Running PyCBC under Docker

The easiest way to start using PyCBC is to install one of our Docker containers. First, install the Docker Community Edition for your Mac or Windows desktop. Docker CE installations for Linux platforms are also available.

To start a Docker container with no graphics, type the commands:

docker pull pycbc/pycbc-el7:latest
docker run -it pycbc/pycbc-el7:latest

This example downloads current version of the code from the GitHub master branch. Replace the string latest with one of the PyCBC release tags (e.g. v1.7.0) to install a container containing a released version of PyCBC. The container includes all of the required software and dependencies to run PyCBC, including a compatible version of LALSuite installed into the root filesystem. The command above starts a login shell as the pycbc user. To override this and log in as root, run the command:

docker run -it pycbc/pycbc-el7:latest /bin/bash -l

Using jupyter notebook within docker

One can start a jupyter notebook within docker and then port forward to your computer’s environment.:

docker run -it -p 8888:8888 --name pycbc_test pycbc/pycbc-el7:latest /bin/su -l pycbc -c "jupyter notebook --no-browser --ip 0.0.0.0"

Once the image is running, you can connect from your computer’s web browser to the address printed to the screen by jupyter. This is typically the local host adddress, e.g. 127.0.0.1

Sharing user files and SSH keys

It can be useful to share your SSH public/private key with the Docker container, for example to allow you to git push and pull from your repository on GitHub. To do this, add the argument -v ${HOME}/.ssh:/opt/pycbc/.ssh to the docker run commands. You can also create e.g. a scratch directory and use the -v option to mount it in the container. This directory can be used to transfer files between the container and the host computer. See the Docker volumes documentation for a detailed explaination of mounting directories inside a docker container.