Jupyter Notebooks have been a widely popular tool for data science in recent years due to their ability to combine code, text, and visualizations in a single document. Despite its popularity, the core functionality and user experience of the Classic Jupyter Notebook interface has remained largely unchanged over the past years. Lately the Jupyter Notebook project decided to base its next major version 7 on JupyterLab components and extensions, which means many JupyterLab features are also available to Jupyter Notebook users. In this presentation, we will demo the new features coming in Jupyter Notebook version 7 and how they are relevant to existing users of the Classic Notebook.
Jupyter Notebook 7 is based on the JupyterLab codebase, but provides an equivalent user experience to the current (version 6) application. Notebook 7 keeps the document-centric user experience at its core, and brings many new features that were not previously available: - Debugger - Real-time collaboration - Theming and dark mode - Internationalization - Improved Web Content Accessibility Guidelines (WCAG) compliance - Support for many JupyterLab extensions, including Jupyter LSP (Language Server Protocol) for enhanced code completions - Performance improvements This talk will be about demoing the new features coming to Notebook 7, and how uses of the Classic Notebook interface should approach. We will also cover other aspects mentioned in the related Jupyter Enhancement Proposal, such as support for popular extensions and future developments: https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html
Speakers: Jeremy Tuloup