PythonHub

In the Making of Python Fitter and Faster How Python's recent performance improvements work under the hood. https://sumercip.com/posts/making-python-fitter-and-faster/

Otter Wiki: A minimalistic wiki powered by Python, Markdown and git https://otterwiki.com/

Pyinstrument v5.0 - flamegraphs for Python! https://www.reddit.com/r/Python/comments/1g1az6i/pyinstrument_v50_flamegraphs_for_python/

I Understand Machine Learning with Numpy and PyTorch Better Since I Started Focusing on the Basics https://www.reddit.com/r/Python/comments/1g1uuyc/i_understand_machine_learning_with_numpy_and/

Python 3.13 and the Latest Trends: A Developer’s Guide to 2025 Learn about the exciting new features in Python 3.13. Get insider insights into the latest updates and learn about the plans for Python 3.14. https://www.youtube.com/live/GPwYSf1t8Lw

Python 3.13.0 The newest major release of Python introduces several new features including an improved interactive interpreter, an experimental free-threaded build mode, and a preliminary JIT, along with various optimizations and changes to the standard library. https://www.python.org/downloads/release/python-3130/

TypedDicts are better than you think This post explains how Python’s TypedDict can enhance code clarity and maintainability by enabling more precise type annotations in dictionaries. It discusses how TypedDict ensures type safety and helps with early error detection in dynamic programming environments. https://blog.changs.co.uk/typeddicts-are-better-than-you-think.html

Python client for the $20 Colmi R02 smart ring https://tahnok.github.io/colmi_r02_client/colmi_r02_client.html

Niquests Niquests is a simple, yet elegant, HTTP library. It is a drop-in replacement for Requests, which is under feature freeze. https://github.com/jawah/niquests

Django + Postgres: The Hunt for Long Running Queries Using django-pgactivity for application-level monitoring of database queries. https://pgilmartin.substack.com/p/django-postgres-the-hunt-for-long

Django dashboard give your django dashboard a new modern skin with new features, Mobile responsive and customizable on top of tailwindcss https://github.com/hypy13/django-daisy/

Splink Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends. https://github.com/moj-analytical-services/splink

Python and SysV shared memory The article explains how to use Python's ctypes to wrap SystemV shared memory functions (like shmat, shmget) for interprocess communication on systems restricted to Python 3.7. The author demonstrates creating, reading, writing, and destroying shared memory segments through Python, noting that while this approach isn't needed in Python 3.8+ due to built-in abstractions, it's useful in re... https://euroquis.nl/blabla/2024/10/08/shm.html

NanoCube Lightning fast OLAP-style point queries on Pandas DataFrames. https://github.com/Zeutschler/nanocube

Switching from virtualenvwrapper to direnv, Starship, and uv Earlier this week I considered whether I should finally switch away from virtualenvwrapper to using ... https://treyhunner.com/2024/10/switching-from-virtualenvwrapper-to-direnv-starship-and-uv/

CSnakes A tool for embedding Python into .NET projects. https://github.com/tonybaloney/csnakes

uv IS the Future of Python Packaging The video discusses the recent release of UV 0.3.0, a Python packaging tool that aims to streamline the development workflow by integrating features that allow it to serve as a comprehensive solution for managing Python projects. The presenter highlights its speed, ease of use, and potential to replace existing tools, while also addressing current limitations and areas for improvement in... https://www.youtube.com/watch?v=8UuW8o4bHbw

Django: Introducing Djade, a template formatter Happy DjangoCon US 2024 to you. Whilst I am not there, I have adopted the spirit of the season and ... https://adamj.eu/tech/2024/09/26/django-introducing-djade/

Scaling AI-Based Data Processing with Hugging Face + Dask The article demonstrates how to scale AI-based data processing using Hugging Face and Dask, progressing from processing 100 rows locally with pandas to handling 211 million rows across multiple GPUs in the cloud. It showcases the use of Dask for distributed computing, enabling efficient data loading, preprocessing of large datasets, and parallel model inference, with a practical example ... https://huggingface.co/blog/dask-scaling

gptme Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web, vision. https://github.com/ErikBjare/gptme