Aihelpdesk

This is the repository for website ....

Repositories

This project consists of the following repositories:

• A public repository on github that publishes the main branch of the above repository.
• The wagtail-helpdesk project on github contains the reusable Django wagtail-helpdesk app that comprises the main functionality of Klimaathelpdesk: asking questions, and answering, tagging, reviewing and publishing them. This package can be used to implement similar-working websites.

Requirements

The aihelpdesk.org website uses wagtail-helpdesk, which builds on wagtail, for its main functionality.

Database

We assume you have Postgres on your $PATH, for example:

PATH=$PATH:/Applications/Postgres.app/Contents/Versions/13/bin/

Create a database:

createdb aihelpdesk

Front-end build

We require:

• NodeJS (see package.json for which version)

Installation

make develop

Possibly, create a superuser by activating the virtualenv and:

./manage.py createsuperuser

Running

To start the Django server:

make run

Note that manage.py assumes the default settings file to be settings/development.py. (Production configs don't use that, see the "Deployment and environments" section below.)

Development

Development workflow

Setup your local sources

• Clone ai-helpdesk from gitlab:

git clone [email protected]:fourdigits/aihelpdesk.git

• Create default development setup:

createdb aihelpdesk
make develop

• Get data from acceptance environment and test the website:

# The fabfile is in a different branch to ensure we don't push it to the public github repo
git checkout ci-utils
fab get_data acceptance
git checkout main
make run
firefox http://localhost:8000

• Replace the pip-installed wagtail-helpdesk package with a local git checkout:

# This checks out the repository next to the ai-helpdesk repo
git clone [email protected]:fourdigits/aihelpdesk.git ../wagtail-helpdesk
pip install -e ../wagtail-helpdesk
make run

Make development changes

Changes to the ai-helpdesk repo can be handled as a regular development change.

For changes to wagtail-helpdesk:

• Run make run in the ai-helpdesk repo to get to see changes on http://localhost:8000
• Run yarn start in the wagtail-helpdesk repo to rebuild frontend files automatically, refresh the page for updates.

If you made changes to frontend files, after all files have been updated, run yarn build and commit the produced changes to the repo (yes, in the static folder).

Deploy a new version

• Create a new release for wagtail-helpdesk (if you made changes to the repo). After all changes are merged, update the version in __init__.py and create a corresponding git tag.

• Update the used version of the wagtail-helpdesk package in the website requirements if needed, and run make requirements. Commit the new requirements.

• After all other changes are done, create a development tag (x.y.zdevN) and deploy to test/acceptance. If the changes are accepted, add a production tag (x.y.z) and deploy to acceptance and production.

• Push the updated ai-helpdesk main branch to the github repo by adding an additional remote in git:

git remote add github [email protected]:fourdigits/aihelpdesk.git
git push github main
git push github --tags

Testing

Run:

make test

For more control locally:

make test PYTEST_ADDOPTS="-k test_only_this_test --pdb"

Note: You can also run pytest directly, but make test also runs Python in development mode, which provides more warnings (for example, about unclosed files).

Test coverage

Running pytest or make test will also generate a coverage report. An HTML version will be placed in htmlcov/.

The file .gitlab-ci.yml uses the generated coverage.xml to show (in the MR on Gitlab) which code changes are being hit by automatic tests, making code review easier.

Code conventions

Python

Flake-8 is enforced by the test suite.

You can configure the exceptions to ignore in setup.cfg, for example if you want change the maximum allowed line length.

You can easily fix all code convention errors with make fix-codestyle.

Frontend

Prettier is enforced for code formatting. The easiest way to apply prettier is to install a plugin for your editor and apply the formatting on save. For linting we use ESLint and Stylelint.

To check formating and linting run yarn lint and to automatically fix things (if possible) run yarn lint:fix.

Dependency management

Our dependencies are managed with pip-tools. In requirements/base.in, we pin as few packages as we can, and pip-tools generates the rest for us.

To upgrade dependencies, run:

make requirements

By default, all dependencies that can be upgraded to a newer version are automatically pinned to the newest available version.

If you only changed a pinning of a single package, or only added a new dependency, use:

make requirements UPGRADE=no

Deployment and environments

Test is deployed automatically when the main branch is updated, for acceptance and production you can use the deploy button in gitlab, available after you add a tag (and a successful build).

It's also possible to run deployment manually from you own command line with::

fab deploy production --ref=<tag/branch>