Python Weekly (Issue 668 September 19 2024)

Python Weekly - Issue 668

September 19, 2024

Python Weekly

Welcome to issue 668 of Python Weekly. Let's get straight to the links this week.

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A weekly newsletter featuring the best hand curated news, articles, tutorials, talks, tools and libraries etc for programmers.

Articles, Tutorials and Talks

Learn full stack stack development with the FARM stack. You will learn to quickly create an application using FastAPI, React, and MongoDB.

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 variations like aegraphs used in Cranelift.

The article explains how to implement an advanced Retrieval-Augmented Generation (RAG) system using MongoDB Atlas Vector Search and LangChain, focusing on self-querying retrieval. It demonstrates how to create a system that can dynamically generate and execute queries based on user input, improving the relevance and accuracy of retrieved information for large language models.

Python code too slow? You can quickly create a Rust extension to speed it up.

UV can be seen as an alternative to pip, but that might be a limiting way to think about the tool. Instead of looking at faster builds, which are still super nice, it might also make sense to rethink the stuff that we might be able to do from Python going forward.

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.

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.

Discover seven ways you can use Jupyter notebooks in PyCharm to explore and work with your data more quickly and effectively.

The article explores optimizing argument parsing in Python, demonstrating techniques to reduce execution time for functions with multiple arguments. Through various methods like manual unpacking and using faster calling conventions, the author achieves a 35.2% overall speedup in argument parsing, highlighting the potential performance gains in high-demand applications.

Go beyond vector search. Learn how to improve your RAG system with Text2SQL, filtered search, structured extraction, and eval-driven development.

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.

Interesting Projects, Tools and Libraries

Things you can do with the token embeddings of an LLM.

rustls-based modern TLS for Python.

Formatron empowers everyone to control the format of language models' output with minimal overhead.

Brand new TTS solution.

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.

3D Reconstruction with Spatial Memory.

A library of utilities to support efficient, scalable Python development leveraging Free Threaded Python.

A type-safe C successor that compiles directly to various platforms.

The fastest way to bring multi-agent workflows to production.

Upcoming Events and Webinars

There will be following talks

  • From text to actions: LLMs as the new software consumers

  • Ragtime: An Approach to Retrieval-Augmented Generation

There will be following talks

  • How to calculate sample size in your head

  • Helping people get 3D prints of their own brain with Python

  • When Driving Is Not an Option: Steering Away from Car Dependency

There will be following talks

  • How to allocate marketing budget - Bayesian approach to the rescue

  • Questioning the fundamentals - intro to Kalmogorov-Arnold Networks

There will be following talks

  • Big Data in Medicine: The Mysterious Links Between Blood Sugar and Arm Problems

  • Sewer Inspection with Computer Vision

  • The Grand Challenge of Emotion-Based Music Recommendation: How well can you predict someone's emotional response to music with AI?

There will be following talks

  • Empowering Data Teams: Self-Serve Infrastructure, Reusable Components & Automation

  • Struggling to scale GenAI. You are not alone!

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