What are the key components or building blocks that make up a Streamlit application?

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What are the key components or building blocks that make up a Streamlit application?

Daniel Steinhold Asked question September 17, 2023

The key components or building blocks that make up a Streamlit application are:

  • Python code: Streamlit applications are written in Python. The code defines the layout of the application, the data that is displayed, and the interactions that users can have with the application.
  • Streamlit functions: Streamlit provides a number of functions that can be used to create and display different elements of a web application, such as text, images, charts, and widgets.
  • HTML, CSS, and JavaScript: Streamlit automatically generates HTML, CSS, and JavaScript code to render the application in a web browser. However, users can also write their own HTML, CSS, and JavaScript code to customize the appearance and behavior of their applications.

Here is a simple example of a Streamlit application:

import streamlit as st

# Create a title
st.title('My Streamlit App')

# Display some text
st.write('This is my first Streamlit app.')

# Create a chart
data = [1, 2, 3, 4, 5]

This application uses the following Streamlit functions:

  • st.title(): Creates a title for the application.
  • st.write(): Displays text in the application.
  • st.line_chart(): Creates a line chart.

The application also uses HTML, CSS, and JavaScript to render the chart and display the text.

Streamlit applications can be much more complex than this simple example. However, all Streamlit applications are built on the same basic components: Python code, Streamlit functions, and HTML, CSS, and JavaScript.

In addition to the basic components, there are a number of other features that can be used to build Streamlit applications, such as:

  • Interactive widgets: Streamlit provides a variety of interactive widgets, such as sliders, checkboxes, and drop-down menus. These widgets can be used to allow users to interact with the data and the application in different ways.
  • Caching: Streamlit can cache expensive computations, so that they do not have to be recalculated every time the application is re-rendered. This can improve the performance of applications that work with large datasets.
  • Deployment: Streamlit applications can be deployed to the cloud with a single click. This makes it easy to share applications with others.

Streamlit is a powerful and flexible tool for building interactive data applications. By understanding the key components of Streamlit applications, users can create a wide variety of applications, from simple data visualizations to complex dashboards to machine learning models.

Daniel Steinhold Changed status to publish September 17, 2023
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