Implement a research paper as an interactive marimo notebook together with the user. Start by understanding what the user wants to explore, fetch the paper via alphaxiv, then build a focused notebook.

2026-06-15161

marimo-notebook

marimo-team/skills

Write a marimo notebook in a Python file in the right format.

2026-06-15161

marimo-batch

marimo-team/skills

An opintionated skill to prepare a marimo notebook to make it ready for a scheduled run.

2026-04-15161

implement-paper-auto

marimo-team/skills

Implement a research paper in a marimo notebook fully automatically without extra user input.

2026-03-26161

auto-paper-demo

marimo-team/skills

Make a demo of a research paper in a marimo notebook fully automatically without extra user input.

2026-03-26161

anywidget-generator

marimo-team/skills

Generate anywidget components for marimo notebooks.

2026-03-11161

name	streamlit-to-marimo
description	Convert a Streamlit app to a marimo notebook

Converting Streamlit Apps to Marimo

For general marimo notebook conventions (cell structure, PEP 723 metadata, output rendering, marimo check, variable naming, etc.), refer to the marimo-notebook skill. This skill focuses specifically on mapping Streamlit concepts to marimo equivalents.

Steps

Read the Streamlit app to understand its widgets, layout, and state management.
Create a new marimo notebook following the marimo-notebook skill conventions. Add all dependencies the Streamlit app uses (pandas, plotly, altair, etc.) — but replace streamlit with marimo. You should not overwrite the original file.
Map Streamlit components to marimo equivalents using the reference tables below. Key principles:
- UI elements are assigned to variables and their current value is accessed via .value.
- Cells that reference a UI element automatically re-run when the user interacts with it — no callbacks needed.
Handle conceptual differences in execution model, state, and caching (see below).
Run uvx marimo check on the result and fix any issues.

Widget Mapping Reference

Input Widgets

Streamlit	marimo	Notes
`st.slider()`	`mo.ui.slider()`
`st.select_slider()`	`mo.ui.slider(steps=[...])`	Pass discrete values via `steps`
`st.text_input()`	`mo.ui.text()`
`st.text_area()`	`mo.ui.text_area()`
`st.number_input()`	`mo.ui.number()`
`st.checkbox()`	`mo.ui.checkbox()`
`st.toggle()`	`mo.ui.switch()`
`st.radio()`	`mo.ui.radio()`
`st.selectbox()`	`mo.ui.dropdown()`
`st.multiselect()`	`mo.ui.multiselect()`
`st.date_input()`	`mo.ui.date()`
`st.time_input()`	`mo.ui.text()`	No dedicated time widget
`st.file_uploader()`	`mo.ui.file()`	Use `.contents()` to read bytes
`st.color_picker()`	`mo.ui.text(value="#000000")`	No dedicated color picker
`st.button()`	`mo.ui.button()` or `mo.ui.run_button()`	Use `run_button` for triggering expensive computations
`st.download_button()`	`mo.download()`	Returns a download link element
`st.form()` + `st.form_submit_button()`	`mo.ui.form(element)`	Wraps any element so its value only updates on submit

Display Elements

Streamlit	marimo	Notes
`st.write()`	`mo.md()` or last expression
`st.markdown()`	`mo.md()`	Supports f-strings: `mo.md(f"Value: {x.value}")`
`st.latex()`	`mo.md(r"$...$")`	marimo uses KaTeX; see `references/latex.md`
`st.code()`	mo.md("```python\n...\n```")
`st.dataframe()`	`df` (last expression)	DataFrames render as interactive marimo widgets natively; use `mo.ui.dataframe(df)` only for no-code transformations
`st.table()`	`df` (last expression)	Use `mo.ui.table(df)` if you need row selection
`st.metric()`	`mo.stat()`
`st.json()`	`mo.json()` or `mo.tree()`	`mo.tree()` for interactive collapsible view
`st.image()`	`mo.image()`
`st.audio()`	`mo.audio()`
`st.video()`	`mo.video()`

Charts

Streamlit	marimo	Notes
`st.plotly_chart(fig)`	`fig` (last expression)	Use `mo.ui.plotly(fig)` for selections
`st.altair_chart(chart)`	`chart` (last expression)	Use `mo.ui.altair_chart(chart)` for selections
`st.pyplot(fig)`	`fig` (last expression)	Use `mo.ui.matplotlib(fig)` for interactive matplotlib

Layout

Streamlit	marimo	Notes
`st.sidebar`	`mo.sidebar([...])`	Pass a list of elements
`st.columns()`	`mo.hstack([...])`	Use `widths=[...]` for column ratios
`st.tabs()`	`mo.ui.tabs({...})`	Dict of `{"Tab Name": content}`
`st.expander()`	`mo.accordion({...})`	Dict of `{"Title": content}`
`st.container()`	`mo.vstack([...])`
`st.empty()`	`mo.output.replace()`
`st.progress()`	`mo.status.progress_bar()`
`st.spinner()`	`mo.status.spinner()`	Context manager

Key Conceptual Differences

Execution Model

Streamlit reruns the entire script top-to-bottom on every interaction. Marimo uses a reactive cell DAG — only cells that depend on changed variables re-execute.

No need for st.rerun() — reactivity is automatic.
No need for st.stop() — structure cells so downstream cells naturally depend on upstream values.

State Management

Streamlit	marimo
`st.session_state["key"]`	Regular Python variables between cells
Callback functions (`on_change`)	Cells referencing `widget.value` re-run automatically
`st.query_params`	`mo.query_params`

Caching

Streamlit	marimo
`@st.cache_data`	`@mo.cache`
`@st.cache_resource`	`@mo.persistent_cache`

@mo.cache is the primary caching decorator — it works like functools.cache but is aware of marimo's reactivity. @mo.persistent_cache goes further by persisting results to disk across sessions, useful for expensive computations like model training.

Multi-Page Apps

Marimo offers two approaches for multi-page Streamlit apps:

Single notebook with routing: Use mo.routes with mo.nav_menu or mo.sidebar to build multiple "pages" (tabs/routes) inside one notebook.
Multiple notebooks as a gallery: Run a folder of notebooks with marimo run folder/ to serve them as a gallery with navigation.

Deploying

marimo features molab to host marimo apps instead of the streamlit community cloud. You can generate an "open in molab" button via the add-molab-badge skill.

Custom components

streamlit has a feature for custom components. These are not compatible with marimo. You might be able to generate an equivalent anywidget via the marimo-anywidget skill but discuss this with the user before working on that.