From Async/Await to Virtual Threads
Armin Ronacher revisits his earlier critique of async/await in Python, arguing for a simpler and more composable concurrency model built around structured, virtual threads that avoid colored functions and simplify cancellation and context passing. He proposes rethinking Python’s concurrency by embracing thread-first APIs with virtual thread groups, which can yield, cancel, and propagate ...
https://lucumr.pocoo.org/2025/7/26/virtual-threads/
Armin Ronacher revisits his earlier critique of async/await in Python, arguing for a simpler and more composable concurrency model built around structured, virtual threads that avoid colored functions and simplify cancellation and context passing. He proposes rethinking Python’s concurrency by embracing thread-first APIs with virtual thread groups, which can yield, cancel, and propagate ...
https://lucumr.pocoo.org/2025/7/26/virtual-threads/
Armin Ronacher's Thoughts and Writings
From Async/Await to Virtual Threads
A follow-up to how I wish async would work.
QwenLM / Qwen3
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
https://github.com/QwenLM/Qwen3
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
https://github.com/QwenLM/Qwen3
GitHub
GitHub - QwenLM/Qwen3: Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud. - QwenLM/Qwen3
I built an offline, open‑source desktop Pixel Art Editor in Python
https://github.com/danterolle/tilf
https://github.com/danterolle/tilf
GitHub
GitHub - danterolle/tilf: Tilf (Tiny Elf) is a free, simple yet powerful pixel art editor built with PySide6. It’s designed for…
Tilf (Tiny Elf) is a free, simple yet powerful pixel art editor built with PySide6. It’s designed for creating sprites, icons, and small 2D assets with essential drawing tools, live preview, undo/r...
PyPI: Preventing ZIP parser confusion attacks on Python package installers
https://blog.pypi.org/posts/2025-08-07-wheel-archive-confusion-attacks/
https://blog.pypi.org/posts/2025-08-07-wheel-archive-confusion-attacks/
blog.pypi.org
Preventing ZIP parser confusion attacks on Python package installers - The Python Package Index Blog
PyPI will begin warning and will later reject wheels that contain differentiable ZIP features or incorrect RECORD files.
Forget metaclasses; Python’s `__init_subclass__` is all you really need
https://www.reddit.com/r/Python/comments/1mevs3i/forget_metaclasses_pythons_init_subclass_is_all/
https://www.reddit.com/r/Python/comments/1mevs3i/forget_metaclasses_pythons_init_subclass_is_all/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
HRT's Python Fork: Leveraging PEP 690 for Faster Imports
https://www.hudsonrivertrading.com/hrtbeat/inside-hrts-python-fork/
https://www.hudsonrivertrading.com/hrtbeat/inside-hrts-python-fork/
Hudson River Trading
Inside HRT’s Python Fork: Leveraging PEP 690 for Faster Imports
At HRT, we’ve found that centralizing our codebase facilitates cross-team collaboration and rapid deployment of new projects. Therefore, the majority of our software development takes place in a monorepo, and our Python ecosystem is set up such that internal…
joinly
Build personalized, conversational meeting agents in minutes
https://github.com/joinly-ai/joinly
Build personalized, conversational meeting agents in minutes
https://github.com/joinly-ai/joinly
GitHub
GitHub - joinly-ai/joinly: Make your meetings accessible to AI Agents
Make your meetings accessible to AI Agents. Contribute to joinly-ai/joinly development by creating an account on GitHub.
OpenPipe / ART
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, Kimi, and more!
https://github.com/OpenPipe/ART
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, Kimi, and more!
https://github.com/OpenPipe/ART
GitHub
GitHub - OpenPipe/ART: Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on…
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more! - OpenPipe/ART
Why Python's deepcopy() is surprisingly slow (and better alternatives)
https://www.reddit.com/r/Python/comments/1mehrc0/why_pythons_deepcopy_is_surprisingly_slow_and/
https://www.reddit.com/r/Python/comments/1mehrc0/why_pythons_deepcopy_is_surprisingly_slow_and/
Reddit
From the Python community on Reddit: Why Python's deepcopy() is surprisingly slow (and better alternatives)
Explore this post and more from the Python community
Llmswap – Python package to reduce LLM API costs by 50-90% with caching
https://pypi.org/project/llmswap
https://pypi.org/project/llmswap
microsoft / MoGe
CVPR'25 Oral MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
https://github.com/microsoft/MoGe
CVPR'25 Oral MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
https://github.com/microsoft/MoGe
GitHub
GitHub - microsoft/MoGe: [CVPR'25 Oral] MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal…
[CVPR'25 Oral] MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision - microsoft/MoGe
Why Are Not More People Using These Python Libraries?
Python’s standard library is one of its greatest strengths, but many developers only scratch the surface. This video explores 10 powerful and sometimes overlooked modules that can simplify your code, improve performance, and eliminate unnecessary dependencies. From dataclasses and pathlib to functools, graphlib, and heapq, you’ll see practical, real-world examples of how to use these too...
https://www.youtube.com/watch?v=F09EK4ztG34
Python’s standard library is one of its greatest strengths, but many developers only scratch the surface. This video explores 10 powerful and sometimes overlooked modules that can simplify your code, improve performance, and eliminate unnecessary dependencies. From dataclasses and pathlib to functools, graphlib, and heapq, you’ll see practical, real-world examples of how to use these too...
https://www.youtube.com/watch?v=F09EK4ztG34
YouTube
Why Are Not More People Using These Python Libraries?
💡 Learn how to design great software in 7 steps: https://arjan.codes/designguide.
Python’s standard library is one of its greatest strengths, but many developers only scratch the surface. In this video, I explore 10 powerful and sometimes overlooked modules…
Python’s standard library is one of its greatest strengths, but many developers only scratch the surface. In this video, I explore 10 powerful and sometimes overlooked modules…
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