django-stubs
Poetry
django-stubs | Poetry | |
---|---|---|
7 | 377 | |
1,462 | 29,552 | |
1.8% | 1.3% | |
9.6 | 9.7 | |
3 days ago | 3 days ago | |
Python | Python | |
MIT License | MIT 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
-
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.
-
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.
https://github.com/typeddjango/django-stubs/tree/master
-
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
-
Is Rust Web Yet?
Mypy together with this plug-in gives you typing for django. https://github.com/TypedDjango/django-stubs
-
Django projects with type hints?
Have you looked at stubs for Django?
- Neovim + Django - LSP config
Poetry
-
Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
-
Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
-
From Kotlin Scripting to Python
Poetry
-
How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
-
Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
https://github.com/python-poetry/poetry/issues/6409
-
Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
-
Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
-
Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
[1] https://github.com/python-poetry/poetry/issues/2184
[2] https://pypi.org/project/pypiserver/
-
Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
-
How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
What are some alternatives?
strawberry - A GraphQL library for Python that leverages type annotations 🍓
Pipenv - Python Development Workflow for Humans.
phantom-types - Phantom types for Python.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
pandas-stubs - Pandas type stubs. Helps you type-check your code.
hatch - Modern, extensible Python project management
lagom - 📦 Autowiring dependency injection container for python 3
pyenv - Simple Python version management
pandas-stubs - Public type stubs for pandas
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
returns - Make your functions return something meaningful, typed, and safe!
virtualenv - Virtual Python Environment builder