awesome-flake8-extensions
Lark
awesome-flake8-extensions | Lark | |
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4 | 35 | |
1,193 | 4,497 | |
- | 1.6% | |
6.4 | 7.5 | |
about 1 month ago | 20 days ago | |
Python | ||
GNU General Public License v3.0 or later | MIT License |
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awesome-flake8-extensions
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Ultimately we want to test our code with Flake8 and plugins to enforce a more consistent code style and to encourage best practices. When you first introduce flake8 or a new plug-in commonly you have a lot of violations that you can silence with a #noqa comment. When you first introduce a new flake8 plugin, you will likely have a lot of violations, which you silence with #noqa comments. Over time these comments will become obsolete because you fixed the. yesqa will automatically remove these unnecessary #noqa comments.
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Python toolkits
flake8 for linting along with following plugin (list of awesome plugin can be found here, but me and my teammates have selected the below one. Have linting but don't make it too hard.) flake8-black which uses black for code formatting check. flake8-isort which uses isort for separation of import in section and formatting them alphabetically. flake8-bandit which uses bandit for security linting. flake8-bugbear for finding likely bugs and design problems in your program. flake8-bugbear - Finding likely bugs and design problems in your program. pep8-naming for checking the PEP-8 naming conventions. mccabe for Ned’s script to check McCabe complexity flake8-comprehensions for writing better list/set/dict comprehensions.
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Write better Python - with some help!
In addition to this out of the box -linting, there are loads of flake8 extensions that can help you with for example switching from .format() to using f-strings or checking that your naming follows the PEP8 guidelines. For example, adding flake8-length adds line length checking to the linting.
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Standards to be aware of
And if you're using flake8, make sure to check out its plugins. Here's a good list: https://github.com/DmytroLitvinov/awesome-flake8-extensions
Lark
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Show HN: I wrote a RDBMS (SQLite clone) from scratch in pure Python
Lark supports, and recommends, writing and storing the grammar in a .lark file. We have syntax highlighting support in all major IDEs, and even in github itself. For example, here is Lark's built-in grammar for Python: https://github.com/lark-parser/lark/blob/master/lark/grammar...
You can also test grammars "live" in our online IDE: https://www.lark-parser.org/ide/
The rationale is that it's more terse and has less visual clutter than a DSL over Python, which makes it easier to read and write.
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Oops, I wrote yet another SQLAlchemy alternative (looking for contributors!)
First, let me introduce myself. My name is Erez. You may know some of the Python libraries I wrote in the past: Lark, Preql and Data-diff.
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Hey guys, have any of you tried creating your own language using Python? I'm interested in giving it a shot and was wondering if anyone has any tips or resources to recommend. Thanks in advance!
It's not super maintained but you might enjoy building something with ppci, Pure Python Compiler Infrastructure. It has some front-ends and some back-ends. There's also PeachPy for an assembler. People like using Lark for parsing, I hear.
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Is it possible to propagate higher level constructs (+, *) to the generated parse tree in an LR-style parser?
lark, a parsing library where I am somewhat involved has a really nice solution to this: Rules starting with _ are inlined in a post processing step.
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can you create your own program language in python, if yes how?
Lark is a good library to assist with this.
- Lark a Python lexer/parser library
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Create your own scripting language in Python with Sly
If I may ask, did you consider Lark, and if so, why wasn't it fit for your purposes?
- Creating a language with Python.
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Not Your Grandfather’s Perl
A grammar provides the high level constructs you need to define the "shape" of your data, and it largely takes care of the rest. Grammar libraries exist in other language (eg. lark or Parsimonius in Python) and they weren't created just to make XML parsing easier.
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Earley Parsing Explained
I made a solid attempt at an Earley parser framework of my own, but apparently to get the most reliable performance from Earley parsing you need to implement Joop Leo's improvement for right-recursive grammars, which nobody has been able to adequately explain to me. I've read Kegler's open letter to Vaillant, I've tried to read other implementations, I've even tried to beat my head against the original academic paper, but I don't have the background knowledge to make sense of it all.
What are some alternatives?
black - The uncompromising Python code formatter
pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
PLY - Python Lex-Yacc
unimport - :rocket: The ultimate linter and formatter for removing unused import statements in your code. [Moved to: https://github.com/hakancelikdev/unimport]
pydantic - Data validation using Python type hints
pep8-naming - Naming Convention checker for Python
sqlparse - A non-validating SQL parser module for Python
pyre-check - Performant type-checking for python.
Atoma - Atom, RSS and JSON feed parser for Python 3
flakes - list of flake8 plugins and their codes
Construct - Construct: Declarative data structures for python that allow symmetric parsing and building