Good day everyone. I would like to ask why I’ m having an error like this.
Hi @Bosti07! Welcome to the Streamlit community!
Apps deployed on Streamlit Sharing get up to 1 CPU, 800 MB of RAM, and 800 MB of dedicated storage in a shared execution environment.
What is the size of your dataset? If it’s on the order of Synthetic Financial Datasets For Fraud Detection, uploading subsets of that size a couple of times while simultaneously training your models are bound to exhaust the allotted 800 MB of RAM. It might help to cache the dataset with a shorter TTL.
Happy Streamlit-ing!
Snehan
Thank you so much for your reply.
Good day snehankekre. How can I read a csv file from the upload file. I have a snippet code but I’m having an error.
@Bosti07 You can avoid the error by first reading the file with pd.read_csv()
and then returning the dataframe df
. Here’s an example:
import streamlit as st
import pandas as pd
@st.cache
def read_file(file_path):
df = pd.read_csv(file_path)
return df
def main():
uploaded_file = st.file_uploader("Upload file", type=".csv")
if uploaded_file:
st.markdown("Uploaded file:")
df = read_file(uploaded_file)
st.dataframe(df)
if __name__=='__main__':
main()
Hope this helps!
Best,
Snehan
Wow it really works on me. Thank you so much.
Hi @snehankekre . Can I limit a upload file size from 200MB to 100MB?
Thank you so much.
You can change the default limit for st.file_uploader
by editing the following configuration option in your config.toml
to be 100MB:
# Max size, in megabytes, for files uploaded with the file_uploader.
# Default: 200
maxUploadSize = 100
Happy Streamlit-ing!
Snehan
Thank you so much I’m gonna try it now.
Good day @snehankekre . Is there a chance I can view it I’m already hitting the limit for my resources?
Thank you.