Streamlit Widgets: Collecting and Handling User Input

Widgets are the interactive building blocks of every Streamlit app. They let users provide data, make selections, upload files, and trigger actions — and because Streamlit reruns your script on every interaction, the rest of your app responds to widget values automatically. Each widget function returns the current value chosen by the user, which you can store in a variable and use anywhere in your Python logic. This page covers every major widget type with ready-to-use code examples.

Buttons

A button triggers an action when clicked. The button function returns True for the single rerun that follows a click, then False again on all subsequent reruns.

import streamlit as st

if st.button("Generate Report"):
    st.write("Report generated successfully!")

# Disabled button
st.button("Submit", disabled=True)

Text Input and Text Area

Use text fields for free-form user input. text_input is for short, single-line values; text_area is for longer, multi-line content.

import streamlit as st

name    = st.text_input("Your name", placeholder="e.g. Amit Patel")
email   = st.text_input("Email address", placeholder="[email protected]")
bio     = st.text_area("Short bio", height=120, placeholder="Tell us about yourself…")

if name:
    st.write(f"Hello, {name}!")

Selectbox, Radio, and Checkbox

These widgets handle single-choice and toggle selections:

import streamlit as st

# Drop-down — single choice from a list
city = st.selectbox("Choose city", ["Mumbai", "Delhi", "Bengaluru", "Hyderabad"])

# Radio buttons — visible options, single choice
gender = st.radio("Gender", ["Male", "Female", "Prefer not to say"])

# Checkbox — boolean toggle
agree = st.checkbox("I agree to the terms and conditions")

st.write(f"Selected city: {city}")
if agree:
    st.success("Thank you for agreeing!")

Multiselect

Allow users to choose multiple values from a list:

import streamlit as st

skills    = st.multiselect("Select your skills", ["Python", "SQL", "Machine Learning", "FastAPI"])
languages = st.multiselect("Programming languages", ["Python", "JavaScript", "Java", "C++"])

if skills:
    st.write(f"You selected: {', '.join(skills)}")

Number Input and Slider

For numeric values, choose between a text field with increment/decrement arrows or a draggable slider:

import streamlit as st

age    = st.number_input("Age", min_value=0, max_value=120, value=25, step=1)
salary = st.number_input("Monthly salary (₹)", min_value=0, value=50000, step=1000)
rating = st.slider("Customer rating", min_value=1, max_value=10, value=5)
budget = st.slider("Budget range (₹)", min_value=0, max_value=100000, value=(20000, 60000))

st.write(f"Age: {age}, Rating: {rating}")
st.write(f"Budget: ₹{budget[0]:,} – ₹{budget[1]:,}")

Passing a tuple as the value argument to st.slider creates a range slider with two handles, perfect for price or date range filters.

File Uploader

Let users upload files from their local machine. The returned object behaves like a file handle you can pass directly to Pandas or other libraries:

import streamlit as st
import pandas as pd

uploaded_file = st.file_uploader(
    "Upload a CSV file",
    type=["csv"],
    help="Only CSV files are accepted"
)

if uploaded_file is not None:
    df = pd.read_csv(uploaded_file)
    st.success(f"Loaded {len(df)} rows and {len(df.columns)} columns.")
    st.dataframe(df.head())

You can accept multiple file types simultaneously:

media = st.file_uploader("Upload image or document", type=["png", "jpg", "pdf"])

Date and Time Inputs

Use date and time pickers for scheduling or filtering by date:

import streamlit as st
import datetime

birthday     = st.date_input("Date of birth", value=datetime.date(2000, 1, 1))
meeting_time = st.time_input("Meeting time", value=datetime.time(9, 0))

# Date range
start_date = st.date_input("Start date")
end_date   = st.date_input("End date")

st.write(f"Birthday: {birthday}")
st.write(f"Meeting at: {meeting_time}")

Combining Widgets

In a real app, you’ll combine multiple widgets and use their values together. Here’s a simple employee filter:

import streamlit as st
import pandas as pd

employees = pd.DataFrame({
    "Name":       ["Rahul", "Anitha", "Kiran", "Sneha"],
    "City":       ["Hyderabad", "Bengaluru", "Hyderabad", "Chennai"],
    "Salary":     [65000, 55000, 72000, 50000],
    "Department": ["Engineering", "HR", "Engineering", "Sales"]
})

st.title("Employee Filter")

city    = st.selectbox("Filter by city", ["All"] + employees["City"].unique().tolist())
min_sal = st.slider("Minimum salary", 0, 100000, 50000, step=5000)

filtered = employees.copy()
if city != "All":
    filtered = filtered[filtered["City"] == city]
filtered = filtered[filtered["Salary"] >= min_sal]

st.dataframe(filtered)
st.info(f"Showing {len(filtered)} of {len(employees)} employees.")

All widget values are re-evaluated on every script rerun. If you need to persist a value across reruns (e.g., a counter or authenticated user), use st.session_state — covered in the Building Apps chapter.

SQL & Databases

Data Analysis

FastAPI

Frontend

Streamlit Widgets: Collecting and Handling User Input

Buttons

Text Input and Text Area

Selectbox, Radio, and Checkbox

Multiselect

Number Input and Slider

File Uploader

Date and Time Inputs

Combining Widgets

​Buttons

​Text Input and Text Area

​Selectbox, Radio, and Checkbox

​Multiselect

​Number Input and Slider

​File Uploader

​Date and Time Inputs

​Combining Widgets

Buttons

Text Input and Text Area

Selectbox, Radio, and Checkbox

Multiselect

Number Input and Slider

File Uploader

Date and Time Inputs

Combining Widgets