Western Australian Sea Turtles Database (WASTD)

This project is the Department of Biodiversity, Conservation and Attractions Sea Turtles Database corporate application.

Project layout / description

• wastd: the core Django project directory, containing common settings, configuration and templates.
• observations: the primary data model for the project, defining the Encounter and Observation models and subclasses.
• users: an extension of the Django contrib.auth.models.User class, customised for this project.
• wamtram2: auto-generated model classes to provide readonly ORM utility for the legacy WAMTRAM database.

The intent is for this project to replace the WAMTRAM legacy project and to act as the repository for turtle tagging data. The wamtram application was created to ease access to the legacy database, and the tagging application was created as an interim step to refactoring the legacy data into the Encounter/Observation model defined in the observations application. It is expected that wamtram will be removed after data migration, and that tagging will be removed after the data is refactored.

Installation

The recommended way to set up this project for development is using Poetry to install and manage a virtual Python environment. With Poetry installed, change into the project directory and run:

poetry install

To run Python commands in the virtualenv, thereafter run them like so:

poetry run python manage.py

Manage new or updating project dependencies with Poetry also, like so:

poetry add newpackage==1.0

Environment variables

This project uses python-dotenv to set environment variables (in a .env file). The following variables are required for the project to run:

DATABASE_URL="postgis://USER:PASSWORD@HOST:5432/DATABASE_NAME"

Variables below may also need to be defined (context-dependent):

SECRET_KEY=ThisIsASecretKey
DEBUG=True
GEOSERVER_URL=https://geoserver.url/service

Running

Use runserver to run a local copy of the application:

poetry run python manage.py runserver 0:8080

Run console commands manually:

poetry run python manage.py shell_plus

Media uploads

The production system stores media uploads in Azure blob storage. Credentials for doing so should be defined in the following environment variables:

AZURE_ACCOUNT_NAME=name
AZURE_ACCOUNT_KEY=key
AZURE_CONTAINER=container_name

To bypass this and use local media storage (for development, etc.) simply set the LOCAL_MEDIA_STORAGE=True environment variable and create a writable media directory in the project directory.

Docker image

To build a new Docker image from the Dockerfile:

docker image build -t ghcr.io/dbca-wa/wastd .

Docs

Use sphinx-build build docs locally:

poetry run sphinx-build -b html docs _build

Use http.server serve them:

poetry run python -m http.server --directory _build 8080

Pre-commit hooks

This project includes the following pre-commit hooks:

• TruffleHog (credential scanning): https://github.com/marketplace/actions/trufflehog-oss

Pre-commit hooks may have additional system dependencies to run. Optionally install pre-commit hooks locally like so:

poetry run pre-commit install

Reference: https://pre-commit.com/