Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver interactive data apps – in only a few lines of code. 🚀 Release 1.42 is here: authentication, dataframe updates, and more! 🤩

You'll learn what makes Streamlit the most powerful way to build data apps, including the ability to display and style data, draw charts and maps, add interactive widgets, customize app layouts, cache computation, and define themes.

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver dynamic data apps with only a few lines of code. Build and deploy powerful data apps in minutes. Let's get started!

The goal is to use Streamlit to create an interactive app for your data or model and along the way to use Streamlit to review, debug, perfect, and share your code. In this guide, you're going to use Streamlit's core features to create an interactive app; exploring a public Uber dataset for pickups and drop-offs in New York City.

In summary, Streamlit offers a quick, efficient, and code-friendly way to build interactive dashboard apps in Python, making it a go-to tool for data scientists and developers working with data visualization.

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver interactive data apps – in only a few lines of code. 🚀 Release 1.42 is here: authentication, dataframe updates, and more! 🤩

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver interactive data apps – in only a few lines of code.

Streamlit's architecture allows you to write apps the same way you write plain Python scripts. To unlock this, Streamlit apps have a unique data flow: any time something must be updated on the screen, Streamlit reruns your entire Python script from top to bottom.

2024年7月23日 · What is Streamlit? Streamlit is an open-source Python framework to build highly interactive data apps – in only a few lines of code. The point of Streamlit is to allow you to focus on what’s most important to you: Your data analysis! Intuitive syntax

There are multiple ways to set up your development environment and install Streamlit. Read below to understand these options. Developing locally with Python installed on your own computer is the most common scenario.