mottosso/maya

Supported tags

• 2013sp1, 2013sp2, 2014sp1, 2014sp2, 2014sp3, 2014sp4, 2015sp1, 2015sp2, 2015sp3, 2015sp4, 2015sp5, 2015sp6, 2016sp1, 2017, 2018

For more information about this image and its history, please see its the https://github.com/mottosso/docker-maya/wiki.

Usage

To use this image and any of it's supported tags, use docker run.

bash
$ docker run -ti --rm mottosso/maya

Without a "tag", this would download the latest available image of Maya. You can explicitly specify a version with a tag.

bash
$ docker run -ti --rm mottosso/maya:2016sp1

Images occupy around 5 gb of virtual disk space once installed, and about 1.5 gb of bandwidth to download.

Example

This example will run the latest available version of Maya, create a new scene and save it in your current working directory.

bash
$ docker run -ti -v $(pwd):/root/workdir --rm mottosso/maya
$ mayapy
>>> from maya import standalone, cmds
>>> standalone.initialize()
>>> cmds.file(new=True)
>>> cmds.polySphere(radius=2)
>>> cmds.file(rename="my_scene.ma")
>>> cmds.file(save=True, type="mayaAscii")
>>> exit()
$ cp /root/maya/projects/default/scenes/my_scene.ma workdir/my_scene.ma
$ exit
$ cat my_scene.ma

What's in this image?

This image builds on https://registry.hub.docker.com/u/mottosso/mayabase-centos/ which has the following software installed.

• git
• pip

Each tag represents a particular version of Maya, such as 2016 SP1. In this image, python is an alias to maya/bin/mayapy which has the following Python packages installed via pip.

• nose

User Feedback

Documentation

Documentation for this image is stored in the https://github.com/mottosso/docker-maya/wiki for this project.

Issues

If you have any problems with or questions about this image, please contact me through a https://github.com/mottosso/docker-maya/issues.

Contributing

You are invited to contribute new features, fixes, or updates, large or small; I'm always thrilled to receive pull requests, and do my best to process them as fast as I can.

Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.