You probably were careful enough to understand the limits of the Jupyter server and client (frontend). It's easy to screw up a terminal application in data sci

You probably were careful enough to understand the limits of the Jupyter server and client (frontend). It's easy to screw up a terminal application in data science when dumping a large array. Many REPLs cannot handle this properly (and CTRL+C won't work). It's easy to test this: What does your favourite notebook do when you call some command such as (pseudocode/python here) print(range(int(1e7))) # or 1e8 In this particular example, the python CLI seems to handle keyboard interrupts fine when the terminal (or RAM) is flooded.