django-gcloud-connectors 0.3.3

A Django library for connecting to Google Cloud Datastore from Python 3 runtimes.

Django GCloud Connectors (gcloudc)

Note: This project is now living in GitLab

The aim of this project is to create Django database connector / backend for Google Cloud.

Currently it contains a connector for the Google Cloud Datastore (Datastore in Firestore mode) but in the future it may also include a Firestore connector, or even a MemoryStore one.

This is the continuation of the Datastore connector from the Djangae project but converted to use the Cloud Datastore API on Python 3.

If you are interested in submitting a patch, please refer to CONTRIBUTING.md

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Running the tests

$ pip3 install --user tox
$ tox

Under the hood tox runs ./manage.py test. To pass down arguments to this command simply separate them with a double hyphen. e.g.

tox -e py37 -- --failfast

Automatic Cloud Datastore Emulator startup

gcloudc provides overrides for the runserver and test commands which start and stop a Cloud Datastore Emulator instance. To enable this functionality add gcloudc.commands at the beginning of your INSTALLED_APPS setting.

Release process

Release to pypi is managed by GitLab CI. To create a new release create the relevant tag and push it to the gitlab remote. But first you should do some version fiddling...

1. Update the version in setup.py to the new version by removing the 'a' suffix (most likely)
2. Commit this change
3. Run `git tag -a X.Y.Z -m "Some description"
4. Run `git push origin master && git push --tags`
5. Open setup.py again, bump to the *next* release version, use an 'a' suffix
6. Run `git commit -am "Bump to alpha version" && git push origin master`

This will trigger a pipeline that will publish the package in test.pypi.org. If that is successful, you can then manually trigger the job publish to prod pypi on the same pipeline to deploy to the official pypi registry.

Caveats

It is strongly recommended that you read the Cloud Datastore API documentation before using this ORM backend. Understanding of the Datastore vs SQL will help avoid unexpected surprises!

The Google Cloud Datastore is not your traditional SQL database, and for that reason the Datastore backend doesn't support all of the functionality of the Django ORM (although it supports the majority). Also, some things don't always work the way you'd expect. As the Datastore is a No-SQL database, anything relying on cross-table queries or aggregates is basically unsupported.

Here are some of the limitations and differences:

• We ship specialised atomic() decorators, including support for "independent" transactions
• There is no support for savepoints, nested atomic() blocks are effectively a no-op
• Django's atomic() decorators WILL NOT WORK
• No support for select_related(), although prefetch_related() works
• No support for cross-table ordering
• Only up-to 500 entities can be read or written inside an atomic() block
• No support for aggregate queries
• Queries can only contain a single inequality operation (gt, lt, lte, gte, isnull=False), and the resultset must be ordered by the field you're testing for inequality

The advantage of course is that you can build your Django application for near-infinite scalability of data, and increased uptime.