tiny_python_projects
yapf
tiny_python_projects | yapf | |
---|---|---|
4 | 21 | |
1,389 | 13,663 | |
- | 0.3% | |
3.7 | 8.0 | |
2 months ago | 17 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tiny_python_projects
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Coding Programs and Sites for Learning R and Python?
My book, Mastering Python for Bioinformatics (O'Reilly, 2021), uses many biofx challenges from the Rosalind.info site, but it's not necessarily a beginner book. The most important thing I teach is the use of tests to verify that a program/function is correct (or at least behaves predictably). You can see https://github.com/kyclark/biofx_python for all the code/tests. To learn more about Python and testing, I would recommend you start with other books such at my Tiny Python Projects (Manning, 2020). Code and tests are at https://github.com/kyclark/tiny_python_projects. I recorded videos showing how to write and test all those programs at tinypythonprojects.com. Best of luck!
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AWK wildcard, is it possible?
From Clark's Tiny Python Projects (the corresponding code shared on GitHub) I learned the concept of test driven development (specific to Python, the book elected pytest for quality control) which equally can be applied for other programming languages. For me, continuous integration tests (some projects on GitHub use), or unit tests tap into this field.
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Help they’re turning me into a programmer
What the 101 beginner courses sometimes/often skip (because there isn't enough time, attendees become tired, etc) is the next level, automated testing. As an example, pytest for Python allows you to set up "a test bank" to monitor if the output of your program's result are reasonable. This then is test driven development (e.g., Clark's Tiny Python Projects).
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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).
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?
bioawk - BWK awk modified for biological data
black - The uncompromising Python code formatter
Biopython - Official git repository for Biopython (originally converted from CVS)
isort - A Python utility / library to sort imports.
biofx_python - Code for Mastering Python for Bioinformatics (O'Reilly, 2021, ISBN 9781098100889)
flake8
autopep8 - A tool that automatically formats Python code to conform to the PEP 8 style guide.
awesome-python-typing - Collection of awesome Python types, stubs, plugins, and tools to work with them.
pyright - Static Type Checker for Python
vim-sleuth - sleuth.vim: Heuristically set buffer options
pycodestyle - Simple Python style checker in one Python file
prettier - Prettier is an opinionated code formatter.