Python Workflow for internal proprietary project.
Project description
Welcome to pywf_internal_proprietary Documentation
pywf_open_source streamlines open source Python project development by providing a unified workflow automation framework. It eliminates the cognitive overhead of switching between projects by normalizing common development tasks through a consistent interface.
The library automates common operations for projects using:
A public GitHub repo to host your project.
Use poetry to manage your project dependencies and build distribution package.
Use pytest unit test framework for testing.
Use GitHub Actions to run your test.
Use Codecov.io to publish your test coverage result.
Use sphinx-doc to build your documentation website.
A private CloudFlare Pages project that requires email login to host your documentation website.
A private AWS S3 Bucket to store your historical versioned document site as a record.
Use twine to publish your package to AWS CodeArtifact.
Use AWS CodeArtifact to publish your package.
Use GitHub Release to track your historical assets.
It assumes the following code folder structure:
.github/workflows/main.yml # GitHub Actions CI/CD configuration file
${package_name}/
${package_name}/__init__.py
${package_name}/*.py
docs/
docs/source # documentation source folder
docs/source/conf.py # sphinx doc configuration file
tests/ # unit test folder
bin/ # development workflow automation scripts
bin/pywf.py
bin/s01_....py
bin/s02_....py
bin/...
Makefile # makefile for automation
.coveragerc # code coverage test configuration file
codecov.yml # code coverage CI rules configuration file
pyproject.toml # Python project configuration file, no setup.py
Project Maintainer Note
This project follows the best practice mentioned in THIS DOCUMENT.
Seed Repository (Private Git Repo to simulate internal proprietary project): cookiecutter_pywf_internal_proprietary_demo-project
Automation Library: pywf_internal_proprietary-project
Cookiecutter Template: cookiecutter-pywf_internal_proprietary
Install
pywf_internal_proprietary is released on PyPI, so all you need is to:
$ pip install pywf-internal-proprietary
To upgrade to latest version:
$ pip install --upgrade pywf-internal-proprietary
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