Streamlit Download Graph !!link!! Page

Whether you are building a data dashboard or a machine learning tool, users eventually want to take your visualizations with them. Streamlit makes creating interactive charts easy, but exporting those charts as high-quality images or interactive files requires a few specific techniques.

💡 Always use io.BytesIO() when handling downloads in Streamlit. It keeps your app fast by processing everything in RAM instead of cluttering your server with temporary files. To help you get this working perfectly, let me know: streamlit download graph

If you use , Altair , or Vega-Lite , Streamlit displays these charts using a frontend component that already includes a download button. Whether you are building a data dashboard or

import plotly.express as px import io fig = px.bar(df, x='Year', y='Sales') # Create buffer buffer = io.BytesIO() fig.write_image(file=buffer, format="pdf") buffer.seek(0) st.download_button( label="Download High-Res PDF", data=buffer, file_name="report.pdf", mime="application/pdf" ) Use code with caution. Summary Table: Which Method Should You Use? Best Format Retains all zooms, tooltips, and toggles. Matplotlib Best for static reports and academic papers. Seaborn Easiest for quick statistical snapshots. Altair Good for web developers using Vega-Lite. It keeps your app fast by processing everything

This requires the kaleido library installed ( pip install kaleido ).

If you need a high-quality PNG or PDF for a presentation, you can use Plotly's write_image function.