Streamlit: Free Open Source Data Apps Builder w/ Python
Data visualization and interactive dashboards used to require heavy frameworks, frontend knowledge, and long development cycles.
Streamlit changes this by providing a free, open-source Python framework that allows you to turn scripts into fully interactive web apps in just a few lines of code. It’s designed for data scientists, engineers, and analysts who want to share insights without learning complex frontend stacks.
With Streamlit, you can quickly create apps for machine learning, data exploration, simulations, and reporting — all powered by Python.
Watch our Streamlit platform overview video
Playground Examples
Streamlit provides an interactive playground where you can test widgets like sliders, buttons, checkboxes, and charts in real time. These examples help new users understand how a few lines of Python can generate interactive elements, such as:
- Adjusting a slider to control model parameters
- Create an interactive Chatbot
- Interacting with maps or charts without writing JavaScript
The playground gives a hands-on introduction before building full apps.
Streamlit API
The Streamlit API is minimal, intuitive, and built to feel like standard Python scripting. Common elements include:
- st.write() – Display text, dataframes, and charts
- st.slider() – Add a slider for numeric input
- st.selectbox() – Create dropdown menus
- st.file_uploader() – Upload files directly from the app
- st.map() – Quickly visualize geospatial data
Because the API is designed with simplicity in mind, building interactivity doesn’t require callbacks or complex state management.
Free Third-Party Components
Beyond the core API, Streamlit has a growing community-driven ecosystem of components. These components expand what’s possible, offering:
- Advanced charting libraries (Plotly, ECharts, Altair, Deck.GL)
- Interactive tables and grids
- Rich media viewers (video, audio, 3D models)
- Authentication and UI extensions
Developers can also create their own custom components using JavaScript, making Streamlit flexible for specialized use cases.
App Gallery
The Streamlit App Gallery showcases apps built by the community, demonstrating the framework’s versatility. Popular categories include:
- Machine Learning dashboards
- NLP text analyzers
- Financial data explorers
- Sports statistics apps
- Scientific simulations
Browsing the gallery can spark inspiration and help you adapt existing projects to your own needs.
Conclusion
Streamlit has redefined how Python developers and data professionals build and share interactive applications. With its simple API, thriving ecosystem of components, and active community, it enables anyone to create powerful apps quickly and for free.
Whether you’re building a data science prototype, ML demo, or business dashboard, Streamlit provides the fastest path from Python script to interactive app.