An enhanced interactive environment for the computer algebra system Maxima, based on CL-Jupyter, a Jupyter kernel for Common Lisp, by Frederic Peschanski. Thanks, Frederic! These days Maxima-Jupyter depends heavily on Common-Lisp-Jupyter, by Tarn Burton. Thanks, Tarn!
This file describes the installation and usage of Maxima-Jupyter on a local machine, but you can try out Maxima-Jupyter without installing anything by clicking on the Binder badge above.
MaximaJupyterExample.ipynb — General usage of Maxima from within JupyterLab.
MaximaJupyterTalk.ipynb — My notes for a talk given to the Portland Python User Group.
Plots.ipynb — Usage of plotting facilities from within JupyterLab.
These examples make use of nbviewer. You can submit a link to your own notebook to tell nbviewer to render it.
Maxima-Jupyter may be installed on a machine using a local installation, a repo2docker installation, or via a Docker image.
To try Maxima-Jupyter you need :
a Maxima executable
built with a Common Lisp implementation which has native threads
SBCL works for sure
Clozure CL works for sure
Other implementations which support the Bordeaux Threads package might work. The Bordeaux Threads project description says "Supports all major Common Lisp implementations: SBCL, CCL, Lispworks, Allegro, ABCL, ECL, Clisp." Aside from SBCL and CCL (i.e. Clozure CL) which are known to work, the others in that list are untested with maxima-jupyter.
Note also that ECL might theoretically work, since it is supported by Bordeaux Threads. However, nobody (neither Maxima-Jupyter developers nor users) has been able to get ECL to work, therefore you should assume ECL does not work with Maxima-Jupyter. SBCL and Clozure CL are known to work, try those instead.
Note specifically that GCL is not supported by Bordeaux Threads, and therefore GCL cannot work with maxima-jupyter.
You might or might not need to build Maxima. (A) If you have available a Maxima binary package compiled with a compatible Lisp implementation (i.e. SBCL, Clozure CL, Lispworks, etc. as enumerated above), then you do not need to build Maxima. (B) Otherwise, you must install a compatible Lisp implementation and compile Maxima yourself.
- When you load Maxima-Jupyter into Maxima for the first time, Quicklisp will download some dependencies automatically. Good luck.
Python 3.2 or above
If the build aborts because the file
zmq.his missing, you may need to install the development files for the high-level C binding for ZeroMQ. On debian-based systems, you can satisfy this requirement by installing the package
First you must install Jupyter, then you can install Maxima-Jupyter. If you
plan on using JupyterLab then you must install with the
python3 -m pip --user install jupyterlab jupyter-console
If you are using Windows then installation via conda is recomended since this will also install the ZeroMQ libraries.
conda install -c conda-forge jupyterlab jupyter_console m2w64-gcc m2w64-zeromq
Once Jupyter is installed you can either install from the source files of this repository, or you can install via the AUR if you are using Arch Linux.
Method 1. Source Based Installation
To install from the current source files first download the source files and then start a shell in the source directory. Then start Maxima and load the initialization script.
$ maxima Maxima 5.43.0 http://maxima.sourceforge.net using Lisp SBCL 1.5.5 Distributed under the GNU Public License. See the file COPYING. Dedicated to the memory of William Schelter. The function bug_report() provides bug reporting information. (%i1) load("load-maxima-jupyter.lisp");
After the install script has loaded then install using one of the kernel types.
- User specific Quicklisp kernel:
- User specific binary image kernel:
- System-wide Quicklisp bundled kernel:
After the installation is complete then exit Maxima. For the System-wide
installation copy the files in
pkg to the system root, i.e.
sudo cp -r pkg/* / on Linux.
Method 2. Installation on Arch/Manjaro
The package for Arch Linux is maxima-jupyter-git. Building and installing (including dependencies) can be accomplished with:
yaourt -Sy maxima-jupyter-git
curl -L -O https://aur.archlinux.org/cgit/aur.git/snapshot/maxima-jupyter-git.tar.gz tar -xvf maxima-jupyter-git.tar.gz cd maxima-jupyter-git makepkg -Csri
Please consult the Arch Wiki for more information regarding installing packages from the AUR.
Code Highlighting Installation
Highlighting Maxima code is handled by CodeMirror in the notebook and Pygments in HTML export.
A CodeMirror mode for Maxima has been published on npmjs.com. It is not clear how that needs to be installed in order for Maxima-Jupyter to make use of it; stay tuned for further info.
A Maxima lexer for Pygments has been submitted and accepted by the Pygments project, and it will be bundled with the next release of Pygments (2.11). In the meantime, we are lacking highlighting in HTML export.
Maxima-Jupyter may be run from a local installation in console mode by the following.
Notebook mode is initiated by the following.
When you enter stuff to be evaluated, you must include the usual trailing semicolon or dollar sign:
In : 2*21; Out: 42 In :
Maxima-Jupyter may be run as a Docker image managed by repo2docker which will fetch the current code from GitHub and handle all the details of running the JupyterLab server.
First you need to install repo2docker (
sudo may be required)
pip install jupyter-repo2docker
Once repo2docker is installed then the following will build and start the server. Directions on accessing the server will be displayed once the image is built.
jupyter-repo2docker --user-id=1000 --user-name=mj https://github.com/robert-dodier/maxima-jupyter
A Docker image of Maxima-Jupyter may be built using the following command
sudo may be required). This image is based on the docker image
docker build --tag=maxima-jupyter .
If you'd like to build with a different user than the default (
mj), you may
override it with the following:
docker build --build-arg NB_USER=alice --tag=maxima-jupyter .
After the image is built the container may be run with:
docker run -it maxima-jupyter
Dockerfile makes use of the
ENTRYPOINT command; the default behaviour
jupyter binary with the arguments
If you'd like to run using Juypter's notebook web server, you may do the
following to override the default use of
docker run -it \ -v `pwd`/notebooks:/home/USER/maxima-jupyter/examples \ -p 8888:8888 \ maxima-jupyter \ notebook --ip=0.0.0.0 --port=8888
where the last line is the set of arguments to
jupyter that cause it to run
in the notebook server mode.
To run the Bash shell on the container, just override the entry point:
docker run -it --entrypoint=bash maxima-jupyter
If you cannot build the Docker image, you may use a
by subsituting the Docker image name
maxima-jupyter in the above
calyau/maxima-jupyter. Note that the default user on the
calyau image is not
mj, but is rather
Additional examples of notebooks created using this mode have been created here (taken from the Maxima tutorial): https://github.com/calyau/maxima-tutorial-notebooks.
Have fun! If you run into problems, please open a ticket on the issue tracker for this project.