import-linter VS django-stubs

Never heard of https://import-linter.readthedocs.io/ before. Not sure if I like this type of solution, but it's interesting, and certainly the problem is real.

Before clicking on this, I expected to see import-linter [0] which achieves something very similar but with, in my opinion, a bit less magic. Another solution in a similar spirit is Pants [1], though this is actually a build system which allows you to constrain dependencies between different artifacts (e.g. which modules are allowed to depend on which modules).

To Sourcery's credit, their product looks much more in the realm of "developer experience" -- closer to Copilot (or what I understand of it) than to import-linter. Props to them for at least having a page about security [2] and building a solution which doesn't inherently require all of your source code to be shared with a vendor's server.

[0] https://github.com/seddonym/import-linter

[1] https://www.pantsbuild.org/

[2] https://docs.sourcery.ai/Product/Permissions-and-Security/

import-linter on GitHub

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.

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.

https://github.com/typeddjango/django-stubs/tree/master

> 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.

Mypy together with this plug-in gives you typing for django. https://github.com/TypedDjango/django-stubs

Have you looked at stubs for Django?