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News & links about Python programming. https://pythonhub.dev/

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Create space-saving clones on macOS with Python https://alexwlchan.net/2025/cloning-with-python/

Python performance myths and fairy tales https://lwn.net/SubscriberLink/1031707/73cb0cf917307a93/

joinly Build personalized, conversational meeting agents in minutes https://github.com/joinly-ai/joinly

PYX: The next step in Python packaging https://astral.sh/blog/introducing-pyx

HRT's Python Fork: Leveraging PEP 690 for Faster Imports https://www.hudsonrivertrading.com/hrtbeat/inside-hrts-python-fork/

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/

PyPI: Preventing ZIP parser confusion attacks on Python package installers https://blog.pypi.org/posts/2025-08-07-wheel-archive-confusion-attacks/

I built an offline, open‑source desktop Pixel Art Editor in Python https://github.com/danterolle/tilf

Representing Python notebooks as dataflow graphs https://marimo.io/blog/dataflow

QwenLM / Qwen3 Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud. https://github.com/QwenLM/Qwen3

Python Hub Weekly Digest for 2025-08-10 https://pythonhub.dev/digest/2025-08-10/

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/

Uvify Turn python repositories to environments and oneliners with uv python manager, without diving into the code. https://github.com/avilum/uvify

Vulnhuntr Zero shot vulnerability discovery using LLMs. https://github.com/protectai/vulnhuntr

Enterprise AI Tutorial – Embeddings, RAG, and Multimodal Agents Using Amazon Nova and Bedrock Amazon Nova’s course teaches Embeddings, RAG, Multimodal Models, and Agents using tools like Bedrock, LangChain, and Titan Embeddings to build real-world AI applications. You’ll learn to automate workflows like insurance claims by integrating Bedrock Agents and Knowledge Bases for smarter, faster customer service. https://www.youtube.com/watch?v=HaUe2AN210g

Executing arbitrary Python code from a comment The article explains how, in a CTF challenge, seemingly harmless Python code that only allows user input in a comment can actually be exploited for arbitrary code execution by constructing a valid ZIP file within the comment and leveraging Python's ability to run ZIP archives. By carefully crafting an ASCII-safe ZIP archive (with a main.py), even restrictive single-line comments can trig... https://www.hacktron.ai/blog/posts/python-zip-confusion