mccabe
yapf
mccabe | yapf | |
---|---|---|
5 | 21 | |
625 | 13,655 | |
0.0% | 0.3% | |
2.1 | 8.0 | |
5 months ago | 10 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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mccabe
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Python toolkits
mccabe for Ned’s script to check McCabe complexity
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Why do people use multiple scripts when programming in Python?
Cyclomatic Complexity is a metric used to determine the stability of your code. It basically boils down to the more code you have the more problems that can arise in said code. There are even modules for python to check your cyclomatic complexity. It goes hand in hand with separating your code out into modules. I work for a FAANG company and we usually want to keep our cyclomatic complexity less than 10 with that tool above.
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How to Audit the Quality of Your Python Code: A Step-by-Step Guide (Checklist Inside)
Mccabe—a Python complexity checker;
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Pybudget: A Solution to My Small-Brain Financial Decisions
A more advanced best practice would be separating different functions of your code into different files to keep Cyclomatic Complexity low. More code usually = more problems can be in said code. There’s even a tool you can use to determine how complex your code is called mccabe. Lower is better with that
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Code Quality Tools in Python
Flake8: a combination of following linters: PyFlakes, pycodestyle, Ned Batchelder’s McCabe script
yapf
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Enhance Your Project Quality with These Top Python Libraries
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.
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Why is Prettier rock solid?
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
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
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.
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Front page news headline scraping data engineering project
Use yapf to format code -> https://github.com/google/yapf
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Confused by Google's docstring "Attributes" section.
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.
- Alternate python spacing.
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Not sure if this is the worst or most genius indentation I've seen
https://github.com/google/yapf has configs, do ctrl+f SPLIT_COMPLEX_COMPREHENSION in the readme
- Google Python Style Guide
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Enable hyphenation only for code blocks
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).
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3 popular Python style guides that will help your team write better code
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.
What are some alternatives?
pylama - Code audit tool for python.
black - The uncompromising Python code formatter
flake8-length - Flake8 plugin for a smart line length validation.
isort - A Python utility / library to sort imports.
autopep8 - A tool that automatically formats Python code to conform to the PEP 8 style guide.
flake8
pyflakes - A simple program which checks Python source files for errors
awesome-python-typing - Collection of awesome Python types, stubs, plugins, and tools to work with them.
pybudget - This is a python script that will determine a budget for your current pay period.
pyright - Static Type Checker for Python