Python Hub Weekly Digest for 2025-09-14
This week in Python, Zuban, a high-performance Python Language Server, gained popularity for its speed and efficiency. Django views were discussed for their simplicity and flexibility in handling HTTP requests. SQLModel's asynchronous use with FastAPI and PostgreSQL was highlighted for improving web application scalability. PageIndex, a reasoning-based RAG system, and the use of Pydantic AI for building AI-powered Python applications were also featured. Polars' new GPU engine was noted for accelerating data processing. Happy coding and have a great week!
💖 Most Popular
Zuban
Zuban is a high-performance Python Language Server and type checker implemented in Rust, by the author of Jedi. Zuban is 20–200× faster than Mypy, while using roughly half the memory and CPU compared to Ty and Pyrefly. It offers both a PyRight-like mode and a Mypy-compatible mode, which behaves just like Mypy; supporting the same config files, command-line flags, and error messages.
How I write Django views
The author advocates using Django's base View class over generic class-based or function-based views for simplicity and flexibility in handling HTTP requests. By avoiding complex mixins and leveraging straightforward helper methods, developers can write clearer, more maintainable view code with minimal cognitive overhead.
TIL: Using SQLModel Asynchronously with FastAPI (and Air) with PostgreSQL
This post explains how to leverage SQLModel with FastAPI and PostgreSQL to enable fully asynchronous database operations, improving scalability and efficiency for concurrent web applications. Key steps include setting up async database engines and sessions, using dependency injection in FastAPI, and aligning everything with non-blocking patterns.
PageIndex
PageIndex is a reasoning-based RAG system that simulates how human experts navigate and extract knowledge from long documents through tree search, enabling LLMs to think and reason their way to the most relevant document sections.
📖 Articles
How to Write Great Unit Tests in Python
The video teaches how to write effective and maintainable unit tests in Python, focusing on practical techniques such as mocking, monkey patching, fixtures, and parametrization with pytest. It uses a realistic WeatherService example to demonstrate these concepts, emphasizing best practices for robust testing and improving code quality in production systems.
Sharing a mutable reference between Rust and Python
vLLM with torch.compile: Efficient LLM inference on PyTorch
Learn how to optimize PyTorch code with minimal effort using torch.compile, a just-in-time compiler that generates optimized kernels automatically.
Build an AI Coding Agent in Python
This tutorial teaches how to build a functional agentic AI coding assistant in Python using the free Gemini Flash API, covering agentic loops, tool-calling, file manipulation, and autonomous debugging. By constructing an agent that can read, modify, and execute code, viewers gain practical skills and deep insight into how modern coding agents operate beneath the surface.
When You No Longer Need That Object • Dealing With Garbage in Python
Let's explore reference counting and cyclic garbage collection in Python.
playwright-use
playwright-use turns natural-language UI test goals into executable Playwright steps using AI, then produces human-friendly and machine-readable reports with screenshots, video, and traces.
PydanticAI: the AI Agent Framework Winner
The video showcases how to use Pydantic AI to build Python applications with AI-powered agents that provide validated, structured outputs by integrating large language models like GPT-5. It demonstrates a healthcare triage assistant that personalizes responses using domain data, dependencies, and customizable prompts, enabling robust, real-world AI integration beyond simple chatbots.
Scheduling Background Tasks in Python with Celery and RabbitMQ
We'll build background tasks using Celery and RabbitMQ to create a weather notification service.
Polars GPU Execution. (70% speed up)
Polars' new GPU engine, powered by NVIDIA RAPIDS cuDF, accelerates data processing up to 70% compared to CPU-based execution, enabling faster handling of large datasets. The beta release supports common operations, leveraging GPU parallel processing for significant performance gains in data analytics workflows.
Speeding up PyTorch inference by 87% on Apple devices with AI-generated Metal kernels
The post describes how AI models can automatically generate optimized Metal GPU kernels that speed up PyTorch inference on Apple devices by an average of 87% across 215 modules, with some kernels running hundreds of times faster than baseline. Using an agentic swarm approach and adding context like CUDA references and profiling data, the system outperforms standalone models, making kerne...
Python: capture stdout and stderr in unittest
The article explains how to capture stdout and stderr during Python unittest runs using contextlib.redirect_stdout and redirect_stderr, enabling tests to programmatically access console output. It also provides examples and custom context managers to simplify capturing both streams simultaneously, improving test logging and debugging capabilities.
Python Hub Weekly Digest for 2025-09-07
⚙️ Projects
Elysia
Elysia is an agentic platform designed to use tools in a decision tree. A decision agent decides which tools to use dynamically based on its environment and context.
sync-with-uv
The sync-with-uv package automates version synchronization between uv.lock and .pre-commit-config.yaml, ensuring consistent dependency management for tools like black, ruff, and mypy. It integrates as a pre-commit hook, streamlining workflows by aligning versions from a single source while leaving unspecified tools unchanged.
toolfront
Simple data retrieval for AI with unmatched control, precision, and speed.
WhisperLiveKit
Real-time & local speech-to-text, translation, and speaker diarization. With server & web UI.
Youtu-agent
A simple yet powerful agent framework that delivers with open-source models.
LEANN
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
GENIE
Experience near-instantaneous speech synthesis on your CPU.
oLLM
oLLM is a lightweight Python library for large-context LLM inference, built on top of Huggingface Transformers and PyTorch. It enables running models like Llama-3.1-8B-Instruct on 100k context using ~$200 consumer GPU with 8GB VRAM. Example performance: ~20 min for the first token, ~17s per subsequent token.
DiffMem
Git Based Memory Storage for Conversational AI Agent.
Kronos
A Foundation Model for the Language of Financial Markets.
yesglot
LLM-powered Django translations. Just call me "python manage.py translatemessages"
👾 Reddits
Niche Python tools, libraries and features - whats your favourite?
Project by Ruslan Keba. Since 2012. Powered by Python. Made in 🇺🇦Ukraine.