PythonHub

TurboAPI FastAPI-compatible Python framework. Zig HTTP core. 7x faster. https://github.com/justrach/turboAPI

dimos The Agentive Operating System for Physical Space. https://github.com/dimensionalOS/dimos

parameter-golf Train the smallest LM you can that fits in 16MB. Best model wins! https://github.com/openai/parameter-golf

mvanhorn / last30days-skill AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary https://github.com/mvanhorn/last30days-skill

Build a smart financial assistant with LlamaParse and Gemini 3.1 Learn how to extract high-quality data from complex, unstructured PDFs using LlamaParse powered by Gemini 3.1 Pro. This guide demonstrates an event-driven workflow to automate the parsing of dense financial tables and generate intelligent summaries with Gemini 3.1 Flash. Perfect for developers building scalable document-parsing pipelines and AI personal finance assistants. https://developers.googleblog.com/build-a-smart-financial-assistant-with-llamaparse-and-gemini-31/

Modern Terminal User Interfaces in Python In this video, we take a quick look at how to easily develop Terminal User Interfaces (TUIs) in Python using a package called blessed. https://www.youtube.com/watch?v=RJ-ZFzaEvzM

Reducing Pydantic's memory footprint using bitsets In this post, we are going to see how the original issue was investigated and how we can leverage bitsets to greatly reduce the memory usage of Pydantic model instances. https://pydantic.dev/articles/pydantic-bitset-performance

Stop Passing Primitives Everywhere (Use Value Objects) By replacing primitives with immutable Value Objects, you can centralize validation and eliminate domain ambiguity for types like prices and percentages. This pattern ensures that invalid states are impossible to represent, creating a self-documenting and more reliable codebase without the overhead of heavy frameworks. https://www.youtube.com/watch?v=CWYwz3iV1g0

openclaw / skills All versions of all skills that are on clawhub.com archived https://github.com/openclaw/skills

Building an Invisible Daemon Many developer tools need a long-running local process — an LSP server, a file watcher, an indexing service. The challenge isn't just building the daemon. It's making it invisible. https://cocoindex.io/blogs/building-an-invisible-daemon

The Slow Collapse of MkDocs How personality clashes, an absent founder, and a controversial redesign fractured one of Python's most popular projects. https://fpgmaas.com/blog/collapse-of-mkdocs/

Avoiding empty strings in non-nullable Django string-based model fields Django allows empty strings ('') even on non-nullable string fields, so you must explicitly enforce non-empty values using validation or database constraints rather than relying on null=False. The post argues for treating empty strings as invalid at the model or DB level (e.g., validators or CHECK constraints) to ensure true “required” semantics for string fields. https://peateasea.de/avoiding-empty-strings-in-non-nullable-django-string-based-model-fields/

ClawTeam One Command Line: Full Automation - agents spawn swarms, delegate tasks, and deliver results. https://github.com/HKUDS/ClawTeam

AutoResearchClaw Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. https://github.com/aiming-lab/AutoResearchClaw

D-MemFS In-process virtual filesystem with hard quota for Python. https://github.com/nightmarewalker/D-MemFS

GraphZero High-Performance, Zero-Copy Graph Engine for Massive Datasets on Consumer Hardware. https://github.com/KrishSingaria/graphzero

Python Hub Weekly Digest for 2026-03-29 https://pythonhub.dev/digest/2026-03-29/

Python Hub Weekly Digest for 2026-03-22 https://pythonhub.dev/digest/2026-03-22/

Invent your own comprehensions in Python Python doesn't have tuple, frozenset, or Counter comprehensions, but you can invent your own by passing a generator expression to any iterable-accepting callable. https://www.pythonmorsels.com/custom-comprehensions/

Pytest parameter functions The post shows how to make complex pytest.mark.parametrize data more readable and maintainable by wrapping each test case in small helper functions instead of raw tuples. It also demonstrates using pytest.param with custom IDs inside those helpers so long, messy parameter values become clear, concise test names that are easier to work with. https://nedbatchelder.com/blog/202602/pytest_parameter_functions