Simple way to run heavy computations without slowing down other Streamlit users

streamlit_app.py

import streamlit as st
import concurrent.futures # We'll do computations in separate processes!
import mymodule # This is where you'll do the computation

# Your st calls must go inside this IF block.
if __name__ == '__main__':
    st.write("Starting a long computation on another process")

    # Pick max number of concurrent processes. Depends on how heavy your computation is, and how
    # powerful your machine is.
    MAX_WORKERS = 50

    @st.cache_resource
    def get_executor():
        return concurrent.futures.ProcessPoolExecutor(max_workers=MAX_WORKERS)

    future = get_executor().submit(
      # Function to run on a separate process.
      mymodule.some_heavy_computation,

      # Arguments to pass to the function above.
      a=100, b=200, c=300)

    # Wait for result.
    result = future.result()

    st.write("Here's the result of that computation:", result)