jupyter contrib nbextension installĪfter installing, open Jupyter Notebook. Next, run the following code to add the nbextensions files into the Jupyter server’s search directory. We will run the following code in the command prompt to install these Jupyter Notebook extensions. As mentioned earlier, since most of the extensions are written in Javascript, these can be run locally in the browser. Jupyter Notebook ExtensionsĪll the extensions mentioned in this article are available through an open-source package, ‘jupyter_contrib_nbextensions.’ This python package includes multiple unofficial extensions provided by the community that extends the capability of the Jupyter Notebook. It is important to note that these extensions are not supported in Jupyter Lab. Written in JavaScript, these extensions are presently supported in the Jupyter Notebooks environment only. These extensions can autoformat the code, provide information while the cell is running, and display a browser message when code execution is finished. These are simple add-ons that improve the Jupyter Notebook environment’s core features. In such a situation, Jupyter Notebook extensions come in handy to make the above task easier. However, the vanilla environment lacks certain features which makes it tedious to handle complex codes. The basic Jupyter Notebook environment is more befitting for general training and educational machine learning/deep learning model development requirements. Therefore, most data science professionals tend to use Jupyter Notebooks to create and share documents, including code, equations, visualizations, computational outputs, markdown text, etc. ![]() The Jupyter Notebook supports more than 40 different programming languages like R, Python, Java, etc. Jupyter Notebook is an easy-to-use, open-source tool for web-based interactive computing. This article was published as a part of the Data Science Blogathon.
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