ClawTeam

One Command Line: Full Automation - agents spawn swarms, delegate tasks, and deliver results.

https://github.com/HKUDS/ClawTeam

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/

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/

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

openclaw / skills

All versions of all skills that are on clawhub.com archived

https://github.com/openclaw/skills

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

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

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

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/

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

parameter-golf

Train the smallest LM you can that fits in 16MB. Best model wins!

https://github.com/openai/parameter-golf

dimos

The Agentive Operating System for Physical Space.

https://github.com/dimensionalOS/dimos

TurboAPI

FastAPI-compatible Python framework. Zig HTTP core. 7x faster.

https://github.com/justrach/turboAPI

open-terminal

A lightweight, self-hosted terminal that gives AI agents and automation tools a dedicated environment to run commands, manage files, and execute code — all through a simple API.

https://github.com/open-webui/open-terminal

Starlette 1.0

After nearly eight years since its creation, Starlette has reached its first stable release. Today, it's downloaded almost 10 million times a day, serves as the foundation for FastAPI, and has inspired many other frameworks. In the age of AI, Starlette continues to play an important role as a dependency of the Python MCP SDK.

https://marcelotryle.com/blog/2026/03/22/starlette-10-is-here/

ProperDocs

ProperDocs is a static site generator intended for project documentation. Source files are written in Markdown and converted to static HTML during the build process.

https://github.com/ProperDocs/properdocs

Pydantic AI intro - Agents and Instructions!

In this video, we'll take a look at Agents in Pydantic AI, and will create a simple Agent that can be run synchronously and asynchronously. We'll explore how to inspect agent outputs, and how to amend outputs using instructions that are passed to the LLM.

https://www.youtube.com/watch?v=XyGHYG7QNK0

Terrapod

Open-source Terraform Enterprise replacement.

https://github.com/mattrobinsonsre/terrapod