Reading up on python
30 deep · digging since nov 20, 25
- Why OOP exists | mathspp
The article explains that OOP exists to model real-world entities via abstractions, showing how Python classes encapsulate data and behavior.
- Introducing Stagehand v4: The SDK for browser agents.
Stagehand v4 moves browser automation state management into a Chrome extension, enabling feature-parity SDKs in TypeScript, Python, and Go by treating the remote browser as the source of truth.
- What's the best programming language for coding agents?
Dan Luu's empirical tests with LLMs on Zstd and Pandoc implementations show that language popularity weakly correlates with better outcomes, but claims about dynamic or token-efficient languages being superior for coding agents do not hold across non-trivial tasks.
- What is fenic? - fenic, by typedef
fenic is a PySpark-inspired DataFrame framework built from scratch for LLM inference, featuring semantic operators, native unstructured data support, and batch inference across providers.
- In Defense of YAML :: Posit Open Source
Posit releases py-yaml12, a Rust-backed Python library implementing YAML 1.2, arguing many criticisms of YAML stem from outdated PyYAML's 1.1 behavior rather than the modern spec.
- What’s new in Python 3.15 — Python 3.15.0b2 documentation
Python 3.15 introduces PEP 810, which enables explicit lazy imports to defer module loading and improve startup performance.
- Use boring languages with LLMs
Using boring languages like Go with LLMs reduces variance in training data, leading to more predictable and reliable code generation.
- Honker | Honker
Honker is a SQLite extension that provides durable queues, pub/sub, and task scheduling within the same database file, enabling atomic transactional enqueue without a separate broker like Redis.
- Agents can't choose between structure and flexibility
The article argues that employing pure code or pure markdown to specify AI agent behavior is a failure mode, and advocates for a hybrid approach.
- Show HN: Plain – The full-stack Python framework designed for humans and agents
Plain, a fork of Django with opinionated defaults and Postgres-only models, claims to be optimized for both human developers and AI coding agents.
- Mechanical sympathy
Good engineers possess mechanical sympathy—an intuitive feel for affordances and boundaries—which current AI coding agents lack, leading to context-blind fixes and poor product design.
- Astral to Join OpenAI
Astral, the company behind Python tools Ruff and uv, has agreed to join OpenAI's Codex team to continue building open-source tooling at the frontier of AI and software development.
- Thoughts on OpenAI acquiring Astral and uv/ruff/ty
OpenAI acquires Astral, the company behind uv, ruff, and ty, to accelerate Codex development while promising continued open-source support.
- Python 3.15's JIT is now back on track
CPython's volunteer-driven JIT project achieved 11-12% speedups on macOS AArch64 and is back on track for Python 3.15, overcoming funding loss and earlier performance setbacks.
- A case for Go as the best language for AI agents
The Hacker News discussion debates whether Go's simplicity, fast compilation, and opinionated style make it ideal for AI agents, with commenters offering counterarguments favoring Python, Rust, and other languages.
- GitHub - apple/python-apple-fm-sdk: Python bindings for access to the on-device model at the core of Apple Intelligence through the Foundation Models framework
Apple released a Python SDK for accessing the on-device foundation model powering Apple Intelligence on macOS.
- Parse, Don't Validate (2019)
The article argues that data should be parsed into types that make illegal states unrepresentable at system boundaries, rather than scattered through validation checks.
- Two kinds of AI users are emerging. The gap between them is astonishing. - Martin Alderson
A bifurcation in AI adoption sees power users shipping products in days with tools like Claude Code, while enterprise users remain stuck with poor tools like Microsoft Copilot, widening a productivity gap.
- Show HN: A creative coding library for making art with desktop windows
A Python library called window-art enables live coding animations of desktop windows with moves, fades, colors, and media display.
- Introducing FastMCP 3.0 🚀
FastMCP 3.0 introduces a composable architecture based on Components, Providers, and Transforms to build durable, production-ready MCP servers in Python.
- Show HN: TinyCity – A tiny city SIM for MicroPython (Thumby micro console)
TinyCity is a SimCity-inspired city simulation game built for the Thumby micro console running MicroPython.
- Building Agents with the Gemini Interactions API
Building an agent with the Gemini Interactions API requires only an LLM loop, tool definitions, and server-side state management in under 100 lines of Python.
- Anthropic invests $1.5M in the Python Software Foundation
Anthropic donated $1.5 million over two years to the Python Software Foundation, earmarked primarily for improving Python ecosystem security and supply-chain protection.
- Why AI is pushing developers toward typed languages - The GitHub Blog
AI-generated code's unreliability pushes developers toward typed languages like TypeScript, which catch type-check errors that cause 94% of LLM compilation failures.
- Python numbers every programmer should know
A reference of Python memory and latency numbers for common operations, aiming to help developers build a mental model of performance costs.
- Technology | 2025 Stack Overflow Developer Survey
Python adoption accelerated sharply in 2025, Docker saw a record +17 point usage jump, and Rust remained the most admired language, according to the Stack Overflow Developer Survey.
- Ask HN: What open source projects are you grateful for?
In an Ask HN post, commenters list open source projects they are grateful for, such as Linux, Git, Vim, and Python.
- GitHub - facebook/pyrefly: A fast type checker and language server for Python
Meta开源Pyrefly,一个比Mypy和Pyright快15倍以上的Python类型检查器和语言服务器。
Takes
Fable one-shotted a Rust rewrite of the TerminalTextEffects Python library in 11M tokens. Startup time went from 87ms to 2ms and rendering speed is up by 9.6x. Now zero dependencies and a 3mb single exec 🤯 https://claude.ai/code/artifact/287825bc-7aad-4541-a7e7-fa4ba8d03612
@dhh
One of the most productive engineers I know cannot read code. @mvanhorn is not an engineer by training. He co-founded June, has 44,000 GitHub stars, and got contributions merged into Go & Python. I had him build live for an hour & walk me through his process. My fav lessons & quotes from the convo: 1) He never reads code. He does not have an IDE installed. In his words, "I fundamentally believe that very soon no humans should ever write any code and that no humans should ever read any code." 2) Every project starts with the agent writing itself a plan.md file using Compound Engineering. Agents are lazy, he says, and the plan keeps them honest. He never reads the plan either. "Plans are for agents, you silly human." 3) His CLIs leave notes for themselves. Each run records what it learned in a markdown file, so the next run starts where the last one ended. He calls them self-healing. 4) His agent has an email address. From Telegram on his phone, he sends a task. It emails his Mac, authenticated, and the work starts while he is at his kids' soccer practice. 5) He feeds whole transcripts, not summaries. After a two-hour meeting with a Google Ventures researcher, his agent read the researcher's entire book, wrote itself a report on every chapter, and turned it all into a plan for his business. 6) Him yapping to his agents is like nerd ASMR. "Go agent go" is how he likes to finish telling the agent what to do. 7) How he thinks about this next chapter of building: "Every generation of tools moves the engineer's job up a level. The code was never the point. The problem was."
@businessbarista