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 

1. 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