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Justin's Object-Oriented Paradigms

Project description

joop

image

OOP Paradigms with an emphasis on DAO patterns, HTMX, and AlpineJS.

Features

  • HTML Components for server-side rendering.
  • Declarative DataFlow module:
  • Data model based.
  • Supports local caching of inbound & outbound data, especially via SQLite.
  • Supports fanout of outbound data to multiple sources of different varieties.
  • Ideal for IoT use cases.

Getting Started

Setting Up a Virtual Environment

It is recommended to use poetry to manage the virtual environment and dependencies. Follow these steps:

  1. Install poetry globally if it is not already installed:

    pip install poetry
    
  2. Install the Poetry Shell plugin to enable the poetry shell command:

    poetry self add poetry-plugin-shell
    
  3. Use poetry to install all dependencies (including development tools like twine):

    poetry install
    

    This will automatically create a virtual environment in the .venv folder inside the project directory, as specified in the poetry.toml file.

  4. To activate the virtual environment, use:

    poetry shell
    

Build commands

  1. Run poetry check to validate the pyproject.toml file:

    poetry check
    
  2. Build the package using python -m build:

    poetry run python -m build
    

    This will generate distribution files in the dist/ directory.

  3. Verify the distribution files using twine check:

    poetry run twine check dist/*
    

    This ensures the distribution files are ready for upload to PyPI.

Building the Documentation

To build the documentation, follow these steps:

  1. Ensure all dependencies, including development dependencies, are installed:

    poetry install --with dev
    
  2. Build the documentation using Sphinx:

    poetry run sphinx-build -b html docs/source docs/build/html
    

    The generated HTML files will be located in the docs/build/html directory.

  3. Open the documentation in your browser by navigating to:

    docs/build/html/index.html
    

Commands

For all commands, run in joop/python

To run the CLI: python -m joop.cli

For tests, run python -m unittest joop.tests (add -vvv to see output)

For coverage, run:

coverage run -m unittest joop.tests
coverage report

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