https://github.com/robinklaassen/artistic-intelligence-data

Data collector, query API and more to make digital art. https://artisticintelligence.nl/
https://github.com/robinklaassen/artistic-intelligence-data

Last synced: 29 days ago
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Data collector, query API and more to make digital art. https://artisticintelligence.nl/

• Host: GitHub
• URL: https://github.com/robinklaassen/artistic-intelligence-data
• Owner: robinklaassen
• License: gpl-3.0
• Created: 2024-04-21T05:51:19.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-11-20T10:42:09.000Z (about 2 months ago)
• Last Synced: 2024-11-20T12:13:45.855Z (about 2 months ago)
• Language: Python
• Size: 473 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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.