plexe

Build a machine learning model from a prompt.

https://github.com/plexe-ai/plexe

SQL-tString

SQL-tString allows for f-string like construction of sql queries.

https://github.com/pgjones/sql-tstring

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/

blast

A high-performance serving engine for web browsing AI.

https://github.com/stanford-mast/blast

LlamaFirewall

The framework to detect and mitigate AI centric security risks.

https://meta-llama.github.io/PurpleLlama/LlamaFirewall/

djobs.dev

Asyncio Demystified: Rebuilding it From Scratch One Yield at a Time

https://djobs.dev

Enhancing the Python ecosystem with type checking and free threading

Meta describes its efforts to enhance the Python ecosystem by advancing type checking and introducing free-threading capabilities, aiming to improve code reliability and performance at scale. The post highlights the technical challenges, solutions, and community collaboration involved in making Python more robust and concurrent for large-scale applications.

https://engineering.fb.com/2025/05/05/developer-tools/enhancing-the-python-ecosystem-with-type-checking-and-free-threading

ACI

An open source platform that connects your AI agents to 600+ tool integrations with multi-tenant auth, granular permissions, and access through direct function calling or a unified MCP server.

https://github.com/aipotheosis-labs/aci

Python type hints: mixin classes

The article explains how to properly add Python type hints to mixin classes, addressing common challenges with attributes that mixins assume exist in their base classes. It shows solutions using subclassing or protocols to satisfy type checkers like Mypy without compromising runtime behavior or type safety.

https://adamj.eu/tech/2025/05/01/python-type-hints-mixin-classes/

Making PyPI's test suite 81% faster

See how we slashed PyPI’s test suite runtime from 163 to 30 seconds.

https://blog.trailofbits.com/2025/05/01/making-pypis-test-suite-81-faster

RealtimeVoiceChat

Have a natural, spoken conversation with AI!

https://github.com/KoljaB/RealtimeVoiceChat

strif

A tiny, useful Python lib of string, file, and object utilities.

https://github.com/jlevy/strif

dataframely

A declarative, native data frame validation library

https://github.com/Quantco/dataframely

Suna

Open Source Generalist AI Agent.

https://github.com/kortix-ai/suna

Function calling using LLMs

While LLMs excel at generating cogent text based on their training data, they may also need to interact with external systems. Function calling allows them to construct such calls. The LLM does not execute these calls directly, instead it creates a data structure that describes the call, passing that to a separate program for execution and further processing. The LLM's prompt includes de...

https://martinfowler.com/articles/function-call-LLM.html

Asyncio Demystified: Rebuilding it From Scratch One Yield at a Time

The article demystifies Python’s asyncio by rebuilding its core concepts from scratch, starting with basic generators and coroutines, then constructing a cooperative multitasking scheduler, and finally integrating non-blocking I/O using custom awaitable Future objects. Through step-by-step code examples, it shows how Python’s async/await syntax is just syntactic sugar over these primitiv...

https://dev.indooroutdoor.io/asyncio-demystified-rebuilding-it-from-scratch-one-yield-at-a-time

Vibe Coding with Django, React and Cursor: My Experience and Takeaways

Cory Zue shares his experience with "vibe coding," a new approach to software development using AI tools, and how he built a Django/React app calleddjobs.devin just two days. He emphasizes the importance of planning, iterating, and reviewing code when working with AI, and shares tips for effectively using tools like Cursor and managing rules files.

https://www.youtube.com/watch?v=ELiiMX_o2LI