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Description

JS Bin is an online platform designed for testing and experimenting with various web technologies, most notably HTML, CSS, and JavaScript, while also accommodating other languages such as Markdown, Jade, and Sass. At its core, JS Bin serves as a code-sharing hub, enabling users to share not just their code but also the complete results produced by it with fellow developers, peers, or students. As you make changes in one of the editing panels, both you and anyone observing your bin can see the output update in real-time within the designated output panel. JS Bin is packed with numerous features, yet it adheres to a design philosophy ensuring that every user has access to a cursor from the moment they arrive. Upon your first visit, you will encounter a basic starter HTML page along with minimal distractions, although there is the option to customize your default code for convenience. By registering for a free account, which is a straightforward process, you can have your profile retain a record of the bins you've created and also provide you with a shortcut URL that directs you to the most recent bin you worked on, making it easy to revisit your projects. Moreover, this allows for a seamless workflow, enabling programmers to efficiently iterate on their coding experiments.

Description

Project Jupyter is dedicated to the creation of open-source tools, standards, and services that facilitate interactive computing in numerous programming languages. At the heart of this initiative is JupyterLab, a web-based interactive development environment designed for Jupyter notebooks, coding, and data manipulation. JupyterLab offers remarkable flexibility, allowing users to customize and organize the interface to cater to various workflows in fields such as data science, scientific research, and machine learning. Its extensibility and modular nature enable developers to create plugins that introduce new features and seamlessly integrate with existing components. The Jupyter Notebook serves as an open-source web application enabling users to produce and share documents that incorporate live code, mathematical equations, visualizations, and descriptive text. Common applications of Jupyter include data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Supporting over 40 programming languages—including popular ones like Python, R, Julia, and Scala—Jupyter continues to be a valuable resource for researchers and developers alike, fostering collaborative and innovative approaches to computing challenges.