![]() ![]() The notebook server persists the output in a file, ending in. When a cell is executed, the output from the kernel is captured. ![]() ![]() The server ensures that all user edits and actions are executed in the kernel. The cells can contain code or documentation, like markdown. However, nothing in this article requires that Python be the language of choice for the kernel.Ī user interacts with a notebook server (usually, but not always via a web browser as you’ll soon see) to edit cells in the notebook. Jupyter supports other languages, but for now, we’ll assume we’re talking about Python. The kernel is the process where the notebook runs, and each is independent of the other. As you can see in the architecture diagram below, the notebook server can communicate to multiple kernels. A notebook file is usually created via an interactive process by the author using a web application for authoring the notebook document. Since a cell can be executed multiple times in an interactive session, the notebook will contain the most recent execution and results. It contains cells that contain code or descriptive text, along with the output of executing the code. It’s essentially a captured interactive session with an interpreter. A notebook is a combination of code, documentation, and output. First, what is a notebook?īefore we look at the options, let’s review what a Jupyter notebook is. The notebook ecosystem is expanding and there are a lot of options, so let’s dig in. It will also talk about some of the advantages and disadvantages of each. This article will cover four ways to run Jupyter notebooks. Jupyter notebooks are an increasingly popular way to write, execute, document, and share code and communicate the results, especially in the Python ecosystem. ![]()
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