PythonHub

djobs.dev Asyncio Demystified: Rebuilding it From Scratch One Yield at a Time https://djobs.dev

LlamaFirewall The framework to detect and mitigate AI centric security risks. https://meta-llama.github.io/PurpleLlama/LlamaFirewall/

blast A high-performance serving engine for web browsing AI. https://github.com/stanford-mast/blast

Using Python to Automate 3D Workflows with OpenUSD The post explains how Python’s scripting capabilities can automate and streamline 3D workflows using OpenUSD, making tasks like data transformation, validation, and scene creation more accessible and efficient. It highlights NVIDIA’s tools, SDKs, and learning resources that empower developers to build, validate, and optimize complex 3D scenes with Python in the OpenUSD ecosystem. https://developer.nvidia.com/blog/using-python-to-automate-3d-workflows-with-openusd/

SQL-tString SQL-tString allows for f-string like construction of sql queries. https://github.com/pgjones/sql-tstring

Ty: A fast Python type checker and language server, written in Rust https://github.com/astral-sh/ty

plexe Build a machine learning model from a prompt. https://github.com/plexe-ai/plexe

Python Hub Weekly Digest for 2025-05-11 https://pythonhub.dev/digest/2025-05-11/

GoogleCloudPlatform / agent-starter-pack A collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges (Deployment & Operations, Evaluation, Customization, Observability) in building and deploying GenAI agents. https://github.com/GoogleCloudPlatform/agent-starter-pack

Using JWTs in Python Flask REST Framework This post provides a comprehensive guide to implementing JWT-based authentication in a Flask API. It covers setting up the Flask environment, creating a to-do list API, managing user sessions with token refresh, and adding role-based permissions. https://blog.appsignal.com/2025/04/30/using-jwts-in-python-flask-rest-framework.html

CocoIndex - Open-source real-time data framework for AI Open-source real-time data framework for AI, supporting incremental processing and custom logic. SDK in Python. https://github.com/cocoindex-io/cocoindex

Kate and Python Language Server https://akselmo.dev/posts/kate-python-lsp/

sooperset / mcp-atlassian MCP server for Atlassian tools (Confluence, Jira) https://github.com/sooperset/mcp-atlassian

funstory-ai / BabelDOC Yet Another Document Translator https://github.com/funstory-ai/BabelDOC

Tkintergalactic - Declarative Tcl/Tk UI Library for Python https://github.com/leontrolski/tkintergalactic

Garmin Grafana A Python Script to fetch Garmin health data and populate that in a InfluxDB Database, for visualization long term health trends with Grafana. https://github.com/arpanghosh8453/garmin-grafana

evalstate / fast-agent Define, Prompt and Test MCP enabled Agents and Workflows https://github.com/evalstate/fast-agent

SQLFlow SQLFlow is a high-performance stream processing engine that simplifies building data pipelines by enabling you to define them using just SQL. Think of SQLFLow as a lightweight, modern Flink. https://github.com/turbolytics/sql-flow

Debugging Python f-string errors Brandon Chinn's blog post delves into a perplexing Python bug where using f"{x}" raises a TypeError, while str(x) functions correctly. He uncovers that f-strings internally invoke theformatmethod, which can behave unexpectedly when dealing with proxy objects, such as those introduced by Temporal's sandboxing mechanism. https://brandonchinn178.github.io/posts/2025/04/26/debugging-python-fstring-errors/

The Hidden Dangers of Python Decorators Python decorators look like a great way to add functionality—until they break your type safety, hide function requirements, and turn debugging into a nightmare. This video shows you why decorators can be dangerous, the biggest pitfalls to watch out for, and when you should actually use them. https://www.youtube.com/watch?v=dVnNc9oEnF8