Using Jupyter with custom environments
This post demonstrates running a “global” user-scoped Jupyter notebook that can be used to manage a collection of notebooks across many projects.
Using Jupyter in this way builds on top of a common workflow using IPython for interactive development, which has been a common process for me during development.
An example of when this is especially useful, would be when applying logic to a data construct which I am not familiar with by allowing interactive exploration of the data and then rolling up the code from that exercise into the actual code.
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