Experimental Features
From time to time, Hera will release a new feature under the “experimental feature” flag while we develop the feature and ensure stability. Once the feature is stable and we have decided to support it long-term, it will “graduate” into a fully-supported feature.
To enable experimental features you must set the feature by name to True in the global_config.experimental_features
dictionary before using the feature:
Note that experimental features are subject to breaking changes in future releases of the same major version. We will usually announce changes in the Hera slack channel.
Currently supported experimental features:
Script IO Models
Hera provides Pydantic models for you to create subclasses from, which allow you to more easily declare script template
inputs. Any fields that you declare in your subclass of Input will become input parameters or artifacts, while
Output fields will become output parameters artifacts. The fields that you declare can be Annotated as a Parameter
or Artifact, as any fields with a basic type will become Parameters. Turning on the script_pydantic_io flag will
automatically enable the script_annotations experimental feature.
To enable Hera input/output models, you must set the experimental_feature flag script_pydantic_io
Read the full guide on script pydantic IO in the script user guide.
Decorators for main template types
Decorators for dags, steps and containers are provided alongside a new script decorator, letting your declare Workflows via Python functions alone.
To enable the decorators, you must install the optional extras under experimental
You can then set the experimental_feature flag decorator_syntax in your code
Read the full guide on decorators in the decorator user guide.
Graduated features
Once an experimental feature is robust and reliable, we “graduate” them to allow their use without setting the
experimental_features flag of the global_config. This comes with better support and guarantees for their feature
set. We list graduated features here so you can keep up to date.
RunnerScriptConstructor (since 5.10)
The RunnerScriptConstructor found in hera.workflows.script and seen in the
callable script example is a robust way to run Python functions on
Argo. The image used by the script should be built from the source code package itself and its dependencies, so that the
source code’s functions, dependencies, and Hera itself are available to run. The RunnerScriptConstructor is also
compatible with Pydantic so supports deserializing inputs to Python objects and serializing outputs to json strings.
Read the Script Guide to learn more!
Script Annotations (since 5.19)
Annotation syntax using typing.Annotated is supported for Parameters and Artifacts as inputs and outputs for
functions decorated as scripts. They use Annotated as the type in the function parameters and allow us to simplify
writing scripts with parameters and artifacts that require additional fields such as a description or alternative
name.
Read the full guide on script annotations in the script user guide.