MPI-IS/nightskycam-images

under construction

🚧 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.