developing-with-streamlit

Create, debug, and deploy Streamlit applications with caching and Snowflake integrations.

629|85|Updated May 4, 2020

Search Tags:#performance #deployment #streamlit #layouts #session-state #custom-components #streamlit-app

Ready to run

npx skills add https://github.com/andfanilo/streamlit-echarts --skill developing-with-streamlit-andfanilo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: developing-with-streamlit
Source: https://github.com/andfanilo/streamlit-echarts/tree/main/.claude/skills/developing-with-streamlit
Command: npx skills add https://github.com/andfanilo/streamlit-echarts --skill developing-with-streamlit-andfanilo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides concise, actionable guidance for creating, editing, debugging, and deploying Streamlit applications so teams can move from prototypes to production with fewer mistakes and less rework.

Core Features & Use Cases

Project structure & environment: recommendations for entrypoints, module layout, pyproject/uv usage, and reproducible environments.
Performance & reliability: caching strategies, fragments, forms, and patterns to avoid expensive reruns.
Layouts, design, and data display: practical guidance for sidebars, columns, dialogs, metrics, and dataframe column configuration.
Integrations & advanced features: session state management, custom components (CCv2), theming, Snowflake connections, and CLI/uv deployment workflows.
Use case: take an internal dashboard from a single-file prototype to a multipage, themed, cached app that queries Snowflake, supports live metrics, and uses a packaged custom component.

Quick Start

Scaffold and deploy a production-ready Streamlit app with project structure, caching, responsive layouts, session state, and deployment steps.

Frequently Asked Questions about developing-with-streamlit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I structure a Streamlit app for production?▼

Structure a Streamlit app for production by using a modular project layout with dedicated entrypoints, reproducible pyproject/uv environments, and organized module hierarchies. This setup reduces rework when moving from single-file prototypes to multipage applications.

What is the best way to optimize Streamlit app performance and prevent expensive reruns?▼

Optimize Streamlit app performance by implementing caching strategies, using fragments, and structuring forms to avoid unnecessary full reruns. These patterns ensure responsive dashboards and reliable data display without redundant computations.

How do I manage session state in a Streamlit multipage application?▼

Manage session state in a Streamlit multipage application by applying established patterns for data persistence across reruns. Proper session state management maintains user inputs and live metrics while navigating between different dashboard pages.

Does this Streamlit guidance include Snowflake integration and deployment workflows?▼

Yes, the Streamlit guidance includes Snowflake integration and CLI/uv-based deployment workflows. It supports connecting data sources, querying Snowflake directly, and packaging custom components for production deployment.

Can I use custom components and theming in my Streamlit dashboard?▼

Yes, you can use custom components (CCv2) and theming in your Streamlit dashboard. The guidance covers best practices for integrating packaged components and applying themes to create a cohesive, production-grade user interface.