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Python package PyPI version

🚧 Under Construction
This project is currently under development. Please check back later for updates.

Nightskycam Images

This is the repository for nightskycam_images, a python package for managing images captured by the camera-RaspberryPi systems of the nightskycam project. These images are managed in a filesystem.

Its functions include:

  • managing images (and related data) in a filesystem
  • generating thumbnail images
  • generating summary videos.

Requirements

  • Operating system: Linux or macOS
  • Python 3.9+

Getting Started as a User (using pip)

Dependency management with pip is easier to set up than with poetry, but the optional dependency-groups are not installable with pip.

  • Create and activate a new Python virtual environment:
    python3 -m venv --copies venv
    source venv/bin/activate
    
  • Update pip and build package:
    pip install -U pip  # optional but always advised
    pip install .       # -e option for editable mode
    

Getting Started as a Developer (using poetry)

Dependency management with poetry is required for the installation of the optional dependency-groups.

  • Install poetry.

  • Install dependencies for package (also automatically creates project's virtual environment):

    poetry install
    
  • Install dev dependency group:

    poetry install --with dev
    
  • Activate project's virtual environment:

    poetry shell
    
  • Optional: Set up pre-commit git hook (automatic isort and black formatting):

    pre-commit install
    

    The hook will now run automatically on git commit. It is not recommended, but the hook can be bypassed with the option --no-verify.

    The hook can also be manually run with:

    # Force checking all files (instead of only changed files).
    pre-commit run --all-files
    

Tests (only possible for setup with poetry, not with pip)

To install test dependency group:

poetry install --with test

To run the tests:

python -m pytest

To extract coverage data:

  • Get code coverage by measuring how much of the code is executed when running the tests:
    coverage run -m pytest
    
  • View coverage results:
    # Option 1: simple report in terminal.
    coverage report
    # Option 2: nicer HTML report.
    coverage html  # Open resulting 'htmlcov/index.html' in browser.
    

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