typeshed VS Poetry

"csv.pyi is from VS Code Pylance extension" is misleading. Yes, it's included in the code base of the extension, but it's likely originally from python/typeshed. I diffed csv.pyi in the extension and the repository, and they're exactly the same.

You can check the typeshed library that offers stubs for many packages.

https://github.com/python/typeshed is Python's equivalent of DefinitelyTyped. I'm not 100% sure why it's not more of a popular thing the way DefinitelyTyped is; I think there might, to some extent, be different attitudes around the appropriateness of having third-party typings for packages, when the actual maintainer of the package isn't interested in providing first-party ones.

https://github.com/python/mypy same with typeshed https://github.com/python/typeshed

Here's the tensorflow type stubs on typeshed. https://github.com/python/typeshed/tree/main/stubs/tensorflow

Also, be aware that there is already a central place for stubs files. If you are going to take the time to write one, contributing it there will help everyone if the package owners aren't already including some type hints.

Python's type hints are definitely an improvement and they're getting better all the time, but they're still frustrating to use at anything approaching the edge. I long for something as elegant and functional as TypeScript.

One hurdle I've stumbled over recently is the question "what is a type?", the answer can be surprising. Unions, for example, are types but not `Type`s. A function that takes an argument of type `Type` will not accept a Union. So if you want to write a function that effectively "casts" a parameter to a specified type, you can't. The best you can do is have an overload that accepts `Type` and does an actual cast, and then another that just turns it into `Any`. This is, in fact, how the standard library types its `cast` function [1]. The argument I've seen for the current behavior is that `Type` describes anything that can be passed to isinstance, but that's not a satisfying answer. Even then, `Union` can be passed to isinstance and still does not work with `Type`. Talk currently is to introduce a new kind of type called `TypeForm` or something to address this, which is certainly an improvement over nothing, but still feels like technical debt.

[1]: https://github.com/python/typeshed/blob/main/stdlib/typing.p...

>Ultimately if you care enough about Fody to spend over a hundred dollars worth of your time contributing to it, you probably care enough about Fody to drop them three dollars.

No, I really don't.

https://github.com/keepassxreboot/keepassxc/pull/8500 - I was randomly reading keepassxc's manpage and spotted a curious option, spent some time spelunking through the code and history to discover that it was an outdated option, sent a PR.

https://github.com/python/typeshed/pull/8617 - I converted one of the scripts I use in my DE from shell to Python, saw that VSCode has this new fancy typing support for Python, quickly found a basic bug in the type definitions for the os module, tested a fix locally, sent a PR.

https://gitlab.gnome.org/GNOME/gtk/-/issues/5250 - I found an issue with copy-paste on my phone, investigated it all the way through to the GTK stack, found the commits that introduced the issue, created a distro patch for it while discussing it with GTK upstream.

https://gitlab.alpinelinux.org/alpine/aports/-/merge_request... - I noticed that gnome-passwordsafe crashes some times, debugged it to discover that it was missing a dependency, sent a PR to the distro package to update the dependencies.

etc etc. I've made lots of fixes like these. I have no interest in paying for each and every one of them. The projects are all better off for fixes like mine and gatekeeping them on payment would've been nothing but their loss.

The csv module is one of those standard library modules that doesn't provide its own type hints, but instead gets them through the external typeshed project, and (for compatibility/implementation reasons, I surmise) the name of these types sometimes don't quite align with the objects they correspond to. So, for all intents and purposes, _csv._reader is the correct name of the type that csv.reader() returns, as ugly as it is.

You have to do handling like that in other languages like TypeScript anyway.

Painpoint with type annotations:

- not being able to reuse "shapes" of data: TypedDict, NamedTuple, dataclasses.dataclass, and soon kwargs (PEP 692 [1]) all have named, typed fields now. You have to

- Since there's no generic "shape" structure that works across data types, there isn't a way to load up a JSON / YAML / TOML into a dictionary, upcast it via a `TypedGuard`, and pass it into a TypedDict / NamedTuple / Dataclass. dataclasses.asdict() or dataclasses.astuple() return naive / untyped tuples and dicts. Also the factory functions will not work with TypedDict or NamedTuple, respectively, even if you duplicate the fields by hand. See my post here: https://github.com/python/typeshed/issues/8580

- Standard library doesn't have runtime validation (e.g. pydantic / https://github.com/pydantic/pydantic).

- pytest fixtures are hard.

- Django is hard. PEP 681 may not be a saving grace either. [3]

[1] https://peps.python.org/pep-0692/

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.

Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:

Poetry

The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:

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

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...

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.

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/

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.

I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github