An opinionated list of Python frameworks, libraries, tools, and resources
You asked Claude to build a feature. It worked. You shipped it. Six weeks later, you're adding something related, and nothing makes sense anymore. The code is technically correct but completely opaque. You can't remember why anything was structured this way. Claude can't figure it out either — it starts guessing, and the guesses start breaking things. This is the scenario I keep seeing. And it's n
If you’ve been around data engineering long enough, you’ve probably heard these terms thrown around in meetings: “Just dump it in the data lake” “We’ll expose it through the warehouse” “That goes into the mart” “We’re moving to a lakehouse architecture” And honestly… it can sound like four different ways of saying the same thing. They’re not. Each one solves a slightly different problem in the dat