+1 to everything @narush said.
It's important to us that the software we build is empowering to users and not restrictive. This plays out in two primary ways: 1) Since Mito is open source and generates Python code for every edit, Mito doesn't lock users into a 'Mito ecosystem', instead it help users interact with the powerful & robust Python ecosystem. 2) Because Mito is an extension to Jupyter Notebooks + JupyterLab, Mito improves your existing workflows instead of completely altering your data analytics stack.
Excited to interact with you all in the comments :)
Last time I checked the code was under a proprietary license.
Edit: I found in another comment below that mito is now available under GPL license here: https://github.com/mito-ds/monorepo/blob/dev/LICENSE
Edit2: Just saw your answer now - thanks for the clarification and links!
There is an additional version of Mito, Mito Pro, that is licensed under a different license that provides access to advanced functionality only if you are paying for a Mito Pro / Enterprise subscription.
[1] https://github.com/mito-ds/monorepo/blob/dev/LICENSE [2] https://github.com/mito-ds/monorepo/blob/dev/mitosheet/src/p...
Or does it mean it can only be used with notebook software (eg. Jupyter) that is open source but in a closed source notebook?
bamboolib is very similar to mito (hard to tell who was first).
The advantage is that it runs within Databricks which gives you the ability to scale to any amount of data easily and Databricks has many (and growing) security certifications e.g. HIPAA compliance.
bamboolib can be used in plain Jupyter. Also, bamboolib private preview within Databricks is about to start within the next days.
Full disclosure: I am a co-founder of bamboolib and employed by Databricks
It's correct that bamboolib is (still) closed-source (which might be subject to change but I don't make promises).
It's also correct that customers can extend the bamboolib UI in various ways via plugins that they can author themselves. That empowers them to build bamboolib into the kind of tool that they want.
Also, all the code is always exported and thus, there is at least no "code lockin".
Regarding being "at their mercy", I can say that there are many customers who are happy by the service that we provide.
IMHO investing in a closed-source product like bamboolib as a tool for an important business function is very risky. Imagine you're a small company, and you start using bamboolib for some part of your data analysis pipeline. Bamboolib gets acquired (you have exited kite_and_code, congratulations), and the now very large company that controls it decides to stop supporting some feature critical to what you're doing, make an addition that messes everything up, go full-on SaaS somehow, or just shut the product down. What now? You've been growing, so you've got a small team of junior non-experts who were getting the hang of it...switching will be painful (or you could lock yourself in that walled garden and pay the SaaS price...).
I guess in this specific case at hand, companies can switch between bamboolib, mito, dtale and it is less likely that all of them will become unavailable at the same time. The switch is also not so hard because there are no underlying proprietary file formats involved (except for bamboolib plugins) because the generated code is pandas, plotly, etc.
Similarly as described below/above: counter-intuitively, the availability of open-source LibreCalc makes it easier and safer to adopt closed-source Excel.
Mito (pronounced my-toe) was born out of our personal experience with spreadsheets, and a previous (failed) spreadsheet version control product.
Spreadsheets were the original killer app for computers, and are the most popular programming language used worldwide today. That being said, spreadsheets have some growing to do! They don’t handle large datasets well, they don’t lead to repeatable or auditable processes, and generally they disrespect many of the hard won software engineering principals that us engineers fight for.
More than that, as spreadsheet users run into these problems and turn to Python to solve them, they struggle to use pandas to accomplish what would have been two clicks in a spreadsheet. Pandas is great, but the syntax is not always so obvious (not is learning to program in the first place!)
Mito is the our first step in addressing these problems. Take any dataframe, edit it like a spreadsheet, and generate code that corresponds to those edits. You can then take this Python code and use it in other scripts, send it to your colleagues, or just rerun it.
We’ve been working on Mito for over a year now. Growth has really picked up in the past few months - and we’ve begun working with larger companies to help accelerate their transition to Python.
To any companies who are somewhere in that Python transition process - please do reach out - we would love to see if we can be helpful for all your spreadsheet users!
Feel free to browse my profile for other spreadsheet related thoughts, I’m a bit of a HN junkie. Of course, any and all feedback (positive or negative) is appreciated.
My cofounders and I will be trolling about in the comments. Say hey! :-)