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I do the opposite, my job is kind of bad data engineer/scientist/etl minion so it's a lot of dataframes. Work (and often debug) in jupyter -> open the notebook

I do the opposite, my job is kind of bad data engineer/scientist/etl minion so it's a lot of dataframes. Work (and often debug) in jupyter -> open the notebook from pycharm when it's got some completed thoughts and write into a python module + test module, tidying up and adding type annotations. Sometimes doing that multiple times so that the notebook is importing from modules which were originally pulled out of the notebook. It sucks having to use two tools but I don't think there's any one tool that can do both as well as pycharm/jupyter, short of me getting a lot better at emacs or writing a lot of custom Atom extensions (I think).

agibsonccc 8y ago
Data frame rendering in the various notebooks (beaker,jupyter,zeppelin,..) is wonderful. Your workflow sounds closest to what I do. If I want to visualize something I tend to compile my thoughts/imports and organize things in an editor first and put it in a notebook in parallel. It helps with version control as well.
bunderbunder 8y ago
I am very hopeful that JupyterLab will get support for the Language Server Protocol sometime soon. That would make all the difference in the world for me. I'd still have to use a terminal to build and run tests, but I wouldn't be surprised if a test runner comes along fairly quickly after that. (Relevant issue: https://github.com/jupyterlab/jupyterlab/issues/2163 https://github.com/jupyterlab/jupyterlab/issues/2163)