PythonHub

x-algorithm Algorithm powering the For You feed on X. https://github.com/xai-org/x-algorithm

bzfs bzfs is a reliable near real-time, parallel replication and backup command-line tool for ZFS. https://github.com/whoschek/bzfs

Stelvio – Ship Python to AWS https://stelvio.dev/

Engineering VP Josh Clemm on how we use knowledge graphs, MCP, and DSPy in Dash Dropbox’s VP of Engineering explains how the company built Dropbox Dash, an AI-driven cross-app search and knowledge system that uses indexing, knowledge graphs, and contextual reasoning to unify work content from many tools into a single, context-aware platform. The piece highlights engineering decisions about when to use indexed retrieval over federated approaches, how MCP tool calls a... https://dropbox.tech/machine-learning/vp-josh-clemm-knowledge-graphs-mcp-and-dspy-dash

RAG for Legacy Systems: 7,432 Pages to 3s Answers Production RAG for legacy systems: model-agnostic reranking validated across four LLM families. Real metrics, no vendor lock-in, 7,432 pages to 3s queries. https://clouatre.ca/posts/rag-legacy-systems/

kimi-cli Kimi Code CLI is an AI agent that runs in the terminal, helping you complete software development tasks and terminal operations. It can read and edit code, execute shell commands, search and fetch web pages, and autonomously plan and adjust actions during execution. https://github.com/MoonshotAI/kimi-cli

Learn Matplotlib in 30 Minutes In this video, you'll learn how to use the Matplotlib library in Python. If you're interested at all in data science, AI, machine learning, or scientific computing, then Matplotlib is a must learn. https://www.youtube.com/watch?v=7Lc2AxiM17o

hive Outcome driven agent development framework that evolves. https://github.com/adenhq/hive

redress redress is a failure-policy library for Python services. It treats retries, circuit breakers, and stop conditions as coordinated responses to classified failure, rather than independent wrappers. https://github.com/aponysus/redress

Al is killing programming and the Python community https://www.reddit.com/r/Python/s/bIYkLZu9Se

4 Pyrefly Type Narrowing Patterns that make Type Checking more Intuitive Learn about 4 ways Pyrefly narrows types, reducing the need to explicitly cast in your code. https://pyrefly.org/blog/type-narrowing/

OpenHands / OpenHands 🙌 OpenHands: AI-Driven Development https://github.com/OpenHands/OpenHands

earth2studio Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows. https://github.com/NVIDIA/earth2studio

Prototyping a Live Product Recommender With Python The article shows how to build a real-time product recommender prototype in Python using Contextual Multi-Armed Bandits to simulate user behavior and validate online learning algorithms like LinUCB. It explains why bandits handle cold-start and context better than traditional models, walks through data generation, feature engineering, offline evaluation, and sets up a live simulation as ... https://jaehyeon.me/blog/2026-01-29-prototype-recommender-with-python/

Microcode Microcode is an efficient terminal-based AI agent with an internal REPL environment for coding assistance. It leverages Reasoning Language Models (RLMs) to help developers with coding tasks directly from the command line. https://github.com/modaic-ai/microcode

PicoFlow – a tiny DSL-style Python library for LLM agent workflows https://news.ycombinator.com/item?id=46706535

I created a game engine for Django? The author built a multiplayer Snake game in the browser using only Python and Django LiveView, with no custom JavaScript, by keeping game state on the server and broadcasting rendered HTML over WebSockets. https://en.andros.dev/blog/6e9e4485/i-created-a-game-engine-for-django/

Let's Build Pipeline Parallelism from Scratch The tutorial walks through building pipeline parallelism from the ground up, explaining how to split large AI models and training workloads across multiple GPUs to improve training efficiency. It breaks down concepts with step-by-step examples so developers can understand how data and compute are partitioned and coordinated in a distributed training system. https://www.youtube.com/watch?v=D5F8kp_azzw

Oban, the job processing framework from Elixir, has come to Python https://www.dimamik.com/posts/oban_py/

Vision-Agents Open Vision Agents by Stream. Build Vision Agents quickly with any model or video provider. Uses Stream's edge network for ultra-low latency. https://github.com/GetStream/Vision-Agents