Streamlit is an open source
python library which is use to create and develop custom web applications for
data science and machine learning.
Following are the steps one
can follow to build streamlit app
- Package installation
To use streamlit app, once has to install
streamlit python package.Following command using pip can be use to install
pip install streamlit
- Sample program - Hello
World
Create a python script app.py and start with simple "Hello World" streamlit app
import streamlit as st
def main():
st.title("Hello
Streamlit!")
st.write("This is a simple Streamlit app.")
if __name__ == "__main__":
main()
Following are the essential python components
1) Creating Widgets
Widgets are interactive components allowing
user input.
- Slider
import streamlit as st
value = st.slider('Select a value',
min_value=0, max_value=100)
- Text Input
text = st.text_input('Enter text')
- Checkbox
option = st.checkbox('Show/hide')
2) Displaying Data
Presenting data in various formats
- Display Dataframe
import pandas as pd
df = pd.DataFrame(data) # Your DataFrame
st.dataframe(df)
- Display Charts
import matplotlib.pyplot as plt
plt.plot(data)
st.pyplot()
3) Layouts and Styling
Providing structure to app and styling
- Columns
col1, col2 = st.columns(2)
with col1:
st.write("Column
1")
with
col2:
st.write("Column 2")
- Markdown and HTML
st.markdown('**Bold** text')
st.write("This is a regular text")
st.write("<p style='color:red'>This
is HTML</p>", unsafe_allow_html=True)
4) Handling User Inputs and Events
- Button Click
if st.button('Click me'):
st.write('Button clicked!')
- Event Handling
selection = st.selectbox('Choose an option',
options)
if selection == 'Option 1':
st.write('Option 1 selected!')
5) File Upload and Download
Managing file uploads/downloads
- File Upload
uploaded_file = st.file_uploader("Upload
file", type=['csv', 'txt'])
- File Download
download_button =
st.download_button('Download', data=your_data, file_name='data.csv')
6) Deployment Configuration
Configuration settings for deployment
- Page Title
st.set_page_config(page_title='My Streamlit
App', layout='wide')
- Caching
@st.cache
def expensive_computation(input):
# Perform costly computation
return result
result = expensive_computation(input_value)
