Notebook interface

A notebook interface (also called a computational notebook) is a virtual notebook environment used for literate programming, a method of writing computer programs.^[1] Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections. Notebooks share some goals and features with spreadsheets and word processors but go beyond their limited data models.

Modular notebooks may connect to a variety of computational back ends, called "kernels". Notebook interfaces are widely used for statistics, data science, machine learning, and computer algebra.^[2]

At the notebook core is the idea of literate programming tools which "let you arrange the parts of a program in any order and extract documentation and code from the same source file."^[3], the notebook takes this approach to a new level extending it with some graphic functionality and a focus on interactivity. According to Stephen Wolfram: "The idea of a notebook is to have an interactive document that freely mixes code, results, graphics, text and everything else."^[4], and according to the Jupyter Project Documentation: "The notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based application suitable for capturing the whole computation process: developing, documenting, and executing code, as well as communicating the results. The Jupyter notebook combines two components".^[5]

History

VisiCalc, the first spreadsheet for personal computers, was published in 1979. Its idea of visual calculations is still widely used today but limited to documents that fit into a table.

Research on WYSIWYG mathematical systems supporting mixed text and calculations with a document metaphor begin to be published in 1987:^[6] Ron Avitzur's Milo,^[7] William Schelter's INFOR, Xerox PARC's Tioga^[8] and CaminoReal.^[9]

The earliest commercial system using the document metaphor was MathCAD, which also came out in 1987.^[10] Wolfram Mathematica 1.0 followed soon afterwards (1988).^[11][12][13] Later came Maple 5.2 (1992)^[14] and Macsyma 2.0 (1995).^[15]

As the notebook interface increased in popularity over the next two decades, notebooks for various computational back ends ("kernels") have been introduced, including MATLAB, Python, Julia, R, Scala, SQL, and others.^[16][17]

The variety of notebook interface has since been extended and new forms are still evolving.^[18]

Use

Notebooks are traditionally used in the sciences as electronic lab notebooks to document research procedures, data, calculations, and findings. Notebooks track methodology to make it easier to reproduce results and calculations with different data sets.^[16][17] In education, the notebook interface provides a digital learning environment, particularly for the teaching of computational thinking.^[19][4] Their utility for combining text with code makes them unique in the realm of education. Digital notebooks are sometimes used for presentations as an alternative to PowerPoint and other presentation software, as they allow for the execution of code inside the notebook environment.^[20][21] Due to their ability to display data visually and retrieve data from different sources by modifying code, notebooks are also entering the realm of business intelligence software.^{[16][22][23][24]}

Notable examples

Example of projects or products of notebooks:

Free/open-source notebooks

• Apache Zeppelin – Apache License 2.0^[25]
• Apache Spark Notebook^[26] – Apache License 2.0
• IPython – BSD
• Jupyter Notebook (formerly IPython) – Modified BSD License (shared copyright model)^[27]
  • Google Colaboratory – No setup Jupyter notebook environment – Free software^[28]
  • Amazon SageMaker – ML Focused Jupyter notebook environment – Free Basic Access
  • Pycharm Notebook Integration – Jupyter notebook interface/frontend notebooks for Jetbrains IDEs, this is a premium feature but source code can be found here
  • VSCode Notebook Support – Jupyter notebook interface/frontend and API for VSCode
• JupyterLab – Revised BSD License^[29]
• Starboard – A shareable In-browser literal notebook, source code can be found here
• Mozilla Iodide – MPL 2.0; development in alpha stage^[30]
• R Markdown^[31] – GPLv3;^[32] source code can be found here
• SageMath – GPLv3
• Org-mode on emacs (with the built-in babel addon) – GPL
• Xamarin Workbooks for DotNet – MIT
• Polynote Apache License 2.0
• GNU TeXmacs (a document processor which can act as notebook interface as well) – GPLv3^[33]
• Javalí Notebooks: Java-based notebooks environment and LMS with debugging and unit test support, designed for the academy, a presentation video can be found here.,

Partial copyleft

• SMath Studio – Freeware, not libre: licensed under Creative Commons Attribution-No Derivatives

Proprietary notebooks

• Wolfram Mathematica
• Mathcad
• Matlab – Live Editor since 2016.
• Noteable^[34]
• Noteable^[35]
• Deepnote^[36]
• Carbide^[37]
• Databricks cloud (founded 2013).^[16][38]
• Datalore^[39]
• Nextjournal^[40]
• Observable^[41] – Uses open-source components,^[42] but the look and feel are proprietary^[43]
• WolframAlpha Notebooks^[44]

References

1. Standage, Daniel (2015-03-13). "Literate programming, RStudio, and IPython Notebook". BioWize. Wordpress. Retrieved 2016-12-01.
2. Jupyter, Project (20 February 2018). "JupyterLab is Ready for Users". Retrieved 30 May 2018.
3. Ramsey, N. (September 1994). "Literate programming simplified". IEEE Software. 11 (5): 97–105. doi:10.1109/52.311070. ISSN 0740-7459. S2CID 18593796.
4. "How to Teach Computational Thinking—Stephen Wolfram". blog.stephenwolfram.com. Retrieved 2016-11-23.
5. "The Jupyter Notebook — Jupyter Notebook 6.2.0 documentation". jupyter-notebook.readthedocs.io. Retrieved 2021-05-03.
6. Dennis S. Arnon, ed., "Workshop on Environments for Computational Mathematics (July 1987)", Computer Graphics 22:1 (February 1988)
7. Richard J. Fateman, "Computer Systems for the Representation and Manipulation of Mathematical Knowledge", Final report, August 1987 (DTIC AD-A193 547)
8. Butler W. Lampson, "Personal Distributed Computing: The Alto and Ethernet Software", A history of personal workstations, 1988, ISBN 0201112590, p. 318.
9. Dennis Arnon, Richard Beach, Kevin McIsaac, "CaminoReal: An Interactive Mathematical Notebook", in J.C. van Vliet, ed., Document Manipulation and Typography, Proceedings of the International Conference on Electronic Publishing, Document Manipulation and Typography, Nice, April 20–22, 1988, ISBN 0521362946, p. 2.
10. N. Kajler, N. Soiffer, "A Survey of User Interfaces for Computer Algebra Systems", Journal of Symbolic Computation 25:2:127-159 (February 1998), doi:10.1006/jsco.1997.0170
11. The ReDiscovered Future (2016-04-04), Macintosh + Mathematica = Infinity - April 1989, retrieved 2016-11-23
12. Hayes, Brian (1990). "Thoughts on Mathematica" (PDF). PIXEL. January/February 1990: 28–35.
13. "Launching Wolfram Player for iOS—Wolfram". Retrieved 2016-11-23.
14. "Maple V Release 2 - Maple Help". www.maplesoft.com. Retrieved 2023-01-18.
15. "Macsyma 2.0", Design News, April 24, 1995
16. Osipov, Matt (2016-05-04). "The Rise of Data Science Notebooks". Datanami. Tabor Communications. Retrieved 2016-12-20.
17. "The IPython notebook: a historical retrospective". blog.fperez.org. Retrieved 2016-11-23.
18. Lau, Sam; Drosos, Ian; Markel, Julia M.; Guo, Philip J. (August 2020). "The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry". 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC): 1–11. doi:10.1109/VL/HCC50065.2020.9127201.
19. Barr, Valerie; Stephenson, Chris (2011). "Bringing computational thinking to K-12: what is involved and what is the role of the computer science education community?".
20. Databricks (2015-07-06), Spark Summit 2015 demo: Creating an end-to-end machine learning data pipeline with Databricks, retrieved 2016-11-23
21. Frazier, Cat (2018-04-17). "Announcing Wolfram Presenter Tools". Retrieved 2018-11-27.
22. Andrews, Ian (2016-03-30). "Delivering information in context". O'Reilly Media. Retrieved 2016-11-23.
23. "jupyter-incubator/dashboards". GitHub. Retrieved 2016-11-23.
24. Sharma, Shad. "Business Intelligence with Mathematica and CDF". Retrieved 2018-11-27.
25. "Zeppelin". Apache. Retrieved 2018-12-20.
26. . Archived from the original on 2018-10-01. Retrieved 2018-09-30.
27. Jupyter Development Team (2015-04-22). "Licensing terms". Jupyter Notebook. GitHub. Retrieved 2018-12-20.
28. "a Jupyter notebook environment that requires no setup to use". Retrieved 2020-12-29.
29. "LICENSE". Project Jupyter Contributors. 2018-07-19. Retrieved 2018-12-20.
30. "Iodide". GitHub. Retrieved 2018-12-20.
31. "R Markdown". R Studio. Retrieved 2018-09-30.
32. "Licene". Readme. GitHub. 2018-12-07. Retrieved 2018-12-20.
33. "Welcome to GNU TeXmacs". Retrieved 2020-11-28.
34. "Noteable". noteable.io. Noteable, Inc. Retrieved 2021-05-21.
35. "Noteable - Computational Notebook Platform for Education". noteable.edina.ac.uk. Retrieved 2021-08-12.
36. "Deepnote". deepnote.com. Deepnote, Inc. Retrieved 2020-12-30.
37. "Carbide Alpha | Buggy But Live!". Try Carbide. Retrieved 2018-12-20.
38. "Databricks Unified Analytics Platform". San Francisco, CA: Databricks Inc. 2018. Retrieved 2018-12-20.
39. "Datalore". JetBrains s.r.o. Retrieved 2019-08-08.
40. "Nextjournal". nextjournal.com. Nextjournal GmbH. 2018. Retrieved 2018-12-20.
41. "Observable". Observable HQ. Retrieved 2018-09-30.
42. Observable (2018-12-15). "Repositories". San Francisco, California: Observable via GitHub. Retrieved 2018-09-30.
43. "Terms of Service". Observable. 2018. Retrieved 2018-01-12.
44. "WolframAlpha Notebook Edition". Retrieved 2021-01-12.