Polar

Open Source payments infrastructure for the 21st century

https://github.com/polarsource/polar

wshobson / agents

Intelligent automation and multi-agent orchestration for Claude Code

https://github.com/wshobson/agents

hyperflask

Full stack Python web framework to build websites and web apps with as little boilerplate as possible

https://github.com/hyperflask/hyperflask

uv-lock-report

A GitHub Action to report changes to uv.lock.

https://github.com/mw-root/uv-lock-report

DeepAnalyze: Agentic Large Language Models for Autonomous Data Science

DeepAnalyze is the first agentic LLM for autonomous data science, supporting:
🛠 Data preparation, analysis, modeling, visualization, and insight.
🔍 Data research and produce research report.

https://ruc-deepanalyze.github.io/

The future of Python web services looks GIL-free

The free-threaded Python variant in 3.14 removes the Global Interpreter Lock (GIL), enabling true parallel multithreading for CPU-bound tasks. While it may have a modest performance cost on single-threaded code, it significantly improves memory efficiency and concurrency in web applications, simplifying deployment and boosting throughput, especially for ASGI and WSGI based services.​

https://blog.baro.dev/p/the-future-of-python-web-services-looks-gil-free

Three times faster with lazy imports

This post tests Python 3.15’s proposed PEP 810 explicit lazy imports, which delay loading modules until first use to cut startup time.? Using the feature on author's CLI tool pypistats, he found it ran 2.92× faster (reducing startup from 104 ms to 36 ms), demonstrating how lazy imports can significantly speed up Python applications with large dependency graphs.

https://hugovk.dev/blog/2025/lazy-imports/

DeepAnalyze: Agentic Large Language Models for Autonomous Data Science

DeepAnalyze is the first agentic LLM for autonomous data science, supporting:
🛠 Data preparation, analysis, modeling, visualization, and insight.
🔍 Data research and produce research reports.

https://github.com/ruc-datalab/DeepAnalyze

Recursive Language Models

Recursive Language Models (RLMs) let language models recursively call themselves within an environment, like a Python REPL, to handle extremely long contexts without performance drop (context rot). They dynamically break down queries into smaller parts, delivering strong, cost-efficient results on big benchmarks and enabling scalable, interpretable reasoning beyond fixed context limits.

https://alexzhang13.github.io/blog/2025/rlm/

Introducing PyTorch Monarch

PyTorch Monarch is a distributed programming framework designed to simplify scaling AI workflows by enabling a single-controller model that orchestrates distributed resources like a single machine. It provides actor-based programming with scalable messaging, fault tolerance, and distributed tensor support, allowing seamless development, debugging, and efficient handling of large-scale tr...

https://pytorch.org/blog/introducing-pytorch-monarch/

Katakate

Self-hosted secure VM sandboxes for AI compute at scale.

https://github.com/Katakate/k7

caniscrape

Know before you scrape. Analyze any website's anti-bot protections in seconds.

https://github.com/ZA1815/caniscrape

Create Your Own Bash Computer Use Agent with NVIDIA Nemotron in One Hour

A tutorial on building a computer use AI agent capable of executing multi-step tasks in a Bash shell, powered by the NVIDIA Nemotron Large Language Model. It covers creating the agent's brain, the Bash interface for safe command execution, and the agent loop, demonstrating how to build and deploy an autonomous assistant within an hour.

https://www.youtube.com/watch?v=F7f-eFou2-o