Developer’s guide¶

This section contains information on how to perform various task and an overview of how our development infrastructure is set up.

Local development¶

These tasks are usually performed on an individual developer’s machine.

Run the test suite¶

The tox automation tool is used to run tests inside their own virtualenv. This way we can be sure that we know which packages are required to run the tests. By default tests are run in a sqlite database within a per-environment temporary directory. Other databases can be used by setting the DJANGO_DB_... environment variables. See Specifying the database.

$ tox

By default, tox will run the test suite using the version of Python used when we deploy and will compile a local version of the documentation. The -e flag may be used to explicitly specify an environment to run. For example, to build only the documentation:

$ tox -e doc

Note

The Travis CI job runs tox configured with a PostgreSQL database to match that deployed in production. To replicate this, either run a PostgreSQL instance on the local machine, use the Google Cloud SQL proxy or run the tests via docker-compose.

tox environments¶

The following tox environments are available.

py36: Run by default. Launch the test suite under Python 3.6. Generate a code-coverage report and display a summary coverage report.
doc: Run by default. Build documentation and write it to the build/doc/ directory.
flake8: Run by default. Check for code-style violations using the flake8 linter.
collectstatic: Collect static files used by Django to the build/static/ directory.
makemigrations: Run the “makemigrations” Django command to examine models for changes. Useful if you don’t have a virtualenv set up in your local environment.

Run the development server¶

Django comes with a development web server which can be run via:

$ python manage.py runserver 0.0.0.0:8080

The server should now be browsable at http://localhost:8080/.

Building the documentation¶

This documentation may be built using the “doc” tox environment.

Docker images¶

The application is deployed using Docker containers on the Google Container Engine. Usually one can just use the local development server to develop the application but occasionally one needs to test the container or make use of the same PostgreSQL database which is used in production.

Running a development server within the container¶

There is a docker-compose file at the top-level of the iarbackend repository which contains configuration allowing the application container to be launched in a development mode. In this mode the application repository is mounted read-only as a volume within the container over the top of the application code so changes are reflected within the container without need to rebuild it.

The local repository is mounted read-only because any files written by the application will appear in the local repository as a root-owned file which can be troublesome.

Before you bring the development server container up, run an initial database migration:

$ docker-compose run --rm migrate

To run the development server:

$ docker-compose up devserver

This makes use of the iarbackend.settings.developer settings, launches a PostgreSQL container for the development server and a MailHog server to monitor outgoing email. The web app is available at http://localhost:8080/ and the MailHog instance at http://localhost:8025/.

Note

If the requirements.txt file is modified, you’ll need to re-build the container image via docker-compose build.

Occasionally, it is useful to get an interactive Python shell which is set up to be able to import the application code and to make database queries, etc. You can launch such a shell via:

$ docker-compose run --rm shell

Running tests within the container¶

The test-suite can be run within the container using a PostgreSQL database in the following way:

$ docker-compose run --rm tox

Additional options can be passed to tox by appending them to the command. E.g.

$ docker-compose run --rm tox -e doc

Output generated by tox is persisted into a volume called “tox-data”. See the docker-compose configuration for the specifics.

Using an external OAuth2 endpoint¶

If the IAR_USE_EXPERIMENTAL_OAUTH2_ENDPOINT environment variable is set then the server brought up with docker-compose up devserver will use the deployed OAuth2 server for authorisation. In this case you must specify the client id and client secret for the backend:

$ export IAR_USE_EXPERIMENTAL_OAUTH2_ENDPOINT=1
$ export IAR_CLIENT_ID="<iar-backend-client-id>"
$ export IAR_CLIENT_SECRET="<iar-backend-client-secret>"
$ docker-compose up devserver

Cloud infrastructure¶

This section provides a brief outline of cloud infrastructure for development.

Source control¶

The source code is hosted on GitHub at https://github.com/uisautomation/django-boilerplate. The repository has master set up to be writeable only via pull request. It is intended that local development happens in personal forks and is merged via pull request. The main rationale for this is a) it guards against accidentally git push-ing the wrong branch and b) it reduces the number of “dangling” branches in the main repository.

Unit tests¶

The project is set up on Travis CI to automatically run unit tests and build documentation on each commit to a branch and on each pull request.

Note

By logging into Travis CI via GitHub, you can enable Travis CI for your personal fork. This is highly recommended as you’ll get rapid feedback via email if you push a commit to a branch which does not pass the test suite.

In order to better match production, Travis CI is set up to run unit tests using the PostgreSQL database and not sqlite. If you only run unit tests locally with sqlite then it is possible that some tests may fail.

Code-coverage¶

Going to CodeCov, logging in with GitHub and adding the django-boilerplate repository will start code coverage reporting on pull-requests.

Documentation¶

Travis CI has been set up so that when the master branch is built, the documentation is deployed to https://uisautomation.github.io/django-boilerplate via GitHub pages. The UIS robot machine account’s personal token is set up in Travis via the GITHUB_TOKEN environment variable.

Code-style¶

The tox test runner will automatically check the code with flake8 to ensure PEP8 compliance. Sometimes, however, rules are made to be broken and so you may find yourself needing to use the noqa in-line comment mechanism to silence individual errors.

To run the flake8 tests manually, specify the tox environment:

$ tox -e flake8

Documentation¶

This documentation is re-built on each commit to master by Travis and posted to GitHub pages at https://uisautomation.github.io/django-boilerplate/.