PythonHub

Just for fun: animating a mosaic of 90s GIFs The post describes an experiment in animating a mosaic of vintage 90s GIFs collected from the GeoCities archive, using HTML Canvas for random, lively playback. It celebrates the playful aesthetics of early web graphics and highlights the technical and nostalgic joy of reintroducing these classic GIFs into a modern browser setting. https://alexplescan.com/posts/2025/09/15/gifs/

Sphinx Docs Instantly in Your Browser (MyST Markdown + reStructuredText) Edit and preview reStructuredText or MyST Markdown instantly in a Sphinx running in a browser. Runs entirely in Python using WebAssembly, so it’s private, fast, and ideal for learning markup. https://snippets.documatt.com

Mini-o3 Scaling Up Reasoning Patterns and Interaction Turns for Visual Search. https://mini-o3.github.io/

List of 87 Programming Ideas for Beginners (with Python implementations) https://www.reddit.com/r/Python/comments/1nitzoz/list_of_87_programming_ideas_for_beginners_with/

detroit detroit is a Python implementation of d3js. https://github.com/bourbonut/detroit

Python 3.13 is 10% slower than 3.12 for my file parser https://www.reddit.com/r/Python/comments/1nmuy7t/python_313_is_10_slower_than_312_for_my_file/

Microsoft Python Driver for SQL Server https://github.com/microsoft/mssql-python

Nvmath-Python: Nvidia Math Libraries for the Python Ecosystem https://github.com/NVIDIA/nvmath-python

Post-training 101 A hitchhiker's guide into LLM post-training. https://tokens-for-thoughts.notion.site/post-training-101

Python Hub Weekly Digest for 2025-09-21 https://pythonhub.dev/digest/2025-09-21/

Jaxformer Scaling Modern Transformers This is a zero-to-one guide on scaling modern transformers with n-dimensional parallelism. Transformers have driven much of the deep learning revolution, yet no practical guide reflects SOTA architectures and the complexities of large-scale language modelling. While excellent resources such as DeepMind’s How to Scale Your Model and HuggingFace’s Ultra Scale Playbook exist, a gap remains ... https://jaxformer.com/

datalab-to / marker Convert PDF to markdown + JSON quickly with high accuracy https://github.com/datalab-to/marker

TensorRT-Model-Optimizer A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM or TensorRT to optimize inference speed. https://github.com/NVIDIA/TensorRT-Model-Optimizer

I decoupled FastAPI dependency injection system in pure python, no dependencies. https://www.reddit.com/r/Python/comments/1ndj5vz/i_decoupled_fastapi_dependency_injection_system/

wall-x Building General-Purpose Robots Based on Embodied Foundation Model. https://github.com/X-Square-Robot/wall-x

IBM / mcp-context-forge A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP). https://github.com/IBM/mcp-context-forge

Add Agents to your Web Applications with Pydantic AI and Django The video demonstrates how to integrate Pydantic AI with Django to add agent-like features to web applications, allowing developers to enrich chatbots with app-specific context and tools such as real-time weather services and database interactionsattached file. It showcases building customizable agents that can use dependencies, execute functions, and securely manipulate database recor... https://www.youtube.com/watch?v=Z33IBfgVbxI

HunxByts / GhostTrack Useful tool to track location or mobile number https://github.com/HunxByts/GhostTrack

Pyproc – Call Python from Go Without CGO or Microservices https://github.com/YuminosukeSato/pyproc

Python REPL Shortcuts & Features Python 3.13 introduced a completely redesigned REPL with a much more modern feel. It's easy to overlook many of the features in the new Python REPL. Let's explore the various hidden features the new Python REPL supports, with a focus on tips that are useful for everyday usage. https://www.pythonmorsels.com/repl-features/