# Create a conda build recipe for Autodesk Maya to Arnold (MtoA) plugin
<a name="create-conda-recipe-mtoa-plugin"></a>

The Maya to Arnold (MtoA) plugin adds the Arnold renderer as an option within Maya. The [MtoA sample recipe](https://github.com/aws-deadline/deadline-cloud-samples/tree/mainline/conda_recipes/maya-mtoa-2026) demonstrates how to package a plugin as a separate conda package that integrates with the host application package.

## Understanding the recipe
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The [recipe.yaml](https://github.com/aws-deadline/deadline-cloud-samples/blob/mainline/conda_recipes/maya-mtoa-2026/recipe/recipe.yaml) specifies a dependency on the `maya` package for both build and run requirements. This dependency uses a version constraint so that the plugin is only installed with a compatible Maya version.

The recipe uses the same source archives as the Maya recipe. The build script installs MtoA and creates a `mtoa.mod` file in the `$PREFIX/usr/autodesk/maya$MAYA_VERSION/modules` directory that the Maya package configures in `MAYA_MODULE_PATH`. Arnold and Maya use the same licensing technology, so the Maya package already includes the licensing information that Arnold needs.

## Building the MtoA package
<a name="mtoa-build-package"></a>

Build the Maya package before you build the MtoA package, because MtoA depends on Maya at build time. Use `rattler-build publish` to build and publish the package. From the `conda_recipes` directory, run the following command.

```
rattler-build publish maya-mtoa-2026/recipe/recipe.yaml \
    --to file://$HOME/my-conda-channel \
    --build-number=+1
```

The `rattler-build publish` command uses the target channel as the highest priority channel when resolving dependencies, so the `maya` package you published earlier is available automatically.

For other publishing options:
+ To publish to an Amazon S3 channel, see [Publish packages to an S3 conda channel](publish-packages-s3-channel.md).
+ To automate builds using a Deadline Cloud package building queue, see [Automate package builds with Deadline Cloud](automate-package-builds.md).

# Test your packages with a Maya render job
<a name="submit-render-maya-mtoa"></a>

After you build the Maya, MtoA, and `maya-openjd` packages, you can test them with a render job. The Deadline Cloud samples repository contains a [turntable with Maya/Arnold](https://github.com/aws-deadline/deadline-cloud-samples/tree/mainline/job_bundles/turntable_with_maya_arnold) job bundle that renders an animation using Maya and Arnold. The job bundle also uses FFmpeg to encode a video, which is available from the `conda-forge` channel.

## Testing locally
<a name="maya-test-locally"></a>

You can run the job template on your workstation using the [Open Job Description CLI](https://github.com/OpenJobDescription/openjd-cli#readme). Install the CLI with `pip`.

```
pip install openjd-cli
```

From the `job_bundles` directory in the samples repository, run the following command. The `ErrorOnArnoldLicenseFail=false` parameter tells Arnold to render with watermarks instead of failing when no license is available.

```
openjd run turntable_with_maya_arnold/template.yaml \
    --environment ../queue_environments/conda_queue_env_pyrattler.yaml \
    -p CondaPackages="maya maya-mtoa maya-openjd ffmpeg" \
    -p CondaChannels="file://$HOME/my-conda-channel conda-forge" \
    -p ErrorOnArnoldLicenseFail=false \
    -p FrameRange=1-5
```

The `--environment` option applies the conda queue environment, which creates a conda virtual environment with the packages specified in `CondaPackages`. The `CondaChannels` parameter includes both the local channel for your custom packages and `conda-forge` for `ffmpeg`. If you published to an Amazon S3 channel instead of a local channel, replace the `file://` path with your `s3://` channel URL.

When the job completes, the rendered output is in the `turntable_with_maya_arnold/output/` directory.

## Testing on Deadline Cloud
<a name="maya-test-deadline-cloud"></a>

After you configure your production queue to use the Amazon S3 conda channel, submit the render job to Deadline Cloud. Add the `conda-forge` channel to the `CondaChannels` parameter in your conda queue environment to provide a source for `ffmpeg` and the Python dependencies that the adaptor requires. From the `job_bundles` directory in the samples repository, run the following command.

```
deadline bundle submit turntable_with_maya_arnold
```

Use the Deadline Cloud monitor to track the progress of the job. In the monitor, select the task for the job and choose **View logs**. Select the **Launch Conda** session action to verify that the `maya`, `maya-mtoa`, and `maya-openjd` packages were found in the Amazon S3 channel.