PythonHub

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

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/

Flask 3.1.0 Released https://flask.palletsprojects.com/en/stable/changes/#version-3-1-0

Deply: keep your python architecture clean https://www.reddit.com/r/Python/comments/1gthdpy/deply_keep_your_python_architecture_clean/

PyPI now has attestation. Thanks I hate it. https://www.reddit.com/r/Python/comments/1gs05hm/pypi_now_has_attestation_thanks_i_hate_it/

Python Hub Weekly Digest for 2024-11-24 https://pythonhub.dev/digest/2024-11-24/

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

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

CPython's Garbage Collector and Its Impact on Application Performance https://blog.codingconfessions.com/p/connecting-cpythons-gc-internals

alphafold3 AlphaFold 3 inference pipeline. https://github.com/google-deepmind/alphafold3

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/

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

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/