So I was mainly a Haskell programmer in grad school before getting into scientific computing, and the main good habit I picked up was working at the REPL and br

So I was mainly a Haskell programmer in grad school before getting into scientific computing, and the main good habit I picked up was working at the REPL and breaking my code up into small, testable functions/components, and thinking very hard about state. The main bad habit I had was expecting the Julia compiler to be as helpful as GHC when refactoring code. While I was writing my thesis and job hunting, I attended a few workshops aimed at “grad students breaking into industry”. The main thing I noticed from applied mathematics students in particular was they would write out long functions (really hard to debug) or they worked exclusively in Jupyter notebooks (these have super complicated state, so it takes a lot of discipline to be able to translate these into usable code).