typeshed
Pytorch
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typeshed | Pytorch | |
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24 | 338 | |
4,066 | 77,783 | |
2.2% | 2.4% | |
9.9 | 10.0 | |
4 days ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 1-Clause 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.
typeshed
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What's the point of using `Any` in Union, such as `str | Any`
"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.
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Importing python libraries "Cannot find implementation or library stub for module named ..."
You can check the typeshed library that offers stubs for many packages.
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Ask HN: Will we see a TypeScript for Python?
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.
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Why Type Hinting Sucks!
https://github.com/python/mypy same with typeshed https://github.com/python/typeshed
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When the client's management is happy but their dev team is a pain
Here's the tensorflow type stubs on typeshed. https://github.com/python/typeshed/tree/main/stubs/tensorflow
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Offer to Type Hint API's, or Start a Statically Typed Python?
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.
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Ruby 3.2’s YJIT is Production-Ready
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...
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GitHub stars won't pay your rent
>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.
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Wrapping my head around type hinting
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.
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Using Mypy in Production
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/
Pytorch
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
What are some alternatives?
pyre-check - Performant type-checking for python.
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
mypy - Optional static typing for Python
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
flask-parameter-validation - Get and validate all Flask input parameters with ease.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
NumPy - The fundamental package for scientific computing with Python.
flax - Flax is a neural network library for JAX that is designed for flexibility.
dactyl-keyboard - Web generator for dactyl keyboards.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more