Streamlit - Introduction and Setup

Streamlit – Introduction and Setup

Last Updated : 23 Oct, 2020

Streamlit is an open source app framework in python language. It helps us create beautiful web-apps for data science and machine learning in a little time. It is compatible with major python libraries such as scikit-learn, keras, pytorch, latex, numpy, pandas, matplotlib, etc.. Syntax for installing this library is shown below.

Install StreamLit –
In the command-prompt type

pip install streamlit

Creating a Simple application (Hello World) –

The 'hello, world!' script in Streamlit:
streamlit hello

# to run your python script
streamlit run myFirstStreamlitApp.py

You can stop running your app any time using Ctrl + C.

Advantages:
1. It embraces python-scripting.
2. Less code is needed to create amazing web-apps.
3. No callbacks are needed since widgets are treated as variables.
4. Data caching simplifies and speeds up computation pipelines.

Disadvantages:
1. Streamlit’s Data caching cannot keep track of changes to the data happening outside the function body.

Some of its basic functions are described here.

1. Adding a Title

# myFirstStreamlitApp.py
  
#import the library
import streamlit as stl
  
# add title to your app
stl.title("Geeks for Geeks")

Output:

2. Adding some text

# myFirstStreamlitApp.py
  
#import the library
import streamlit as stl
  
# add title to your app
stl.title("Geeks for Geeks")
  
#adding text to your app
stl.write("A Computer Science portal for Geeks")

Output:

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My Personal Notes

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