access to train, evaluate, and deploy models for image classification, text analysis, tabular data, and other tasks without requiring deep machine learning expertise. The library handles authentication, RPC communication, and data serialization through dependencies on google-api-core, google-auth, grpcio, proto-plus, and protobuf.
Developers use this library to integrate AutoML workflows into Python applications—submitting training jobs, monitoring progress, retrieving predictions, and managing deployed models. It's designed for teams building applications that need custom ML capabilities but prefer managed infrastructure over building and maintaining their own training pipelines. The library is actively maintained, supports current Python versions (3.10+), and carries no known security vulnerabilities.
Use it for
- Build and deploy custom image classification models for product categorization or quality inspection without training infrastructure
- Train text classification or entity extraction models for document processing or content moderation workflows
- Create predictive models on tabular business data (sales forecasting, churn prediction) through a managed API
- Integrate model training and inference into production applications that need to adapt to new data over time
- Prototype ML solutions quickly without managing GPUs, distributed training, or hyperparameter tuning infrastructure
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is the official, actively maintained client for a Google-managed ML service. Install it if you're building on Google Cloud and need to programmatically train or deploy custom models. Low install friction, permissive license, no vulnerabilities, and recent maintenance make it a straightforward dependency. Prerequisite: you must have a Google Cloud project with AutoML enabled and proper authentication configured.
Install
google-cloud-automl on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained with a recent release (72 days ago) and ongoing repository activity. Depends on standard Google Cloud authentication and protocol libraries.
Requires Python 3.10 or later. Requires Google Cloud project setup, billing enabled, Cloud AutoML service enabled, and authentication credentials configured.
License in practice
Licensed under Apache-2.0 (permissive), allowing use in commercial and open-source projects with minimal restrictions beyond attribution and liability disclaimers.
Quickstart
pip install google-cloud-automl
from google.cloud import automl_v1
client = automl_v1.AutoMlClient()
# Use client to interact with Cloud AutoML serviceVerify before relying
- Specific AutoML capabilities supported (image classification, text, tabular, etc.) beyond the generic client library interface
- Whether the library supports all current Cloud AutoML API versions or has version constraints
- Real-world latency and throughput characteristics for model training and prediction workflows
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesgoogle-api-coregoogle-authgrpcioproto-plusprotobuf |
| Maintenance | Actively maintained 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 76,019,197 / month, #446 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Internet |
Evidence: google_cloud_automl-2.20.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “google cloud automl client”
- google-cloud-automlPython client library for Google Cloud AutoML, enabling programmatic…
- google-cloud-pipeline-componentsProvides predefined Kubeflow Pipelines components for Google Cloud…
- pyglovePyGlove provides symbolic object-oriented programming for Python,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Internet packages
Botocore provides low-level, data-driven access to Amazon Web Services APIs, serving as the foundation for the AWS CLI and boto3 libraries.
Install it if you need programmatic access to AWS services.
Provides an async client for AWS services using botocore and aiohttp, allowing you to call AWS APIs asynchronously within asyncio-based applications.
Install it if you need to call AWS services from async Python code; it is the standard way to do so.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides a platform-independent file locking mechanism to coordinate access to files across processes and threads.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides common Protocol Buffer message definitions used across Google Cloud APIs, enabling Python clients to interact with Google services.
See also google-cloud-documentai · google-cloud-functions · google-cloud-run · google-cloud-workflows · google-cloud-deploy · google-cloud-language · google-cloud-dataflow-client · google-cloud-build · google-cloud-vision · google-cloud-modelarmor