Contributing

Contributions are welcome. Here is how to get started.

Development setup

Follow the installation guide, then install docs dependencies:

pip install -e ".[docs]"

Running tests

Run all fast (unit) tests:

pytest tests/ -m "not slow"

Run everything including slow integration tests (requires the test raster under assets/ and model weights):

pytest tests/

Run a specific test file:

pytest tests/engine/test_pipeline.py

Building the docs locally

pip install -e ".[docs]"
mkdocs serve

Then open http://localhost:8000 in your browser.

Adding a new component

1. Create a config parser in canopyrs/engine/config_parsers/mycomponent.py (subclass BaseConfig), then add it to canopyrs/engine/config_parsers/__init__.py so it can be imported from the package
2. Create canopyrs/engine/components/mycomponent.py
3. Subclass BaseComponent, declare requires_state, requires_columns, produces_state, produces_columns
4. Implement __call__ with the @validate_requirements decorator
5. Register it in Pipeline.from_config() in pipeline.py
6. Add a docs entry in docs/user-guide/components.md and a new page under docs/api/components/ (then register it in mkdocs.yml nav)

Code style

• Follow existing patterns in the component files
• Keep component logic focused — I/O and state updates are the pipeline's job
• Add hints to state_hints and column_hints for helpful error messages