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News & links about Python programming. https://pythonhub.dev/ Administrator: @rukeba
TransformerEngine
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
https://github.com/NVIDIA/TransformerEngine
alphafold3
AlphaFold 3 inference pipeline.
https://github.com/google-deepmind/alphafold3
Tutorial: How to rate limit Python async API requests
With an example that performs 100 simultaneous requests to the Etherscan API
https://elnaril.hashnode.dev/how-to-rate-limit-python-async-requests-to-etherscan-and-other-apis
Understanding Multimodal LLMs
An introduction to the main techniques and latest models.
rasbt/p-151078631">rasbt/p-151078631" rel="nofollow">https://substack.com/@rasbt/p-151078631
Python dependency management is a dumpster fire
This article is all about fire safety techniques and tools. It's about how you should think about dependency management, which tools you should consider for different scenarios, and what trade offs you'll have to make. Finally, it exposes the complexity and lingering problems in the ecosystem.
https://nielscautaerts.xyz/python-dependency-management-is-a-dumpster-fire.html
Python, C++ inspired language that transpiles to C and can be embedded within C
https://github.com/AnilBK/C-Preprocessor-Language
ML in Go with a Python Sidecar
https://eli.thegreenplace.net/2024/ml-in-go-with-a-python-sidecar/
NanoDjango - single-file Django apps | uv integration
NanoDjango is a cool package that lets you build small scripts using all the power of Django, and also supports django-ninja for APIs. We'll dive into NanoDjango in this video, and will use uv and inline script metadata for dependency management.
https://www.youtube.com/watch?v=0-iuJgfQMOw
chonkie
The no-nonsense RAG chunking library that's lightweight, lightning-fast, and ready to CHONK your texts.
https://github.com/bhavnicksm/chonkie
BeamerQt
PyQt-based application to create Beamer-LaTeX Presentations.
https://github.com/acroper/BeamerQt
Thoughts on Django’s Core
Django's longevity is attributed to its stable core, time-based releases, and API stability policy. While there's enthusiasm for expanding Django's features, the author argues that the core should remain focused and prioritize stability. Instead, the community should embrace third-party packages as a way to innovate and extend Django's capabilities without compromising its core.
https://buttondown.com/carlton/archive/thoughts-on-djangos-core
The Polars vs pandas difference nobody is talking about
A closer look at non-elementary group-by aggregations.
https://labs.quansight.org/blog/dataframe-group-by
Python Hub Weekly Digest for 2024-11-17
https://pythonhub.dev/digest/2024-11-17/
Django bugfix release issued: 5.1.3
https://www.djangoproject.com/weblog/2024/nov/05/bugfix-release/
mac_computer_use
A fork of Anthropic Computer Use that you can run on Mac computers to give Claude and other AI models autonomous access to your computer.
https://github.com/deedy/mac_computer_use
CPython's Garbage Collector and Its Impact on Application Performance
https://blog.codingconfessions.com/p/connecting-cpythons-gc-internals
Proposal for a Django project template
The author's take on what could be a project template for Django advanced usage, with modern tooling (for Python and UI dependencies, as well as configuration/environment management), but not too opinionated.
https://david.guillot.me/en/posts/tech/proposal-for-a-django-project-template/
Query Your Python Lists
https://github.com/mkalioby/leopards
Protenix
A trainable PyTorch reproduction of AlphaFold 3.
https://github.com/bytedance/Protenix
The Practical Guide to Scaling Django
Most Django scaling guides focus on theoretical maximums. But real scaling isn’t about handling hypothetical millions of users - it’s about systematically eliminating bottlenecks as you grow. Here’s how to do it right, based on patterns that work in production.
https://slimsaas.com/blog/django-scaling-performance
Cosmos-Tokenizer
A suite of image and video neural tokenizers.
https://github.com/NVIDIA/Cosmos-Tokenizer
pipe-operator
Elixir's pipe operator in Python.
https://github.com/Jordan-Kowal/pipe-operator
Flash Attention derived and coded from first principles with Triton (Python)
This video provides an in-depth, step-by-step explanation of Flash Attention, covering its derivation, implementation, and underlying concepts. The presenter explains CUDA, Triton, and autograd from scratch, then derives and codes both the forward and backward passes of Flash Attention.
https://www.youtube.com/watch?v=zy8ChVd_oTM
microsoft / autogen
A programming framework for agentic AI 🤖
https://github.com/microsoft/autogen
Muon
Muon optimizer for neural networks: >30% extra sample efficiency, <3% wallclock overhead.
https://github.com/KellerJordan/Muon
Pex: A tool for generating .pex (Python EXecutable) files, lock files and venvs
https://github.com/pex-tool/pex
Basilisp: Clojure on the Python VM
Everyone knows Clojure runs on the JVM and CLR, in Node, and in the browser, but what about Python? Basilisp is a mostly-compatible implementation of Clojure for Python, enabling users who may not be familiar with Java or JavaScript to experience the joy of Clojure.
https://www.youtube.com/watch?v=ruGRHYpq448
crewAIInc / crewAI
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
https://github.com/crewAIInc/crewAI
Step-by-Step Python Package Deployment with GitHub Actions
Publishing a Python package doesn't have to be overwhelming! This video walks you through the entire deployment process step-by-step. You'll learn how to automate releases with GitHub Actions and how to successfully publish your package on PyPi.
https://www.youtube.com/watch?v=NMQwzI9hprg