Hey, I'm using mo.ui.radio for filtering a dataset as part of a larger ML model evaluation UI. I find that when I have a lot options using the inline option just makes a really wide element for the radio component.

It'd be a nice feature to have ncols, nrows or columns for the UI element to define a little radio grid or similar arguments

hey guys, I am not a css/frontend guy in any way. I was trying to get a panel with a main callout on the left and a right panel with scrollable callouts. I would like the right callouts to be closer to each other and the left one to take more space on the left.

Also is it possible to make the right ones scrollable while the left one stays in place?

Attached a picture of what I've tried + code

Hi, when I use marimo without the sandbox feature I often end up installing packages via the integrated package manager - I use uv. If i were to install packages directly from the terminal using uv they would be added to pyproject.toml, it would be great to have packages added to the dependencies in pyproject toml when such file is available and if not running in a sandbox

heya, I often call methods one after the other (e.g. using polars or pandas) but I only see the interactive docstring for the first method as the type of the ouptut cannot be inferred, is that the expected behaviour?

Off the back of https://discord.com/channels/1059888774789730424/1345036219884765244/1345083635476205568

Would it make sense to have marimo be installable via OS package managers (apt, brew, pacman, etc?). I've read before that system wide marimo is discouraged but I always (unless when developing apps) use marimo as a system wide tool

I imagine this would require some initial complexity distributing the marimo build to different package managers repositories but I think it could make sense

Hey, I've got some notebooks where I use UI components (selectors) that have some default values. I'd expect the default behaviour is that the variables assigned to those components would simply use those values when running the notebooks as scripts but I am unsure that's the expected/designed behaviour but i don't see my script returning an error or warning either

hey, I thought it'd be very useful to have the data explorer show possible values for filters as well as perhaps showing those values when hovering over unique: {unique_count}

I often find myself going back and forth between the data explorer and the data panel on the left menu for this. I think it'd be neat to have the filter values directly in the data explorer

It'd be nice to have to have a checkbox in SQL cells for caching with perhaps a timer (e.g 1 hr, 1 day, 7 weeks) where an expensive SQL query will not be executed within that time window if a cache entry exist for it - perhaps it doesn't encourage best practices (probably moving expensive queries to a data warehouse) but i could see it being useful in some instances

Hey, I have a notebook that loads data (~1.6M rows), has some UI elements for filtering that dataset and creates some altair plots. I find that when I go from app mode to edit mode the notebook first shows as blank, then tries to render elements then crashes and finally if I refresh the page it will reconnect and display things properly

Any clue on what could be going on? How can I figure out what's the culprit here?

As you can see in the picture attached from my notebook data flow the cell where I create my DB connection is not linked to the SQL cell below it. This is to be expected because these two cells don't share variables but at the same is wrong because these cells depend on each other for execution. I don't know what a good solution for this is at the moment.

I think I suggested in another post to have a DB connection tab on the left side menu, this wouldn't solve this particular issue but might be beneficial. @Myles Scolnick

Hey, I can't reproduce https://marimo.io/blog/altair

I am trying to take advantage of the marimo/altair integration but the click and drag selection doesn't work out of the box for me - I'm running the latest marimo

Heya, as it sounds, I’m using mo.stop in a SQL cell (after turning the SQL cell into a python one) and when I restart a notebook the mo.stop disappear and I’m back with a SQL cell but with no stop

I've been losing cells when going from editing to run/app mode today, very weird, I wish I could have some code to reproduce it. For instance I had ipynb conversion switched on and I was getting some errors in the terminal:



Let me know if you'd like the full log

Unlike jupyter notebooks, marimo cells are linked, nodes of a DAG. I like the fact that I can put a cell anywhere in the notebook and it will run but sometimes I miss having my cells outlined in order of execution - though I know there would be many ways of sorting parallel branches of a dag but this would be useful still, or maybe even a DAG editor (I know the canvas exist but maybe something more UX/dev focused)

Hi, I work with kedro at work. Kedro is a framework to build DS/ML pipelines, I don't love it but it's what my company uses and I think we can make it work, it's pretty customisable at least.

Kedro is very geared towards jupyter notebook users. They rely on magic command to load special kedro variables such as the catalog, conf file, etc. I use to love magic when I got to know jupyter but nowadays I really don't like anymore.

The point is, this magic makes some variables available in the global namespace so that the user doesn't have to worry about loading the right config/catalog. This seems like a patchy fix, because to be honest, they don't have a robust solution to load these files from a simple python script or for example marimo notebook. They also have special commands kedro jupyter lab and kedro jupyter notebook that "inject" these variables for the user before hand. See a thread of the issues with Kedro configs + marimo here: https://kedro-org.slack.com/archives/C03RKP2LW64/p1736872610928369

I wonder if it'd be possible to have a similar kedro marimo edit command to integrate marimo into this framework.

PS: With all the work you've done on data flows and DAGs I think you actually are in a prime position to create a clean ML pipeline framework, would love to hear your thoughts on that. @Akshay @Myles Scolnick

I am a bit confused at this warning message, I have defined a valid requires-python attribute yet this is happening.

On another front, is it incorrect to use sandboxes the way I am doing it? i.e. using uv run before the marimo call?

Do you recommend using a global marimo installation or a per-environment marimo installation?

https://docs.marimo.io/api/caching.html

Or would I need to turn it into a python cell then run it?

I know this isn't a uv community but the marimo one but I know there are a lot of big uv fans here. I am little confused about some elements of uv, can somebody enlighten me please?

https://github.com/astral-sh/uv/issues/9219