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Running in singularity

Singularity or Docker containers can encapsulate the entire stempy environment so that you don't have to build it. We provide a container that has a Python 3.7 environment with stempy pre-installed. This container will work in Docker, Singularity, and NERSC's Shifter.

Install Singularity (Ubuntu)

sudo apt-get install singularity-container

Note

Version 2.4.2-dist on Ubuntu has a bug with squashfs. Version 3.6.1 has been tested to work. Follow installation instructions here: https://github.com/hpcng/singularity/blob/master/INSTALL.md

Then you will run /usr/local/bin/singularity

Pulling the latest image

Use singularity or docker interchangeably below.

singularity pull docker://openchemistry/stempy

singularity pull docker://openchemistry/stempy-scipy-notebook

Running a script inside the container

By default singularity will mount your home directory into the container. So for example if you have a script called test.py in your home directory you can execute it in the container with the following command:

singularity exec stempy/stempy.simg python3 ~/test.py

Running a Jupyter Lab instance inside the container. The -B option mounts directories on the host to directories inside the notebook.

singularity exec -B /tmp:/home/jovyan,/mnt:/mnt stempy-scipy-notebook_latest.sif jupyter lab

Mounting other directories into the container

You can also bind mount other directories into the container. For example if your script reference data at for example /mnt/nvmedata1/temp/, you can mount with the following command:

singularity exec -B /mnt/nvmedata1/temp/:/mnt/nvmedata1/temp/ stempy.simg python3 ~/test.py

Creating and Connecting to a Jupyter Lab Server

Using Jupyter Lab (or notebook) is very useful for interactively working with stempy.

On your local machine create a ssh tunnel:

ssh username@server_name -L 7777:localhost:8888

On the remote machine start up the Jupyter server:

singularity exec -B /mnt:/mnt,/tmp:/home/jovyan ~/stempy-scipy-notebook-latest.simg jupyter lab

The remote machine will print out a message similar to:

The Jupyter Notebook is running at:
http://server_name:8888/?token=
or http://127.0.0.1:8888/?token=

Copy the entire http://127.0.0.1:8888/?token= address including the long string of letters and numbers after token= which is the secret key for this server.

On your local machine paste the address into your browser of choice.

AND THEN

change the :8888 to :7777

Jupypter Lab will start up in your browser and all calculations will be run on the remote server.