AWS Deadline Cloud for Unreal Engine
User guide | Service documentation | Deadline Cloud on GitHub
AWS Deadline Cloud for Unreal Engine is a C++ and python package for Unreal that allows users to create Unreal Movie Render Queue jobs for AWS Deadline Cloud from within Unreal Engine. Using the Open Job Description (OpenJD) Adaptor Runtime this package also provides a command line application on the worker side to that adapts Unreal's command line interface to support the OpenJD specification and allows efficient rendering of multiple shots from a sequence without restarting Unreal.
For instructions on installing and using this integration, visit the user guide.
Compatibility
This library requires:
- Python 3.9 or higher; and Unreal Engine 5.4 through 5.8.
- Windows operating system.
Submitter
This package provides a Unreal Engine plugin that creates Unreal Movie Render Queue jobs for AWS Deadline Cloud using the AWS Deadline Cloud client library. Based on the loaded scene it determines the files required, allows the user to specify render options, and builds an OpenJD template that defines the workflow.
See Submitter Setup Guide for instructions on setting up your Unreal Submitter plugin and Deadline Cloud Service Managed Fleets (SMF) or Customer Managed Fleets (CMF).
For Deadline Cloud submission hooks (pre-GUI, pre/post-submission) from DEADLINE_HOOKS_DIR, see Submission Hooks.
Adaptor
The Unreal Engine Adaptor implements the OpenJD interface that allows render workloads to launch Unreal Engine and feed it commands. This gives the following benefits:
- a standardized render application interface,
- sticky rendering, where the application stays open between tasks (Shots)
For more information on the commands the OpenJD adaptor runtime provides, see here.
Jobs created by the submitter use this adaptor by default. The Unreal Engine Adaptor supports both Service Managed Fleets (SMF) and Customer Managed Fleets (CMF) for rendering workloads on Windows fleets.
Service Managed Fleets (SMF)
On Service Managed Fleets (SMF) worker hosts, the Unreal Engine and adaptor are automatically available via the deadline-cloud-v2 and deadline-cloud Conda channels with the default Queue Environment.
Perforce is supported on SMF!
Customer Managed Fleets (CMF)
The Unreal Engine and adaptor must be manually installed on worker hosts of Customer Managed Fleets (CMF). See CMF Worker Setup Guide for instructions on setting up an instance to act as a worker node.
Versioning
This package's version follows Semantic Versioning 2.0, but is still considered to be in its initial development, thus backwards incompatible versions are denoted by minor version bumps. To help illustrate how versions will increment during this initial development stage, they are described below:
- The MAJOR version is currently 0, indicating initial development.
- The MINOR version is currently incremented when backwards incompatible changes are introduced to the public API.
- The PATCH version is currently incremented when bug fixes or backwards compatible changes are introduced to the public API.
Security
See CONTRIBUTING for more information.
Telemetry
See telemetry for more information.
License
This project is licensed under the Apache-2.0 License.
Release files for deadline-cloud-for-unreal-engine 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deadline_cloud_for_unreal_engine-1.0.0.tar.gz | 287.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deadline_cloud_for_unreal_engine-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 418.4 kB
Release files / deadline_cloud_for_unreal_engine-1.0.0.tar.gz
| Download URL | deadline_cloud_for_unreal_engine-1.0.0.tar.gz |
|---|---|
| Size | 287.0 kB |
| Tags | Source |
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| Download URL | deadline_cloud_for_unreal_engine-1.0.0-py3-none-any.whl |
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| Tags | Python 3 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Provenance
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