JupyterLab will eventually replace Jupyter notebook. Lab offers a much more IDE like experience with better collaboration for coders, including debuggers and other extensions that help coders tremendously. Notebook interfaces are notorious for producing dirty code. While JupyterLab is not perfect, it helps to organize code and supporting files and folders more effectively than a standalone notebook. It would enhance the quality of code in python recipes on the flow due to better documentation features and markdown + console support in a single view. Consoles would allow for more effective testing and keep books clean. My team spends a ton of time surfing through old code and test code in notebooks. Thus we spend a significant amount of time "productionizing" code in Dataiku before projects can be merged to main and deployed to auto.
Default features like expanding and collapsing, dragging and dropping cells help organize and enhance collaboration. Side by side views and window organization help coders to be more effective on the Dataiku platform.
One key feature that's highly enjoyable for collaboration is kernel sharing. My team is global and all virtual now because of COVID. With standard Jupyter notebooks, our data science leads need to re-run time intensive/costly cells to catch up to a point where an analyst or another colleague needs help.
A user could push various notebooks in a lab session to the flow sequentially. One potential aspect to account for is the inherent filesystem.
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