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docs/comparisons/utility/notebooks.md

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@@ -13,31 +13,32 @@ They are particularly useful for sharing and showing computations.
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> Julia kernel for Jupyter
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[Jupyter](https://github.com/jupyter/) is the original notebook. The name is a reference to the three core programming languages supported by Jupyter: Julia, Python and R[^1]. It
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This is very mature, and used by a large community. This should probably be the first one you try.
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A jupyter notebook is organized in "cells".
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It is very mature, and used by a large community. This should probably be the first one you try.
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A Jupyter notebook is organized in "cells".
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Cells can contain either text (in [markdown](https://en.wikipedia.org/wiki/Markdown) format) or code.
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The code is evaluated in the kernel as if you were entering the same code into a Julia session.
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The [Colab](https://colab.google/) service makes it easy to test Jupyter without needing to install anything locally.
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It also includes a Julia kernel.[^2]
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The main kernels are :
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The main kernels supported by Jupyter are :
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* Python: [IPython](https://github.com/ipython/ipython) (the default kernel shipped with Jupyter)
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* Juila: [IJulia.jl](https://github.com/JuliaLang/IJulia.jl)
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* Julia: [IJulia.jl](https://github.com/JuliaLang/IJulia.jl)
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* R: [IRkernel](https://github.com/IRkernel/IRkernel), [ark](https://github.com/posit-dev/ark) (a new kernel developed by [Posit](https://posit.co/) (previously RStudio) for the [Positron](https://github.com/posit-dev/positron) IDE)
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## Pluto
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{{badge Pluto}}
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> 🎈 Simple reactive notebooks for Julia
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Where Jupyter is multi language (and mainly python), [Pluto.jl](https://github.com/fonsp/Pluto.jl) is a Julia project and mainly (only?) supports Julia.
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It also differs from Jupyter in the execution model.
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Where Jupyter is multi language (and mainly Python), [Pluto.jl](https://github.com/fonsp/Pluto.jl) is a Julia project and mainly (only?) supports Julia.
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Where the state of the jupyter kernel depends on the order in which cellse were run, Pluto maintains a consistent state, where all cells are updated in a [reactive](https://en.wikipedia.org/wiki/Reactive_programming) manner.
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It also differs from Jupyter in the execution model.
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Where the state of the Jupyter kernel depends on the order in which cells were run, Pluto maintains a consistent state, where all cells are updated in a [reactive](https://en.wikipedia.org/wiki/Reactive_programming) manner.
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An other difference is that cells in Pluto only contain a single line of code.
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Many people are very happy with the Pluto model, where the state is always consistent (as in a spreadsheet), where others prefer the linar execution model of Jupyter notebooks where you often need to restart the kernel and run from the top to make sure all is consistent.
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Many people are very happy with the Pluto model, where the state is always consistent (like in a spreadsheet). Others prefer the linear execution model of Jupyter notebooks, which is more similar to an interactive Julia session, but where you often need to "restart the kernel and run from the top" to make sure all is consistent.
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You can test Pluto in the browser without installing it at <https://binder.plutojl.org/>.
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{{badge Neptune}}
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> Simple (Pluto-based) non-reactive notebooks for Julia
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From the README:
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From the [README](https://github.com/compleathorseplayer/Neptune.jl):
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Neptune originated as a fork of the Notebook platform Pluto, for those (like Data Scientists) who have requirements which conflict with the 'reactive' aspect of Pluto (where all cells re-evaluate every time a single cell is evaluated or re-evaluated). It may turn out to be that Neptune is only an interim solution, and that the capabilities it enables will eventually exist within the Pluto, but that it is not certain. Users with projects or applications which are not logically sequential or linear in execution/design, or which do not load external scripts, should first try Pluto.
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See also [announcement](https://discourse.julialang.org/t/announcing-neptune-jl-now-updated-to-multi-line-cells/54088)
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See also [announcement](https://discourse.julialang.org/t/announcing-neptune-jl-now-updated-to-multi-line-cells/54088).
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## BonitoBook
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{{badge BonitoBook}}
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> BonitoBook excels in plotting, customizability, ai integration and language interoperability, making it perfect for exploring data, building dashboards and any other interactive application.
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[BonitoBook](https://github.com/SimonDanisch/BonitoBook.jl) was [announced](https://discourse.julialang.org/t/ann-bonitobook-jl/131442) in 2025 by [Simon Danisch](https://github.com/SimonDanisch) who is also the main author of [Bonito](https://github.com/simondanisch/Bonito.jl) and [Makie](https://github.com/MakieOrg/Makie.jl).
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[BonitoBook](https://github.com/SimonDanisch/BonitoBook.jl) was [announced](https://discourse.julialang.org/t/ann-bonitobook-jl/131442) in 2025 by [Simon Danisch](https://github.com/SimonDanisch) who is also the main author of [Bonito](https://github.com/simondanisch/Bonito.jl) and [Makie](https://github.com/MakieOrg/Makie.jl).
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It integrates very well with Makie, and part of the motivation for BonitoBook seems to be that Makie support in Jupyter and Pluto is limited.
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BonitoBook uses the linar execution model as Jupyter.
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BonitoBook uses the linear execution model as Jupyter.
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From the [website](https://bonitobook.org/website/):
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As Jupyter, Quarto is not a Julia project, but supports a Julia kernel as well as Python and R.
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A quarto document is written in [Markdown](https://en.wikipedia.org/wiki/Markdown) with metadata in [YAML](https://en.wikipedia.org/wiki/YAML) code in codeblocks.
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A quarto document is written in [Markdown](https://en.wikipedia.org/wiki/Markdown) with metadata in [YAML](https://en.wikipedia.org/wiki/YAML) code in code-blocks.
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From the README:
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Quarto is an open-source scientific and technical publishing system built on [Pandoc](https://pandoc.org). Quarto documents are authored using [Markdown](https://en.wikipedia.org/wiki/Markdown), an easy to write plain text format.
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> Julia extension for Visual Studio Code
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[vscode](https://github.com/microsoft/vscode) is the most popular editor for editing Julia code.
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Julias is well supported through the [julia-vscode](https://github.com/julia-vscode/julia-vscode) extension.
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Julia is well supported through the [julia-vscode](https://github.com/julia-vscode/julia-vscode) extension.
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Vscode also has support for editing (an evaluating) Jupyter notebooks.
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