Docker Images for Intel® Distribution for Python*

We have published Docker images for Intel Python. The images can be found on Docker Hub and Google Cloud Platform Container Registry, and the Dockerfiles are also available on GitHub. We have images for Python 2 & Python 3, with both core and full configurations. Core contains NumPy/Scipy and dependences, and full contains everything that we distribute.  If you want to customize the Docker image, then you can start with the Dockerfiles that we publish or use the Docker FROM command to use our image as a base.

Getting started:

Docker is a popular Linux container technology that allows for deployment and repeatability of services and applications through a simple command line interface.  More information can be found at Docker’s official website, https://www.docker.com/

Obtaining the Docker images for the distribution:

To see the images that are available, visit the Docker Hub link and use the docker pull command to obtain the desired distribution version and configuration.  

docker pull intelpython/intelpython3_full
docker pull intelpython/intelpython3_core
docker pull intelpython/intelpython2_full
docker pull intelpython/intelpython2_core

Using the Docker Images:

Several options exist for using these Docker images.  The native command when running the image gives the user a shell to operate the distribution with.  To use this, try the following command:

docker run -it intelpython/intelpython3_core

If the desire is to immediately use Python upon startup, use the following command:

docker run -it intelpython/intelpython3_core python

In order to utilize a Jupyter Notebook, use the following command:

docker run -p 8888:8888 intelpython/intelpython3_full jupyter notebook --ip='*' --port=8888 --allow-root --no-browser

The Jupyter Notebook can be opened by going to http://localhost:8888 in your browser, or http://<DOCKER-MACHINE-IP>:8888 if you are using a Docker Machine VM.

If you create a new environment within the container, one will need to install the kernel into IPython using the following information: Installing the IPython Kernel  

For tasks in which a volume needs to be mounted, please reference the Docker documentation on volume mounts.

For more complete information about compiler optimizations, see our Optimization Notice.

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walker, joseph's picture

jiMac:~ $ docker images

REPOSITORY                      TAG                 IMAGE ID            CREATED             SIZE

jupyter/all-spark-notebook      latest              2bc4265a2151        2 weeks ago         5.64GB

intelpython/intelpython3_full   latest              e574a87e66d8        6 weeks ago         3.82GB

jiMac:~ $ docker ps

CONTAINER ID        IMAGE               COMMAND             CREATED             STATUS              PORTS               NAMES

jiMac:~ $ docker run -it intelpython/intelpython3_full

(base) root@9e31032700d1:/# exit

exit

jiMac:~ $ docker run -p 8888:8888 intelpython/intelpython3_full jupyter notebook --ip='*' --port=8888 --allow-root --no-browser

[FATAL tini (6)] exec jupyter failed: No such file or directory

jiMac:~ $

this on docker toolbox on an iMac 2009

jiMac:~ $ docker version

Client:

Version: 18.03.0-ce

API version: 1.37

Go version: go1.9.4

Git commit: 0520e24

Built: Wed Mar 21 23:06:22 2018

OS/Arch: darwin/amd64

Experimental: false

Orchestrator: swarm

 

Server: Docker Engine - Community

Engine:

  Version: 18.09.2

  API version: 1.39 (minimum version 1.12)

  Go version: go1.10.6

  Git commit: 6247962

  Built: Sun Feb 10 04:20:28 2019

  OS/Arch: linux/amd64

  Experimental: false

jiMac:~ $

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