Streamlit Starlette

Streamlit-Starlette Integration Skill

This skill provides instructions and code patterns for using the streamlit.starlette.App wrapper, organized by architectural concern.

1. The Skeleton (Mounting & Structure)

This defines how the application is structured. The primary decision is: Who is the parent?

Pattern A: Streamlit as Root, FastAPI Mounted

Use when the dashboard is the main product and the API is a supporting feature.

Reference: references/mount_fastapi.py

Pattern B: FastAPI as Root, Streamlit Mounted

Use when FastAPI is the main product and the dashboard is a visualization add-on.

Reference: references/mount_streamlit_as_subapp.py

Pattern C: Custom Starlette Routes (No FastAPI)

Use when you need simple endpoints without FastAPI overhead (no OpenAPI docs).

Reference: references/route_custom_endpoints.py

Pattern D: Static File Serving

Use when you need to host a folder as a website or serve JS/CSS assets.

Reference: references/mount_static_files.py

Pattern E: Django Integration

Use when integrating with an existing Django project.

Reference: references/mount_django.py

Pattern F: Flask Integration

Use when integrating with an existing Flask app (requires a2wsgi).

Reference: references/mount_flask.py

2. The Guard (Middleware & Security)

This defines how requests are intercepted and processed before they reach the Streamlit UI.

Pattern: Security Headers

Add security headers (CSP, X-Frame-Options, HSTS) to all responses.

Reference: references/middleware_security_headers.py

Pattern: Auth Cookie Middleware

Block access if user is not authenticated (cookie check).

Reference: references/middleware_auth.py

Pattern: Cookie Management

Set and read cookies via middleware.

Reference: references/middleware_cookies.py

Pattern: IP Whitelist

Restrict access to specific IP addresses.

Reference: references/middleware_ip_whitelist.py

3. The Bridge (Communication, State & Metadata)

This defines how the API layer and the UI layer share data, and how metadata is served.

Pattern: Lifespan for Resource Management

Pre-load resources (ML models, DB pools) on startup and clean up on shutdown. Includes cache pre-warming.

Reference: references/core_lifespan_lifecycle.py

Pattern: MCP Server Integration

Expose endpoints as MCP tools for AI agents (requires fastmcp).

Reference: references/route_mcp_server.py

Pattern: SEO Endpoints

Serve robots.txt, sitemap.xml, and manifest.json for SEO and PWA support.

Reference: references/route_seo_metadata.py

Best Practices

• Async First: Keep all Starlette/FastAPI route handlers async to avoid blocking the event loop.
• Single Port: The unified app runs on one port. No CORS configuration is needed between UI and API.
• Relative Paths: Paths to Streamlit scripts (e.g., "dashboard.py") are relative to the entry point file.