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What is Streamlit?

Streamlit serves as an incredibly efficient solution for the creation and dissemination of data applications. With this platform, users can convert their data scripts into easily shareable web apps in a matter of minutes, leveraging Python without incurring any costs, and it removes the barriers that come with needing front-end development expertise. The platform is anchored by three foundational principles: it promotes the use of Python scripting for application creation; it allows users to build applications with minimal code by utilizing a user-friendly API that automatically updates upon saving the source file; and it enhances user interaction by enabling the inclusion of widgets as effortlessly as declaring a variable, all without the need to handle backend development, define routes, or manage HTTP requests. Furthermore, applications can be deployed instantly through Streamlit’s sharing platform, which streamlines the processes of sharing, managing, and collaborating on projects. This straightforward framework allows for the development of powerful applications, such as the Face-GAN explorer that integrates Shaobo Guan’s TL-GAN project and utilizes TensorFlow and NVIDIA’s PG-GAN for generating attribute-based facial images. Another compelling example is a real-time object detection application designed as an image browser for the Udacity self-driving car dataset, demonstrating impressive capabilities in real-time object processing and recognition. Overall, Streamlit is not only beneficial for developers but also serves as a vital resource for data enthusiasts, enabling them to explore innovative projects with ease. Each of these features highlights why Streamlit has become a preferred choice for many in the data community.

What is Jupyter Notebook?

Jupyter Notebook is a versatile, web-based open-source application that allows individuals to generate and share documents that include live code, visualizations, mathematical equations, and textual descriptions. Its wide-ranging applications include data cleaning, statistical modeling, numerical simulations, data visualization, and machine learning, highlighting its adaptability across different domains. Furthermore, it acts as a superb medium for collaboration and the exchange of ideas among professionals within the data science community, fostering innovation and collective learning. This collaborative aspect enhances its value, making it an essential tool for both beginners and experts alike.

Media

Media

Integrations Supported

Azure Marketplace
Beam Cloud
Gradient
NewsData.io
Streamoku

Integrations Supported

Azure Marketplace
Beam Cloud
Gradient
AMD Developer Cloud
AnzoGraph DB
CodeSquire
Dropbox
Giskard
Great Expectations
Kedro
Kubernetes
LocalStack
Pop!_OS
Sharon AI
Spell
Tengu
Zepl

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Streamlit

Company Location

United States

Company Website

www.streamlit.io

Company Facts

Organization Name

Project Jupyter

Date Founded

2014

Company Website

jupyter.org

Categories and Features

Data Science

Not specified

Categories and Features

Data Science

Not specified

Popular Alternatives

Popular Alternatives

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