arguably

arguably turns functions into command line interfaces (CLIs). arguably has a tiny API and is extremely easy to integrate.

https://github.com/treykeown/arguably

The Annotated S4

This post provides an overview of the Structured State Space for Sequence Modeling (S4) architecture which is a new approach to very long-range sequence modeling tasks for vision, language, and audio, showing a capacity to capture dependencies over tens of thousands of steps. It also includes code implementations that allow readers to experiment with the S4 architecture.

https://srush.github.io/annotated-s4

Designing Pythonic library APIs

The article discusses some principles for designing good Python library APIs, including structure, naming, error handling, type annotations, and more. The author argues that Python's flexibility can be a double-edged sword, and that it's important to design APIs that are easy to use and understand.

https://benhoyt.com/writings/python-api-design/

ChristianLempa / videos

This is my video documentation. Here you'll find code-snippets, technical documentation, templates, command reference, and whatever is needed for all my YouTube Videos.

https://github.com/ChristianLempa/videos

Geospatial Data in your Graph

In this stream we explore some techniques for working with geospatial data in Neo4j. We will cover some basic spatial Cypher functions, spatial search, routing algorithms, and different methods of importing geospatial data into Neo4j.

https://www.youtube.com/watch?v=djMsdSxvd2E

Building Real-time Machine Learning Foundations at Lyft

The article highlights Lyft's efforts in developing real-time machine learning foundations to enhance their platform's performance and user experience. It explores the challenges faced and the strategies employed to build scalable and reliable machine learning systems within the context of a ride-sharing company.

https://eng.lyft.com/building-real-time-machine-learning-foundations-at-lyft-6dd99b385a4e

embedchain

Framework to easily create LLM powered bots over any dataset.

https://github.com/embedchain/embedchain

When NumPy is too slow

What do you do when your NumPy code isn’t fast enough? We’ll discuss the options, from Numba to JAX to manual optimizations.

https://pythonspeed.com/articles/numpy-is-slow/

XingangPan / DragGAN

Official Code for DragGAN (SIGGRAPH 2023)

https://github.com/XingangPan/DragGAN

PromtEngineer / localGPT

Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.

https://github.com/PromtEngineer/localGPT

A Tale of Debugging: The Competitive Programmer Approach

Have the computer find the bugs for you.

https://albexl.substack.com/p/a-tale-of-debugging-the-competitive

Caching in Django with Redis

A step-by-step guide on implementing caching with Redis in Django.

https://fly.io/django-beats/caching-in-django-with-redis/

Automata

The Future is Self-Written.

https://github.com/emrgnt-cmplxty/Automata

Automating Python code quality

The article emphasizes the importance of code quality in Python software development, discussing various aspects such as style consistency, code readability, testing, and documentation. It provides practical tips and best practices to improve code quality and maintainability, ultimately enhancing the overall software development process.

https://blog.fidelramos.net/software/python-code-quality

generative-models

Generative Models by Stability AI.

https://github.com/Stability-AI/generative-models

Building a Toy Programming Language in Python

I thought it would be fun to go outside of my comfort zone of web development topics and write ...

http://blog.miguelgrinberg.com/post/building-a-toy-programming-language-in-python

OAuth Authentication with Flask in 2023

A long time ago I wrote a tutorial on how to add logins with a social network to your Flask ...

http://blog.miguelgrinberg.com/post/oauth-authentication-with-flask-in-2023