autoflake VS yapf

Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.

Ruff can be used to replace Flake8 (plus dozens of plugins), isort, pydocstyle, yesqa, eradicate, pyupgrade, and autoflake, all while executing tens or hundreds of times faster than any individual tool.

Having unused imports in a Python file is a prevalent issue, with a very easy solution: autoflake. Running it over your files will remove any unused imports in place.

cleanimports: runs isort and removes unused imports with Autoflake. Be sure to set up profile=black in isort settings to avoid conflicts with Black.

We use isort[0] for this. It even has a "black" compatible profile that line spits along black's defaults. Additionally we use autoflake[1] to remove unused import statements in place.

[0](https://github.com/PyCQA/isort)

[1](https://github.com/PyCQA/autoflake)

yaml repos: - repo: https://github.com/myint/autoflake rev: v1.4 hooks: - id: autoflake args: - --in-place - --remove-all-unused-imports - --expand-star-imports - --remove-duplicate-keys - --remove-unused-variables - repo: https://github.com/asottile/pyupgrade rev: v2.29.0 hooks: - id: pyupgrade args: [--py36-plus] - repo: https://github.com/PyCQA/isort rev: 5.9.3 hooks: - id: isort - repo: https://github.com/psf/black rev: 21.10b0 hooks: - id: black args: [--safe, --quiet] - repo: https://github.com/PyCQA/flake8 rev: 4.0.1 hooks: - id: flake8 - repo: local hooks: - id: pylint name: pylint entry: pylint language: system types: [python] args: [ "-rn", "-sn", ] - repo: https://github.com/pre-commit/mirrors-mypy rev: v0.910-1 hooks: - id: mypy name: mypy entry: mypy language: python types: [python] args: [] require_serial: true - repo: https://github.com/pre-commit/mirrors-prettier rev: v2.4.1 hooks: - id: prettier args: [--prose-wrap=always, --print-width=88]

autoflake 400+⭐️

YAPF (Yet Another Python Formatter): YAPF takes a different approach in that it’s based off of ‘clang-format’, a popular formatter for C++ code. YAPF reformats Python code so that it conforms to the style guide and looks good.

I think I agree about the testing and labor of complicated translation rules.

But it doesn't appear that almost every pretty printer uses the Wadler pretty printing paper. It seems like MOST of them don't?

e.g. clang-format is one of the biggest and best, and it has a model that includes "unwrapped lines", a "layouter", a line break cost function, exhaustive search with memoization, and Dijikstra's algorithm:

https://llvm.org/devmtg/2013-04/jasper-slides.pdf

The YAPF Python formatter is based on this same algorithm - https://github.com/google/yapf

The Dart formatter used a model of "chunks, rules, and spans"

https://journal.stuffwithstuff.com/2015/09/08/the-hardest-pr...

It almost seems like there are 2 camps -- the functional algorithms for functional/expression-based languages, and other algorithms for more statement-based languages.

Though I guess Prettier/JavaScript falls on the functional side.

I just ran across this survey on lobste.rs and it seems to cover the functional pretty printing languages influenced by Wadler, but functional style, but not the other kind of formatter ("Google" formatters perhaps)

https://arxiv.org/pdf/2310.01530.pdf

To get all your code into a consistent format the next step is to run a formatter. I recommend black, the well-known uncompromising code formatter, which is the most popular choice. Alternatives to black are autoflake, prettier and yapf, if you do not agree with blacks constraints.

Use yapf to format code -> https://github.com/google/yapf

Google is surprisingly rigorous when it comes to code formatting. I have been a software engineer at Amazon and it was nothing like what the book says happens at Google. So the conventions you see for python docstring formatting are primarily designed to integrate with Google's internal tooling. By using docstrings following the Google conventions, you will ultimately end up with automated documentation and other fancy automated things (like type checking which they did in the docstring before there were type hints). Also notably, Google has an open source python formatting tool that they use internally called YAPF (which stands for "Yet Another Python Formatter". So if you really want to go all-in on Google python style, grab that, too.

https://github.com/google/yapf has configs, do ctrl+f SPLIT_COMPLEX_COMPREHENSION in the readme

Only as recommendation: If the lines of the source code (here: you C code you aim to document) are kept short, in manageable bytes (similar to entries parser.add_argument in Clark's "Tiny Python Projects", example seldomly pass beyond the frequently recommended threshold of 80 characters/line), reporting with listings becomes easier (equally, the reading of the difference logs/views by git and vimdiff), than with lines of say 120 characters per line. Though we no longer are constrained to 80 characters per line by terminals/screens and punch cards (when Fortran still was FORTRAN), this is a reason e.g., yapf for Python allows you to choose between 4 spaces/indentation (PEP8 style), or 2 spaces/indentation (Google style).

There is also a formatter for Python files called yapf that your team can use to avoid arguing over formatting conventions. Plus, Google also provides a settings file for Vim, noting that the default settings should be enough if you're using Emacs.