SageMath Docker Image

This is an attempt to standardize and streamline computational work that combines SnapPy, SageMath, and friends via a custom Docker <http://www.docker.com>_ image that is based around Ubuntu 22.04 LTS and the latest and greatest SageMath <http://sagemath.org>. It is directly derived from the official sagemath/sagemath Docker image, but includes SnapPy <http://bitbucket.org/t3m/snappy>, and the Python interfaces to Regina <http://regina-normal.github.io/>, and PHCPack <http://homepages.math.uic.edu/~jan/>.

A container instance of this image starts a shell as the user sage with all the environment variables set as if you had executed sage -sh.

This image takes a long time to build, even on a fast computer, since it compiles SageMath from source, and weighs in at 5.2 GB (1.6 GB compressed). We recommend you use the posted image <http://hub.docker.com/r/computop/sage/>_ on DockerHub via::

docker pull computop/sage docker run -it computop/sage

Here, the first command downloads the image from DockerHub and the second starts a container that is running said image. Moving files between the container and the rest of the world can be done using scp or having the container mount a local directory as in this example::

docker run -it --mount type=bind,source="$HOME/Dropbox/linux_share",target=/home/sage/linux_share computop/sage

where the directory linux_share inside the user's Dropbox folder is shared.

If you want to use Sage's Jupyter notebook interface, start the container via::

docker run -it -p 127.0.0.1:8888:8888 computop/sage

and in said container type::

sage --notebook

and then point your computer's web browser to http://localhost:8888. As of computop/sage:10.5, this uses Notebook 7 <https://jupyter-notebook.readthedocs.io/en/latest/notebook_7_features.html>_. If you want interactive plots with MatplotLib, the command is now %matplotlib widget rather than %matplotlib notebook.

If you want to use JupyterLab <https://jupyterlab.readthedocs.io/en/stable/>_, you can instead do::

sage --notebook jupyterlab

In JupyterLab, you have access not just to notebooks but also Python consoles and shell terminal windows.

Python 2 versus Python 3

The images for SageMath 8.9 and older use Python 2 (and Ubuntu 16.04) and those for SageMath 9.0 and newer use Python 3 (and Ubuntu 18.04, 20.04, or 22.04). You can always request Docker run a particular version of the image, for example if you want SageMath 8.9 do::

docker run -it computop/sage:8.9

Components

A partial list of included software:

• SageMath <http://sagemath.org>_
• SnapPy <http://snappy.computop.org>_
• Regina <http://regina-normal.github.io/>_
• Two Python interfaces to PHCPack <http://homepages.math.uic.edu/~jan/>_
• pandas <http://pandas.pydata.org/>_
• pe <http://bitbucket.org/t3m/pe>_
• gridlink <http://bitbucket.org/t3m/gridlink>_
• flipper <http://flipper.readthedocs.io>_ and curver <http://curver.readthedocs.io>_
• heegaard <http://bitbucket.org/t3m/heegaard>_
• pygraphviz <http://pygraphviz.github.io/>_
• snap <http://snap-pari.sourceforge.net>_

We no longer include HIKMOT <http://www.oishi.info.waseda.ac.jp/~takayasu/hikmot/>_ as it is not compatible with Python 3.

Building

To build from scratch, which takes 1.3 hours using all 8 cores on a Mac Pro::

docker build --tag=computop/sage sage

If compiling Sage fails, make sure the Docker application is configured so that it can use at least 4GB of memory.

Put out on DockerHub::

docker push computop/sage