What is Streamlit and How to Use it for Building Interactive Web Applications

Streamlit is an open-source Python library that allows users to create and share interactive web applications for data science and machine learning projects. It simplifies the process of building and deploying web applications by providing an intuitive and user-friendly interface.

Streamlit vs Flask: Which is Better?

While both Streamlit and Flask are popular choices for building web applications, they serve different purposes and have different strengths.

Flask is a micro web framework that provides a solid foundation for building web applications in Python. It offers more flexibility and control over the application’s structure and components. Flask is a great choice for developers who prefer to have full control over the backend and want to build complex web applications with custom functionalities.

On the other hand, Streamlit focuses on simplicity and ease of use. It is specifically designed for quickly building interactive data science applications without requiring extensive web development knowledge. Streamlit provides a higher level of abstraction and automates many common tasks, such as rendering charts and handling user inputs. It is an excellent choice for data scientists and researchers who want to create and share interactive visualizations and prototypes.

Ultimately, the choice between Streamlit and Flask depends on the specific requirements and preferences of your project. If you need more control and customization, Flask may be the better option. However, if you prioritize simplicity and rapid prototyping, Streamlit can be a powerful tool.

Streamlit for Backend or Frontend?

Streamlit is primarily used for building the frontend of web applications. It provides a simple way to create interactive user interfaces and visualize data in a web browser. However, Streamlit can also interact with backend services and APIs to fetch and process data.

When using Streamlit, you can write Python code to define the layout and functionality of your web application. Streamlit takes care of rendering the user interface and handling user interactions. It provides a variety of built-in components, such as sliders, dropdowns, and buttons, that you can use to create interactive elements.

Streamlit also supports integrating with backend services and databases. You can use Python libraries and frameworks, such as Flask or Django, to handle data processing and communication with external APIs. Streamlit can then consume the processed data and display it in the frontend.

Example of Using Streamlit

Here is a simple code example that demonstrates how to use Streamlit to create an interactive web application:

import streamlit as st

# Define the title and introductory text
st.title("Interactive Web Application")
st.write("Welcome to my web application!")

# Add a slider component
age = st.slider("Select your age", 0, 100)

# Add a button component
button_clicked = st.button("Click Me")

# Display the selected age and button click status
st.write("Your age:", age)
st.write("Button clicked:", button_clicked)

In this example, we import the Streamlit library and use its functions to define the title, introductory text, slider, and button components. The selected age and button click status are then displayed using the write function.

By running this code with the Streamlit command, you can launch a web application that allows users to select their age using a slider and click a button. The selected age and button click status will be dynamically updated and displayed on the web page.

Streamlit simplifies the process of building interactive web applications by providing an intuitive and streamlined interface. It allows data scientists and developers to quickly prototype and share their projects without the need for extensive web development knowledge.

Whether you choose Streamlit or Flask, both tools offer unique advantages for building web applications. Consider your project requirements and preferences to make an informed decision on which tool is best suited for your needs.