A Pluto notebook is made up of small blocks of Julia code (cells) and together they form a reactive notebook. When you change a variable, Pluto automatically re-runs the cells that refer to it. ...
The main difference between using Pluto.jl and Jupyter Notebooks with Julia is that Pluto.jl is dynamic. It re-runs all the above cells according to the last cell. Whereas outputs of Jupyter Notebook only change when the code blocks that created them change
I find the largest pro of Pluto to be, that by design notebooks the same resuts. In Jupyter it is quite easy to create results that are dependent on the cell-execution order, which is hard to do in Pluto.
In jupyter you can chose to execute cells one-by-one, which can be beneficial, if you have large calculations going. This can not be done in Pluto, but one learns to take this into consideration, when writing notebooks.
Support for slides is very good for Jupyter. For Pluto only proof of concepts exist as far as I am aware.
Both are performant.
For teaching students I personally prefer Pluto. Some of the restrictions imposed make it much simpler to debug these notebooks (results do not depend on cell execution order). Also the notebook is basically a standard Julia source code file, which can be manipulated easily using any text editor. Pluto's Reactivity is also great in an educational setting, as it encourages students to play around with the notebooks. Lastly, there is the MIT course Introduction to Computational Thinking, which uses these notebooks for lectures and exercises and they are a great inspiration on how to use Pluto notebooks for teaching. I hope these insights are what you were looking for.
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来自 pluto.jl github page ：
使用Julia 使用 pluto.jl 和 jupyter笔记本之间的主要区别在于pluto.jl是动态的。它根据最后一个细胞重新运行上述所有细胞。而Jupyter笔记本电脑的输出仅在创建它们的代码块更改时才更改
From Pluto.jl github page:
The main difference between using Pluto.jl and Jupyter Notebooks with Julia is that Pluto.jl is dynamic. It re-runs all the above cells according to the last cell. Whereas outputs of Jupyter Notebook only change when the code blocks that created them change
我发现冥王星是最大的专业人士，通过设计笔记本相同的重新计算。在jupyter中，创建取决于细胞执行顺序的结果很容易，这在冥王星中很难做到。
在jupyter中，您可以选择一对一执行单元格，如果您进行的计算大量计算，这可能是有益的。这不能在冥王星中完成，但是在编写笔记本时，人们会学会考虑这一点。
对幻灯片的支持非常适合Jupyter。据我所知，只有概念证明。
两者都是表现。
对于教学学生，我个人更喜欢冥王星。施加的一些限制使调试这些笔记本更简单（结果不取决于单元执行顺序）。此外，笔记本基本上是标准的朱莉娅源代码文件，可以使用任何文本编辑器轻松地操纵它。在教育环境中，冥王星的反应性也很棒，因为它鼓励学生玩笔记本。最后，有麻省理工学院课程计算思维简介，它使用这些笔记本进行了这些笔记本，并进行了练习和练习，他们和他们的练习和他们是如何使用冥王星笔记本进行教学的巨大灵感。我希望这些见解是您想要的。
I find the largest pro of Pluto to be, that by design notebooks the same resuts. In Jupyter it is quite easy to create results that are dependent on the cell-execution order, which is hard to do in Pluto.
In jupyter you can chose to execute cells one-by-one, which can be beneficial, if you have large calculations going. This can not be done in Pluto, but one learns to take this into consideration, when writing notebooks.
Support for slides is very good for Jupyter. For Pluto only proof of concepts exist as far as I am aware.
Both are performant.
For teaching students I personally prefer Pluto. Some of the restrictions imposed make it much simpler to debug these notebooks (results do not depend on cell execution order). Also the notebook is basically a standard Julia source code file, which can be manipulated easily using any text editor. Pluto's Reactivity is also great in an educational setting, as it encourages students to play around with the notebooks. Lastly, there is the MIT course Introduction to Computational Thinking, which uses these notebooks for lectures and exercises and they are a great inspiration on how to use Pluto notebooks for teaching. I hope these insights are what you were looking for.