Python Client for Cloud AutoML API

The Cloud AutoML API is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs, by leveraging Google’s state-of-the-art transfer learning, and Neural Architecture Search technology.

• Client Library Documentation
• Product Documentation

Quick Start

In order to use this library, you first need to go through the following steps:

1. Select or create a Cloud Platform project.
2. Enable billing for your project.
3. Enable the Cloud AutoML API.
4. Setup Authentication.

Installation

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.

With virtualenv, it's possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.

Supported Python Versions

Python >= 3.5

Deprecated Python Versions

Python == 2.7. Python 2.7 support will be removed on January 1, 2020.

Mac/Linux

pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-automl

Windows

pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-automl

Example Usage

from google.cloud.automl_v1beta1 import PredictionServiceClient

client = PredictionServiceClient()
model_path = client.model_path('my-project-123', 'us-central', 'model-name')
payload = {...}
params = {'foo': 1}
response = client.predict(model_path, payload, params=params)

Next Steps

• Read the Client Library Documentation for Cloud AutoML API API to see other available methods on the client.
• Read the Product documentation to learn more about the product and see How-to Guides.

Making & Testing Local Changes

If you want to make changes to this library, here is how to set up your development environment:

1. Make sure you have virtualenv installed and activated as shown above.

2. Run the following one-time setup (it will be persisted in your virtualenv):

   pip install -r ../docs/requirements.txt
   pip install -U nox mock pytest

3. If you want to run all tests, you will need a billing-enabled GCP project, and a service account with access to the AutoML APIs. Note: the first time the tests run in a new project it will take a _long_ time, on the order of 2-3 hours. This is one-time setup that will be skipped in future runs.

export PROJECT_ID=<project-id> GOOGLE_APPLICATION_CREDENTIALS=</path/to/creds.json>
nox