Skip to main content

Cloud AutoML API client library

Project description

alpha pypi versions

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.

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

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

google-cloud-automl-0.6.0.tar.gz (175.5 kB view details)

Uploaded Source

Built Distribution

google_cloud_automl-0.6.0-py2.py3-none-any.whl (227.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file google-cloud-automl-0.6.0.tar.gz.

File metadata

  • Download URL: google-cloud-automl-0.6.0.tar.gz
  • Upload date:
  • Size: 175.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.0

File hashes

Hashes for google-cloud-automl-0.6.0.tar.gz
Algorithm Hash digest
SHA256 2cc9b476abcf7ca24f9693b3687c51e16c795c55c33f7e6195a20b709dbebef7
MD5 10753e29e5e972036a1946d2aec489ad
BLAKE2b-256 8b0ea9152a38eb65f7b572966327d49afa3b157ef5ab7ecd086ac2d86afbf0b8

See more details on using hashes here.

Provenance

File details

Details for the file google_cloud_automl-0.6.0-py2.py3-none-any.whl.

File metadata

  • Download URL: google_cloud_automl-0.6.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 227.7 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.0

File hashes

Hashes for google_cloud_automl-0.6.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 8a4a1b520d257bf8e8b6a02bc2c06b0226994ab896a56c42e0c2df51ce4797b4
MD5 fea2bf9f97e7f751751c819374839d88
BLAKE2b-256 35f38abefe80c1c66596a9bfad2bf7f466ef57bbbcd200f7ac438a5c16bc2dcc

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page