streamlit

Streamlit Core Knowledge

Installation & Run

pip install streamlit
streamlit run app.py
streamlit run app.py --server.port 8080

Core Concepts

App Execution Model

Streamlit re-runs the entire script top-to-bottom on every user interaction. Use caching and session_state to avoid redundant work.

Session State

import streamlit as st

# Initialize (always check first)
if "data" not in st.session_state:
    st.session_state.data = []

# Read and write
st.session_state.data.append(item)
st.write(st.session_state.data)

# Callback pattern (preferred for widget interactions)
def on_submit():
    st.session_state.result = process(st.session_state.input_val)

st.text_input("Input", key="input_val")
st.button("Submit", on_click=on_submit)

Caching

# @st.cache_data — serializable return values (DataFrames, dicts, lists)
@st.cache_data(ttl=600)  # cache expires in 10 min
def load_dataset(path: str) -> pd.DataFrame:
    return pd.read_csv(path)

# @st.cache_resource — non-serializable (DB connections, ML models)
@st.cache_resource
def get_model():
    return load_ml_model("model.pkl")

# Clear cache programmatically
load_dataset.clear()

Layout & Components

Columns

col1, col2 = st.columns(2)          # equal width
col1, col2, col3 = st.columns([3, 1, 1])  # weighted

with col1:
    st.metric("Revenue", "$12,345", delta="+5%")
with col2:
    st.image("logo.png")

Tabs

tab1, tab2, tab3 = st.tabs(["Overview", "Details", "Export"])
with tab1:
    show_overview()
with tab2:
    show_details()

Sidebar

with st.sidebar:
    selected = st.selectbox("Area", options=["11301", "11090", "27301"])
    date_range = st.date_input("Date range", value=(start, end))

Expander

with st.expander("Advanced Options", expanded=False):
    threshold = st.slider("Threshold", 0.0, 1.0, 0.5)

Input Widgets

# Text
name = st.text_input("Name", placeholder="Enter tag name")
text = st.text_area("Description", height=100)

# Numbers
n = st.number_input("Count", min_value=0, max_value=1000, value=10, step=1)
ratio = st.slider("Ratio", 0.0, 1.0, 0.5)

# Selection
choice = st.selectbox("Type", ["Motor", "Valve", "Analog"])
choices = st.multiselect("Areas", ["11301", "11090"])
flag = st.checkbox("Include alarms", value=True)
option = st.radio("Export format", ["CSV", "Excel", "JSON"])

# File upload
uploaded = st.file_uploader("Upload Excel", type=["xlsx", "xls"])
if uploaded:
    df = pd.read_excel(uploaded)