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PyLops Docker

Set of Docker containers for running PyLops in different scenarios

Docker images

  • pylops_notebook: basic container to run a notebook (use pip for installing packages)
  • pylops_conda_notebook: basic container to run a notebook (use conda for installing packages)
  • pylops_batchjobs: container to run pylops jobs in batch

Getting started

Create a docker environment from the directory containing the Dockerfile. For example from pylops_notebook directory:

docker build -t pylops-notebook .

Run:

docker images

you should see pylops-notebook as one of the the ImageID. At this point run:

docker run -it -p 8888:8888 pylops-notebook

or

docker run -d -p 8888:8888 $IMAGEID

in detached mode and docker logs <container> to retrive the IP for the notebook. Note that you find the name of <container> by typing docker container ls.

Finally run this command to stop the container:

docker container stop <container>

You can also map a local folder into a docker folder by running:

docker run -d -v /path/to/local/folder:/home/jupyter/notebook -p 8888:8888 pylops-notebook

At this point upload the image. First we need to login:

docker login

Then we tag our image

docker tag pylops-notebook mrava87/pylops:notebook

and push it

docker push mrava87/pylops:notebook

and run it

docker run -it -v /path/to/local/folder:/home/jupyter/notebook -p 8888:8888 mrava87/pylops:notebook

We will see something like this appearing on terminal:

Or copy and paste one of these URLs:
    http://(c4a12e6adad3 or 127.0.0.1):8888/?token=a991d5879c7a574c8b37e1ff3934029617df09c4f71735b8

simply copy this to the browser by subsituting (c4a12e6adad3 or 127.0.0.1) with just 127.0.0.1. Moreover the first 8888 in the docker run command corresponds to the local port we want to use. If we choose something different from 8888 we will need to also substitute that in the path we are going to copy into the browser.

Alternatively we can use docker-compose. Simply move to the folder with docker-compose.yml file and run:

docker-compose up

which can be monitored via:

docker-compose ps

and stopped using:

docker-compose stop

Useful commands

When running a container, it will always stay there unless you run it with --rm . You can delete all unused resources by running:

docker system prune

and then you can remove images with

docker rmi $IMAGEID

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