Note
This will use a shared dataset, which means any data you save will be available to anyone. If you want to create your own dataset, follow the (pretty simple) instructions in the :doc:`datastore-getting-started`.
The source code for the library
(and demo code)
lives on GitHub,
You can install the library quickly with pip:
$ pip install gcloud
In order to run the demo, you need to have registred an actual gcloud
project and so you'll need to provide some environment variables to facilitate
authentication to your project:
GCLOUD_TESTS_PROJECT_ID: Developers Console project ID (e.g. bamboo-shift-455).GCLOUD_TESTS_DATASET_ID: The name of the dataset your tests connect to. This is typically the same asGCLOUD_TESTS_PROJECT_ID.GCLOUD_TESTS_CLIENT_EMAIL: The email for the service account you're authenticating withGCLOUD_TESTS_KEY_FILE: The path to an encrypted key file. See private key docs for explanation on how to get a private key.
Run the example script included in the package:
$ python -m gcloud.datastore.demo
And that's it! You just read and wrote a bunch of data to the Cloud Datastore.
You can interact with a demo dataset in a Python interactive shell.
Start by importing the demo module and instantiating the demo dataset:
>>> from gcloud.datastore import demo >>> dataset = demo.get_dataset()
Once you have the dataset, you can create entities and save them:
>>> dataset.query('MyExampleKind').fetch()
[<Entity{...}, ]
>>> entity = dataset.entity('Person')
>>> entity['name'] = 'Your name'
>>> entity['age'] = 25
>>> entity.save()
>>> dataset.query('Person').fetch()
[<Entity{...} {'name': 'Your name', 'age': 25}>]
Note
The get_dataset method is just a shortcut for:
>>> from gcloud import datastore >>> from gcloud.datastore import demo >>> dataset = datastore.get_dataset( >>> demo.DATASET_ID, demo.CLIENT_EMAIL, demo.PRIVATE_KEY_PATH)
Next, take a look at the :doc:`datastore-getting-started` to see how to create your own project and dataset.
And you can always check out the :doc:`datastore-api`.