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    <p>I participate in an effort to make software for doing science analysis more available to the research community. Often, the software in question is written by one individual or just a few without sufficient planning for reuse, such as one person on their own computer writing a Python script or a Matlab module. If the software works well, often others would like to try it themselves...but it can be a real challenge in some cases to successfully replicate an environment that's undocumented or difficult to reimplement.</p> <p>Docker is a great tool to help others reuse software like this, since it is an even lower barrier of entry that writing a Vagrant script to install software in an environment. If I give a person a Docker container, she can do whatever she wants inside of it (write code, install libraries, set up environment, etc. When it's "done", she can save an image of it and publish the image in a Docker repository and tell another researcher, "here it is, just start it up and run this..."</p> <p>We are also considering using containers as our own configuration management strategy for delivering and archiving production software...at least the server-side components.</p> <p>We have also done some work with writing scripts in Python and shell to run data processing workflows of multiple Docker containers. One demo that we concocted was to run OpenCV on an image to extract faces of people, then ImageMagick to crop out the faces, and finally ImageMagick again to make a collage of all of the faces. We built a container for OpenCV and a container for ImageMagick, then wrote a Python script to execute a "docker run ..." on each of the containers with the requisite parameters. The Python scripting was accomplished using the <a href="https://github.com/dotcloud/docker-py" rel="noreferrer">docker-py</a> project which worked well for what we needed from it.</p>
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