I have a cached function that does a time consuming operation on the data. There is a loop in the function and I have a progress bar to display the status. The inputs to the function are hashable and the outputs are 2 dataframes.
However, I found that the progress bar “reruns” each time the user interacts with the app even though the function is not supposed to be reran (it’s cached and the parameters did not change). It’s very quick but still annoying. The progress bar would drop to something like 30% and then quickly go up to 100%. But nothing is being done in the function, otherwise it would take far longer.
So I’m curious if there ways to avoid this behavior. Thanks
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import streamlit as st
progress_text = "Operation in progress. Please wait."
my_bar = st.progress(0, text=progress_text)
mylist = 
for i in range(num_iterations):
my_bar.progress(int(i/num_iterations * 100), text=progress_text)
output = append_list(10000)
selection = st.selectbox('Make a selection', ['Good','Bad'])
if selection == 'Good':
st.write('You selected Good')
st.write('You selected Bad')
In the above code, I have a progress bar inside a cached function. Upon completion of the function the progress should be 100%. However, if the user toggles the selection box at the bottom, the progress will fall to a lower value and go to 100% again, even though the function is cached, which means it shouldn’t be doing any more work.