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A Jupyter Notebook document is a JSON file, following a versioned schema, usually ending with the ".ipynb" extension. The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Metadata is a data Dictionary of definitions to set up and display the notebook. Notebook Format is a version number of the software.
Notably, this review and other lists of ELN software often do not include widely used generic notetaking software like Onenote, Notion, Jupyter etc, due to their lack ELN nominal features like time-stamping and append-only editing. Some ELNs are web-based; others are used on premise and a few are available for both environments.
IPython continued to exist as a Python shell and kernel for Jupyter, but the notebook interface and other language-agnostic parts of IPython were moved under the Jupyter name. [11] [12] Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. [13]
A notebook interface or computational notebook is a virtual notebook environment used for literate programming, a method of writing computer programs. [1] Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections.
NotebookLM (Google NotebookLM) is a research and note-taking online tool developed by Google Labs that uses artificial intelligence (AI), specifically Google Gemini, to assist users in interacting with their documents. It can generate summaries, explanations, and answers based on content uploaded by users.
CoCalc supports Jupyter notebooks, which are enhanced with real-time synchronization for collaboration and a history recording function. Additionally, there is also a full LaTeX editor, with collaboration support, a preview of the resulting document and also support for SageTeX .
To complement the existing Rappture GUI tools within nanoHUB, the more recent browser based Jupyter notebooks are also available on nanoHUB, since 2017. Jupyter in nanoHUB offer new possibilities using the existing scientific software, and most notably all Rappture tools, within nanoHUB with the notebooks of interspersed code (e.g. Python ...
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