PythonHub

Query Your Python Lists https://github.com/mkalioby/leopards

Understanding Multimodal LLMs An introduction to the main techniques and latest models. https://substack.com/@rasbt/p-151078631

Protenix A trainable PyTorch reproduction of AlphaFold 3. https://github.com/bytedance/Protenix

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

weft https://github.com/dpunj/weft

Python, C++ inspired language that transpiles to C and can be embedded within C https://github.com/AnilBK/C-Preprocessor-Language

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

ML in Go with a Python Sidecar https://eli.thegreenplace.net/2024/ml-in-go-with-a-python-sidecar/

Cosmos-Tokenizer A suite of image and video neural tokenizers. https://github.com/NVIDIA/Cosmos-Tokenizer

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

pipe-operator Elixir's pipe operator in Python. https://github.com/Jordan-Kowal/pipe-operator

chonkie The no-nonsense RAG chunking library that's lightweight, lightning-fast, and ready to CHONK your texts. https://github.com/bhavnicksm/chonkie

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

BeamerQt PyQt-based application to create Beamer-LaTeX Presentations. https://github.com/acroper/BeamerQt

microsoft / autogen A programming framework for agentic AI 🤖 https://github.com/microsoft/autogen

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

Muon Muon optimizer for neural networks: >30% extra sample efficiency, <3% wallclock overhead. https://github.com/KellerJordan/Muon

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

Pex: A tool for generating .pex (Python EXecutable) files, lock files and venvs https://github.com/pex-tool/pex

Python Hub Weekly Digest for 2024-11-17 https://pythonhub.dev/digest/2024-11-17/