TriOTP

The OTP framework for Python Trio.

https://github.com/linkdd/triotp

Counting CPU Instructions in Python

Did you know it takes about 17,000 CPU instructions to print("Hello") in Python? And that it takes ~2 billion of them to import seaborn?

https://blog.mattstuchlik.com/2024/02/08/counting-cpu-instructions-in-python.html

Toolong

A terminal application to view, tail, merge, and search log files (plus JSONL).

https://github.com/textualize/toolong

Why AI has a Python Problem

Artificial Intelligence (AI) has propelled Python to unprecedented popularity, making it the go-to language for developers and researchers worldwide. Yet, beneath the surface, a significant challenge looms. Let's get into the specific difficulties Python poses for AI's evolution, backed by real-world examples and technical insights.

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

HypoFuzz

Open source smart fuzzing for Python's best testing workflow.

https://github.com/Zac-HD/hypofuzz

The Many Ways to Deploy a Model

There are many ways to deploy models and perform inference. Here, we share our decision rubric for model deployments using LLM inference as an example.

https://outerbounds.com/blog/the-many-ways-to-deploy-a-model

Lag-Llama

Towards Foundation Models for Probabilistic Time Series Forecasting.

https://github.com/time-series-foundation-models/lag-llama

Visualizing Neural Network Internals

Visualizing some of the internals of a neural network during training and inference.

https://www.youtube.com/watch?v=ChfEO8l-fas

Summary of Major Changes Between Python Versions

This post is designed to be a quick reference for the major changes introduced with each new version of Python. This can help with taking advantages of using new features as you upgrade your code base, or ensuring that you have the correct guards for compatibility with older versions.

https://www.nicholashairs.com/posts/major-changes-between-python-versions/

mwmbl

An open source, non-profit search engine implemented in Python.

https://github.com/mwmbl/mwmbl

netease-youdao / QAnything

Question and Answer based on Anything.

https://github.com/netease-youdao/QAnything

magika

Detect file content types with deep learning.

https://github.com/google/magika

Building an LLM from scratch

Learn how to build a modern language model with all the bells and whistles completely from scratch: from vanilla Python to functional coding assistant

https://bclarkson-code.github.io/posts/llm-from-scratch-scalar-autograd/post.html

Deploy a Serverless FastAPI App with Neon Postgres and AWS App Runner at any scale

Create a serverless API using FastAPI, deployed on AWS App Runner and powered by Neon Postgres.

https://neon.tech/blog/deploy-a-serverless-fastapi-app-with-neon-postgres-and-aws-app-runner-at-any-scale

Algorithmic Art with Python

In this talk we’re going to start from nothing and build out our own tools for making art in Python, no AI needed! We’ll show how Python’s expressiveness allows us to describe graphics elegantly and use that to make some unique art programmatically.

https://www.youtube.com/watch?v=_XeRM-4DZz0

Streamline-Analyst

An AI agent powered by LLMs that streamlines the entire process of data analysis.

https://github.com/Wilson-ZheLin/Streamline-Analyst

How to dockerize a Django, Preact, and PostgreSQL Application

Dockerizing your Django application can be intimidating, but the rewards outweigh the risks. In this guide, Charlie Macnamara walks you through the setup process so you can get the most out of your applications.

https://www.honeybadger.io/blog/dockerize-django-preact-postgres