BioSys - Biological Survey Database System

BioSys is a biological survey database system for Science and Conservation Division within the Department of Parks and Wildlife.

GitHub: BioSys

Getting Started

Biosys is built on Django, the Python web framework and also requires a PostgreSQL database server (9.3+) with the PostGIS extension.

It is recommended that the system is run in a Python virtual environment to allow the dependent libraries to be installed without possible collisions with other versions of the same libraries.

Using Docker to take the app for a test-drive

Note: this Docker configuration is not production-ready. It is a super-quick way to get hands on with Biosys though.

Using Docker can help you get up and running quicker. To use this method, you'll need both Docker and docker-compose installed.

First, we need to build the Docker image of the biosys app:

docker build -t dbca-wa/biosys .

Then we can start a stack that includes the app and a database:

docker-compose up

We need to wait ~15 seconds while the database schema is created and a superuser is created for us. Once that's done, you'll be able to access the UI at http://localhost:8080/ and login with username=admin and password=admin.

To clean up, you need to stop the running docker-compose stack using <ctrl>+c. Beware that the next step will permanently delete any data you created in the app. Then we can delete the stopped containers with:

docker-compose rm -f

A note about postgres race condition: Starting the docker-compose stack starts the database (postgres) and the app at the same time. Postgres needs to perform some startup steps before it's ready for a connection and we need the app to wait for this. At the moment it's done (badly) with a sleep. If you find that postgres starts slowly on your machine, edit the docker-compose.yml file and uncomment the services.biosys.command line and increase seconds if necessary.

Requirements

Supporting Applications / Packages:

• PostgreSQL (>=9.3)
• PostGIS extension (>=2.1)
• GDAL (>=1.10)

Python Libraries

Python library requirements should be installed using pip:

pip install -r requirements.txt

Environment settings

The following environment settings should be defined in a .env file (set at runtime by django-confy). Typical required settings (adjust to suit):

DEBUG=True
DATABASE_URL="postgis://USER:PASSWORD@HOST:PORT/DBNAME"
SECRET_KEY="ThisIsASecretKey"
ALLOWED_DOMAINS=localhost,hostname,.some.other.domain

Running

Start the application on port 8080:

python manage.py runserver 0.0.0.0:8080

Testing

To run unit tests or generate test coverage reports:

python manage.py test -k -v2
coverage run --source='.' manage.py test -k -v2
coverage report -m

AWS Elastic Beanstalk deployment

This project is set for Elastic Beanstalk deployment through the .elasticbeanstalk dir with the .ebextensions\* environment configuration. Note: the deployment is set tu use the 3.6 eb platform.

You have to install the eb cli: pip install awsebcli Note: It is recommended to install the eb cli in a different virtual env than the project.

You have to have the right credentials set for you AWS account. (~/.aws/credentials)

Example of how to create an environment:

# create a environment with a load balancer with 2 EC2 + a postgres RDS micro
eb create --scale 2 -db -db.engine postgres -db.i db.t2.micro
# same as above with no load balancer (single instance)
eb create --single -db -db.engine postgres -db.i db.t2.micro

Check environment

eb status

Deploy :

    # example: deploy on staging
    eb deploy eb-biosys-staging