Cloud AutoML API client library
Project description
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:
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-automlWindows
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-automlExample 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:
Make sure you have virtualenv installed and activated as shown above.
Run the following one-time setup (it will be persisted in your virtualenv):
pip install -r ../docs/requirements.txt pip install -U nox mock pytestIf 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>
noxRelease history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file google-cloud-automl-0.7.1.tar.gz.
File metadata
- Download URL: google-cloud-automl-0.7.1.tar.gz
- Upload date:
- Size: 222.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | fa92a77fcc79032dba756b82196a29f63a7b374379bacdb78be128e09b8abc03 |
|
| MD5 | 0b596950386dd92024d85ab716d3657b |
|
| BLAKE2b-256 | 412c4a9418a91c83c2ec571a8fe75145856d79a1ea1ff124eb0a2c9fd9df2bf5 |
Provenance
File details
Details for the file google_cloud_automl-0.7.1-py2.py3-none-any.whl.
File metadata
- Download URL: google_cloud_automl-0.7.1-py2.py3-none-any.whl
- Upload date:
- Size: 297.8 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/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 02298f54fc5812bae8083c06f0e6beeb3cad4e169fd519aee179699d0041578b |
|
| MD5 | 2cf4a000c781fb767f79bc94d0b22b54 |
|
| BLAKE2b-256 | 2211569b00b3eb4ce66d95f70f3c94f379d49eb8f34cd9dd4ba83576b9f38012 |
