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Streamlit Data Application Framework Cheat Sheet

Streamlit Data Application Framework Cheat Sheet

Back to Data ScienceUpdated 2026-05-15

Streamlit is an open-source Python framework that transforms data scripts into interactive web applications with minimal code. Built specifically for data scientists and ML engineers, Streamlit eliminates the need for frontend development expertise β€” write simple Python scripts and instantly see results as responsive UIs. Its pure-Python declarative model runs scripts top-to-bottom on every interaction, automatically managing UI updates and enabling rapid prototyping. The framework's true power lies in its caching primitives, session state management, and fragment-based partial reruns, which together enable building production-grade data apps that handle complex workflows, real-time updates, and stateful interactions efficiently.

What This Cheat Sheet Covers

This topic spans 24 focused tables and 141 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core Display FunctionsTable 2: Data Display ElementsTable 3: Simple Chart ComponentsTable 4: Advanced Chart LibrariesTable 5: Button WidgetsTable 6: Selection WidgetsTable 7: Numeric Input WidgetsTable 8: Text and Date Input WidgetsTable 9: File and Media Input WidgetsTable 10: Session State and StatefulnessTable 11: Caching for PerformanceTable 12: Layout and ContainersTable 13: Multipage Apps and NavigationTable 14: Forms and Batched InputTable 15: Execution Flow ControlTable 16: Status and Progress ElementsTable 17: Media Display ElementsTable 18: Chat Interface ElementsTable 19: Page ConfigurationTable 20: Connections and Data AccessTable 21: Custom ComponentsTable 22: Authentication and User InfoTable 23: Deployment on Streamlit Community CloudTable 24: Advanced Patterns and Best Practices

Table 1: Core Display Functions

FunctionExampleDescription
st.write
st.write("Hello **world**!")
st.write(df)
st.write(fig)
Streamlit's "magic" function that intelligently renders almost any Python object β€” dataframes, charts, markdown, dicts, or plain text β€” choosing the appropriate display format automatically.
st.markdown
st.markdown("# Header")
st.markdown("Text with **bold**")
Renders a string as formatted Markdown with full support for headers, emphasis, lists, links, and inline HTML; set unsafe_allow_html=True to enable raw HTML rendering.
st.title
st.title("My App Title")
Displays text in large title formatting at the top of your app β€” the visual headline users see first.
st.header
st.header("Section Header")
Displays text in header formatting β€” larger than regular text but smaller than title β€” used to organize app sections.
st.subheader
st.subheader("Subsection")
Displays text in subheader formatting β€” useful for creating visual hierarchy within sections.
st.caption
st.caption("Small explanatory text")
Displays text in small font β€” ideal for footnotes, disclaimers, or supplementary information.

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