PythonHub

Automate Excel with Python: From manual grind to one-click workflow https://nostarch.com/automate-excel-with-python

A peek into Reddit's anti-spam internals How Reddit accidentally leaked its spamurai system. https://lyra.horse/blog/2026/06/reddit-spam-internals/

Sandboxing an AI Agent The post explains why autonomous AI agents should run in isolated sandboxes instead of directly on a developer’s laptop, especially as agents gain auto-approval, long-running tasks, file access, and network access. It compares sandbox architectures, from tool-backend setups to agents living fully inside the sandbox, and explains the tradeoffs across security, secrets, streaming, performa... https://sajalsharma.com/posts/sandboxing-an-ai-agent/

antigravity-sdk-python A Python library for building AI agents that leverage the full power of Google Antigravity. https://github.com/google-antigravity/antigravity-sdk-python

PEP 814: Add frozendict built-in type The post explains the path from rejected PEP 416 and stalled PEP 603 to accepted PEP 814, which adds a built-in frozendict type to Python 3.15. It covers how frozendict works, why it is hashable only when values are hashable, where the standard library now supports it, and what C/Python code may need to update. https://vstinner.github.io/pep-814-add-frozendict-builtin-type.html

Miles: A PyTorch-Native Stack for Large-Scale LLM RL Post-Training Miles is an open source PyTorch-native framework for large-scale LLM reinforcement-learning post-training, combining SGLang for rollouts, Megatron-LM for training, Ray for orchestration, and PyTorch for extensibility. The post explains how Miles handles the hard systems problems behind frontier RL, including async rollout/training, fast weight sync, MoE alignment, low-precision recipes, ... https://pytorch.org/blog/miles-a-pytorch-native-stack-for-large-scale-llm-rl-post-training/

Pure-Python symbolic regression that rediscovered Kepler's law from 8 data point https://github.com/ariel95500-create/gp-elite

harvard-edge / cs249r_book Machine Learning Systems https://github.com/harvard-edge/cs249r_book

Hamiltonian Neural Networks from a Differential Geometry Perspective The post explains Hamiltonian Neural Networks through differential geometry, showing why a normal MLP can fit motion data but still invent or lose energy over long rollouts. It shows that by learning a scalar Hamiltonian and deriving motion through the symplectic gradient, HNNs make energy conservation structurally unavoidable instead of hoping the network learns it from data. https://abscondita.com/blog/symplectic-sledgehammer-for-a-spring

Protobuf-py: Protobuf for Python, without compromises https://buf.build/blog/protobuf-py

ProtoMotions3 A GPU-Accelerated Framework for Simulated Humanoids. https://github.com/NVlabs/ProtoMotions

ipblocklist IP lists full of bad IPs - Updated every 2H. https://github.com/bitwire-it/ipblocklist

Write a coding agent from first principles: better tools This tutorial builds on the coding agent you implemented in the tutorial “Write a coding agent from first principles”. In this tutorial, you'll take your agent and improve its capabilities by implementing the text edit and bash command tools that Anthropic provides. https://mathspp.com/blog/write-a-coding-agent-from-first-principles-better-tools

You shouldn't trust Trusted Publishing The post explains that PyPI Trusted Publishing is an authentication mechanism for machine-to-machine trust between CI/CD workflows and package registries, not a signal that a package is safe or high quality. It shows how Trusted Publishing reduces long-lived credential risk, while warning that users should not treat it like a “green checkmark” because malicious or low-quality packages ca... https://blog.yossarian.net/2026/07/07/You-shouldnt-trust-trusted-publishing

Runloom – Go-style coroutines for Python free-threaded https://github.com/robertsdotpm/runloom

Otary – Image and Geometry Python Library Now Has Tutorials https://alexandrepoupeau.com/otary/learn/

bradautomates / claude-video Give Claude the ability to watch any video. /watch downloads, extracts frames, transcribes, hands it all to Claude. https://github.com/bradautomates/claude-video

fortress Stealth Chromium engine that stops scrapers and browser agents from getting blocked, with one line of code change. https://github.com/tiliondev/fortress

cupy / cupy NumPy & SciPy for GPU https://github.com/cupy/cupy

How to publish to PyPI using GitHub Actions securely The post gives three practical steps for publishing Python packages to PyPI more securely from GitHub Actions: run zizmor, use Trusted Publishing, and require manual approval through GitHub environments. It focuses on reducing credential risk by removing long-lived PyPI tokens, pinning actions, limiting workflow permissions, disabling persisted checkout credentials, and adding a human ap... https://snarky.ca/how-to-publish-to-pypi-using-github-actions-securely/