I’m reading data from sensors, which I understand might not be the best use case for Streamlit. Nonetheless, I like all the other features so much that I am willing to use Streamlit.
I’m wondering if there’s a way to speed up how fast line_charts take.
Here is an example:
import time import random import streamlit as st data1 = deque(*5) data2 = deque(*5) graph1 = st.empty() graph2 = st.empty() while True: data1.popleft() data1.append(5 + random.randint(-5, 5)) data2.popleft() data2.append(4 + random.randint(3, 9)) graph1.line_chart(list(data1)) graph2.line_chart(list(data2)) time.sleep(1)
I expect the two graphs to update at around the same time every second, but instead the first one updates, a brief half second pause, and then the second one updates, and then there’s the 1 second delay. I don’t believe it’s because of the various deque operations as there is only 5 elements in these lists.
Also, because this is simulating sensor data, data is random and caching will be pretty much impossible.