Examples from "Docker for Data Scientists" talk, PyBay 2018.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
pitfall-1
workflow-1
workflow-2a
workflow-2b
workflow-3a
workflow-3b
workflow-4
Docker-for-Data-Scientists--Jeff-Fischer.pdf
LICENSE
README.rst

README.rst

Docker for Data Scientists Examples

These are examples from my PyBay 2018 talk: Docker for Data Scientists. The slides are available in PDF form here.

Example Format

Each example has a README.txt file that explains the example and a run.sh bash script that will pull the base Docker image, build the image for the example, and run the container.

Most examples have a Dockerfile defining how to build the image. Those that leave containers running have a cleanup.sh script to delete the containers.

Contents

Here is a short explanation of each specific example:

  • workflow-1 — run a machine learning script inside a container
  • pitfall-1 — example of an anti-pattern: containers with mutable state inside
  • workflow-2a — mount the current directory inside a container and run an interactive shell
  • workflow-2b — example of user mapping with the docker run command
  • workflow-3a — run TensorFlow and Jupyter in a detached container
  • workflow-3b — run the GPU-enabled version of TensorFlow in a detached container
  • workflow-4 — load and run a Neo4j database

For a full explanation of all the examples, see my blog series at https://data-ken.org/docker-for-data-scientists-part1.html.