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by aarondia
1492 days ago
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Heyo, one of the Mito creators here. Thanks for sharing Datasette. I haven't seen that one before. It looks neat! You're right though, there are several tools that fit the general shape of: GUI on top of Jupyter on top of Python. There's a few general vectors to understand these tools by: 1. Excel-ness: Although most (if not all) of these tools incorporate some type of spreadsheet, the interface for interacting with the data in that spreadsheet differs greatly. Some tools, like Bamboolib [1] and Datasette [2] resemble Excel only in the spreadsheet. Other tools, like Mito [3], stick to a lot of the other Excel design decisions -- things like having a toolbar with buttons and menu items to access functionality, the ability to write spreadsheet formulas inside of the cell & formula bar, etc. In many ways, this Excel-ness design vector is a proxy for how easy it is to get started with the tool. What we see, is that users are able to download Mito and get something useful out their first analysis because the interface is one that they are used to! 2. Ownership of your analysis / lack of lockin: We believe that the most powerful low-code spreadsheet tools allow spreadsheet users to easily transition to full programming languages, if they want to. Instead oflocking users into a limited and proprietary product, it's better if users can transition to a full programming language (like Python) very naturally. This transition is super natural in Mito because we generate Python code for every edit that a user makes. So if Mito doesn't support the exact transformation that you want, you can use Mito as a starting point for your analysis and customize the script that Mito generates. [1] https://bamboolib.8080labs.com/
[2] https://datasette.io/
[3] https://www.trymito.io/ |
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However, please be aware that bamboolib might soon only be available within Databricks notebooks instead of local Jupyter notebooks like mito.