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Environment Variables

Default environment variables are declared in env.default. If you wish to override any of the values, you can create a local .env file in the root of the project.

The domain used to fetch static content from Network Pulse can be customized by specifying PULSE_API_DOMAIN. By default it uses

The URL for fetching static content from the Network API can be customized by specifying NETWORK_SITE_URL. By default it uses NOTE: this variable must include a protocol (such as https://)

Pipenv and Invoke commands

Pipenv pattern to run Django management commands is:

  • pipenv run python [path to] [ command] [options]

For example, you can run your development server that way:

  • pipenv run python network-api/ runserver

But it's a bit long. So instead, you can use invoke:

  • inv runserver

Invoke tasks available:

  • inv -l: list available invoke tasks
  • inv makemigrations: Creates new migration(s) for apps
  • inv migrate: Updates database schema
  • inv runserver: Start a web server
  • inv setup: Prepare your dev environment after a fresh git clone
  • inv test: Run tests
  • inv catch-up: Install dependencies and apply migrations

For management commands not covered by an invoke tasks, use inv manage [command] (example: inv manage load_fake_data). You can pass multiple arguments to inv manage by using double quotes. Ex: inv manage "load_fake_data --delete".

Generating a new set of fake model data

By default, your dev site will use production data (read only!). To load fake model data into your dev site:

  • Run inv manage load_fake_data
  • Replace NETWORK_SITE_URL value with http://localhost:8000 in your .env file.

You can empty your database and create a full new set of fake model data using the following command

  • inv manage "load_fake_data --delete"


  • pipenv run python network-api/ load_fake_data --delete

You can generate a specific set of fake model data by entering a seed value

  • inv manage "load_fake_data --delete --seed VALUE"


  • pipenv run python network-api/ load_fake_data --delete --seed VALUE

Alternatively, the seed value can be specified through the use of the RANDOM_SEED environment variable.

If a seed is not provided, a pseudorandom one will be generated and logged to the console. You can share this value with others if you need them to generate the same set of data that you have.

Landing Page and Campaign links

The load_fake_data command will output pages with the following slugs:

  • /
  • /about/
  • /styleguide/
  • /people/
  • /news/
  • /initiatives/
  • /campaigns/single-page/
  • /campaigns/multi-page/
  • /opportunity/single-page/
  • /opportunity/multi-page/
  • `/blog/post/

This list is available on review apps by clicking on DEV HELP in the menu or going to [review app url]/help.

Using a copy of the staging database for critical testing

Some development work requires testing changes against "whatever the current production database looks like", which requires having postgresql installed locally (brew install postgresql on mac; download and run the official installer for windows; if you use linux/unix, you know how to install things for your favourite flavour, so just do that for postgresql). We backport prod data to staging every week, scrubbing PII, so we'll be creating a copy of that for local testing, too.

The steps involved in cloning the database for local use are as follows:

  1. grab a copy of the staging database by running pg_dump DATABASE_URL > foundation.psql on the commandline. In this, DATABASE_URL is a placeholder, and needs to be replaced with the value found for the DATABASE_URL environment variable that is used on heroku, for the staging instance.

If you are unsure how to get to this value, or how to get to the heroku staging settings, ask someone in the engineering team.

This will take a little while, but once the operation finishes, open foundation.psql in your favourite text/code editor and take note of who the owner is by looking for the following statements:

SET search_path = public, pg_catalog;

-- Name: clean_user_data(); Type: FUNCTION; Schema: public; Owner: ...... <= we want to know this string
  1. Run createdb foundation on the command line so that you have a postgresql database to work with. If you get an error that you already have a database called foundation, either create a new database with a new name (and then use that name in the next steps) or delete the old database using dropdb foundation before issuing createdb foundation.

  2. Run psql foundation on the command line to connect to that database.

  3. Run CREATE ROLE TheOwnerNameFromTheDBdump WITH SUPERUSER; in the postgresql command line interface, making sure to have that semi-colon at the end, and making sure NOT to quote the owner name string.

  4. Run \i foundation.psql in the postgresql command line interface to import the foundation database content. Once this finishes you will have an exact copy of the production database set up for local testing.

You will now also need to update your .env file to make sure you're using this database, setting DATABASE_URL=postgres://localhost:5432/foundation.

If you need to reset this database, rerun step 2 (with dropdb foundation as first command) through 5 to get back to a clean copy of the production database.

Resolving conflicting Django migrations

AKA: What to do when someone else's migration for the same app lands before yours

  • Create a new, separate local instance of foundation per "Setup steps" above.
  • Check out your new PR branch locally.
  • Delete all your PR's migrations and commit the deletion.
  • Run inv makemigrations
  • Commit the newly generated migration.
  • Run inv migrate to verify and run new migration.
  • Push changes to your PR branch.

Running the project with live front-end reloading

  • At the root of the project you can run npm start, which will start the server as well as watch tasks for recompiling changes to JS(X) and Sass files.

This project is based on Wagtail, which is itself based on Django, so the documentation for both projects applies. If you're new to Django, Django official documentation provide a tutorial and a handful of topics and how-to guides to help you get started. If you're completely new to programming, check Django Girls tutorial.

Pipenv workflow

Checking Pipenv documentation is highly recommended if you're new to it.

Virtual environment

  • pipenv shell activates your virtual environment and automatically loads your .env. Run exit to leave it. You don't need to be in your virtual environment to run python commands: Use pipenv run python [...] instead.

Installing dependencies

  • pipenv install [package name]

After installing a package, pipenv automatically runs a pipenv lock that updates the pipfile.lock. You need to add both pipfile and pipfile.lock to your commit.

Updating dependencies

  • pipenv update --outdated to list dependencies that need to be updated,
  • pipenv update to update dependencies

If a dependency is updated, pipenv automatically runs a pipenv lock that updates the pipfile.lock. You need to add both pipfile and pipfile.lock to your commit.

Listing installed dependencies

  • pipenv graph

Overriding templates and static content

Sometimes it is necessary to override templates or static js/css/etc assets. In order to track what we changed in these files please surround your changes with:

# override: start #123
... override code here...
# override: end #123

Where #... is an issue number pointing to the issue that these changes are being made for.

Django Migrations

You need to generate a migration file when you add, remove or modify a model. Django migrations documentation is a must read on the subject.

You need to follow a special workflow described in the engineering workflow documentation if you intend to remove a field or a model, or if you want to rename or change a field type.

You can’t perform that action at this time.