MUSE2 data analysis

Python scripts and Jupyter notebooks for analysing and visualising MUSE2 data files.

This is a Python application that uses uv for packaging and dependency management. It provides pre-commit hooks for various linters and formatters and automated tests using pytest and GitHub Actions. Pre-commit hooks are automatically kept updated with a dedicated GitHub Action, this can be removed and replaced with pre-commit.ci if using a public repo. The package version is dynamically generated from the most recent git tag using setuptools-scm.

It was developed by the Imperial College Research Software Engineering Team.

Usage

To get started:

1. Download and install uv following the instructions for your OS.

2. Activate a git repository (required for pre-commit and the package versioning with setuptools-scm):

   git init

3. Install the package and dependencies and set up the virtual environment:

   uv sync

4. Activate the virtual environment, or just preface your commands with uv run to use the virtual environment (see uv activate for more info):

   source .venv/bin/activate
   <command>

   or

   uv run <command>

5. Install the pre-commit git hooks:

   uv run pre-commit install

6. Update the pre-commit hooks

   uv run pre-commit autoupdate

7. Run the main app:

   uv run python -m muse2_data_analysis

8. Run the tests:

   uv run pytest

9. Create an initial commit (it's possible there might be some failures in pre-commit):

   git add .
   git commit -m "Initial commit"

Updating Dependencies

Use the commands uv add <package> and uv remove <package> to add or remove dependencies.

• Use the optional flag --dev to add/remove development dependencies.
• Include the optional flag --group <group-name> to add/remove dependencies from specific groups.
• These will automatically update the pyproject.toml file.

For further information, see the uv docs for managing dependencies.