1140
News & links about Python programming. https://pythonhub.dev/ Administrator: @rukeba
EasyAnimate
An End-to-End Solution for High-Resolution and Long Video Generation Based on Transformer Diffusion.
https://github.com/aigc-apps/EasyAnimate
Introducing DjangoVer
The article introduces DjangoVer, a versioning system for Django-related packages that aligns the package version with the latest supported Django feature release. It provides clarity on compatibility, signaling maintenance and compatibility status through the version number while addressing limitations of traditional versioning systems like Semantic Versioning.
https://www.b-list.org/weblog/2024/nov/18/djangover/
Deply: keep your python architecture clean
https://www.reddit.com/r/Python/comments/1gthdpy/deply_keep_your_python_architecture_clean/
Python Hub Weekly Digest for 2024-11-24
https://pythonhub.dev/digest/2024-11-24/
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
Is async django ready for prime time?
Explore async Django's readiness for production use, its benefits, challenges, and how AI workloads can leverage its capabilities effectively.
https://jonathanadly.com/is-async-django-ready-for-prime-time
Flask 3.1.0 Released
https://flask.palletsprojects.com/en/stable/changes/#version-3-1-0
PyPI now has attestation. Thanks I hate it.
https://www.reddit.com/r/Python/comments/1gs05hm/pypi_now_has_attestation_thanks_i_hate_it/
Everything I've learned so far about running local LLMs
A post about running large language models (LLMs) locally on a computer. It discusses what LLMs are and how to set them up to run on your own machine. The article also covers some of the limitations of LLMs, but highlights their potential for tasks like proofreading and creative writing.
https://nullprogram.com/blog/2024/11/10
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