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Plugin-package for csspin providing Python related plugins

Project description

Latest Package Version Supported Python Versions License

csspin-python is maintained and published by CONTACT Software GmbH and serves Python-based plugins for the csspin task runner.

The following plugins are available:

  • csspin_python.behave: A plugin for running tests using Behave.

  • csspin_python.debugpy: A plugin for debugging Python code using debugpy.

  • csspin_python.devpi: A plugin for simplified usage of devpi.

  • csspin_python.pytest: A plugin for running tests using pytest.

  • csspin_python.python: A plugin for provisioning Python environments and installing dependencies.

  • csspin_python.radon: A plugin for running radon to analyze code complexity.

  • csspin_python.sphinx: A plugin for building Sphinx documentation.

  • csspin_python.playwright: A plugin for running tests using playwright. This plugin is deprecated, use the pytest plugin with the ‘pytest.playwright.enabled=true’ setting instead.

  • csspin_python.uv_provisioner: A plugin that uses uv to provision the Python environment.

The package provides an aws_auth extra, that, if enabled, can authenticate to CONTACT Software GmbH’s AWS Codeartifact. It also provides an uv extra, that is necessary for using the csspin_python.uv_provisioner plugin.

Prerequisites

csspin is available on PyPI and can be installed using pip, pipx or any other Python package manager, e.g.:

python -m pip install csspin

Using csspin-python

The csspin-python package and its plugins can be installed by defining those within the spinfile.yaml configuration file of your project.

spin:
  project_name: my_project

# To develop plugins comfortably, install the packages editable as
# follows and add the relevant plugins to the list 'plugins' below
plugin_packages:
  - csspin-python

# The list of plugins to be used for this project.
plugins:
  - csspin_python.pytest

python:
  version: 3.9.8
  requirements:
    - sphinx-click
    - sphinx-rtd-theme
    - pytest-mock

pytest:
  opts: [-m, "not slow"]
  tests: [tests]

If the spinfile.yaml is configured correctly, you can provision the project using spin provision, that will automatically create a Python virtual environment and install the required dependencies. After that, you can run tests using spin pytest and do other great things.

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