Suggestion for project structure/setup improvements

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#355 1 commentaire 1 réaction 0 personnes assignées Voir sur GitHub

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Évaluation

Difficulté
5/5
Temps estimé
Plus d'une semaine
Accessibilité débutants
25/100
Type d'issue
Fonctionnalité
Clarté
Plutôt claire
Activité
À l'abandon
Stack technique
python
Domaine
build-system, developer-experience, testing, tooling

Piste de recherche

No files, tests, or entry points are named. Review the current dependency, formatting, test automation, hook, lint, CI, and contribution setup, then define a focused scope and verify that development setup and documented test commands work consistently across the supported Python versions.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

kind/enhancement

I'd like to suggest an (in my opinion) improvement of the project structure/setup and the involved tooling to ease contributions and maintenance.

  1. Use Poetry for dependency management and packaging. Poetry has a number of advantages over plain pip including proper dependency resolution, built-in dependency locking, specification of dev-dependencies, a unified CLI for dependency and package management, virtual env management, etc. Poetry is used in some popular projects including, e.g., isort, diagrams, Rasa among others. I've been using Poetry since v0.12 and believe that it's the best tool available at this point for managing Python projects.
  2. Use code formatters: Black for most of the code and isort for imports. Those two are the de-facto standard code formatters for Python.
  3. Use Tox for test automation, e.g. for running the test suite against all officially supported Python versions (and if applicable against different versions of specific dependencies).
  4. Use pre-commit to run code formatters and linters before a commit to avoid erroneous commits.
  5. Optionally replace Flake8 by Pylint for more sophisticated linting. This is a matter of taste, I personally like Pylint a lot.
  6. Write a contribution guide on how to set up a development environment, how to run the test suite (against multiple Python versions), etc.

If done well, this setup has a single source of truth for all (dev-)dependencies and tool configurations for local development environments, IDEs, pre-commit hooks and CI jobs, integrates with common IDEs like VS Code out of the box (e.g. formatters can be applied when saving a file), and offers reproducible environments and builds for all contributors. I have numerous private projects set up this way, the DX is very smooth.

What do you think? I'd be happy to send a PR.

Langage dominant
Python
Étoiles
368
Forks
140
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