Thanks, Matthias. Yes, https://github.com/lstagner/idl_kernel <https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2Flstagner%2Fidl_kernel&sa=D&sntz=1&usg=AFQjCNFtWFr3bFcYPWz-MzlEC3oxOHgi7A> is the page I was referring to. In it, there is a statement: #This package is no longer maintained since IDL now has an official Jupyter kernel <https://www.harrisgeospatial.com/docs/IDL_Kernel.html> #IDL/GDL kernel for IPython/Jupyter and the link is as you described.
What I failed to realize is that IDL is a commercial software. Once it is bought and installed, perhaps there will be a IDL_DIR with the appropriate file. Because of the syntax (mostly) compatibility between the two (IDL & GDL), I was under the impression that the same .py file can be used to link up Jupyter and GDL, with possibly minor modifications, but perhaps I am being too simple-minded about what a Jupyter kernel actually is. I have never seen a gdl_kernel.py, I was hoping one existed somewhere. I do not know much about python, but since Jupyter is trying to be a language-agnostic tool, which I like very much and would like to use in my teaching, I sort of assumed that a way to link a pipe to an external executable that would receive my text and return a tagged (html?) stream, a mixture of text and svg graphics, would be a matter of adjusting a configuration file, mostly. Isn't this what Jupyter does when the cell magic is set to %%bash, for example? The instructions for installing a new kernel that I have found out there are universally inadequate. Under RHEL 7, I have access to pip, but not conda. Unfortunately, the simple-minded pip install gnuplot_kernel to use an example, I have tried several, not one of them showing up under the list of Jupiter notebook kernels available. However, if I do this instead pip install --upgrade --no-cache-dir git+https://github.com/has2k1/gnuplot_kernel.git@master it works as expected! I have not yet discovered the equivalent solutions for other kernels, or how to make my own (to an external executable... see above). $ pip list | grep kernel gnuplot-kernel (0.2.3) ipykernel (4.6.1) metakernel (0.20.8) octave-kernel (0.28.1) scilab-kernel (0.8.1) yet the Jupiter kernel drop down menu only lists Python, Python 3, and octave. And, after I re-did the installation as above, gnuplot, but no scilab, for example. My interest is to unite several different legacy tools under one Jupyter "roof", and I want to use multiple kernels in a single notebook, though I am having trouble with that right now: it seems that it's only possible if the "primary" kernel is python, because in my octave-kernel notebook, the command %load_ext gnuplot-kernel does not seem to be working for me, presumably because octave kernel does not have the load_ext functionality, like a python kernel does. Before I start looking into writing custom kernel interfaces to my other tools, I need to make sure I understand and can make robust the installation process. The gnuplot trick I found here: https://github.com/has2k1/gnuplot_kernel/issues/5 together with the expressions of puzzlement of why it was needed, so I am not the only one confused. -- You received this message because you are subscribed to the Google Groups "Project Jupyter" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/jupyter/a6f19fa7-c1a4-41b7-8da3-a825278a074a%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
