Documentation: https://cookiecutter-cruft-poetry-tox-pre-commit-ci-cd.readthedocs.io
Source Code: https://github.com/TeoZosa/cookiecutter-cruft-poetry-tox-pre-commit-ci-cd
Example Project: https://github.com/TeoZosa/cookiecutter-cruft-poetry-tox-pre-commit-ci-cd-instance
📝 Note
Originally inspired by @cjolowicz's fantasticcookiecutter-hypermodern-python
project and eponymous Hypermodern Python article series.
A robust and extensible (nearly feature-complete), DevSecOps-centric Cookiecutter template for Python packages and/or projects with rich automated tooling for high-quality software development and maintenance, from testing and code quality to documentation and template synchronization.
Pre-configured to seamlessly run both locally and via the GitHub Actions CI/CD system to not only provide powerful guardrails and out-of-the-box audit trails, but significant quality of life improvements such as automated dependency upgrades, PR-based release notes, and many other high-level features for agile, defect-free software development.
Best of all, best practices are baked in order to provide you with the best foundation on which you can build your best work!
Table of Contents
- 🎉 Creating a New Project
- 🔗 Linking an Existing Project
- ✨ Features
- 🧑⚖️ Legal
Via cruft
(recommended):
pip install --user cruft # Install `cruft` on your path for easy access
cruft create https://github.com/TeoZosa/cookiecutter-cruft-poetry-tox-pre-commit-ci-cd
Via cookiecutter
:
pip install --user cookiecutter # Install `cookiecutter` on your path for easy access
cookiecutter gh:TeoZosa/cookiecutter-cruft-poetry-tox-pre-commit-ci-cd
Note: Cookiecutter uses gh:
as short-hand for https://github.com/
If the project was originally installed via
cookiecutter
, you must first use
cruft
to link the project with the original
template:
cruft link https://github.com/TeoZosa/cookiecutter-cruft-poetry-tox-pre-commit-ci-cd
Then/else:
cruft update
- Python packaging and dependency management with Poetry
- Project workflow orchestration
with Make
as an interface shim
- Self-documenting Makefile; just type
make
on the command line to display auto-generated documentation on available targets:
- Self-documenting Makefile; just type
self_documenting_makefile.mov
- Automated Cookiecutter template synchronization with cruft
- Test automation with Tox
- Code quality tooling automation and management with pre-commit
- Continuous integration and deployment with GitHub Actions
- [Optional] Command-line interface boilerplate with Typer
- Project-specific Docker image Dockerfile1 with production dependencies for a completely reproducible execution environment
- [Optional] Jupyter support1
- Python module to C-extension compilation (enabled by standard Python type hints)
with Mypyc
- Automatically configured for Python package builds (see the template's build.py file)
⚠️ ️ Warning
Mypyc is currently alpha software. It’s only recommended for production use cases with careful testing, and if you are willing to contribute fixes or to work around issues you will encounter.
- Static type-checking with Mypy2
- Run-time type-checking
with Typeguard
- See the Typeguard user guide for usage overview
🔥 Tip
Complementary to type-checking, function-specific input validation is another useful technique. This helps eliminate an implicit knowledge violation from hidden argument requirements:"Hidden argument requirements occur when a method signature implies a wider range of valid inputs than the method actually accepts. For example, accepting an int while only allowing numbers 1 to 10 is a hidden constraint." [1]
[1] C. Riccomini and D. Ryaboy, The Missing README: A Guide for the New Software Engineer, Paperback. No Starch Press, 2021.
- Testing
with
pytest
- Doctests
with
xdoctest
2 - Performance testing
with
pytest-benchmark
- Property-based testing with Hypothesis
- Mutation testing with mutmut
ℹ️ Info
For a good overview of how property-based testing and mutation testing work together to improve the value and quality of your tests, see this stackoverflow post and the follow-up by themutmut
author.
- Code coverage with Coverage.py
- Coverage reporting with Codecov
- Code quality:
- Code formatting:
- General file formatting:
- Unsanitary commits:
- Secrets
with
detect-secrets
- Debugger imports and py37+
breakpoint()
calls withdebug-statements
- Large files
with
check-added-large-files
- Invalid Python files
with
check-ast
- Secrets
with
- Docker image builds and pushes to Docker Hub4
- Python package uploads to PyPI and TestPyPI14
- Documentation building and hosting with Read the Docs
- Release notes (PR-based) drafting and publishing with Release Drafter
- Dependency updates
with Dependabot
- Automated Dependabot PR merging with the Dependabot Auto Merge GitHub Action4
- Project issue labels management with GitHub Labeler
- Lightweight polyglot static analysis for code quality enforcement in addition to bug and security vulnerability identification with Semgrep
- Structured logging
with
structlog-sentry-logger
(viastructlog
)- Granular control flow context logging (via call stack introspection):
- Namespaced module-specific loggers
- Function name logging
- Environment-dependent standard output stream log formatting:
- Production: JSON logs
- Development: Colorized human-readable logs, with JSON logs saved locally for retrospective analysis
- [Optional] Exception logging to Sentry with
structlog-sentry
- Granular control flow context logging (via call stack introspection):
- [Optional] Exception monitoring
with Sentry
- see: the cookiecutter's
.env
file for a detailed activation guide
- see: the cookiecutter's
- Documentation building
with Sphinx
- Rich automatic documentation from type annotations and docstrings (NumPy, Google,
etc.)
with
sphinx-autoapi
- Automated emoji shortcode conversion5
- Rich automatic documentation from type annotations and docstrings (NumPy, Google,
etc.)
with
- Docstring coverage
with
interrogate
- Automated README table of contents generation
with
markdown-toc
- Publishing to Confluence with Atlassian Confluence Builder for Sphinx
- Production service design documentation and deployment checklist templates
with Mercari's
production-readiness-checklist
- [Optional] Architecture knowledge management
with Log4brains to systematically
facilitate and record the planning process and context for each of a software system's
architectural changes that occur over time and their consequences.
- See: Documenting Architecture Decisions for an overview on Architecture Decision Records (ADR)
cookiecutter-cruft-poetry-tox-pre-commit-ci-cd is licensed under the Apache License, Version 2.0. See LICENSE for the full license text.
Footnotes
-
Conditionally rendered based on the configurations specified in the project setup phase to avoid tooling bloat ↩ ↩2 ↩3
-
Requires definitions of one or more of the below repository secrets: AUTO_MERGE_DEPENDABOT_TOKEN DOCKERHUB_TOKEN DOCKERHUB_USERNAME PYPI_TOKEN TEST_PYPI_TOKEN ↩ ↩2 ↩3
-
Custom setup steps in Sphinx configuration file for Read the Docs compatibility (see: conf.py:117-139) ↩