PythonHub

Netflix ML Infra: Stop Bottlenecks! Scale Python Like Never Before Netflix’s Metaflow team built a scalable ML infrastructure using Python to support use cases like recommendations and content modeling while boosting developer productivity. Their design focuses on reducing cognitive load by improving data handling, dependency management, and environment isolation so engineers can focus on ML instead of infrastructure. https://www.youtube.com/watch?v=QaP5xl7EA2Y

9 Signs You’re Writing Java in Python https://medium.com/techtofreedom/9-signs-youre-writing-java-in-python-931bc22d3885?sk=f6b04f4f57a1e1846f02ab7cade4b403

asyncio: a library with too many sharp corners An explanation of some major issues with asyncio. https://sailor.li/asyncio

copyparty Turn almost any device into a file server with resumable uploads/downloads using any web browser. https://github.com/9001/copyparty

Stop Using Django's squashmigrations: There's a Better Way Squashing Django migrations often breaks or complicates projects, especially when all environments are under your control. A clean reset by deleting old migrations, generating new ones, and faking migration history is a simpler and more reliable approach. https://johnnymetz.com/posts/squash-django-migrations/

awesome-claude-code A curated list of awesome commands, files, and workflows for Claude Code. https://github.com/hesreallyhim/awesome-claude-code

Semi-Automated Assembly Verification in Python using pypcode Semantics Philip Zucker introduces a Python toolkit that lets users add verification annotations directly to assembly code using macros, enabling semi-automated proof of correct assembly behavior via pypcode, which supports portable, architecture-agnostic analysis. This approach keeps formal verification practical and accessible for real-world low-level programming. https://www.philipzucker.com/assembly_verify/

metap: A Meta-Programming Layer for Python metap is a new Python meta-programming layer that supports program augmentation, user-defined code generation, and structural introspection. It allows developers to automate coding patterns, extend Python with customizable macros, and have code inspect and enforce its own structure, improving maintainability and correctness. Unlike Python’s built-in tools, metap offers a unified, extensi... https://sbaziotis.com/compilers/metap.html

Python Hub Weekly Digest for 2025-08-03 https://pythonhub.dev/digest/2025-08-03/

Django: iterate through all registered URL patterns Adam Johnson demonstrates a Python generator function that recursively traverses Django’s URLResolver structure to enumerate all registered URLPattern objects, including those in nested namespaces. He shows how this can be used for tasks like auditing registered views or writing tests to ensure all class-based views inherit from a specific base class. https://adamj.eu/tech/2025/07/22/django-iterate-url-patterns/

Python Tutorial: Type Hints - From Basic Annotations to Advanced Generics Corey Schafer explains Python’s type hints, from basic function annotations to advanced features like generics, with practical examples showing their benefits for code clarity, early bug detection, and IDE support. He highlights that type hints are optional and flexible, letting you gradually adopt them in your projects. https://www.youtube.com/watch?v=RwH2UzC2rIo

Announcing Toad - a universal UI for agentic coding in the terminal Will McGugan announces Toad, a new universal terminal UI for AI coding agents built with Textual, offering a flicker-free and interactive experience compared to existing tools. Toad will be open source, supports any backend language, and uses JSON for communication between frontend and backend. https://willmcgugan.github.io/announcing-toad/

3 pandas Workflows That Slowed to a Crawl on Large Datasets—Until We Turned on GPUs NVIDIA shows how switching from pandas to GPU-accelerated cuDF made slow data workflows run up to 30× faster. Common tasks like time-series analysis and dashboard filtering became near-instant with minimal code changes. https://developer.nvidia.com/blog/3-pandas-workflows-that-slowed-to-a-crawl-on-large-datasets-until-we-turned-on-gpus/

passage-of-time-mcp An MCP server that gives language models temporal awareness and time calculation abilities. Teaching AI the significance of the passage of time through collaborative tool development. https://github.com/jlumbroso/passage-of-time-mcp

higgs-audio Text-audio foundation model from Boson AI. https://github.com/boson-ai/higgs-audio

Tinyio: A tiny (~200 line) event loop for Python https://github.com/patrick-kidger/tinyio

You might not need a Python class https://adamgrant.micro.blog/2025/07/24/123050.html

AmazingHand Code and model to control the AH! https://github.com/pollen-robotics/AmazingHand

A Python dict that can report which keys you did not use https://www.peterbe.com/plog/a-python-dict-that-can-report-which-keys-you-did-not-use

Fully Homomorphic Encryption and the Dawn of A Truly Private Internet Fully Homomorphic Encryption (FHE) allows computation on encrypted data and is becoming ~8× faster each year. It could enable a privacy-by-default internet, powering secure cloud and AI services without exposing user data. https://bozmen.io/fhe