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streamlit-to-marimo流化为 marimo

Agent Skill

streamlit-to-marimo 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

14,859

周安装

613

GitHub Stars

126

下载量

4,855
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:streamlit-to-marimo(流化为 marimo)
来源仓库:https://github.com/marimo-team/skills
仓库路径:skills/streamlit-to-marimo
安装命令:
npx skills add https://github.com/marimo-team/skills --skill streamlit-to-marimo
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/marimo-team/skills --skill streamlit-to-marimo

简介

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息,适合在多种宿主环境中整理代码变更事项。

  • 支持围绕仓库状态、代码协作流程进行信息组织与分类。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • streamlit-to-marimo 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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.

  1. Handle conceptual differences in execution model, state, and caching (see below).
  2. Run uvx marimo check on the result and fix any issues.

Widget Mapping Reference

Input Widgets

StreamlitmarimoNotes
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

StreamlitmarimoNotes
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

StreamlitmarimoNotes
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

StreamlitmarimoNotes
st.sidebarmo.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

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

Caching

Streamlitmarimo
@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.

适合场景

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能力概览

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能力 2

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能力 3

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能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.33%
按下载量换算1,715

Claude

33.03%
按下载量换算1,604

Cursor

17.06%
按下载量换算828

Gemini CLI

9.23%
按下载量换算448

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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