Cloud Spanner is the world's first fully managed relational database service to offer both strong consistency and horizontal scalability for mission-critical online transaction processing (OLTP) applications. With Cloud Spanner you enjoy all the traditional benefits of a relational database; but unlike any other relational database service, Cloud Spanner scales horizontally to hundreds or thousands of servers to handle the biggest transactional workloads.

• Client Library Documentation
• Product Documentation

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 Google Cloud Spanner API.
4. Setup Authentication.

This package provides a 3rd-party database backend for using Cloud Spanner with the Django ORM. It uses the Cloud Spanner Python client library under the hood.

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python and Django 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.

pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install python-spanner-django
<your-env>/bin/pip install google-cloud-spanner

pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install python-spanner-django
<your-env>\Scripts\pip.exe install google-cloud-spanner

At the moment, this library only supports Django 2.2. It also requires Python version 3.6 or later.

This package follows a common versioning convention for Django plugins: the major and minor version components of this package should match the installed version of Django. That is, django-google-spanner~=2.2 works with Django~=2.2.

To install from PyPI:

pip3 install django-google-spanner

To install from source:

git clone git@github.com:googleapis/python-spanner-django.git
cd python-spanner-django
pip3 install -e .

If you don't already have a Cloud Spanner database, or want to start from scratch for a new Django application, you can create a new instance and database using the Google Cloud SDK:

gcloud spanner instances create $INSTANCE --config=regional-us-central1 --description="New Django Instance" --nodes=1
gcloud spanner databases create $DB --instance $INSTANCE

This package provides a Django application named django_spanner. To use the Cloud Spanner database backend, the application needs to installed and configured:

• Add django_spanner as the first entry in INSTALLED_APPS:

  INSTALLED_APPS = [
      'django_spanner',
      ...
  ]

• Edit the DATABASES setting to point to an existing Cloud Spanner database:

  DATABASES = {
      'default': {
          'ENGINE': 'django_spanner',
          'PROJECT': '$PROJECT',
          'INSTANCE': '$INSTANCE',
          'NAME': '$DATABASE',
      }
  }

You'll need to download a service account JSON key file and point to it using an environment variable:

export GOOGLE_APPLICATION_CREDENTIALS=/path/to/keyfile.json
export GOOGLE_CLOUD_PROJECT=gcloud_project

Please run:

$ python3 manage.py migrate

and that'll take a while to run. After this you should be able to see the tables and indices created in your Cloud Spanner console.

After those migrations are completed, that will be all. Please continue on with the guides.

First you’ll need to create a user who can login to the admin site. Run the following command:

$ python3 manage.py createsuperuser

which will then produce a prompt which will allow you to create your super user

Username: admin
Email address: admin@example.com
Password: **********
Password (again): **********
Superuser created successfully.

Let’s run the server

python3 manage.py runserver

Then visit http://127.0.0.1:8000/admin/

Please follow the guides in https://docs.djangoproject.com/en/2.2/intro/tutorial02/#creating-models to create and register the model to the Django’s automatically-generated admin site.

Here is an example of how to add a row for Model Author, save it and later query it using Django

>>> author_kent = Author( first_name="Arthur", last_name="Kent", rating=Decimal("4.1"),)
>>> author_kent.save()
>>> qs1 = Author.objects.all().values("first_name", "last_name")

Contributions to this library are always welcome and highly encouraged.

See CONTRIBUTING for more information on how to get started.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See the Code of Conduct for more information.

Spanner doesn't have support for auto-generating primary key values. Therefore, django-google-spanner monkey-patches AutoField to generate a random UUID4. It generates a default using Field's default option which means AutoFields will have a value when a model instance is created. For example:

>>> ExampleModel()
>>> ExampleModel.pk
4229421414948291880

To avoid hotspotting, these IDs are not monotonically increasing. This means that sorting models by ID isn't guaranteed to return them in the order in which they were created.

Spanner does not support ON DELETE CASCADE when creating foreign-key constraints, so this is not supported in django-google-spanner.

Spanner does not support Unsigned datatypes so PositiveIntegerField and PositiveSmallIntegerField are both stored as Integer type .

This feature uses a column name that starts with an underscore (_order) which Spanner doesn't allow.

Spanner does not support it and will throw an exception. For example:

>>> ExampleModel.objects.order_by('?')
...
django.db.utils.ProgrammingError: 400 Function not found: RANDOM ... FROM
example_model ORDER BY RANDOM() ASC

There are some limitations on schema changes to consider:

• No support for renaming tables and columns;
• A column's type can't be changed;
• A table's primary key can't be altered.

Spanner requires using different functions for arithmetic depending on the column type:

• TIMESTAMP columns (DateTimeField) require TIMESTAMP_ADD or TIMESTAMP_SUB
• DATE columns (DateField) require DATE_ADD or DATE_SUB

Django does not provide ways to determine which database function to use. DatabaseOperations.combine_duration_expression() arbitrarily uses TIMESTAMP_ADD and TIMESTAMP_SUB. Therefore, if you use a DateField in a DurationField expression, you'll likely see an error such as:

"No matching signature for function TIMESTAMP\_ADD for argument types:
DATE, INTERVAL INT64 DATE\_TIME\_PART."

Spanner does not support this (#331) and will throw an error:

>>> ExampleModel.objects.update(integer=F('integer') / 2)
...
django.db.utils.ProgrammingError: 400 Value of type FLOAT64 cannot be
assigned to integer, which has type INT64 [at 1:46]\nUPDATE
example_model SET integer = (example_model.integer /...

Additions cannot include None values. For example:

>>> Book.objects.annotate(adjusted_rating=F('rating') + None)
...
google.api_core.exceptions.InvalidArgument: 400 Operands of + cannot be literal
NULL ...