How do you deal with Jupyter notebook debt?

This page summarizes the projects mentioned and recommended in the original post on /r/datascience

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  1. ploomber

    Discontinued The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

    nbdev is a pretty interesting project. I'm working on something similar. nbdev allows you to write Python packages from Jupyter while Ploomber allows you to write modular data pipelines from Jupyter, we've had a bunch of companies report big productivity gains with this approach. That was my motivation to ask this question: I think it's possible to hit a balance between interactivity and production code

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  3. jupytermosaic

    A Jupyter Notebook / Jupyter Lab extension allowing for tiling of cells for a customizable and flexible layout reducing white space.

    It's not a miracle cure but if you want a way to make Jupiter notebooks a lot easier to read and be able to present them in day zoom without ludicrous levels of scrolling check out this GitHub plug in for jupyter notebook https://github.com/robertstrauss/jupytermosaic

  4. nbdev

    Create delightful software with Jupyter Notebooks

    For Python development, the fastai people are promoting a notebook-first development approach with nbdev. They are using notebooks as part of a general development workflow, not just in data exploration setting, and apparently they are seeing significant productivity gains.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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Did you know that Jupyter Notebook is
the 15th most popular programming language
based on number of references?