Introducing Streamlit sharing! Check out the blog post here.
Try out Streamlit Components created by the community, and add new functionality to your apps. Want to create your own?
Check out the Streamlit Components API.
A lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data using parallel plots and other graphical ways to represent information.
> pip install hiplot
Making Vega-Lite selection created by user interactions available in Python.
> pip install streamlit-vega-lite
Embed Observable notebooks into Streamlit apps.
> pip install streamlit-observable
Use the echarts package on your Streamlit apps.
> pip install streamlit-echarts
Use Terran for creating video timelines on your Streamlit apps.
> pip install streamlit-terran-timeline
spaCy building blocks and visualizers for Streamlit apps.
> pip install spacy-streamlit
Pandas profiling component for Streamlit.
> pip install streamlit-pandas-profiling
streamlit-embedcode is the easiest way to embed code snippets into your Streamlit app.
> pip install streamlit-embedcode
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit?
> pip install streamlit-drawable-canvas
Streamlit component featuring the Ace code editor.
> pip install streamlit-ace
Take a randomized array in Python, pass it to a React component and build a D3 chart over it with transitions.
> pip install streamlit-d3-demo
A streamlit component for bi-directional communication with bokeh plots.
pip install streamlit-bokeh-events
Streamlit Component for rendering Folium maps.
pip install streamlit-folium
A simple component to display annotated text in Streamlit apps.
> pip install st-annotated-text
Learn how to wrap your JavaScript and HTML code into a Python
package that can be rendered in any Streamlit app.
Components are created and maintained by members of the Streamlit community and issues should be posted directly to their GitHub repos.
