Various personal macOS things.

This project is managed with Hatch and uses uv for faster dependency management within Hatch environments where possible. It incorporates modern Python development practices, including linting with Ruff, type checking with Mypy, testing with Pytest, and pre-commit hooks.

.
├── .github/workflows/        # GitHub Actions CI/CD workflows
│   └── ci.yml
├── .gitignore                # Standard Python .gitignore
├── .pre-commit-config.yaml   # Configuration for pre-commit hooks
├── LICENSE                   # Project license (TODO: Verify/Choose a license)
├── README.md                 # This file
├── pyproject.toml            # Project metadata, dependencies, and tool configurations (Hatch, Ruff, Mypy, Pytest)
├── setup-macos-in-vmware.sh  # Original script (TODO: Integrate or update as needed)
├── src/                      # Source code
│   └── macos_surgery/
│       ├── __init__.py
│       └── example.py        # Example module
└── tests/                    # Test files
    ├── __init__.py
    └── test_example.py       # Tests for the example module

• Python 3.8+
• Git
• Hatch:

  pip install hatch

  It's also recommended to install uv for faster operations, which Hatch can sometimes leverage:

  pip install uv

  (Note: uv is also listed as a dev dependency in pyproject.toml, so hatch env create default will install it into the project's virtual environment.)

1. Clone the repository:

   git clone https://github.com/example-user/macos-surgery.git # TODO: Update with actual URL
   cd macos-surgery

2. Create the Hatch environment: This will create a virtual environment and install all dependencies defined in pyproject.toml (including development dependencies like Ruff, Mypy, Pytest, and pre-commit).

   hatch env create default

   If you prefer to use uv explicitly for faster environment setup after installing hatch and uv globally:

   # Ensure hatch is configured to use uv if desired (this might require global uv setup or future Hatch features)
   # For now, hatch env create will use its default installer (pip or uv if it detects and prefers it)

3. Activate the Hatch environment: To work within the project's isolated environment:

   hatch shell

   You are now inside the virtual environment with all dependencies available.

4. Install pre-commit hooks (recommended): To ensure code quality checks are run before each commit:

   # Ensure you are inside the hatch shell or have pre-commit available in your PATH
   pre-commit install

The following tools are configured:

• Ruff: For linting and formatting.
• Mypy: For static type checking.
• Pytest: For running unit tests.

You can run these checks using Hatch scripts (defined in pyproject.toml). Activate the Hatch shell (hatch shell) first.

• Lint and Format:

  hatch run lint
  # Or directly:
  # hatch run ruff check .
  # hatch run ruff format .

• Type Check:

  hatch run check
  # Or directly:
  # hatch run mypy src tests

• Run Tests:

  hatch run test
  # Or directly:
  # hatch run pytest -v

• Run Tests with Coverage:

  hatch run cov
  # Or directly:
  # hatch run pytest -v --cov=src/macos_surgery --cov-report=term-missing

• Run All Checks (Lint, Test with Coverage, Type Check):

  hatch run all-checks

  (Note: If hatch run <script_name> gives an error like "script not found", it might be due to the Hatch version or environment. In such cases, use the direct commands shown above, e.g., hatch run ruff check . instead of hatch run lint.)

To build the wheel and source distribution:

hatch build

Artifacts will be in the dist/ directory.

This project uses hatch-vcs for versioning based on Git tags. Versions are automatically derived from tags like v0.1.0 or 1.0.0.

• Verify License: The LICENSE file and pyproject.toml currently assume MIT. Please verify and update if necessary.
• Author Information: Update placeholder author name and email in pyproject.toml.
• Repository URL: Update placeholder repository URLs in pyproject.toml and this README.
• setup-macos-in-vmware.sh: Review this original script. Decide if it should be integrated into the Python package, updated, or kept separate. Its functionality is not currently part of the Python package structure.
• Codecov Token: If using Codecov for private repositories or for guaranteed uploads, set the CODECOV_TOKEN secret in your GitHub repository settings for the CI workflow.

Contributions are welcome! Please ensure that your code adheres to the linting and formatting standards (enforced by pre-commit hooks and CI) and that all tests pass.