Ideogram
Link: Ideogram: ""
Linked is (one of many I am sure) tool that creates pretty amazing images from prompts. And there's a pretty capable free tier!
gpiozero — gpiozero 2.0.1 Documentation
Link: gpiozero — gpiozero 2.0.1 Documentation: ""
Linked is a very useful library of code for writing programs on microcontrollers such as arduino and esp32. Just really handy stuff that you would know how to write... but why bother?
A guide to JAX for PyTorch developers | Google Cloud Blog
Link: A guide to JAX for PyTorch developers | Google Cloud Blog: "PyTorch users can learn about JAX in this tutorial that connects JAX concepts to the PyTorch building blocks that they’re already familiar with."
Linked is a very useful tutorial on the use of JAX. I am not an expert. I capture the link here mostly for my own future benefit.
Django vs. FastAPI, An Honest Comparison
Link: Django vs. FastAPI, An Honest Comparison: "After many years of working with Django, I decided to take a closer and more serious look at FastAPI. Extensively using both frameworks has helped me understand their actual strengths and weaknesses with greater accuracy. More and more, I find it challenging to form a relevant opinion on tools I've never used. Reading documentation or blog posts like this one is not enough, as some things simply don't "click" in your mind until you experience them firsthand."
Linked is a very useful article comparing FastAPI with Django. I’ve been a long-time Ruby on Rails developer, having developed a lot of expertise using that framework and genuinely loving it. However, for very practical reasons, I recently switched to Python. This article is highly instructive in explaining the pros and cons of Django versus FastAPI. But it leads me to an unexpected conclusion: neither Django nor fast API can truly fulfill my needs as much as Rails. Consequently, I’ve decided to stick to Ruby on Rails, even though I’ve switched to Python as my primary programming language!
How AI is changing my grading approach -- for now
Link: How AI is changing my grading approach -- for now: "It's not ideal and I have a lot of questions."
Linked is an article detailing one proffers experience modifying their approach to deal with LLMs and AI use by students on submitting homework.
When to use “raise from None” in Python
Link: When to use “raise from None” in Python: "Learn when and why to use Python's 'raise ... from None' to simplify stacktraces by hiding redundant exception context. Improve debugging clarity by focusing on the actual issue."
Linked is a good article about raising exceptions in python. For me it also showed me some interesting “advanced” (or is it idiomatic) python.