Ah, unfortunately Matplotlib relies on generating static images at every Streamlit script rerun, so the FuncAnimation will also somewhere on the line be transformed to static animations, that doesn’t make it very friendly for live data. I usually go for Plotly, Altair or ECharts for dynamic plotting of data in the browser.
Then I would save the latest n points of live data in Streamlit cache and plot it on every tick.
GitHub - ash2shukla/streamlit-stream-stonks: An extended example of streaming application in streamlit of a Stocks Monitoring Dashboard. is my GOTO template for realtime plotting of windowed data in Streamlit and mostly uses this cycle. It uses asyncio (here a smaller example to reproduce locally) to pull data every n seconds, put it in a window cache and plot the results afterwards.
It’s a lot of information at once, but hope it does get you started on this solution!