1140
News & links about Python programming. https://pythonhub.dev/ Administrator: @rukeba
numba-metal
An out-of-tree GPU backend that lets you write a constrained subset of Numba-style Python kernels and run them on the GPU of Apple-silicon Macs through Metal.
https://github.com/eviking/numba-metal
Python sets and dictionaries can have quadratic-time performance
https://lemire.me/blog/2026/09/03/python-sets-and-dictionaries-can-have-quadratic-time-performance/
microsoft / data-formulator
🪄 Data Formulator is an interactive AI-powered data analysis system makes it easy to connect, explore and visualize data.
https://github.com/microsoft/data-formulator
Libraries Run Rust Inside Python (With PyO3)
https://belderbos.dev/blog/how-libraries-run-rust-inside-python/
Inside the megakernel serving engine for North Mini Code
A technical deep dive into how Cohere’s approach to megakernels delivers 1.58x faster LLM serving on H100 devices.
https://cohere.com/blog/megakernels
On solving the Jane Street Reverse Engineering Challenge
Jane Street’s ASIC reverse-engineering challenge turns a raw chip-layout file into a month-long puzzle about reconstructing how the circuit works. The author uses Python, graph algorithms, Verilog, simulation, and Z3 to recover the design, solve the challenge, and even uncover a real hardware bug.
https://jestoph.com/2026/09/04/jane-street-challenge.html
AWS Lambda Functions in Python: A Practical Guide
https://middleware.io/blog/aws-lambda-functions-in-python/
hip-agent
A minimal coding agent harness that fits in the prompt.
https://github.com/changjonathanc/hip-agent
cloud-in-a-bottle
Deploy, use, and share web apps on a server you control. Your apps, data, and infrastructure stay yours.
https://github.com/cloud-in-a-bottle/cloud-in-a-bottle
Ruff, mypy, pytest, and then what?
Structural quality in the age of AI-written Python. What the standard toolchain checks, what it does not, and what a real agent-written repository looks like when you measure it.
https://codescan.dev/blog/ruff-mypy-pytest-and-then-what
Python Hub Weekly Digest for 2026-09-13
https://pythonhub.dev/digest/2026-09-13/
OpenExecutive
AI-powered virtual executive team, a single coherent executive persona backed by 8 specialist Claude agents (FastAPI + Next.js).
https://github.com/SenteLabsAI/OpenExecutive
Neocarta
Library built for generating semantic layer graphs for query routing, query generation and data discovery.
https://github.com/neo4j-labs/neocarta
experiential
An open source model gateway that provides one control plane across closed, open-source, local, and custom models.
https://github.com/experientiallabs/experiential
Nifty Django Feature: Use Index for Custom Migration Operations
Part of the Nifty Django features series: You can hack Django's Index class to define custom migration operations on your model.
https://www.better-simple.com/django/2026/09/02/nifty-feature-use-index-for-custom-migrations/
Astral's python distribution is fast
https://www.reddit.com/r/Python/comments/1wdbhda/astrals_python_distribution_is_fast/
Qwen-Drive
An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving.
https://github.com/QwenLM/Qwen-Drive-1.0
Turn SQLite Into A Vector Database For RAG
This video demonstrates how to turn SQLite into a vector database for AI applications using the sqlite-vec and sqlite-ai-vector extensions. It covers setting up both packages in Python with OpenAI embeddings, implementing similarity search and metadata filtering, and benchmarking their performance, memory efficiency, and quantization capabilities.
https://www.youtube.com/watch?v=VlEoSzkd2gQ
How to Stop Third-Party APIs From Ruining Your Code
The video explains the Facade pattern using a Stripe payment integration to show how it can isolate external APIs from application code. It covers reducing coupling, improving testability, and creating cleaner boundaries that are easier to maintain and evolve.
https://www.youtube.com/watch?v=vskwNNdnqMc
package-doctor: finds Python dependencies at a trust boundary with no one left to fix them
Flags packages that handle untrusted input and look unmaintained. Ranks advisories by real exploitation. Runs beside pip-audit.
https://github.com/binuka200/package-doctor
MongoDB migrations in Python
https://dblift.com/blog/mongodb-migrations-python
Teaching NumPy's ufuncs new tricks
The post explains how NumPy’s universal functions (ufuncs) work in C and how their internals were upgraded to support multi-output reductions, enabling the long-requested np.minmax function. It also covers ongoing work on segmented reductions for ragged data and converting existing functions into generalized ufuncs (gufuncs) for subarray processing.
https://labs.quansight.org/blog/teaching-numpys-ufuncs-new-tricks
Reading __dict__ once permanently deoptimizes attribute access
Since 3.11 attribute access has not been a dict lookup, and reading dict once takes the specialized path away for good
https://deadlovelll.github.io/2026-09-05-reading-dict-deoptimizes-attribute-access/
TPU Inference Externalization Full Steam Ahead
The article examines Google’s push to make TPUs a first-class platform for external LLM inference, including TorchTPU, vLLM, SGLang, and a rapidly maturing open software stack. Benchmarks TPUv7 Ironwood against NVIDIA B200/B300 and dives into the kernel, memory, networking, and serving optimizations behind its performance-per-dollar gains.
https://inferencex.semianalysis.com/blog/tpu-inferencex-full-steam
Citry
Fully typed frontend framework for Python with server events and Alpine.js, inspired by Vue and Livewire.
https://github.com/citry-dev/citry
K-Dense-AI / scientific-agent-skills
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 190,000+ scientists worldwide. 165 ready-to-use validated skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
https://github.com/K-Dense-AI/scientific-agent-skills
Fine-Tuning SOTA Object Detection Models on Real-World Datasets
Learn how to use these models, how to fine-tune them on diverse, specialized datasets that look nothing like their training data, and how to evaluate the results – all within PyCharm.
https://blog.jetbrains.com/pycharm/2026/08/fine-tuning-sota-object-detection-models-on-real-world-datasets/
index-tts / index-tts
An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
https://github.com/index-tts/index-tts
Building AI Agents in Pure Python - Beginner Course
Build a fully functioning AI agent from scratch in pure Python, without frameworks, third-party tools, or vibe coding. The course focuses on the core mechanics behind agents so you understand how they work under the hood, not just how to prompt existing tools.
https://www.youtube.com/watch?v=c9AnqCeyxbI
KV, Prefix, Prompt and Semantic Caching in LLMs, clearly explained
The post explains the four caching layers in LLM stacks: KV cache, prefix caching, prompt caching, and semantic caching, covering what each stores, their trade-offs, interactions, and the most common issues that prevent reuse. It includes first-principles explanations, code demos (with transformers and vLLM-style logic), production pitfalls, and practical takeaways for reducing recomputa...
https://x.com/_avichawla/status/2093265776266637739