Metadata is a data Dictionary of definitions to set up and display the notebook. The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Documents Ī Jupyter Notebook document is a JSON file, following a versioned schema, usually ending with the ".ipynb" extension. It is designed to support many users by spawning, managing, and proxying many singular Jupyter Notebook servers. JupyterHub is a multi-user server for Jupyter Notebooks. GitHub announced in November 2022 that JupyterLab would be available in its online Coding platform called Codespace. Sloan Foundation funded work that led to expanded capabilities of the core Jupyter tools, as well as to the creation of JupyterLab. Helmsley Charitable Trust, The Gordon and Betty Moore Foundation, and The Alfred P. In 2015, a joint $6 million grant from The Leona M. The first stable release was announced on February 20, 2018. JupyterLab is a newer user interface for Project Jupyter, offering a flexible user interface and more features than the classic notebook UI. Jupyter interest overtook the popularity of the Mathematica notebook interface in early 2018. Jupyter Notebook is similar to the notebook interface of other programs such as Maple, Mathematica, and SageMath, a computational interface style that originated with Mathematica in the 1980s. A Jupyter Notebook application is a browser-based REPL containing an ordered list of input/output cells which can contain code, text (using Github Flavored Markdown), mathematics, plots and rich media. Jupyter Notebook is built using several open-source libraries, including IPython, ZeroMQ, Tornado, jQuery, Bootstrap, and MathJax. Jupyter Notebook (formerly IPython Notebook) is a web-based interactive computational environment for creating notebook documents. Jupyter Notebook can colloquially refer to two different concepts, either the user-facing application to edit code and text, or the underlying file format which is interoperable across many implementations. In 2021, Nature named Jupyter as one of ten computing projects that transformed science. Economist Paul Romer, in response, published a blog post in which he reflected on his experiences using Mathematica and Jupyter for research, concluding in part that Jupyter "does a better job of delivering what Theodore Gray had in mind when he designed the Mathematica notebook." The Atlantic published an article entitled "The Scientific Paper Is Obsolete" in 2018, discussing the role of Jupyter Notebook and the Mathematica notebook in the future of scientific publishing. As of July 2022, the Jupyter extension for VS Code has been downloaded over 40 million times, making it the second-most popular extension in the VS Code Marketplace. Visual Studio Code supports local development of Jupyter notebooks. Examples include Amazon SageMaker Notebooks, Google's Colaboratory, and Microsoft's Azure Notebook. Major cloud computing providers have adopted the Jupyter Notebook or derivative tools as a frontend interface for cloud users. In January 2021, nearly 10 million were available, including notebooks about the first observation of gravitational waves and about the 2019 discovery of a supermassive black hole. By 2018, about 2.5 million were available. In 2015, about 200,000 Jupyter notebooks were available on GitHub. Jupyter supports execution environments (called "kernels") in several dozen languages, including Julia, R, Haskell, Ruby, and Python (via the IPython kernel). IPython continues to exist as a Python shell and a kernel for Jupyter, while the notebook and other language-agnostic parts of IPython moved under the Jupyter name. In 2014, Pérez announced a spin-off project from IPython called Project Jupyter. The first version of Notebooks for IPython was released in 2011 by a team including Fernando Pérez, Brian Granger, and Min Ragan-Kelley. A manuscript ascribed to Galileo Galilei's observations of Jupiter (⊛) and four of its moons (✱), which inspired the Jupyter logo
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