It depends what kind of environment you're using. Eg, notebooks like Jupyter are a kind of REPL environment, which is how data scientists typically write code.

It depends what kind of environment you're using. Eg, notebooks like Jupyter are a kind of REPL environment, which is how data scientists typically write code. You prototype in a cell that is the source code that gets saved. If you've finalized the function or piece you're working on, you go to another cell. The reason data scientists do it this way is load times are gruesome for data science work. Sometimes it takes days to process something. Imagine every time you change a line of code having to wait days to see if there is a bug in code or what the output is. Instead we run it in an environment that loads it once and keeps it in ram (a REPL), so when working on code below what is already loaded there are no load times. There are other kinds of environments though. Sometimes video game devs develop on a REPL where the game is running, they pause it, update some code, and then go back into the game with the updates automatically put in. No load times.