Configure Matlab into Jupyter Notebook

I started using Jupyter Notebook only for coding in Python. However, gradually as I learnt more programming languages, I wish I could have all languages in one environment; Then I don’t need to open multiple programs. Luckily, I was told I could easily configure those languages into the Notebook (though not an easy process for me, /(ㄒoㄒ)/~~) and as I would be learning both Matlab and Julia this semester, it would be a good chance to try it out.

Caveats for those who want to keep on reading, this blog (1) doesn’t include how to install Matlab either in your own or remote computer (2) is mainly for installing MATLAB Engine API for Python in a remote location (where you don’t have write permission, in other words, not super user) and troubleshooting as I don’t want to install Matlab on my own laptop but still want to enjoy the benefits. Though, the process can be adapted and generalized to other cases and I do have references listed below that suit a variety of needs.

0. References

You’re encouraged to try it on your own first. Here’re some resources (including troubleshoots) I referred to in the process:

Most tutorials assume the coders already have a relatively high level of understanding. To a newbie like me, I’d appreciate more detailed explanation. That’s also why I immediately write this blog, for my own reference and for those stuggling with getting it right.

1. Create myenv using Conda

I would suggest for this type of task to always create an virtual environment. Then you can personalize any setting and packages in case the task doesn’t align with packages installed in the base or you don’t want to mess with that. The prerequisite is that you should install conda through either Miniconda or Anaconda. I highly regretted not doing this at the beginning because later during one step I found out for some reasons Python 3.8 doesn’t work very well; so I ended up switching to Python 3.7 when I create myenv susu:

1

conda create -n susu python=3.7

For more conda create env related stuff, please check out the documentation linked here.

2. Find your MATLAB Folder matlabroot

Ideally, matlabroot can be found by opening the installed Matlab App and run matlabroot. You will see a path like ans = "???/???/matlab-2021b". But what do you do when the remote computer is not near you? Then you can ssh to that machine and work around this in terminal, which tends to be slow. You can speed it up (though not much I feel) by opening Matlab in terminal by entering matlab -nodesktop -nodisplay. It starts by saying MATLAB is selecting SOFTWARE OPENGL rendering. That’s a good sign, and you will just wait for a few minutes. Once >> symbol pops up, run matlabroot.

3. Build or Install in Nondefault Folders

Basically, if you do not have write permission to the default Matlab folder and default Python folder (look up default vs non-default folder if you’re confused) as I do because I’m accessing a remote machine, do as follows:

1
2

cd "matlabroot\extern\engines\python"
python setup.py build --build-base="builddir" install --prefix="installdir"

Notice that builddir would be a path to the non-default folder that you create under MATLAB folder (the default folder automatically get created when you initialize Matlab program). So is the installdir. It is a path to the non-default folder in the search path for Python packages. I create it directly under myenv susu — ???/yumian/Documents/miniconda/envs/susu"

4. Install the Matlab Kernel for Jupyter

1
2

pip/conda install matlab_kernal
python -m matlab_kernel install

After done with this step, you’re pretty much ready to launch your jupyter notebook and see Matlab as an option.

Before that, Open Python and run import matlab.engine to verify you have this module correctly installed. Another thing you can do is pip list | grep matlab, which should list something like:

1
2

matlab-kernel                 0.16.11
matlabengineforpython         R2021b

If while you’re trying to run the cells, the background keeps reporting Matlab engine not installed: error, go back to check your installed directory; it may be you didn’t install it correctly. If the background says HTTP 404: Not Found (Kernel does not exist: error, try the trick below (c.r. @tensionhead):

1
2

jupyter nbextension install --py widgetsnbextension --user
jupyter nbextension enable --py widgetsnbextension

Happy coding! I will have another blog about configuring Julia which is so much easier than this. (updated: check out the blog about Julia!)