Sourcify
Effortlessly find and manage open-source dependencies for your projects.

The fastest way to build and share data apps.

Streamlit is an open-source Python framework that enables data scientists and ML engineers to rapidly build and deploy interactive data applications. It embraces a scripting-first approach, allowing developers to create apps with minimal code using a simple API. Streamlit automatically updates the application as the source code is iteratively saved. It eliminates the need for traditional front-end development, handling backend routing and HTTP requests. Apps can be deployed for free on Streamlit Community Cloud or on enterprise-grade platforms like Snowflake. Streamlit's component ecosystem extends functionality, allowing developers to create and share custom components. It supports various charting libraries, including Plotly, Altair, and Vega-Lite, and offers theming capabilities for customizing chart colors and appearance. Use cases range from prototyping ML models to creating interactive dashboards for data exploration.
Streamlit is an open-source Python framework that enables data scientists and ML engineers to rapidly build and deploy interactive data applications.
Explore all tools that specialize in create interactive dashboards. This domain focus ensures Streamlit delivers optimized results for this specific requirement.
Explore all tools that specialize in visualize data. This domain focus ensures Streamlit delivers optimized results for this specific requirement.
Explore all tools that specialize in deploy machine learning models. This domain focus ensures Streamlit delivers optimized results for this specific requirement.
Explore all tools that specialize in ml model deployment. This domain focus ensures Streamlit delivers optimized results for this specific requirement.
Widgets are now identified by their keys, preventing resets when other parameters change. Enhances state management and app stability.
Enhanced chart theming capabilities allow customization of chart colors and overall appearance. Integrates with Plotly, Altair, and Vega-Lite.
Developers can build and share custom components to extend Streamlit functionality. Integrates with JavaScript and Python.
Streamlit automatically renders variables and literals on their own line using st.write, simplifying code and reducing boilerplate.
Streamlit supports writing generators or streams to the app with a typewriter effect, enabling real-time data display.
Install Streamlit: `pip install streamlit`
Create a Python script (e.g., `app.py`)
Import Streamlit: `import streamlit as st`
Add Streamlit elements (e.g., `st.write`, `st.line_chart`)
Run the app: `streamlit run app.py`
Deploy to Streamlit Community Cloud or Snowflake
All Set
Ready to go
Verified feedback from other users.
"Streamlit is highly praised for its ease of use, rapid development capabilities, and interactive data visualization features."
Post questions, share tips, and help other users.
Effortlessly find and manage open-source dependencies for your projects.

End-to-end typesafe APIs made easy.

E-commerce intelligence platform providing a centralized view of marketing metrics and attribution.

Page speed monitoring with Lighthouse, focusing on user experience metrics and data visualization.

Topcoder is a pioneer in crowdsourcing, connecting businesses with a global talent network to solve technical challenges.

Explore millions of Discord Bots and Discord Apps.