28 September 2022
Jupyter notebooks are great for software development and documentation. They are widely used in the world of data science and Machine Learning (ML), and it’s an ideal tool to use if you want to experiment with new algorithms, analyze and get familiar with your datasets, and create quick sketches of new approaches.
Almost two years ago, JupyterLab introduced a visual debugger, and Jeremy Howard announced nbdev, a python library to write, test, document, and distribute software packages and technical articles, all in one place, your notebook. Jupyter began a transition to look more like an IDE, although it still kept its own way of doing this, and it still is nothing like any other conventional IDE.