What is the Jupyter kernel, and how does it work?

The computational engine for notebooks is called a kernel. It decouples the evaluation from the read and print process, allowing users to continue writing and executing code while other code is executing. This parallel execution with kernels increases interactivity and speeds up the execution of code. Jupyter kernel architecture consists of several components that work together to execute code, manage the execution environment, and communicate with the frontend. The main benefits of using a kernel include improved UX, more frontends and backends, isolation, and better performance. Understanding how kernels work can help analysts anticipate potential issues, optimize their analyses, and leverage advanced functionalities to unlock the full potential of their data storytelling.

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