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https://github.com/dbca-wa/wastd

Western Australian Sea Turtle and Strandings Database
https://github.com/dbca-wa/wastd

biodiversity conservation-bio marine-species marine-turtles marine-wildlife-incidents strandings

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Western Australian Sea Turtle and Strandings Database

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README 

        
# 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](https://python-poetry.org/docs/) 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



# 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/