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organizing-streamlit-code【开发与工程】Organizing Streamlit code for maintainability. Use when structuring apps with separate modules and utilities. Covers separation of concerns, keeping UI code clean, and import patterns.
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For most simple apps, keep everything in one file—it's cleaner and more straightforward. The app file should read like a normal Python script for data processing, with a few Streamlit commands sprinkled in.
Name the main file streamlit_app.py (Streamlit's default).
Keep in one file (most apps):
Consider splitting when:
If splitting makes sense, here's how to organize it.
my-app/
├── streamlit_app.py # Main entry point
├── app_pages/ # Page UI modules
│ ├── dashboard.py
│ └── settings.py
└── utils/ # Business logic & helpers
├── data.py
└── api.py
When you do split, keep Streamlit files focused on UI and move complex logic to utility modules:
# streamlit_app.py - UI-focused
import streamlit as st
from utils.data import load_sales_data, compute_metrics
st.title("Sales Dashboard")
start = st.date_input("Start")
end = st.date_input("End")
data = load_sales_data(start, end)
metrics = compute_metrics(data)
st.metric("Revenue", f"${metrics['revenue']:,.0f}")
st.dataframe(data)
Streamlit apps run the entire file on each interaction. Don't use the main guard in Streamlit files.
# BAD - don't do this in streamlit_app.py or pages
if __name__ == "__main__":
main()
# GOOD - just put the code directly
import streamlit as st
st.title("My App")
The main guard is fine in utility modules for quick testing:
# utils/data.py
def load_data(path):
...
# Optional: test this module directly with `python utils/data.py`
if __name__ == "__main__":
print(load_data("test.csv"))