streamlit-to-marimo

$27

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.