Streamlit To Marimo

by marimo-team6454470960d3No license174 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 7 weeks ago

Convert a Streamlit app to a marimo notebook

Instructions onlySoftware Development

AI-generated overview

Converts Streamlit apps into marimo notebooks by mapping widgets, layout, state, and caching to marimo equivalents.

What it does: This skill guides the conversion of an existing Streamlit application into a marimo notebook. It provides reference tables mapping Streamlit input widgets, display elements, charts, and layout containers to their marimo counterparts, and explains conceptual differences in execution model, state management, caching, multi-page apps, and deployment. It also instructs running a marimo check on the result and fixing issues.
When to use it: Use it when you have a Streamlit app and want to port it to marimo. It suits users who need guidance on translating Streamlit widgets, reactivity, session state, or caching into marimo conventions.
Requirements: Requires the marimo package and the uvx tool for running marimo check; it references the marimo-notebook, add-molab-badge, and marimo-anywidget skills. It ships no scripts and is instructions only.

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

Caching

@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.

Source and attribution

Source:marimo-team/skillsinskills/streamlit-to-marimoat commit6454470

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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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`

Streamlit To Marimo

Converting Streamlit Apps to Marimo

Steps

Widget Mapping Reference

Input Widgets

Display Elements

Charts

Layout

Key Conceptual Differences

Execution Model

State Management

Caching

Multi-Page Apps

Deploying

Custom components

Source and attribution

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