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Journal Article

Jupyter in Computational Science

MPS-Authors
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Fangohr,  H.
Computational Science, Scientific Service Units, Max Planck Institute for the Structure and Dynamics of Matter, Max Planck Society;

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09387474.pdf
(Publisher version), 148KB

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Citation

Fangohr, H., Kluyver, T., & DiPierro, M. (2021). Jupyter in Computational Science. Computing in Science & Engineering, 23(2), 5-6. doi:10.1109/MCSE.2021.3059494.


Cite as: http://hdl.handle.net/21.11116/0000-0008-1E7D-C
Abstract
The articles in this special section discusses the applications supported by the Jupyter Notebook. Before notebooks, a scientist working with Python code, for instance, might have used a mixture of script files and code typed into an interactive shell. The shell is good for rapid experimentation, but the code and results are typically transient, and a linear record of everything that was tried would be long and not very clear. The notebook interface combines the convenience of the shell with some of the benefits of saving and editing code in a file, while also incorporating results, including rich output, such as plots, in a document that can be shared with others. The Jupyter Notebook is used through a web browser. Although it is often run locally, on a desktop or a laptop, this design means that it can also be used remotely, so the computation occurs, and the notebook files are saved, on an institutional server, a high-performance computing facility or in the clou