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News & links about Python programming. https://pythonhub.dev/ Administrator: @rukeba
Inside Bento: Jupyter Notebooks at Meta
Meta has developed Bento, an internal platform that enhances Jupyter notebooks with features like version control, collaborative editing, and automated dependency management. This system, which handles over 150,000 notebooks and supports 18,000 monthly active users, aims to improve productivity and collaboration for data scientists and engineers across Meta's various teams and projects.
https://engineering.fb.com/2024/09/17/data-infrastructure/inside-bento-jupyter-notebooks-at-meta/
Moshi
A speech-text foundation model for real time dialogue.
https://github.com/kyutai-labs/moshi
WTF is ASGI and WSGI in python apps?
https://samagra.me/wtf/2024/09/27/gateway-interfaces.html
SurfSense
Personal AI Assistant for World Wide Web Surfers. Research & Never forget anything you see on the Internet.
https://github.com/MODSetter/SurfSense
7 New Typing Features in Python 3.13
https://medium.com/techtofreedom/7-new-typing-features-in-python-3-13-58caae5f2f10?sk=6ee66766ba372ea1f62b44a0ef08012d
skrub
A Python library that facilitates prepping your tables for machine learning.
https://github.com/skrub-data/skrub/
Spiderweb
A small web framework, just big enough for a spider. Also check an
https://github.com/itsthejoker/spiderweb
Python Hub Weekly Digest for 2024-09-29
https://pythonhub.dev/digest/2024-09-29/
Hy 1.0.0, the Lisp dialect for Python, has been released
https://github.com/hylang/hy/discussions/2608
Building an Advanced RAG System With Self-Querying Retrieval
https://www.mongodb.com/developer/products/atlas/advanced-rag-self-querying-retrieval
Deploying a Django app with Kamal, AWS ECR, and Github Actions
The article provides a comprehensive guide on deploying a Django app using Kamal, AWS ECR, and GitHub Actions, offering a streamlined approach to containerized deployment. It covers setting up a VPS, creating a Dockerfile, configuring AWS ECR, setting up Kamal, and automating the deployment process with GitHub Actions, aiming to simplify the deployment workflow for developers.
https://dylancastillo.co/posts/deploy-a-django-app-with-kamal-aws-ecr-and-github-actions.html
Ask HN: Kotlin SpringBoot vs. Python Django for Min Viable Product
https://news.ycombinator.com/item?id=41584157
LLaMA-Omni
LLaMA-Omni is a low-latency and high-quality end-to-end speech interaction model built upon Llama-3.1-8B-Instruct, aiming to achieve speech capabilities at the GPT-4o level.
https://github.com/ictnlp/LLaMA-Omni
Serializing package requirements in marimo notebooks
Marimo now allows notebooks to serialize their package requirements as top-level comments, enabling users to run notebooks in isolated virtual environments with a single command. This feature, powered by the uv package manager, enhances reproducibility and sharing of notebooks by eliminating the need for separate requirements files and preventing environment pollution.
https://marimo.io/blog/sandboxed-notebooks
What's in an e-graph?
The article explains e-graphs by incrementally building from union-find to a full e-graph implementation, highlighting key features like equivalence class discovery, pattern matching, and extraction. It demonstrates how e-graphs can be used in compilers for optimizations, offering a more flexible alternative to traditional find-and-replace methods while discussing trade-offs and variatio...
https://bernsteinbear.com/blog/whats-in-an-egraph/
Refactoring Python with Tree-sitter and Jedi
https://jackevans.bearblog.dev/refactoring-python-with-tree-sitter-jedi/
What are some well-known, universally understood things that a self learner might miss?
https://www.reddit.com/r/learnpython/comments/1fsol3z/what_are_some_wellknown_universally_understood/
Building RAG with Postgres
A step by step guide to building a RAG system with Postgres.
https://anyblockers.com/posts/building-rag-with-postgres
Bringing multithreading to Python's async event loop
https://github.com/NeilBotelho/turboAsync
An In-Depth Guide to Contrastive Learning: Techniques, Models, and Applications
Discover the fundamentals of contrastive learning, including key techniques like SimCLR, MoCo, and CLIP. Learn how contrastive learning improves unsupervised learning and its practical applications.
https://myscale.com/blog/what-is-contrastive-learning
meta-llama / llama-stack
Model components of the Llama Stack APIs
https://github.com/meta-llama/llama-stack
rerankers: A Lightweight Python Library to Unify Ranking Methods
Re-ranking is an integral component of many retrieval pipelines; however, there exist numerous approaches to it, all with different implementation methods. To mitigate this, we propose rerankers, a Python library which provides a simple, easy-to-use interface to all commonly used re-ranking approaches.
https://www.answer.ai/posts/2024-09-16-rerankers.html
13 Python Quirks That Will Surprise You
This video presents 13 peculiar aspects of Python programming, with the final example being particularly confusing for newcomers to the language. Each quirk is demonstrated through code examples, accompanied by explanations for their existence and behavior.
https://www.youtube.com/watch?v=eufjIfVOm8s
Totally blown away by python core libraries
https://www.reddit.com/r/learnpython/comments/1fmqke0/totally_blown_away_by_python_core_libraries/
pyrtls
rustls-based modern TLS for Python.
https://github.com/djc/pyrtls
FastAgency
The fastest way to bring multi-agent workflows to production.
https://github.com/airtai/fastagency
Things I've learned serving on the board of the Python Software Foundation
https://simonwillison.net/2024/Sep/18/board-of-the-python-software-foundation/
Let’s build and optimize a Rust extension for Python
Python code too slow? You can quickly create a Rust extension to speed it up.
https://pythonspeed.com/articles/intro-rust-python-extensions/
spann3r
3D Reconstruction with Spatial Memory.
https://github.com/HengyiWang/spann3r
RAG Is More Than Just Vector Search
Go beyond vector search. Learn how to improve your RAG system with Text2SQL, filtered search, structured extraction, and eval-driven development.
https://www.timescale.com/blog/rag-is-more-than-just-vector-search/