How I made dependency injection in Python 130× faster: from reflection to compiling the graph

The post shows how a Python dependency injection container was optimized from ~53 µs to 0.40 µs per resolve by caching plans, eliminating unnecessary checks, and compiling dependency graphs into generated code. Along the way, it demonstrates practical performance engineering techniques, including code generation, common-subexpression elimination, fuzz testing, and reproducible benchmarking

https://vshulcz.hashnode.dev/python-dependency-injection-130x-faster

How to build your first Scrapy extension

This tutorial uses a simple audio notification plugin to explain how Scrapy extensions work, covering signals, lifecycle hooks, settings, testing, and packaging. It provides a practical introduction to extending Scrapy with custom functionality while showcasing common patterns used across the ecosystem.

https://www.zyte.com/blog/how-to-build-your-first-scrapy-extension/

Array API adoption: what to do with compiled code

The post examines how Array API compatibility and JIT compilation can modernize legacy scientific Python code for GPUs and multicore CPUs. The results suggest developers can achieve significant performance gains across hardware platforms without maintaining specialized accelerator-specific code.

https://labs.quansight.org/blog/array-api-aot-jit

The Fastest Python Struct?

The article explores the performance tradeoffs of Python's various struct-like types, focusing on startup and type-definition costs rather than runtime business logic. Extensive benchmarks reveal that NamedTuple sits in the middle of the pack, while msgspec and C-backed implementations deliver the fastest type creation and startup times.

https://www.crumpledpaper.tech/2026-06-21-python-struct-profiling/

Write a coding agent from first principles

This tutorial will show you how to create your own coding agent from first principles. By doing so, you'll understand how coding agents work under the hood.

https://mathspp.com/blog/write-a-coding-agent-from-first-principles

PixelRAG

PixelRAG replaces traditional text-based web RAG with a pixel-native approach that retrieves and reasons over webpage screenshots. By preserving visual structure and using vision-language models, it aims to improve retrieval accuracy and web understanding.

https://github.com/StarTrail-org/PixelRAG

Wagtail as Django admin on steroids

Wagtail can be used as a drop-in replacement for Django Admin, providing a more polished UI and powerful customization capabilities. The article demonstrates how developers can adopt Wagtail incrementally while retaining their existing Django architecture.

https://timonweb.com/wagtail/wagtail-as-django-admin-on-steroids/

NVlabs / Eagle

Eagle: Frontier Vision-Language Models with Data-Centric Strategies

https://github.com/NVlabs/Eagle

Optocam Zero

Optocam Zero is a Raspberry Pi Zero based compact digital camera made using off the shelf components.

https://github.com/dorukkumkumoglu/optocamzero

WinPodX

Windows pod system for Linux.

https://github.com/kernalix7/winpodx

NVIDIA / skills

AI agent skills published by NVIDIA

https://github.com/NVIDIA/skills

Build a fully local voice assistant in 2026

A practical setup for a Raspberry Pi-friendly voice assistant based on Platypush.

https://blog.platypush.tech/article/Local-voice-assistant

virgiliojr94 / book-to-skill

Turn any technical book PDF into a Claude Code skill — ready to study, reference, and use while you work.

https://github.com/virgiliojr94/book-to-skill

You Don’t Need That Design Pattern

Using Python examples, the video explores the tradeoff between simplicity and abstraction, showing how design patterns can introduce unnecessary complexity when applied too early. It provides a practical rule of thumb for recognizing when a pattern adds value versus when it becomes overengineering.

https://www.youtube.com/watch?v=xns3InDkAiA

music-assistant / server

Music Assistant is a free, opensource Media library manager that connects to your streaming services and a wide range of connected speakers. The server is the beating heart, the core of Music Assistant and must run on an always-on device like a Raspberry Pi, a NAS or an Intel NUC or alike.

https://github.com/music-assistant/server

Graphsignal

Graphsignal is a production-scale inference profiling platform that helps engineers optimize AI performance across models, engines, GPUs, and other accelerators. I

https://github.com/graphsignal/graphsignal-profiler

TIRx: An Open Compiler Stack for Evolving Frontier ML Kernels

TIRx introduces an open-source, hardware-native DSL and compiler stack for writing high-performance ML kernels that can keep pace with rapidly evolving AI hardware. Built on Apache TVM, it combines low-level control, compiler-assisted abstractions, and agent-friendly tooling to support expert developers, automated kernel generation, and future accelerator architectures.

https://tvm.apache.org/2026/06/22/tirx

Data-Juicer

Data processing for and with foundation models!

https://github.com/datajuicer/data-juicer