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I like the basic script template that the author provides.

However, when I start development of new code I always use a script that starts off with traceback and pdb, something like this:

    #!/usr/bin/env python

    import traceback
    import pdb
    import sys

    def main():
        # some WIP code that maybe raises an exception
        raise BaseException("oh no, exception!")
        return 0

    if __name__ == "__main__":
        try:
            ret = main()
        except:
            traceback.print_exc()
            pdb.post_mortem()
        sys.exit(ret)
This means that whenever an uncaught exception gets raised, I immediately get told what happened (full backtrace) plus I get dumped into the debugger, from where I can inspect why this happened. I liberally sprinkle assert()s through my code, so this gives me a good edit-run-debug cycle to work with.



This is pretty smart. When I'm making one-off scripts I use the interactive flag

python -i script.py

I've programmed Python for years and never knew this. I'm not sure how well this handles errors. Tab complete works, only thing that is missing is needing to wrap help(<func>) to see signatures. I'm enjoying the standard lib interpreter.


I use ipython for similar task. It has wrapper for 'help' function ('?' symbol after function name), tab completion and syntax highlighting. Also it has special %hist command for easy copy-paste code.


I like IPython unless working with large arrays, because of weird memory issues I experienced (maybe they're fixed?). I miss the %run, !<cd, ls, pip>, %timeit magic and the IPython.terminal.debugger.set_trace().

If you're on linux it's not _that_ bad without it since the shell sort of acts like the notebook (with an equally horrible markup language). The help() and tab-complete and _ __ ___ for last 3 values works, time python <file>.py can benchmark, -i or pdb.set_trace does the debugging. It doesn't keep a persistent history though so the workflow is sort of different.

So I use both, particularly for plots and images knowing IPython is very helpful for working with the notebooks.




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