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

1. Read the Streamlit app to understand its widgets, layout, and state management.

2. 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.

3. 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.

4. Handle conceptual differences in execution model, state, and caching (see below).

5. 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.