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Script Annotations

Annotation syntax is an experimental feature using typing.Annotated for Parameters and Artifacts to declare 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.

This feature must be enabled by setting the experimental_feature flag script_annotations on the global config.

global_config.experimental_features["script_annotations"] = True

Parameters

In Hera, we can currently specify inputs inside the @script decorator as follows:

@script(
    inputs=[
        Parameter(name="an_int", description="an_int parameter", default=1, enum=[1, 2, 3]),
        Parameter(name="a_bool", description="a_bool parameter", default=True, enum=[True, False]),
        Parameter(name="a_string", description="a_string parameter", default="a", enum=["a", "b", "c"])
    ]
)
def echo_all(an_int=1, a_bool=True, a_string="a"):
    print(an_int)
    print(a_bool)
    print(a_string)

Notice how the name and default values are duplicated for each Parameter. Using annotations, we can rewrite this as:

@script()
def echo_all(
    an_int: Annotated[int, Parameter(description="an_int parameter", enum=[1, 2, 3])] = 1,
    a_bool: Annotated[bool, Parameter(description="a_bool parameter", enum=[True, False])] = True,
    a_string: Annotated[str, Parameter(description="a_string parameter", enum=["a", "b", "c"])] = "a",
):
    print(an_int)
    print(a_bool)
    print(a_string)

The fields allowed in the Parameter annotations are: name, enum, and description.

Artifacts

Note: Artifact annotations are only supported when used with the RunnerScriptConstructor.

The feature is even more powerful for Artifacts. In Hera we are currently able to specify Artifacts in inputs, but the given path is not programmatically linked to the code within the function unless defined outside the scope of the function:

@script(inputs=Artifact(name="my-artifact", path="/tmp/file"))
def read_artifact():
    with open("/tmp/file") as a_file:  # Repeating "/tmp/file" is prone to human error!
        print(a_file.read())

# or

MY_PATH = "/tmp/file"  # Now accessible outside of the function scope!
@script(inputs=Artifact(name="my-artifact", path=MY_PATH))
def read_artifact():
    with open(MY_PATH) as a_file:
        print(a_file.read())

By using annotations we can avoid repeating the path of the file, and the function can use the variable directly as a Path object, with its value already set to the given path:

@script(constructor="runner")
def read_artifact(an_artifact: Annotated[Path, Artifact(name="my-artifact", path="/tmp/file")]):
    print(an_artifact.read_text())

The fields allowed in the Artifact annotations are: name, path, and loader.

Artifact Loaders

In case you want to load an object directly from the path of the Artifact, we allow two types of loaders besides the default Path behaviour used when no loader is specified. The ArtifactLoader enum provides file and json loaders.

None loader

With None set as the loader (which is by default) in the Artifact annotation, the path attribute of Artifact is extracted and used to provide a pathlib.Path object for the given argument, which can be used directly in the function body. The following example is the same as above except for explicitly setting the loader to None:

@script(constructor="runner")
def read_artifact(
    an_artifact: Annotated[Path, Artifact(name="my-artifact", path="/tmp/file", loader=None)]
):
    print(an_artifact.read_text())

file loader

When the loader is set to file, the function parameter type should be str, and will contain the contents string representation of the file stored at path (essentially performing path.read_text() automatically):

@script(constructor="runner")
def read_artifact(
    an_artifact: Annotated[str, Artifact(name="my-artifact", path="/tmp/file", loader=ArtifactLoader.file)]
) -> str:
    return an_artifact

This loads the contents of the file at "/tmp/file" to the argument an_artifact and subsequently can be used as a string inside the function.

json loader

When the loader is set to json, the contents of the file at path are read and parsed to a dictionary via json.load (essentially performing json.load(path.open()) automatically). By specifying a Pydantic type, this dictionary can even be automatically parsed to that type:

class MyArtifact(BaseModel):
    a = "a"
    b = "b"


@script(constructor="runner")
def read_artifact(
    an_artifact: Annotated[MyArtifact, Artifact(name="my-artifact", path="/tmp/file", loader=ArtifactLoader.json)]
) -> str:
    return an_artifact.a + an_artifact.b

Here, we have a json representation of MyArtifact such as {"a": "hello ", "b": "world"} stored at "/tmp/file". We can load it with ArtifactLoader.json and then use an_artifact as an instance of MyArtifact inside the function, so the function will return "hello world".

Function parameter name aliasing

Script annotations can work on top of the RunnerScriptConstructor for name aliasing of function parameters, in particular to allow a public kebab-case parameter, while using a snake_case Python function parameter. When using a RunnerScriptConstructor, an environment variable hera__script_annotations will be added to the Script template (visible in the exported YAML file).

Outputs

Note: Output annotations are only supported when used with the RunnerScriptConstructor.

There are two ways to specify output Artifacts and Parameters.

Function return annotations

Function return annotations can be used to specify the output type information for output Artifacts and Parameters, and the function should return a value or tuple. An example can be seen here.

For a simple hello world output artifact example we currently have: 

@script(outputs=Artifact(name="hello-artifact", path="/tmp/hello_world.txt"))
def hello_world():
   with open("/tmp/hello_world.txt", "w") as f:
       f.write("Hello, world!")

The new approach allows us to avoid duplication of the path, which is now optional, and results in more readable code: 

@script()
def hello_world() -> Annotated[str, Artifact(name="hello-artifact")]:
    return "Hello, world!"

For Parameters we have a similar syntax:

@script()
def hello_world() -> Annotated[str, Parameter(name="hello-param")]:
    return "Hello, world!"

The returned values will be automatically saved in files within the Argo container according to this schema: * /hera/outputs/parameters/<name> * /hera/outputs/artifacts/<name>

These outputs are also exposed in the outputs section of the template in YAML.

The object returned from the function can be of any serialisable Pydantic type (or basic Python type) and must be Annotated as an Artifact or Parameter. The Parameter/Artifact’s name will be used for the path of the output unless provided: * if the annotation is an Artifact with a path, we use that path * if the annotation is a Parameter, with a value_from that contains a path, we use that path

See the following two functions for specifying custom paths:

@script()
def hello_world() -> Annotated[str, Artifact(name="hello-artifact", path="/tmp/hello_world_art.txt")]:
    return "Hello, world!"

@script()
def hello_world() -> Annotated[str, Parameter(name="hello-param", value_from={"path": "/tmp/hello_world_param.txt"})]:
    return "Hello, world!"

For multiple outputs, the return type should be a Tuple of arbitrary Pydantic types with individual Parameter/Artifact annotations, and the function must return a tuple from the function matching these types: 

@script()
def func(...) -> Tuple[
    Annotated[arbitrary_pydantic_type_a, Artifact],
    Annotated[arbitrary_pydantic_type_b, Parameter],
    Annotated[arbitrary_pydantic_type_c, Parameter],
    ...]:
    return output_a, output_b, output_c

Input-Output function parameters

Hera also allows output Parameter/Artifacts as part of the function signature when specified as a Path type, allowing users to write to the path as an output, without needing an explicit return. They require an additional field output=True to distinguish them from the input parameters and must have an underlying Path type (or another type that will write to disk).

@script()
def func(..., output_param: Annotated[Path, Parameter(output=True, global_name="...", name="")]) -> Annotated[arbitrary_pydantic_type, OutputItem]:
    output_param.write_text("...")
    return output

The parent outputs directory, /hera/outputs by default, can be set by the user. This is done by adding:

global_config.set_class_defaults(RunnerScriptConstructor, outputs_directory="user/chosen/outputs")

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