Just another autorigger Online Documentation (ReadTheDocs)
My Autorigger. Ain't yo business..yet!
- Caching
- Automated naming conventions
- YAML Config
- Online Documentation
- Temp file generator
- JSON file output
- CLI access
- Dict output
- Automated Custom Docker Image Builds
- Test suite automation using CircleCI
- Automated testing in Maya versions 2015, 2016, 2017, 2018
To run Anvil locally you must have these installed:
- Maya (2015-2017=8)
- Python2.7 (or sudo access to pip install via mayapy)
A universal installation method (that works on Windows, Mac OS X, Linux, โฆ, and always provides the latest version) is to use pip
:
.. code-block:: bash
# Make sure we have an up-to-date version of pip and setuptools:
$ pip install --upgrade pip setuptools
$ pip install Anvil
(If pip
installation fails for some reason, you can try easy_install anvil
as a fallback.)
Use this tool via package level functions
.. code-block:: python
import anvil
anvil.lorem_ipsum()
This package supports only Maya 2015, 2016 and 2017 so far so please be aware...plans for 2018 are in the works.
- Stu Schwartz - For being my constant sounding board and advice giver.
- Marcus Ottosson - Without him I would not have been able to complete the docker side of things.
Adapted README from Marcus Ottosson
maya2015
,maya2016
,maya2017
,maya2018
Each tag represents a particular version of Maya, such as maya2016. In this image, python
is an alias to maya/bin/mayapy
which has the following Python packages installed via pip
.
For more information about this image and its history, please see its the GitHub repository
To use this image and any of it's supported tags, use docker run
.
$ docker run -ti --rm daemonecles/anvil
Without a "tag", this would download the latest available image of Maya. You can explicitly specify a version with a tag.
$ docker run -ti --rm daemonecles/anvil:2018
Images occupy around 5 gb of virtual disk space once installed, and about 1.5 gb of bandwidth to download.
This example will run the latest available version of Maya, create a new scene and save it in your current working directory.
$ docker run -ti -v $(pwd):/root/workdir --rm daemonecles/maya2016
$ 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
This image builds on daemonecles/anvil which has the following software installed.
Additional installations include.
$MAYA_VERSION=####
: for getting the installed maya version quickly in the format #### - e.g. - 2018.$PYTHON_PATH=$HOME/nvenv/lib/python2.7/site-packages
: Placeholder for your test runner virtualenv named "nvenv" so maya can access the installed packages.$TEST_PATH=$HOME/test-results
: A default directory where the user can place test resulting xml files etc.
If you have any problems with or questions about contributing to this image, please contact Marcus Ottosson through a GitHub issue (since the image is basically his with minor additions)