Artistic Intelligence data

Data collector, query API and more to make digital art.

Check out our work at https://artisticintelligence.nl/!

Note: the Python package is named aid, because I found artistic_intelligence_data a bit too verbose.

Setting up

Python environment

This package is managed by Poetry. Install it with pip install poetry if you don't already have it. Then it's simply poetry install --with dev to set up your development environment. Using a virtual environment is recommended.

Database

This project currently uses PostgreSQL with the PostGIS and TimescaleDB extensions for storage.

I recommend setting up on a Linux environment (WSL if you're on Windows). Follow the guides:

• Basic PostgreSQL: https://www.postgresql.org/download/linux/ubuntu/ (manually configure the apt repository to get the latest version)
• PostGIS comes with the above repository, so sudo apt install postgresql-postgis should work.
• TimescaleDB: https://docs.timescale.com/self-hosted/latest/install/installation-linux/

After setting up a database and users, you can use the SQL scripts in the ddl folder to set up raw storage tables for each data source.

Developing

This project uses SCons to standardize quality steps. Remember to run scons all before you commit! This does code fixing, formatting, then quality checks. The GitHub Actions pipeline runs the same quality checks.

Configuration

The application uses python-dotenv to load environment variables from the .env file. You can also pass your own environment variables when running the application.