django-stubs
returns
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django-stubs | returns | |
---|---|---|
7 | 20 | |
1,436 | 3,226 | |
3.3% | 3.9% | |
9.6 | 9.1 | |
2 days ago | 1 day ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
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.
django-stubs
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Mypy 1.6 Released
Pyright doesn't work with Django, as Django's so dynamic that it requires a plugin to infer all types correctly. Sadly, even mypy with plugins is a mess to get set up in vscode, especially if you want it to use the same config as you use for ci checks from the command line.
We use mypy + [django-stubs](https://github.com/typeddjango/django-stubs) (in a huge Django + drf project at day job) which includes a plugin for mypy allowing it to recognize all reverse relations and manager methods. Mypy is still really rough around the edges. The cli args are poorly documented, and how they correspond to declarations in a mypy.ini / pyproject.toml is mysterious. Match-statements still have bugs even a year after release. Exclusion of untyped / partially typed files and packages we've had to solve with grep filtering mypy's output for our whitelisted set of files, as it's been unable to separate properly between errors you care about (in your own codebase) and errors in others code (dependencies, untypable dynamic python packages etc).
The largest issue IMO is that mypy tried to adapt a java / OOP style way of type system onto python, instead of recognizing the language's real power within duck typing and passing structural types around. Typescript chose the right approach here, modelling javascript the way it is actually written, favoring structural over nominal typing, instead of the archaic and now left-behind way of Java-style OOP that has influenced mypy.
There was a recently accepted PEP which allowed for limited dataclass transforms, enough to cover the @attr.s usecase for both mypy and pyright, but nowhere near expressive enough to cover django's models and ORM sadly. It's probably impossible / undesirable to allow for such rich plugins, so i see the future for proper pluginless typing to be more akin to how pydantic / normal dataclasses solve typing, by starting with a specification of the types, deriving its runtime implementation, instead of plugins having to reverse the type representation of a custom DSL.
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Boring Python: Code Quality
You can annotate the manager and get some typing help in the editor. And there’s django-stubs which helps a little when running mypy. It’s not as good as pycharm though.
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Python 3.11.0 final is now available
> Yes, there are type stubs for these libraries but they’re either forced to be more strict, preventing use of dynamism, or opt for being less strict but allowing you to use all the library features, at the cost of safety.
There are type stubs for Django that somewhat avoid these compromises: https://github.com/typeddjango/django-stubs
To be able to do this they have to use a Mypy plugin though. And even then it's still far from perfect.
- Welcome to hassle free coding
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Is Rust Web Yet?
Mypy together with this plug-in gives you typing for django. https://github.com/TypedDjango/django-stubs
returns
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This Week in Python (February 23, 2024)
returns – Make your functions return something meaningful, typed, and safe
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Unleash the Power of Python Monads: A Design Pattern for Elegant Code!
returns from the DRY python group appears to offer similar functionality.
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Rust's Option and Result. In Python.
Not to diminish this at all, but https://github.com/dry-python/returns also exists. The scope is wider, but the look and feel of the types feels very similar.
- Functional python for data process
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Faif/Python-patterns: A collection of design patterns/idioms in Python
https://github.com/dry-python/returns#maybe-container
You can decide for yourself what is more readable: all these lambdas or the `None and f()` code.
One of the repos that I found interesting recently is https://github.com/dry-python/returns
- Show HN: Koda, a Typesafe Functional Toolkit for Python
- A simple Rust-like Result type for Python
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What can you do in Haskell that you can't do in Python(for example)?
Functional semantics are available in Python, but IMO not that great. List, dict, and generator comprehensions allow you to perform most operations that you would use in a functional first programming language and there are third party libraries like toolz and funcy that implement some of the more advanced operations. The main issue I've found with using Python as a functional language is it doesn't support fluent syntax. With Scala you can do a relatively complex map/filter/reduce operation with syntactic ease list_of_ints.map(x => x*x).filter(x => x%2 ==0).reduce(x,y => x+y) With Python it's just clunky and less readable b/c of support of list comprehension syntax over fluent syntax. sum([x**2 for x in list_of_ints if x % 2 == 0]) A codebase with 5000 lines of the Scala style code will be much readable and maintainable than with the Python style code.
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Make tests a part of your app
dry-python/returns is a library with primitives that make typed functional programming in Python easier.
What are some alternatives?
Toolz - A functional standard library for Python.
CyToolz - Cython implementation of Toolz: High performance functional utilities
Deal - 🤝 Design by contract for Python. Write bug-free code. Add a few decorators, get static analysis and tests for free.
Coconut - Simple, elegant, Pythonic functional programming.
fn.py - Functional programming in Python: implementation of missing features to enjoy FP
funcy - A fancy and practical functional tools
effect - effect isolation in Python, to facilitate more purely functional code
classes - Smart, pythonic, ad-hoc, typed polymorphism for Python
Pyrsistent - Persistent/Immutable/Functional data structures for Python
strawberry - A GraphQL library for Python that leverages type annotations 🍓
pandas-stubs - Pandas type stubs. Helps you type-check your code.
fp-ts - Functional programming in TypeScript