Clone the repository
git clone git@github.com:mysociety/caps.git
cd caps
script/bootstrapYou then have two options for a local development environment, Vagrant and Docker. These instructions don't cover installing and setting up these tools.
This application makes calls to MapIt. If you plan on making more than 50 calls a day, you'll need an API key.
The first time you stand-up a local development environment, you'll need to pull down the Council, plans and emissions data and import this into the database and search index. The instructions below provide details on how to do this for each environment.
This process can take some time, and a slightly faster update process is also available.
This project contains a Docker Compose file that uses the Django development server, enables debug mode and maps the local working copy into the container for testing.
If you are using a MapIt API key, add this to your .env file, e.g.: echo 'MAPIT_API_KEY=xxxaaa111222333zzz' >> .env.
Warning running script/setup will remove all locally cached data and reset the environment to the default state!
Having rest the environment, script/setup will perform all the necessary setup steps, including loading all data. Once this has completed, you should have a functional environment.
This may take a long time to run!
Run docker-compose up. This will build an application container and stand-up this, together with PostgreSQL and Solr containers. These will run in the foreground, so you will see console output in the shell from the containers. You can stop the containers by hitting control-C. If you'd rather run in the background, add the -d switch; if you do this you can stop the environment with docker-compose down.
You can then run docker-compose exec app script/update --all to perform the initial data load. This will take a long time. Run the same command without the --all switch to run the short-cut data load.
You can rebuild the application container by running script/build. Bear in mind that when running the container in development mode, your local working copy will be included along with any local uncommitted changes.
The environment will be visible at http://localhost:8000 and the Solr admin interface at http://localhost:8983
In your Github Codespaces settings, set up the relevant secrets (mostly MAPIT_API_KEY) and give the caps repo access to this secret.
Then in the caps repo, click the code dropdown (top right), and select the codespaces tab, then create new codespace.
Once it has cloned and set up the docker configuration (it may prompt you to reload with the pylance extension, this is fine and takea a few seconds), you should have a set-up populated a recent version of the current data process.
If you have used one of the devcontainer options that doesn't use this repopulation:
script/setup-in-docker (as warned above, this takes a while).script/restore-dev-data.Once this is finished script/server will run the test server. You can access this by right clicking the 0.0.0.0:8000 link in the terminal, or follow the links in the ports page (where it can also be made public/shared to organisation).
Copy across some basic config. You may need to add a MapIt API key.
cp conf/config.py-example conf/config.pyA functional Vagrantfile is included for local development so you can create a Vagrant VM with:
vagrant upThen SSH into the VM, and run subsequent commands from inside.
vagrant sshBefore running the development server for the first time, you'll need to import the data and set up the search index:
script/update --allThis process will take some time. Once you have done a full import, you can subsequently run script/update to take a few shortcuts in future.
Then you can start the development server:
script/serverThe site will be visible at http://localhost:8000.
The Solr server interface will be visible at http://localhost:8983
If you want to update the solr schema then you'll need to edit the conf/schema.xml file and then run the script/update_solr_schema on the solr instance:
docker compose exec solr update_solr_schema
This will copy the new schema in to place and reload the core. You will then need to re-index for the changes to be useful. This will only work if you are adding to the schema, if you're altering an existing property then you should probably use the solr API to do so.
black is run for code tidying: python -m black .
This is monitored by a github action for pull requests.