streamlit-to-marimo
Convert a Streamlit app to a marimo notebook
Install
npx skills add https://github.com/marimo-team/skills --skill streamlit-to-marimoConverting 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-notebookskill conventions. Add all dependencies the Streamlit app uses (pandas, plotly, altair, etc.) — but replacestreamlitwithmarimo. 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.
- UI elements are assigned to variables and their current value is accessed via
Handle conceptual differences in execution model, state, and caching (see below).
Run
uvx marimo checkon 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.routeswithmo.nav_menuormo.sidebarto 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.