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README.rst

Google Cloud Datastore Python Samples

https://gstatic.com/cloudssh/images/open-btn.png

This directory contains samples for Google Cloud Datastore. Google Cloud Datastore is a NoSQL document database built for automatic scaling, high performance, and ease of application development.

Set environment variables:
GOOGLE_CLOUD_PROJECT - Google Cloud project id CLOUD_STORAGE_BUCKET - Google Cloud Storage bucket name
Roles to be set in your Service Account and App Engine default service account:
Datastore Import Export Admin, or Cloud Datastore Owner, or Owner Storage Admin, or Owner

Setup

Authentication

This sample requires you to have authentication setup. Refer to the Authentication Getting Started Guide for instructions on setting up credentials for applications.

Install Dependencies

  1. Clone python-docs-samples and change directory to the sample directory you want to use.

    $ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git

  2. Install pip and virtualenv if you do not already have them. You may want to refer to the Python Development Environment Setup Guide for Google Cloud Platform for instructions.

  3. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

    $ virtualenv env
$ source env/bin/activate

  4. Install the dependencies needed to run the samples.

    $ pip install -r requirements.txt

Samples

Quickstart

https://gstatic.com/cloudssh/images/open-btn.png

To run this sample:

$ python quickstart.py

Tasks example app

https://gstatic.com/cloudssh/images/open-btn.png

To run this sample:

$ python tasks.py

Snippets

https://gstatic.com/cloudssh/images/open-btn.png

To run this sample:

$ python snippets.py

usage: snippets.py [-h] project_id

Demonstrates datastore API operations.

positional arguments:
  project_id  Your cloud project ID.

optional arguments:
  -h, --help  show this help message and exit

The client library

This sample uses the Google Cloud Client Library for Python. You can read the documentation for more details on API usage and use GitHub to browse the source and report issues.