Active versions linked in this section, via Binder service.
These are in no particular order and I tried to cover the gamut from ones that are targeted at newcomers to advanced notebooks.
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A notebook solving The Monty Hall problem with Python by C. Titus Brown
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Jupyter notebook demonstrating just the very basics - general introductory example I made to accompany a poster; disregard last few cells as they don't work well without the poster the way I left them for now (Source can be seen: here)
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A Jupyter notebook demonstrating one way to build in interactive features to illustrate science
This advanced example by Bruce Sherwood (his repository) is for VPython, which is made for creating and sharing Physcis simulations. I link to the examples he includes to illustrate the abilities of VPython. When it opens, you can click on individual notebooks. I'd suggest looking at leastHard-sphere gasand/orAtomic Solidand/orPlot 3D function, but any are good. -
example I made for an exercise for some high school students (Source can be seen: here)
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simple calculation example- example I made for a calculation I use a lot that would also work on the poster too. (I would remake this with widgets if I was doing this now.) (Source can be seen: here)
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Active Notebook of Black Hole Signals (Source can be seen: here)
This is probably the most famous Jupyter notebook to date since they won the Nobel prize for the discovery documented in it.
Related: Recounting of the announcement of discovery until a launchable ACTIVE notebook allowing anyone to reproduce data is made available.
Jupyter notebooks are not limited to Python, here is one that runs in the current other darling language of bioinformatics, R. (Source: here)
Importantly, the notbeooks I am discussing run the code that is input specically in the native language like Python or R or Juila or Go or Ruby, etc,, underneath. There are some systems out there that replicate many languages, i.e., Skulpt, CodeSkulptor, RubyJS, etc, but actually run in javascript. The Jupyter notebooks have the native language in a browser-based framework with HTML and javascript proving the UI, as far as I know.
As I understand it...
- IPython is an interactive shell running with Python.
- IPython notebooks started as an advancement of the interactive IPython REPL interface, where REPL stands for "Read–eval–print loop".
- Project Jupyter/Jupyter notebooks was the next advancement as they realized the paradigm went beyond Python and they could offer other languages, like Julia and even Bash terminals, in the notebook format.
- JupyterLab is the direction they are heading as it is the next generation user interface for Project Jupyter.
Static notebooks are great for communicating & documenting.
Static versions notebooks offer a way to display & share analyses already done or demonstrate code for others, build blogs, etc.. The notebooks themselves are JSON code, but they can be rendered beautifully using nbviewer, and by default even Github renders Jupyter notebooks fairly nicely now. For example, here is the Ligo notebook beautifully rendered, but in static form where you cannot interact with it or directly change it and re-run the code.
Binder service -great for empowering data analyses of yours and other notebooks
Some bright people at MyBinder.org realized they could take static code of notebooks and make a service that spins them up as running active notebooks. That is what I have been using as examples because active versions are much more empowering.
JupyterLab will integrate notebook components with a more full-featured browser-based application. Test it here
The Phosphor library is used as the underlying architecture of JupyterLab and provides many of the low level primitives and widget structure used in the application. The JupyterLab community allows integrating with other software and tools by enabling development of extensions that can be thought of as plug-ins.
Full, early account of the new version here.
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http://nglviewer.org/nglview/latest/ (source: https://github.com/arose/nglview )
- Information about it here
- sbio: A Framework for Structural Systems Biology uses nglview to map mutations onto structures, see here
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static notebook example of using Viewing 3D molecules interactively in Jupyter iPython notebooks
* Example use described here: http://rdkit.blogspot.com/2016/05/trying-out-py3dmol.html -
Molecular Design Toolkit --> active demo I used in past at https://mybinder.org/v2/gh/avirshup/mdt-gallery-test/master (Source: here) **BINDERIZED VERSION DOES NOT SEEM TO BE WORKING NOW - when working, I suggest starting with
Example 1. Build and simulate DNA.ipynb. -
Molecular Design Toolkit Demo ***BINDERIZED VERSION DOES NOT SEEM TO BE WORKING NOW - when working, I suggest starting with
Example 1. Build and simulate DNA.ipynb.- Does this mean 'py3dmol' became 'Molecular Design Toolkit'???