Every Friday, you'll get a recap of the most important and exciting Python and coding news. The Friday Loop also keeps everyone posted on new ArjanCodes courses and any limited offers coming up.
Streamlit Explained: Python Tutorial for Data Scientists | Issue #2
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The Friday Loop
Every Friday, you'll get a recap of the most important and exciting Python and coding news. The Friday Loop also keeps everyone posted on new ArjanCodes courses and any limited offers coming up.
You’ve tested the endpoint. The response looks right. No errors in the terminal. So you’re done, right? Well... not quite. In the last video of this year (time flies!) I start with a tiny FastAPI app that "works", and step by step, I turn it into something that’s actually ready for production (and that's more work than you think). That includes: Proper type usage Input validation and error handling Configuration management Rate limiting to prevent abuse ...and more! All using a real example:...
Sometimes your code fails, you change absolutely nothing, and on the next run everything works again. If that sounds familiar, this week’s video is for you. These kinds of failures usually have nothing to do with bad code. They come from the outside world: APIs that time out, networks that briefly misbehave, or LLMs that occasionally return something almost structured, but not quite. It’s frustrating, because the failure feels random, and those types of failures are really annoying to debug!...
If you’ve ever opened a function and instantly regretted it… this week’s video is for you. I’m talking about those legendary functions: ten levels of indentation, contradictory conditions, duplicate branches, mysterious try/except blocks, and business logic so unclear that nobody knows what it actually does anymore. I start with a really messy example and walk through the exact process I use to refactor it safely. You’ll see how to create characterization tests so you don’t break existing...