Hera Workflows

hera.workflows

Hera classes.

Label module-attribute

Label = MetricLabel

AWSElasticBlockStoreVolumeVolume

Representation of AWS elastic block store volume.

Source code in src/hera/workflows/volume.py

class AWSElasticBlockStoreVolumeVolume(_BaseVolume, _ModelAWSElasticBlockStoreVolumeSource):
    """Representation of AWS elastic block store volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            aws_elastic_block_store=_ModelAWSElasticBlockStoreVolumeSource(
                fs_type=self.fs_type, partition=self.partition, read_only=self.read_only, volume_id=self.volume_id
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

partition class-attribute instance-attribute

partition = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

volume_id instance-attribute

volume_id

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

AccessMode

A representations of the volume access modes for Kubernetes.

Notes

See: access modes docs for more information.

Source code in src/hera/workflows/volume.py

class AccessMode(Enum):
    """A representations of the volume access modes for Kubernetes.

    Notes:
        See: [access modes docs](https://kubernetes.io/docs/concepts/storage/persistent-volumes/#access-modes) for
        more information.
    """

    read_write_once = "ReadWriteOnce"
    """
    The volume can be mounted as read-write by a single node. ReadWriteOnce access mode still can allow multiple
    pods to access the volume when the pods are running on the same node
    """

    read_only_many = "ReadOnlyMany"
    """The volume can be mounted as read-only by many nodes"""

    read_write_many = "ReadWriteMany"
    """The volume can be mounted as read-write by many nodes"""

    read_write_once_pod = "ReadWriteOncePod"
    """
    The volume can be mounted as read-write by a single Pod. Use ReadWriteOncePod access mode if you want to
    ensure that only one pod across whole cluster can read that PVC or write to it. This is only supported for CSI
    volumes and Kubernetes version 1.22+.
    """

    def __str__(self) -> str:
        """Returns the value representation of the enum in the form of a string."""
        return str(self.value)

read_only_many class-attribute instance-attribute

read_only_many = 'ReadOnlyMany'

The volume can be mounted as read-only by many nodes

read_write_many class-attribute instance-attribute

read_write_many = 'ReadWriteMany'

The volume can be mounted as read-write by many nodes

read_write_once class-attribute instance-attribute

read_write_once = 'ReadWriteOnce'

The volume can be mounted as read-write by a single node. ReadWriteOnce access mode still can allow multiple pods to access the volume when the pods are running on the same node

read_write_once_pod class-attribute instance-attribute

read_write_once_pod = 'ReadWriteOncePod'

The volume can be mounted as read-write by a single Pod. Use ReadWriteOncePod access mode if you want to ensure that only one pod across whole cluster can read that PVC or write to it. This is only supported for CSI volumes and Kubernetes version 1.22+.

ArchiveStrategy

Base archive strategy model.

Source code in src/hera/workflows/archive.py

class ArchiveStrategy(BaseModel):
    """Base archive strategy model."""

    def _build_archive_strategy(self) -> _ModelArchiveStrategy:
        return _ModelArchiveStrategy()

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Artifact

Base artifact representation.

Source code in src/hera/workflows/artifact.py

class Artifact(BaseModel):
    """Base artifact representation."""

    name: Optional[str]
    """name of the artifact"""

    archive: Optional[Union[_ModelArchiveStrategy, ArchiveStrategy]] = None
    """artifact archiving configuration"""

    archive_logs: Optional[bool] = None
    """whether to log the archive object"""

    artifact_gc: Optional[ArtifactGC] = None
    """artifact garbage collection configuration"""

    deleted: Optional[bool] = None
    """whether the artifact is deleted"""

    from_: Optional[str] = None
    """configures the artifact task/step origin"""

    from_expression: Optional[str] = None
    """an expression that dictates where to obtain the artifact from"""

    global_name: Optional[str] = None
    """global workflow artifact name"""

    mode: Optional[int] = None
    """mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts."""

    path: Optional[str] = None
    """path where the artifact should be placed/loaded from"""

    recurse_mode: Optional[bool] = None
    """recursion mode when applying the permissions of the artifact if it is an artifact folder"""

    sub_path: Optional[str] = None
    """allows the specification of an artifact from a subpath within the main source."""

    loader: Optional[ArtifactLoader] = None
    """used for input Artifact annotations for determining how to load the data.

    Note: A loader value of 'None' must be used with an underlying type of 'str' or Path-like class."""

    optional: Optional[bool] = None
    """whether the Artifact is optional. For an input Artifact, this means it may possibly not
    exist at the specified path during the template's runtime. For an output Artifact, it may
    possibly not be generated during the step/task and available as an output to subsequent steps/tasks."""

    output: bool = False
    """used to specify artifact as an output in function signature annotations"""

    def _check_name(self):
        if not self.name:
            raise ValueError("name cannot be `None` or empty when used")

    def _get_default_inputs_path(self) -> str:
        return _DEFAULT_ARTIFACT_INPUT_DIRECTORY + f"{self.name}"

    def _build_archive(self) -> Optional[_ModelArchiveStrategy]:
        if self.archive is None:
            return None

        if isinstance(self.archive, _ModelArchiveStrategy):
            return self.archive
        return cast(ArchiveStrategy, self.archive)._build_archive_strategy()

    def _build_artifact(self) -> _ModelArtifact:
        self._check_name()
        assert self.name
        return _ModelArtifact(
            name=self.name,
            archive=self._build_archive(),
            archive_logs=self.archive_logs,
            artifact_gc=self.artifact_gc,
            deleted=self.deleted,
            from_=self.from_,
            from_expression=self.from_expression,
            global_name=self.global_name,
            mode=self.mode,
            optional=self.optional,
            path=self.path,
            recurse_mode=self.recurse_mode,
            sub_path=self.sub_path,
        )

    def _build_artifact_paths(self) -> _ModelArtifactPaths:
        self._check_name()
        artifact = self._build_artifact()
        return _ModelArtifactPaths(**artifact.dict())

    def as_name(self, name: str) -> _ModelArtifact:
        """DEPRECATED, use with_name.

        Returns a 'built' copy of the current artifact, renamed using the specified `name`.
        """
        logger.warning("'as_name' is deprecated, use 'with_name'")
        artifact = self._build_artifact()
        artifact.name = name
        return artifact

    def with_name(self, name: str) -> Artifact:
        """Returns a copy of the current artifact, renamed using the specified `name`."""
        artifact = self.copy(deep=True)
        artifact.name = name
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return [
            "mode",
            "name",
            "optional",
            "path",
            "recurseMode",
            "subPath",
        ]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

ArtifactLoader

Enum for artifact loader options.

Source code in src/hera/workflows/artifact.py

class ArtifactLoader(Enum):
    """Enum for artifact loader options."""

    json = "json"
    """Deserialize the JSON-string Artifact file to a Python object (the target variable can be any JSON-compatible type)."""

    file = "file"
    """Read the contents of the Artifact file directly as a string (the target variable must be a `str` type)."""

file class-attribute instance-attribute

file = 'file'

Read the contents of the Artifact file directly as a string (the target variable must be a str type).

json class-attribute instance-attribute

json = 'json'

Deserialize the JSON-string Artifact file to a Python object (the target variable can be any JSON-compatible type).

ArtifactoryArtifact

An artifact sourced from Artifactory.

Source code in src/hera/workflows/artifact.py

class ArtifactoryArtifact(_ModelArtifactoryArtifact, Artifact):
    """An artifact sourced from Artifactory."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.artifactory = _ModelArtifactoryArtifact(
            url=self.url, password_secret=self.password_secret, username_secret=self.username_secret
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + ["url", "password_secret", "username_secret"]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

password_secret class-attribute instance-attribute

password_secret = None

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

url instance-attribute

url

username_secret class-attribute instance-attribute

username_secret = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

AzureArtifact

An artifact sourced from Microsoft Azure.

Source code in src/hera/workflows/artifact.py

class AzureArtifact(_ModelAzureArtifact, Artifact):
    """An artifact sourced from Microsoft Azure."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.azure = _ModelAzureArtifact(
            account_key_secret=self.account_key_secret,
            blob=self.blob,
            container=self.container,
            endpoint=self.endpoint,
            use_sdk_creds=self.use_sdk_creds,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + [
            "endpoint",
            "container",
            "blob",
            "account_key_secret",
            "use_sdk_creds",
        ]

account_key_secret class-attribute instance-attribute

account_key_secret = None

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

blob instance-attribute

blob

container instance-attribute

container

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

endpoint instance-attribute

endpoint

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

use_sdk_creds class-attribute instance-attribute

use_sdk_creds = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

AzureDiskVolumeVolume

Representation of an Azure disk volume.

Source code in src/hera/workflows/volume.py

class AzureDiskVolumeVolume(_BaseVolume, _ModelAzureDiskVolumeSource):
    """Representation of an Azure disk volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            azure_disk=_ModelAzureDiskVolumeSource(
                caching_mode=self.caching_mode,
                disk_name=self.disk_name,
                disk_uri=self.disk_uri,
                fs_type=self.fs_type,
                kind=self.kind,
                read_only=self.read_only,
            ),
        )

caching_mode class-attribute instance-attribute

caching_mode = None

disk_name instance-attribute

disk_name

disk_uri instance-attribute

disk_uri

fs_type class-attribute instance-attribute

fs_type = None

kind class-attribute instance-attribute

kind = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

AzureFileVolumeVolume

Representation of an Azure file that can be mounted as a volume.

Source code in src/hera/workflows/volume.py

class AzureFileVolumeVolume(_BaseVolume, _ModelAzureFileVolumeSource):
    """Representation of an Azure file that can be mounted as a volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            azure_file=_ModelAzureFileVolumeSource(
                read_only=self.read_only, secret_name=self.secret_name, share_name=self.share_name
            ),
        )

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_name instance-attribute

secret_name

share_name instance-attribute

share_name

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

CSIVolume

Representation of a container service interface volume.

Source code in src/hera/workflows/volume.py

class CSIVolume(_BaseVolume, _ModelCSIVolumeSource):
    """Representation of a container service interface volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            csi=_ModelCSIVolumeSource(
                driver=self.driver,
                fs_type=self.fs_type,
                node_publish_secret_ref=self.node_publish_secret_ref,
                read_only=self.read_only,
                volume_attributes=self.volume_attributes,
            ),
        )

driver instance-attribute

driver

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

node_publish_secret_ref class-attribute instance-attribute

node_publish_secret_ref = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

volume_attributes class-attribute instance-attribute

volume_attributes = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

CephFSVolumeVolume

Representation of a Ceph file system volume.

Source code in src/hera/workflows/volume.py

class CephFSVolumeVolume(_BaseVolume, _ModelCephFSVolumeSource):
    """Representation of a Ceph file system volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            cephfs=_ModelCephFSVolumeSource(
                monitors=self.monitors,
                path=self.path,
                read_only=self.read_only,
                secret_file=self.secret_file,
                secret_ref=self.secret_ref,
                user=self.user,
            ),
        )

monitors instance-attribute

monitors

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

path class-attribute instance-attribute

path = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_file class-attribute instance-attribute

secret_file = None

secret_ref class-attribute instance-attribute

secret_ref = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

user class-attribute instance-attribute

user = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

CinderVolume

Representation of a Cinder volume.

Source code in src/hera/workflows/volume.py

class CinderVolume(_BaseVolume, _ModelCinderVolumeSource):
    """Representation of a Cinder volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            cinder=_ModelCinderVolumeSource(
                fs_type=self.fs_type,
                read_only=self.read_only,
                secret_ref=self.secret_ref,
                volume_id=self.volume_id,
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_ref class-attribute instance-attribute

secret_ref = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

volume_id instance-attribute

volume_id

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

ClusterWorkflowTemplate

ClusterWorkflowTemplates are cluster scoped templates.

Since cluster workflow templates are scoped at the cluster level, they are available globally in the cluster.

Source code in src/hera/workflows/cluster_workflow_template.py

class ClusterWorkflowTemplate(WorkflowTemplate):
    """ClusterWorkflowTemplates are cluster scoped templates.

    Since cluster workflow templates are scoped at the cluster level, they are available globally in the cluster.
    """

    @validator("namespace", pre=True, always=True)
    def _set_namespace(cls, v):
        if v is not None:
            raise ValueError("namespace is not a valid field on a ClusterWorkflowTemplate")

    def create(self) -> TWorkflow:  # type: ignore
        """Creates the ClusterWorkflowTemplate on the Argo cluster."""
        assert self.workflows_service, "workflow service not initialized"
        return self.workflows_service.create_cluster_workflow_template(
            ClusterWorkflowTemplateCreateRequest(template=self.build())  # type: ignore
        )

    def get(self) -> TWorkflow:
        """Attempts to get a workflow template based on the parameters of this template e.g. name + namespace."""
        assert self.workflows_service, "workflow service not initialized"
        assert self.name, "workflow name not defined"
        return self.workflows_service.get_cluster_workflow_template(name=self.name)

    def update(self) -> TWorkflow:
        """Attempts to perform a workflow template update based on the parameters of this template.

        Note that this creates the template if it does not exist. In addition, this performs
        a get prior to updating to get the resource version to update in the first place. If you know the template
        does not exist ahead of time, it is more efficient to use `create()` directly to avoid one round trip.
        """
        assert self.workflows_service, "workflow service not initialized"
        assert self.name, "workflow name not defined"
        # we always need to do a get prior to updating to get the resource version to update in the first place
        # https://github.com/argoproj/argo-workflows/pull/5465#discussion_r597797052

        template = self.build()
        try:
            curr = self.get()
            template.metadata.resource_version = curr.metadata.resource_version
        except NotFound:
            return self.create()
        return self.workflows_service.update_cluster_workflow_template(
            self.name,
            ClusterWorkflowTemplateUpdateRequest(template=template),  # type: ignore
        )

    def lint(self) -> TWorkflow:
        """Lints the ClusterWorkflowTemplate using the Argo cluster."""
        assert self.workflows_service, "workflow service not initialized"
        return self.workflows_service.lint_cluster_workflow_template(
            ClusterWorkflowTemplateLintRequest(template=self.build())  # type: ignore
        )

    def build(self) -> TWorkflow:
        """Builds the ClusterWorkflowTemplate and its components into an Argo schema ClusterWorkflowTemplate object."""
        # Note that ClusterWorkflowTemplates are exactly the same as WorkflowTemplates except for the kind which is
        # handled in Workflow._set_kind (by __name__). When using ClusterWorkflowTemplates via templateRef, clients
        # should specify cluster_scope=True, but that is an intrinsic property of ClusterWorkflowTemplates from our
        # perspective.
        return _ModelClusterWorkflowTemplate(**super().build().dict())

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

api_version class-attribute instance-attribute

api_version = None

archive_logs class-attribute instance-attribute

archive_logs = None

arguments class-attribute instance-attribute

arguments = None

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact_repository_ref class-attribute instance-attribute

artifact_repository_ref = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

creation_timestamp class-attribute instance-attribute

creation_timestamp = None

deletion_grace_period_seconds class-attribute instance-attribute

deletion_grace_period_seconds = None

deletion_timestamp class-attribute instance-attribute

deletion_timestamp = None

dns_config class-attribute instance-attribute

dns_config = None

dns_policy class-attribute instance-attribute

dns_policy = None

entrypoint class-attribute instance-attribute

entrypoint = None

executor class-attribute instance-attribute

executor = None

finalizers class-attribute instance-attribute

finalizers = None

generate_name class-attribute instance-attribute

generate_name = None

generation class-attribute instance-attribute

generation = None

hooks class-attribute instance-attribute

hooks = None

host_aliases class-attribute instance-attribute

host_aliases = None

host_network class-attribute instance-attribute

host_network = None

image_pull_secrets class-attribute instance-attribute

image_pull_secrets = None

kind class-attribute instance-attribute

kind = None

labels class-attribute instance-attribute

labels = None

managed_fields class-attribute instance-attribute

managed_fields = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

namespace class-attribute instance-attribute

namespace = None

node_selector class-attribute instance-attribute

node_selector = None

on_exit class-attribute instance-attribute

on_exit = None

owner_references class-attribute instance-attribute

owner_references = None

parallelism class-attribute instance-attribute

parallelism = None

pod_disruption_budget class-attribute instance-attribute

pod_disruption_budget = None

pod_gc class-attribute instance-attribute

pod_gc = None

pod_metadata class-attribute instance-attribute

pod_metadata = None

pod_priority class-attribute instance-attribute

pod_priority = None

pod_priority_class_name class-attribute instance-attribute

pod_priority_class_name = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

resource_version class-attribute instance-attribute

resource_version = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

self_link class-attribute instance-attribute

self_link = None

service_account_name class-attribute instance-attribute

service_account_name = None

shutdown class-attribute instance-attribute

shutdown = None

status class-attribute instance-attribute

status = None

suspend class-attribute instance-attribute

suspend = None

synchronization class-attribute instance-attribute

synchronization = None

template_defaults class-attribute instance-attribute

template_defaults = None

templates class-attribute instance-attribute

templates = []

tolerations class-attribute instance-attribute

tolerations = None

ttl_strategy class-attribute instance-attribute

ttl_strategy = None

uid class-attribute instance-attribute

uid = None

volume_claim_gc class-attribute instance-attribute

volume_claim_gc = None

volume_claim_templates class-attribute instance-attribute

volume_claim_templates = None

volumes class-attribute instance-attribute

volumes = None

workflow_metadata class-attribute instance-attribute

workflow_metadata = None

workflow_template_ref class-attribute instance-attribute

workflow_template_ref = None

workflows_service class-attribute instance-attribute

workflows_service = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Container

The Container template type defines a container to run on Argo.

The container generally consists of running a Docker container remotely, which is configured via fields such as command (the command to run to start the container), args (arguments for the container), working_dir (for setting the active working directory relative to container execution), etc.

Source code in src/hera/workflows/container.py

class Container(
    EnvIOMixin,
    ContainerMixin,
    TemplateMixin,
    ResourceMixin,
    VolumeMountMixin,
    CallableTemplateMixin,
):
    """The Container template type defines a container to run on Argo.

    The container generally consists of running a Docker container remotely, which is configured via fields such as
    `command` (the command to run to start the container), `args` (arguments for the container), `working_dir` (for
    setting the active working directory relative to container execution), etc.
    """

    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    working_dir: Optional[str] = None

    def _build_container(self) -> _ModelContainer:
        """Builds the generated `Container` representation."""
        assert self.image
        return _ModelContainer(
            args=self.args,
            command=self.command,
            env=self._build_env(),
            env_from=self._build_env_from(),
            image=self.image,
            image_pull_policy=self._build_image_pull_policy(),
            lifecycle=self.lifecycle,
            liveness_probe=self.liveness_probe,
            ports=self.ports,
            readiness_probe=self.readiness_probe,
            resize_policy=self.resize_policy,
            resources=self._build_resources(),
            restart_policy=self.restart_policy,
            security_context=self.security_context,
            startup_probe=self.startup_probe,
            stdin=self.stdin,
            stdin_once=self.stdin_once,
            termination_message_path=self.termination_message_path,
            termination_message_policy=self.termination_message_policy,
            tty=self.tty,
            volume_devices=self.volume_devices,
            volume_mounts=self._build_volume_mounts(),
            working_dir=self.working_dir,
        )

    def _build_template(self) -> _ModelTemplate:
        """Builds the generated `Template` representation of the container."""
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container=self._build_container(),
            daemon=self.daemon,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
            volumes=self._build_volumes(),
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

args class-attribute instance-attribute

args = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

command class-attribute instance-attribute

command = None

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

DAG

A DAG template invocator is used to define Task dependencies as an acyclic graph.

DAG implements the contextmanager interface so allows usage of with, under which any hera.workflows.task.Task objects instantiated will be added to the DAG’s list of Tasks.

Examples:

>>> @script()
>>> def foo() -> None:
>>>     print(42)
>>>
>>> with DAG(...) as dag:
>>>     foo()

Source code in src/hera/workflows/dag.py

class DAG(
    IOMixin,
    TemplateMixin,
    CallableTemplateMixin,
    ContextMixin,
):
    """A DAG template invocator is used to define Task dependencies as an acyclic graph.

    DAG implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.task.Task` objects instantiated will be added to the DAG's list of Tasks.

    Examples:
        >>> @script()
        >>> def foo() -> None:
        >>>     print(42)
        >>>
        >>> with DAG(...) as dag:
        >>>     foo()
    """

    fail_fast: Optional[bool] = None
    target: Optional[str] = None
    tasks: List[Union[Task, DAGTask]] = []

    _node_names = PrivateAttr(default_factory=set)
    _current_task_depends: Set[str] = PrivateAttr(set())

    def _add_sub(self, node: Any):
        if not isinstance(node, Task):
            raise InvalidType(type(node))
        if node.name in self._node_names:
            raise NodeNameConflict(f"Found multiple Task nodes with name: {node.name}")
        self._node_names.add(node.name)
        self.tasks.append(node)

    def _build_template(self) -> _ModelTemplate:
        """Builds the auto-generated `Template` representation of the `DAG`."""
        tasks = []
        for task in self.tasks:
            if isinstance(task, Task):
                tasks.append(task._build_dag_task())
            else:
                tasks.append(task)
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            daemon=self.daemon,
            dag=_ModelDAGTemplate(fail_fast=self.fail_fast, target=self.target, tasks=tasks),
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

synchronization class-attribute instance-attribute

synchronization = None

target class-attribute instance-attribute

target = None

tasks class-attribute instance-attribute

tasks = []

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

ModelMapper

Source code in src/hera/workflows/_meta_mixins.py

class ModelMapper:
    def __init__(self, model_path: str, hera_builder: Optional[Callable] = None):
        self.model_path = []
        self.builder = hera_builder

        if not model_path:
            # Allows overriding parent attribute annotations to remove the mapping
            return

        self.model_path = model_path.split(".")
        curr_class: Type[BaseModel] = self._get_model_class()
        for key in self.model_path:
            fields = get_fields(curr_class)
            if key not in fields:
                raise ValueError(f"Model key '{key}' does not exist in class {curr_class}")
            curr_class = fields[key].outer_type_  # type: ignore

    @classmethod
    def _get_model_class(cls) -> Type[BaseModel]:
        raise NotImplementedError

    @classmethod
    def build_model(
        cls, hera_class: Type[ModelMapperMixin], hera_obj: ModelMapperMixin, model: TWorkflow
    ) -> TWorkflow:
        assert isinstance(hera_obj, ModelMapperMixin)

        for attr, annotation in hera_class._get_all_annotations().items():
            if mappers := get_annotated_metadata(annotation, ModelMapperMixin.ModelMapper):
                if len(mappers) != 1:
                    raise ValueError("Expected only one ModelMapper")

                # Value comes from builder function if it exists on hera_obj, otherwise directly from the attr
                value = (
                    getattr(hera_obj, mappers[0].builder.__name__)()
                    if mappers[0].builder is not None
                    else getattr(hera_obj, attr)
                )
                if value is not None:
                    _set_model_attr(model, mappers[0].model_path, value)

        return model

builder instance-attribute

builder = hera_builder

model_path instance-attribute

model_path = split('.')

build_model classmethod

build_model(hera_class, hera_obj, model)

Source code in src/hera/workflows/_meta_mixins.py

@classmethod
def build_model(
    cls, hera_class: Type[ModelMapperMixin], hera_obj: ModelMapperMixin, model: TWorkflow
) -> TWorkflow:
    assert isinstance(hera_obj, ModelMapperMixin)

    for attr, annotation in hera_class._get_all_annotations().items():
        if mappers := get_annotated_metadata(annotation, ModelMapperMixin.ModelMapper):
            if len(mappers) != 1:
                raise ValueError("Expected only one ModelMapper")

            # Value comes from builder function if it exists on hera_obj, otherwise directly from the attr
            value = (
                getattr(hera_obj, mappers[0].builder.__name__)()
                if mappers[0].builder is not None
                else getattr(hera_obj, attr)
            )
            if value is not None:
                _set_model_attr(model, mappers[0].model_path, value)

    return model

Script

A Script acts as a wrapper around a container.

In Hera this defaults to a “python:3.9” image specified by global_config.image, which runs a python source specified by Script.source.

Source code in src/hera/workflows/script.py

class Script(
    EnvIOMixin,
    CallableTemplateMixin,
    ContainerMixin,
    TemplateMixin,
    ResourceMixin,
    VolumeMountMixin,
):
    """A Script acts as a wrapper around a container.

    In Hera this defaults to a "python:3.9" image specified by global_config.image, which runs a python source
    specified by `Script.source`.
    """

    container_name: Optional[str] = None
    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    source: Optional[Union[Callable, str]] = None
    working_dir: Optional[str] = None
    add_cwd_to_sys_path: Optional[bool] = None
    constructor: Optional[Union[str, ScriptConstructor]] = None

    @validator("constructor", always=True)
    @classmethod
    def _set_constructor(cls, v):
        if v is None:
            # TODO: In the future we can insert
            # detection code here to determine
            # the best constructor to use.
            v = InlineScriptConstructor()
        if isinstance(v, ScriptConstructor):
            return v
        assert isinstance(v, str)
        if v.lower() == "inline":
            return InlineScriptConstructor()
        elif v.lower() == "runner":
            return RunnerScriptConstructor()
        raise ValueError(f"Unknown constructor {v}")

    @validator("command", always=True)
    @classmethod
    def _set_command(cls, v):
        return v or global_config.script_command

    @validator("add_cwd_to_sys_path", always=True)
    @classmethod
    def _set_add_cwd_to_sys_path(cls, v):
        if v is None:
            return True

    @root_validator
    @classmethod
    def _constructor_validate(cls, values):
        constructor = values.get("constructor")
        assert isinstance(constructor, ScriptConstructor)
        return constructor.transform_values(cls, values)

    def _build_template(self) -> _ModelTemplate:
        assert isinstance(self.constructor, ScriptConstructor)

        return self.constructor.transform_template_post_build(
            self,
            _ModelTemplate(
                active_deadline_seconds=self.active_deadline_seconds,
                affinity=self.affinity,
                archive_location=self.archive_location,
                automount_service_account_token=self.automount_service_account_token,
                daemon=self.daemon,
                executor=self.executor,
                fail_fast=self.fail_fast,
                host_aliases=self.host_aliases,
                init_containers=self._build_init_containers(),
                inputs=self._build_inputs(),
                memoize=self.memoize,
                metadata=self._build_metadata(),
                metrics=self._build_metrics(),
                name=self.name,
                node_selector=self.node_selector,
                outputs=self._build_outputs(),
                parallelism=self.parallelism,
                plugin=self.plugin,
                pod_spec_patch=self.pod_spec_patch,
                priority=self.priority,
                priority_class_name=self.priority_class_name,
                retry_strategy=self.retry_strategy,
                scheduler_name=self.scheduler_name,
                script=self._build_script(),
                security_context=self.pod_security_context,
                service_account_name=self.service_account_name,
                sidecars=self._build_sidecars(),
                synchronization=self.synchronization,
                timeout=self.timeout,
                tolerations=self.tolerations,
                volumes=self._build_volumes(),
            ),
        )

    def _build_script(self) -> _ModelScriptTemplate:
        assert isinstance(self.constructor, ScriptConstructor)
        if _output_annotations_used(cast(Callable, self.source)) and isinstance(
            self.constructor, RunnerScriptConstructor
        ):
            if not self.constructor.outputs_directory:
                self.constructor.outputs_directory = self.constructor.DEFAULT_HERA_OUTPUTS_DIRECTORY
            if self.constructor.volume_for_outputs is not None:
                if self.constructor.volume_for_outputs.mount_path is None:
                    self.constructor.volume_for_outputs.mount_path = self.constructor.outputs_directory
                self._create_hera_outputs_volume(self.constructor.volume_for_outputs)
        assert self.image
        return self.constructor.transform_script_template_post_build(
            self,
            _ModelScriptTemplate(
                args=self.args,
                command=self.command,
                env=self._build_env(),
                env_from=self._build_env_from(),
                image=self.image,
                # `image_pull_policy` in script wants a string not an `ImagePullPolicy` object
                image_pull_policy=self._build_image_pull_policy(),
                lifecycle=self.lifecycle,
                liveness_probe=self.liveness_probe,
                name=self.container_name,
                ports=self.ports,
                readiness_probe=self.readiness_probe,
                resize_policy=self.resize_policy,
                resources=self._build_resources(),
                restart_policy=self.restart_policy,
                security_context=self.security_context,
                source=self.constructor.generate_source(self),
                startup_probe=self.startup_probe,
                stdin=self.stdin,
                stdin_once=self.stdin_once,
                termination_message_path=self.termination_message_path,
                termination_message_policy=self.termination_message_policy,
                tty=self.tty,
                volume_devices=self.volume_devices,
                volume_mounts=self._build_volume_mounts(),
                working_dir=self.working_dir,
            ),
        )

    def _build_inputs(self) -> Optional[ModelInputs]:
        inputs = super()._build_inputs()
        func_parameters: List[Parameter] = []
        func_artifacts: List[Artifact] = []
        if callable(self.source):
            func_parameters, func_artifacts = _get_inputs_from_callable(self.source)

        return cast(Optional[ModelInputs], self._aggregate_callable_io(inputs, func_parameters, func_artifacts, False))

    def _build_outputs(self) -> Optional[ModelOutputs]:
        outputs = super()._build_outputs()

        if not callable(self.source):
            return outputs

        outputs_directory = None
        if isinstance(self.constructor, RunnerScriptConstructor):
            outputs_directory = self.constructor.outputs_directory or self.constructor.DEFAULT_HERA_OUTPUTS_DIRECTORY

        out_parameters, out_artifacts = _get_outputs_from_return_annotation(self.source, outputs_directory)
        func_parameters, func_artifacts = _get_outputs_from_parameter_annotations(self.source, outputs_directory)
        func_parameters.extend(out_parameters)
        func_artifacts.extend(out_artifacts)

        return cast(
            Optional[ModelOutputs], self._aggregate_callable_io(outputs, func_parameters, func_artifacts, True)
        )

    def _aggregate_callable_io(
        self,
        current_io: Optional[Union[ModelInputs, ModelOutputs]],
        func_parameters: List[Parameter],
        func_artifacts: List[Artifact],
        output: bool,
    ) -> Union[ModelOutputs, ModelInputs, None]:
        """Aggregate the Inputs/Outputs with parameters and artifacts extracted from a callable."""
        if not func_parameters and not func_artifacts:
            return current_io
        if current_io is None:
            if output:
                return ModelOutputs(
                    parameters=[p.as_output() for p in func_parameters] or None,
                    artifacts=[a._build_artifact() for a in func_artifacts] or None,
                )

            return ModelInputs(
                parameters=[p.as_input() for p in func_parameters] or None,
                artifacts=[a._build_artifact() for a in func_artifacts] or None,
            )

        seen_params = {p.name for p in current_io.parameters or []}
        seen_artifacts = {a.name for a in current_io.artifacts or []}

        for param in func_parameters:
            if param.name not in seen_params and param.name not in seen_artifacts:
                if current_io.parameters is None:
                    current_io.parameters = []
                if output:
                    current_io.parameters.append(param.as_output())
                else:
                    current_io.parameters.append(param.as_input())

        for artifact in func_artifacts:
            if artifact.name not in seen_artifacts:
                if current_io.artifacts is None:
                    current_io.artifacts = []
                current_io.artifacts.append(artifact._build_artifact())

        return current_io

    def _create_hera_outputs_volume(self, volume: _BaseVolume) -> None:
        """Add given volume to the script template for the automatic saving of the hera outputs."""
        assert isinstance(self.constructor, RunnerScriptConstructor)

        if self.volumes is None:
            self.volumes = []
        elif isinstance(self.volumes, Sequence):
            self.volumes = list(self.volumes)
        elif not isinstance(self.volumes, list):
            self.volumes = [self.volumes]

        if volume not in self.volumes:
            self.volumes.append(volume)

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

add_cwd_to_sys_path class-attribute instance-attribute

add_cwd_to_sys_path = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

args class-attribute instance-attribute

args = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

command class-attribute instance-attribute

command = None

constructor class-attribute instance-attribute

constructor = None

container_name class-attribute instance-attribute

container_name = None

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

source class-attribute instance-attribute

source = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

Steps

A Steps template invocator is used to define a sequence of steps which can run sequentially or in parallel.

Steps implements the contextmanager interface so allows usage of with, under which any hera.workflows.steps.Step objects instantiated will be added to the Steps’ list of sub_steps.

• Step and Parallel objects initialised within a Steps context will be added to the list of sub_steps in the order they are initialised.
• All Step objects initialised within a Parallel context will run in parallel.

Source code in src/hera/workflows/steps.py

class Steps(
    IOMixin,
    TemplateMixin,
    CallableTemplateMixin,
    ContextMixin,
):
    """A Steps template invocator is used to define a sequence of steps which can run sequentially or in parallel.

    Steps implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.steps.Step` objects instantiated will be added to the Steps' list of sub_steps.

    * Step and Parallel objects initialised within a Steps context will be added to the list of sub_steps
    in the order they are initialised.
    * All Step objects initialised within a Parallel context will run in parallel.
    """

    _node_names = PrivateAttr(default_factory=set)

    sub_steps: List[
        Union[
            Step,
            Parallel,
            List[Step],
            _ModelWorkflowStep,
            List[_ModelWorkflowStep],
        ]
    ] = []

    def _build_steps(self) -> Optional[List[ParallelSteps]]:
        steps = []
        for workflow_step in self.sub_steps:
            if isinstance(workflow_step, Steppable):
                steps.append(ParallelSteps(__root__=workflow_step._build_step()))
            elif isinstance(workflow_step, _ModelWorkflowStep):
                steps.append(ParallelSteps(__root__=[workflow_step]))
            elif isinstance(workflow_step, List):
                substeps = []
                for s in workflow_step:
                    if isinstance(s, Step):
                        substeps.append(s._build_as_workflow_step())
                    elif isinstance(s, _ModelWorkflowStep):
                        substeps.append(s)
                    else:
                        raise InvalidType(type(s))
                steps.append(ParallelSteps(__root__=substeps))
            else:
                raise InvalidType(type(workflow_step))

        return steps or None

    def _add_sub(self, node: Any):
        if not isinstance(node, (Step, Parallel)):
            raise InvalidType(type(node))
        if isinstance(node, Step):
            if node.name in self._node_names:
                raise NodeNameConflict(f"Found multiple Step nodes with name: {node.name}")
            self._node_names.add(node.name)
        if isinstance(node, Parallel):
            node._node_names = self._node_names
        self.sub_steps.append(node)

    def parallel(self) -> Parallel:
        """Returns a Parallel object which can be used in a sub-context manager."""
        return Parallel()

    def _build_template(self) -> _ModelTemplate:
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container=None,
            container_set=None,
            daemon=self.daemon,
            dag=None,
            data=None,
            executor=self.executor,
            fail_fast=self.fail_fast,
            http=None,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            resource=None,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            script=None,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            steps=self._build_steps(),
            suspend=None,
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

sub_steps class-attribute instance-attribute

sub_steps = []

synchronization class-attribute instance-attribute

synchronization = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

parallel

parallel()

Returns a Parallel object which can be used in a sub-context manager.

Source code in src/hera/workflows/steps.py

def parallel(self) -> Parallel:
    """Returns a Parallel object which can be used in a sub-context manager."""
    return Parallel()

add_template_set

add_template_set(template_set)

Add the templates stored in the template_set to this Workflow.

Source code in src/hera/workflows/workflow.py

def add_template_set(self, template_set: TemplateSet) -> None:
    """Add the templates stored in the template_set to this Workflow."""
    for template in template_set.templates:
        self._add_sub(template)

build

build()

Builds the ClusterWorkflowTemplate and its components into an Argo schema ClusterWorkflowTemplate object.

Source code in src/hera/workflows/cluster_workflow_template.py

def build(self) -> TWorkflow:
    """Builds the ClusterWorkflowTemplate and its components into an Argo schema ClusterWorkflowTemplate object."""
    # Note that ClusterWorkflowTemplates are exactly the same as WorkflowTemplates except for the kind which is
    # handled in Workflow._set_kind (by __name__). When using ClusterWorkflowTemplates via templateRef, clients
    # should specify cluster_scope=True, but that is an intrinsic property of ClusterWorkflowTemplates from our
    # perspective.
    return _ModelClusterWorkflowTemplate(**super().build().dict())

container

container(**container_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Container)  # type: ignore
def container(self, **container_kwargs) -> Callable:
    self._check_if_enabled("container")
    from hera.workflows.container import Container

    def container_decorator(func: Callable[FuncIns, FuncR]) -> Callable:
        name = container_kwargs.pop("name", func.__name__.replace("_", "-"))

        signature = inspect.signature(func)
        func_inputs = signature.parameters
        inputs = []
        if len(func_inputs) >= 1:
            input_arg = list(func_inputs.values())[0].annotation
            if issubclass(input_arg, (InputV1, InputV2)):
                inputs = input_arg._get_inputs(add_missing_path=True)

        func_return = signature.return_annotation
        outputs = []
        if func_return and issubclass(func_return, (OutputV1, OutputV2)):
            outputs = func_return._get_outputs(add_missing_path=True)

        # Open context to add `Container` object automatically
        with self:
            container_template = Container(
                name=name,
                inputs=inputs,
                outputs=outputs,
                **container_kwargs,
            )

        @functools.wraps(func)
        def container_call_wrapper(*args, **kwargs) -> Union[FuncR, Step, Task, None]:
            """Invokes a CallableTemplateMixin's `__call__` method using the given SubNode (Step or Task) args/kwargs."""
            if _context.declaring:
                subnode_name = kwargs.pop("name", None)
                if not subnode_name:
                    try:
                        # ignore decorator function assignment
                        subnode_name = varname()
                    except ImproperUseError:
                        # Template is being used without variable assignment (so use function name or provided name)
                        subnode_name = container_template.name  # type: ignore

                    assert isinstance(subnode_name, str)
                    subnode_name = subnode_name.replace("_", "-")

                return self._create_subnode(subnode_name, func, container_template, *args, **kwargs)

            if _context.pieces:
                return container_template.__call__(*args, **kwargs)
            return func(*args)

        # Set the template name to the inferred name
        container_call_wrapper.template_name = name  # type: ignore

        return container_call_wrapper

    return container_decorator

create

create()

Creates the ClusterWorkflowTemplate on the Argo cluster.

Source code in src/hera/workflows/cluster_workflow_template.py

def create(self) -> TWorkflow:  # type: ignore
    """Creates the ClusterWorkflowTemplate on the Argo cluster."""
    assert self.workflows_service, "workflow service not initialized"
    return self.workflows_service.create_cluster_workflow_template(
        ClusterWorkflowTemplateCreateRequest(template=self.build())  # type: ignore
    )

create_as_workflow

create_as_workflow(generate_name=None, wait=False, poll_interval=5)

Run this WorkflowTemplate instantly as a Workflow.

If generate_name is given, the workflow created uses generate_name as a prefix, as per the usual for hera.workflows.Workflow.generate_name. If not given, the WorkflowTemplate’s name will be used, truncated to 57 chars and appended with a hyphen.

Note: this function does not require the WorkflowTemplate to already exist on the cluster

Source code in src/hera/workflows/workflow_template.py

def create_as_workflow(
    self,
    generate_name: Optional[str] = None,
    wait: bool = False,
    poll_interval: int = 5,
) -> TWorkflow:
    """Run this WorkflowTemplate instantly as a Workflow.

    If generate_name is given, the workflow created uses generate_name as a prefix, as per the usual for
    hera.workflows.Workflow.generate_name. If not given, the WorkflowTemplate's name will be used, truncated to 57
    chars and appended with a hyphen.

    Note: this function does not require the WorkflowTemplate to already exist on the cluster
    """
    workflow = self._get_as_workflow(generate_name)
    return workflow.create(wait=wait, poll_interval=poll_interval)

dag

dag(**dag_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(DAG)  # type: ignore
def dag(self, **dag_kwargs) -> Callable:
    self._check_if_enabled("dag")

    from hera.workflows.dag import DAG

    return self._construct_invocator_decorator(DAG, **dag_kwargs)

from_dict classmethod

from_dict(model_dict)

Create a WorkflowTemplate from a WorkflowTemplate contained in a dict.

Examples:

>>> my_workflow_template = WorkflowTemplate(name="my-wft")
>>> my_workflow_template == WorkflowTemplate.from_dict(my_workflow_template.to_dict())
True

Source code in src/hera/workflows/workflow_template.py

@classmethod
def from_dict(cls, model_dict: Dict) -> ModelMapperMixin:
    """Create a WorkflowTemplate from a WorkflowTemplate contained in a dict.

    Examples:
        >>> my_workflow_template = WorkflowTemplate(name="my-wft")
        >>> my_workflow_template == WorkflowTemplate.from_dict(my_workflow_template.to_dict())
        True
    """
    return cls._from_dict(model_dict, _ModelWorkflowTemplate)

from_file classmethod

from_file(yaml_file)

Create a WorkflowTemplate from a WorkflowTemplate contained in a YAML file.

Examples:

>>> yaml_file = Path(...)
>>> my_workflow_template = WorkflowTemplate.from_file(yaml_file)

Source code in src/hera/workflows/workflow_template.py

@classmethod
def from_file(cls, yaml_file: Union[Path, str]) -> ModelMapperMixin:
    """Create a WorkflowTemplate from a WorkflowTemplate contained in a YAML file.

    Examples:
        >>> yaml_file = Path(...)
        >>> my_workflow_template = WorkflowTemplate.from_file(yaml_file)
    """
    return cls._from_file(yaml_file, _ModelWorkflowTemplate)

from_yaml classmethod

from_yaml(yaml_str)

Create a WorkflowTemplate from a WorkflowTemplate contained in a YAML string.

Examples:

>>> my_workflow_template = WorkflowTemplate.from_yaml(yaml_str)

Source code in src/hera/workflows/workflow_template.py

@classmethod
def from_yaml(cls, yaml_str: str) -> ModelMapperMixin:
    """Create a WorkflowTemplate from a WorkflowTemplate contained in a YAML string.

    Examples:
        >>> my_workflow_template = WorkflowTemplate.from_yaml(yaml_str)
    """
    return cls._from_yaml(yaml_str, _ModelWorkflowTemplate)

get

get()

Attempts to get a workflow template based on the parameters of this template e.g. name + namespace.

Source code in src/hera/workflows/cluster_workflow_template.py

def get(self) -> TWorkflow:
    """Attempts to get a workflow template based on the parameters of this template e.g. name + namespace."""
    assert self.workflows_service, "workflow service not initialized"
    assert self.name, "workflow name not defined"
    return self.workflows_service.get_cluster_workflow_template(name=self.name)

get_parameter

get_parameter(name)

Attempts to find and return a Parameter of the specified name.

Source code in src/hera/workflows/workflow.py

def get_parameter(self, name: str) -> Parameter:
    """Attempts to find and return a `Parameter` of the specified name."""
    arguments = self._build_arguments()
    if arguments is None:
        raise KeyError("Workflow has no arguments set")
    if arguments.parameters is None:
        raise KeyError("Workflow has no argument parameters set")

    parameters = arguments.parameters
    if next((p for p in parameters if p.name == name), None) is None:
        raise KeyError(f"`{name}` is not a valid workflow parameter")
    return Parameter(name=name, value=f"{{{{workflow.parameters.{name}}}}}")

get_workflow_link

get_workflow_link()

Returns the workflow link for the workflow.

Source code in src/hera/workflows/workflow.py

def get_workflow_link(self) -> str:
    """Returns the workflow link for the workflow."""
    assert self.workflows_service is not None, "Cannot fetch a workflow link without a service"
    assert self.name is not None, "Cannot fetch a workflow link without a workflow name"
    return self.workflows_service.get_workflow_link(self.name)

lint

lint()

Lints the ClusterWorkflowTemplate using the Argo cluster.

Source code in src/hera/workflows/cluster_workflow_template.py

def lint(self) -> TWorkflow:
    """Lints the ClusterWorkflowTemplate using the Argo cluster."""
    assert self.workflows_service, "workflow service not initialized"
    return self.workflows_service.lint_cluster_workflow_template(
        ClusterWorkflowTemplateLintRequest(template=self.build())  # type: ignore
    )

script

script(**script_kwargs)

A decorator that wraps a function into a Script object.

Using this decorator users can define a function that will be executed as a script in a container. Once the Script is returned users can use it as they generally use a Script e.g. as a callable inside a DAG or Steps. Note that invoking the function will result in the template associated with the script to be added to the workflow context, so users do not have to worry about that.

Parameters

**script_kwargs Keyword arguments to be passed to the Script object.

Returns:

Callable Function wrapper that holds a Script and allows the function to be called to create a Step or Task if in a Steps or DAG context.

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Script)  # type: ignore
def script(self, **script_kwargs) -> Callable:
    """A decorator that wraps a function into a Script object.

    Using this decorator users can define a function that will be executed as a script in a container. Once the
    `Script` is returned users can use it as they generally use a `Script` e.g. as a callable inside a DAG or Steps.
    Note that invoking the function will result in the template associated with the script to be added to the
    workflow context, so users do not have to worry about that.

    Parameters
    ----------
    **script_kwargs
        Keyword arguments to be passed to the Script object.

    Returns:
    -------
    Callable
        Function wrapper that holds a `Script` and allows the function to be called to create a Step or Task if
        in a Steps or DAG context.
    """
    self._check_if_enabled("script")

    from hera.workflows.script import RunnerScriptConstructor, Script

    def script_decorator(func: Callable[FuncIns, FuncR]) -> Callable:
        """The internal decorator function.

        Parameters
        ----------
        func: Callable
            Function to wrap.

        Returns:
        -------
        Callable
            Callable that calls the `Script` object `__call__` method when in a Steps or DAG context,
            otherwise calls function itself.
        """
        # instance methods are wrapped in `staticmethod`. Hera can capture that type and extract the underlying
        # function for remote submission since it does not depend on any class or instance attributes, so it is
        # submittable
        if isinstance(func, staticmethod):
            source: Callable = func.__func__
        else:
            source = func

        # take the client-provided `name` if it is submitted, pop the name for otherwise there will be two
        # kwargs called `name`
        # otherwise populate the `name` from the function name
        name = script_kwargs.pop("name", source.__name__.replace("_", "-"))

        if "constructor" not in script_kwargs and "constructor" not in global_config._get_class_defaults(Script):
            script_kwargs["constructor"] = RunnerScriptConstructor()

        signature = inspect.signature(func)
        func_inputs = signature.parameters
        if len(func_inputs) > 1:
            raise SyntaxError("script decorator must be used with a single `Input` arg, or no args.")

        if len(func_inputs) == 1:
            func_input = list(func_inputs.values())[0].annotation
            if not issubclass(func_input, (InputV1, InputV2)):
                raise SyntaxError("script decorator must be used with a single `Input` arg, or no args.")

        # Open (Workflow) context to add `Script` object automatically
        with self:
            script_template = Script(name=name, source=source, **script_kwargs)

        if not isinstance(script_template.constructor, RunnerScriptConstructor):
            raise ValueError(f"Script '{name}' must use RunnerScriptConstructor")

        @functools.wraps(func)
        def script_call_wrapper(*args, **kwargs) -> Union[FuncR, Step, Task, None]:
            """Invokes a CallableTemplateMixin's `__call__` method using the given SubNode (Step or Task) args/kwargs."""
            if _context.declaring:
                subnode_name = kwargs.pop("name", None)
                if not subnode_name:
                    try:
                        # ignore decorator function assignment
                        subnode_name = varname()
                    except ImproperUseError:
                        # Template is being used without variable assignment (so use function name or provided name)
                        subnode_name = script_template.name  # type: ignore

                    assert isinstance(subnode_name, str)
                    subnode_name = subnode_name.replace("_", "-")

                return self._create_subnode(subnode_name, func, script_template, *args, **kwargs)

            if _context.pieces:
                return script_template.__call__(*args, **kwargs)

            return func(*args)

        # Set the wrapped function to the original function so that we can use it later
        script_call_wrapper.wrapped_function = func  # type: ignore
        # Set the template name to the inferred name
        script_call_wrapper.template_name = name  # type: ignore

        return script_call_wrapper

    return script_decorator

set_entrypoint

set_entrypoint(func)

Decorator function to set entrypoint.

Source code in src/hera/workflows/workflow.py

def set_entrypoint(self, func: Callable[P, T]) -> Callable[P, T]:
    """Decorator function to set entrypoint."""
    if not hasattr(func, "template_name"):
        raise SyntaxError("`set_entrypoint` decorator must be above template decorator")

    if self.entrypoint is not None:
        if self.entrypoint == func.template_name:
            return func

        logging.warning(f"entrypoint is being reassigned from {self.entrypoint} to {func.template_name}")

    self.entrypoint = func.template_name  # type: ignore
    return func

steps

steps(**steps_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Steps)  # type: ignore
def steps(self, **steps_kwargs) -> Callable:
    self._check_if_enabled("steps")

    from hera.workflows.steps import Steps

    return self._construct_invocator_decorator(Steps, **steps_kwargs)

to_dict

to_dict()

Builds the Workflow as an Argo schema Workflow object and returns it as a dictionary.

Source code in src/hera/workflows/workflow.py

def to_dict(self) -> Any:
    """Builds the Workflow as an Argo schema Workflow object and returns it as a dictionary."""
    return self.build().dict(exclude_none=True, by_alias=True)

to_file

to_file(output_directory='.', name='', *args, **kwargs)

Writes the Workflow as an Argo schema Workflow object to a YAML file and returns the path to the file.

Parameters:

Name	Type	Description	Default
output_directory	Union[Path, str]	The directory to write the file to. Defaults to the current working directory.	'.'
name	str	The name of the file to write without the file extension. Defaults to the Workflow’s name or a generated name.	''
*args		Additional arguments to pass to yaml.dump.	()
**kwargs		Additional keyword arguments to pass to yaml.dump.	{}

Source code in src/hera/workflows/workflow.py

def to_file(self, output_directory: Union[Path, str] = ".", name: str = "", *args, **kwargs) -> Path:
    """Writes the Workflow as an Argo schema Workflow object to a YAML file and returns the path to the file.

    Args:
        output_directory: The directory to write the file to. Defaults to the current working directory.
        name: The name of the file to write without the file extension.  Defaults to the Workflow's name or a
              generated name.
        *args: Additional arguments to pass to `yaml.dump`.
        **kwargs: Additional keyword arguments to pass to `yaml.dump`.
    """
    workflow_name = self.name or (self.generate_name or "workflow").rstrip("-")
    name = name or workflow_name
    output_directory = Path(output_directory)
    output_path = Path(output_directory) / f"{name}.yaml"
    output_directory.mkdir(parents=True, exist_ok=True)
    output_path.write_text(self.to_yaml(*args, **kwargs))
    return output_path.absolute()

to_yaml

to_yaml(*args, **kwargs)

Builds the Workflow as an Argo schema Workflow object and returns it as yaml string.

Source code in src/hera/workflows/workflow.py

def to_yaml(self, *args, **kwargs) -> str:
    """Builds the Workflow as an Argo schema Workflow object and returns it as yaml string."""

    def human_readable_ordering(kv: tuple) -> int:
        """Key ordering function for ordering in a more human-readable fashion.

        Ordering is:
        1. "name" keys always first (if present)
        2. Primitives (not dicts/lists)
        3. lists
        4. dict
        """
        k, v = kv
        if k == "name" and isinstance(v, str):
            return 0
        if not isinstance(v, (dict, list)):
            return 1
        if isinstance(v, list):
            return 2
        return 3

    def order_dict(d: dict) -> dict[str, Any]:
        """Recursively orders `d` by the custom_ordering function by inserting them into a copy of the dict in order."""
        d_copy: dict[str, Any] = dict()
        for k, v in sorted(d.items(), key=lambda x: (human_readable_ordering(x), x[0])):
            if isinstance(v, dict):
                d_copy[k] = order_dict(v)
            elif isinstance(v, list):
                if v and isinstance(v[0], dict):
                    d_copy[k] = [order_dict(i) if isinstance(i, dict) else i for i in v]
                elif v and isinstance(v[0], list):
                    d_copy[k] = [[order_dict(i) for i in sublist] for sublist in v]
                else:
                    d_copy[k] = v
            else:
                d_copy[k] = v
        return d_copy

    human_ordered_dict = order_dict(self.to_dict())
    return _yaml.dump(human_ordered_dict, *args, **kwargs)

update

update()

Attempts to perform a workflow template update based on the parameters of this template.

Note that this creates the template if it does not exist. In addition, this performs a get prior to updating to get the resource version to update in the first place. If you know the template does not exist ahead of time, it is more efficient to use create() directly to avoid one round trip.

Source code in src/hera/workflows/cluster_workflow_template.py

def update(self) -> TWorkflow:
    """Attempts to perform a workflow template update based on the parameters of this template.

    Note that this creates the template if it does not exist. In addition, this performs
    a get prior to updating to get the resource version to update in the first place. If you know the template
    does not exist ahead of time, it is more efficient to use `create()` directly to avoid one round trip.
    """
    assert self.workflows_service, "workflow service not initialized"
    assert self.name, "workflow name not defined"
    # we always need to do a get prior to updating to get the resource version to update in the first place
    # https://github.com/argoproj/argo-workflows/pull/5465#discussion_r597797052

    template = self.build()
    try:
        curr = self.get()
        template.metadata.resource_version = curr.metadata.resource_version
    except NotFound:
        return self.create()
    return self.workflows_service.update_cluster_workflow_template(
        self.name,
        ClusterWorkflowTemplateUpdateRequest(template=template),  # type: ignore
    )

wait

wait(poll_interval=5)

Waits for the Workflow to complete execution.

Parameters

poll_interval: int = 5 The interval in seconds to poll the workflow status.

Source code in src/hera/workflows/workflow.py

def wait(self, poll_interval: int = 5) -> TWorkflow:
    """Waits for the Workflow to complete execution.

    Parameters
    ----------
    poll_interval: int = 5
        The interval in seconds to poll the workflow status.
    """
    assert self.workflows_service is not None, "workflow service not initialized"
    assert self.namespace is not None, "workflow namespace not defined"
    assert self.name is not None, "workflow name not defined"

    # here we use the sleep interval to wait for the workflow post creation. This is to address a potential
    # race conditions such as:
    # 1. Argo server says "workflow was accepted" but the workflow is not yet created
    # 2. Hera wants to verify the status of the workflow, but it's not yet defined because it's not created
    # 3. Argo finally creates the workflow
    # 4. Hera throws an `AssertionError` because the phase assertion fails
    time.sleep(poll_interval)
    wf = self.workflows_service.get_workflow(self.name, namespace=self.namespace)
    assert wf.metadata.name is not None, f"workflow name not defined for workflow {self.name}"

    assert wf.status is not None, f"workflow status not defined for workflow {wf.metadata.name}"
    assert wf.status.phase is not None, f"workflow phase not defined for workflow status {wf.status}"
    status = WorkflowStatus.from_argo_status(wf.status.phase)

    # keep polling for workflow status until completed, at the interval dictated by the user
    while status == WorkflowStatus.running:
        time.sleep(poll_interval)
        wf = self.workflows_service.get_workflow(wf.metadata.name, namespace=self.namespace)
        assert wf.status is not None, f"workflow status not defined for workflow {wf.metadata.name}"
        assert wf.status.phase is not None, f"workflow phase not defined for workflow status {wf.status}"
        status = WorkflowStatus.from_argo_status(wf.status.phase)
    return wf

ConfigMapEnv

ConfigMapEnv is an environment variable whose value originates from a Kubernetes config map.

Source code in src/hera/workflows/env.py

class ConfigMapEnv(_BaseEnv):
    """`ConfigMapEnv` is an environment variable whose value originates from a Kubernetes config map."""

    config_map_name: Optional[str]
    """the name of the config map to reference in Kubernetes"""

    config_map_key: str
    """the name of the field key whole value should be registered as an environment variable"""

    optional: Optional[bool] = None
    """whether the existence of the config map is optional"""

    def build(self) -> _ModelEnvVar:
        """Constructs and returns the Argo environment specification."""
        return _ModelEnvVar(
            name=self.name,
            value_from=_ModelEnvVarSource(
                config_map_key_ref=_ModelConfigMapKeySelector(
                    name=self.config_map_name, key=self.config_map_key, optional=self.optional
                )
            ),
        )

config_map_key instance-attribute

config_map_key

the name of the field key whole value should be registered as an environment variable

config_map_name instance-attribute

config_map_name

the name of the config map to reference in Kubernetes

name instance-attribute

name

the name of the environment variable. This is universally required irrespective of the type of env variable

optional class-attribute instance-attribute

optional = None

whether the existence of the config map is optional

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Constructs and returns the Argo environment specification.

Source code in src/hera/workflows/env.py

def build(self) -> _ModelEnvVar:
    """Constructs and returns the Argo environment specification."""
    return _ModelEnvVar(
        name=self.name,
        value_from=_ModelEnvVarSource(
            config_map_key_ref=_ModelConfigMapKeySelector(
                name=self.config_map_name, key=self.config_map_key, optional=self.optional
            )
        ),
    )

ConfigMapEnvFrom

Exposes a K8s config map’s value as an environment variable.

Source code in src/hera/workflows/env_from.py

class ConfigMapEnvFrom(_BaseEnvFrom, _ModelConfigMapEnvSource):
    """Exposes a K8s config map's value as an environment variable."""

    def build(self) -> _ModelEnvFromSource:
        """Constructs and returns the Argo EnvFrom specification."""
        return _ModelEnvFromSource(
            prefix=self.prefix,
            config_map_ref=_ModelConfigMapEnvSource(
                name=self.name,
                optional=self.optional,
            ),
        )

name class-attribute instance-attribute

name = None

optional class-attribute instance-attribute

optional = None

prefix class-attribute instance-attribute

prefix = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Constructs and returns the Argo EnvFrom specification.

Source code in src/hera/workflows/env_from.py

def build(self) -> _ModelEnvFromSource:
    """Constructs and returns the Argo EnvFrom specification."""
    return _ModelEnvFromSource(
        prefix=self.prefix,
        config_map_ref=_ModelConfigMapEnvSource(
            name=self.name,
            optional=self.optional,
        ),
    )

ConfigMapVolume

Representation of a config map volume.

Source code in src/hera/workflows/volume.py

class ConfigMapVolume(_BaseVolume, _ModelConfigMapVolumeSource):  # type: ignore
    """Representation of a config map volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            config_map=_ModelConfigMapVolumeSource(
                default_mode=self.default_mode, items=self.items, name=self.name, optional=self.optional
            ),
        )

default_mode class-attribute instance-attribute

default_mode = None

items class-attribute instance-attribute

items = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

optional class-attribute instance-attribute

optional = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Container

The Container template type defines a container to run on Argo.

The container generally consists of running a Docker container remotely, which is configured via fields such as command (the command to run to start the container), args (arguments for the container), working_dir (for setting the active working directory relative to container execution), etc.

Source code in src/hera/workflows/container.py

class Container(
    EnvIOMixin,
    ContainerMixin,
    TemplateMixin,
    ResourceMixin,
    VolumeMountMixin,
    CallableTemplateMixin,
):
    """The Container template type defines a container to run on Argo.

    The container generally consists of running a Docker container remotely, which is configured via fields such as
    `command` (the command to run to start the container), `args` (arguments for the container), `working_dir` (for
    setting the active working directory relative to container execution), etc.
    """

    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    working_dir: Optional[str] = None

    def _build_container(self) -> _ModelContainer:
        """Builds the generated `Container` representation."""
        assert self.image
        return _ModelContainer(
            args=self.args,
            command=self.command,
            env=self._build_env(),
            env_from=self._build_env_from(),
            image=self.image,
            image_pull_policy=self._build_image_pull_policy(),
            lifecycle=self.lifecycle,
            liveness_probe=self.liveness_probe,
            ports=self.ports,
            readiness_probe=self.readiness_probe,
            resize_policy=self.resize_policy,
            resources=self._build_resources(),
            restart_policy=self.restart_policy,
            security_context=self.security_context,
            startup_probe=self.startup_probe,
            stdin=self.stdin,
            stdin_once=self.stdin_once,
            termination_message_path=self.termination_message_path,
            termination_message_policy=self.termination_message_policy,
            tty=self.tty,
            volume_devices=self.volume_devices,
            volume_mounts=self._build_volume_mounts(),
            working_dir=self.working_dir,
        )

    def _build_template(self) -> _ModelTemplate:
        """Builds the generated `Template` representation of the container."""
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container=self._build_container(),
            daemon=self.daemon,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
            volumes=self._build_volumes(),
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

args class-attribute instance-attribute

args = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

command class-attribute instance-attribute

command = None

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

ContainerNode

A regular container that can be used as part of a hera.workflows.ContainerSet.

See Also

Container Set Template

Source code in src/hera/workflows/container_set.py

class ContainerNode(ContainerMixin, VolumeMountMixin, ResourceMixin, EnvMixin, SubNodeMixin):
    """A regular container that can be used as part of a `hera.workflows.ContainerSet`.

    See Also:
        [Container Set Template](https://argoproj.github.io/argo-workflows/container-set-template/)
    """

    name: str
    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    dependencies: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    working_dir: Optional[str] = None

    def next(self, other: ContainerNode) -> ContainerNode:
        """Sets the given container as a dependency of this container and returns the given container.

        Examples:
            >>> from hera.workflows import ContainerNode
            >>> a, b = ContainerNode(name="a"), ContainerNode(name="b")
            >>> a.next(b)
            >>> b.dependencies
            ['a']
        """
        assert issubclass(other.__class__, ContainerNode)
        if other.dependencies is None:
            other.dependencies = [self.name]
        else:
            other.dependencies.append(self.name)
        other.dependencies = sorted(list(set(other.dependencies)))
        return other

    def __rrshift__(self, other: List[ContainerNode]) -> ContainerNode:
        """Sets `self` as a dependent of the given list of other `hera.workflows.ContainerNode`.

        Practically, the `__rrshift__` allows us to express statements such as `[a, b, c] >> d`, where `d` is `self.`

        Examples:
            >>> from hera.workflows import ContainerNode
            >>> a, b, c = ContainerNode(name="a"), ContainerNode(name="b"), ContainerNode(name="c")
            >>> [a, b] >> c
            >>> c.dependencies
            ['a', 'b']
        """
        assert isinstance(other, list), f"Unknown type {type(other)} specified using reverse right bitshift operator"
        for o in other:
            o.next(self)
        return self

    def __rshift__(
        self, other: Union[ContainerNode, List[ContainerNode]]
    ) -> Union[ContainerNode, List[ContainerNode]]:
        """Sets the given container as a dependency of this container and returns the given container.

        Examples:
            >>> from hera.workflows import ContainerNode
            >>> a, b = ContainerNode(name="a"), ContainerNode(name="b")
            >>> a >> b
            >>> b.dependencies
            ['a']
        """
        if isinstance(other, ContainerNode):
            return self.next(other)
        elif isinstance(other, list):
            for o in other:
                assert isinstance(o, ContainerNode), (
                    f"Unknown list item type {type(o)} specified using right bitshift operator `>>`"
                )
                self.next(o)
            return other
        raise ValueError(f"Unknown type {type(other)} provided to `__rshift__`")

    def _build_container_node(self) -> _ModelContainerNode:
        """Builds the generated `ContainerNode`."""
        return _ModelContainerNode(
            args=self.args,
            command=self.command,
            dependencies=self.dependencies,
            env=self._build_env(),
            env_from=self._build_env_from(),
            image=self.image,
            image_pull_policy=self._build_image_pull_policy(),
            lifecycle=self.lifecycle,
            liveness_probe=self.liveness_probe,
            name=self.name,
            ports=self.ports,
            readiness_probe=self.readiness_probe,
            resize_policy=self.resize_policy,
            resources=self._build_resources(),
            restart_policy=self.restart_policy,
            security_context=self.security_context,
            startup_probe=self.startup_probe,
            stdin=self.stdin,
            stdin_once=self.stdin_once,
            termination_message_path=self.termination_message_path,
            termination_message_policy=self.termination_message_policy,
            tty=self.tty,
            volume_devices=self.volume_devices,
            volume_mounts=self._build_volume_mounts(),
            working_dir=self.working_dir,
        )

args class-attribute instance-attribute

args = None

command class-attribute instance-attribute

command = None

dependencies class-attribute instance-attribute

dependencies = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

name instance-attribute

name

ports class-attribute instance-attribute

ports = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

security_context class-attribute instance-attribute

security_context = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

next

next(other)

Sets the given container as a dependency of this container and returns the given container.

Examples:

>>> from hera.workflows import ContainerNode
>>> a, b = ContainerNode(name="a"), ContainerNode(name="b")
>>> a.next(b)
>>> b.dependencies
['a']

Source code in src/hera/workflows/container_set.py

def next(self, other: ContainerNode) -> ContainerNode:
    """Sets the given container as a dependency of this container and returns the given container.

    Examples:
        >>> from hera.workflows import ContainerNode
        >>> a, b = ContainerNode(name="a"), ContainerNode(name="b")
        >>> a.next(b)
        >>> b.dependencies
        ['a']
    """
    assert issubclass(other.__class__, ContainerNode)
    if other.dependencies is None:
        other.dependencies = [self.name]
    else:
        other.dependencies.append(self.name)
    other.dependencies = sorted(list(set(other.dependencies)))
    return other

ContainerSet

ContainerSet is the implementation of a set of containers that can be run in parallel on Kubernetes.

The containers are run within the same pod.

Examples:

>>> with ContainerSet(...) as cs:
>>>     ContainerNode(...)
>>>     ContainerNode(...)

Source code in src/hera/workflows/container_set.py

class ContainerSet(
    EnvIOMixin,
    ContainerMixin,
    TemplateMixin,
    CallableTemplateMixin,
    VolumeMountMixin,
    ContextMixin,
):
    """`ContainerSet` is the implementation of a set of containers that can be run in parallel on Kubernetes.

    The containers are run within the same pod.

    Examples:
        >>> with ContainerSet(...) as cs:
        >>>     ContainerNode(...)
        >>>     ContainerNode(...)
    """

    containers: List[Union[ContainerNode, _ModelContainerNode]] = []
    container_set_retry_strategy: Optional[ContainerSetRetryStrategy] = None

    def _add_sub(self, node: Any):
        if not isinstance(node, ContainerNode):
            raise InvalidType(type(node))

        self.containers.append(node)

    def _build_container_set(self) -> _ModelContainerSetTemplate:
        """Builds the generated `ContainerSetTemplate`."""
        containers = [c._build_container_node() if isinstance(c, ContainerNode) else c for c in self.containers]
        return _ModelContainerSetTemplate(
            containers=containers,
            retry_strategy=self.container_set_retry_strategy,
            volume_mounts=self.volume_mounts,
        )

    def _build_template(self) -> _ModelTemplate:
        """Builds the generated `Template` representation of the container set."""
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container_set=self._build_container_set(),
            daemon=self.daemon,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
            volumes=self._build_volumes(),
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

container_set_retry_strategy class-attribute instance-attribute

container_set_retry_strategy = None

containers class-attribute instance-attribute

containers = []

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

Counter

Counter metric component used to count specific events based on the given value.

Notes

See https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics

Source code in src/hera/workflows/metrics.py

class Counter(_BaseMetric):
    """Counter metric component used to count specific events based on the given value.

    Notes:
        See [https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics](https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics)
    """

    value: str

    def _build_metric(self) -> _ModelPrometheus:
        return _ModelPrometheus(
            counter=_ModelCounter(value=self.value),
            gauge=None,
            help=self.help,
            histogram=None,
            labels=self._build_labels(),
            name=self.name,
            when=self.when,
        )

help instance-attribute

help

labels class-attribute instance-attribute

labels = None

name instance-attribute

name

value instance-attribute

value

when class-attribute instance-attribute

when = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

CronWorkflow

CronWorkflow allows a user to run a Workflow on a recurring basis.

Note

Hera’s CronWorkflow is a subclass of Workflow which means certain fields are renamed for compatibility, see cron_suspend and cron_status which are different from the Argo spec. See CronWorkflowSpec for more details.

Source code in src/hera/workflows/cron_workflow.py

class CronWorkflow(Workflow):
    """CronWorkflow allows a user to run a Workflow on a recurring basis.

    Note:
        Hera's CronWorkflow is a subclass of Workflow which means certain fields are renamed
        for compatibility, see `cron_suspend` and `cron_status` which are different from the Argo
        spec. See [CronWorkflowSpec](https://argoproj.github.io/argo-workflows/fields/#cronworkflow) for more details.
    """

    concurrency_policy: Annotated[Optional[str], _CronWorkflowModelMapper("spec.concurrency_policy")] = None
    failed_jobs_history_limit: Annotated[Optional[int], _CronWorkflowModelMapper("spec.failed_jobs_history_limit")] = (
        None
    )
    schedule: Annotated[Optional[str], _CronWorkflowModelMapper("spec.schedule")] = None
    schedules: Annotated[Optional[List[str]], _CronWorkflowModelMapper("spec.schedules")] = None
    starting_deadline_seconds: Annotated[Optional[int], _CronWorkflowModelMapper("spec.starting_deadline_seconds")] = (
        None
    )
    stop_strategy: Annotated[Optional[StopStrategy], _CronWorkflowModelMapper("spec.stop_strategy")] = None
    successful_jobs_history_limit: Annotated[
        Optional[int], _CronWorkflowModelMapper("spec.successful_jobs_history_limit")
    ] = None
    cron_suspend: Annotated[Optional[bool], _CronWorkflowModelMapper("spec.suspend")] = None
    timezone: Annotated[Optional[str], _CronWorkflowModelMapper("spec.timezone")] = None
    when: Annotated[Optional[str], _CronWorkflowModelMapper("spec.when")] = None
    cron_status: Annotated[Optional[CronWorkflowStatus], _CronWorkflowModelMapper("status")] = None

    def create(self) -> TWorkflow:  # type: ignore
        """Creates the CronWorkflow on the Argo cluster."""
        assert self.workflows_service, "workflow service not initialized"
        assert self.namespace, "workflow namespace not defined"

        wf = self.workflows_service.create_cron_workflow(
            CreateCronWorkflowRequest(cron_workflow=self.build()),  # type: ignore
            namespace=self.namespace,
        )
        # set the name on the object so that we can do a get/update later
        self.name = wf.metadata.name
        return wf

    def get(self) -> TWorkflow:
        """Attempts to get a cron workflow based on the parameters of this template e.g. name + namespace."""
        assert self.workflows_service, "workflow service not initialized"
        assert self.namespace, "workflow namespace not defined"
        assert self.name, "workflow name not defined"
        return self.workflows_service.get_cron_workflow(name=self.name, namespace=self.namespace)

    def update(self) -> TWorkflow:
        """Attempts to perform a workflow template update based on the parameters of this template.

        Note that this creates the template if it does not exist. In addition, this performs
        a get prior to updating to get the resource version to update in the first place. If you know the template
        does not exist ahead of time, it is more efficient to use `create()` directly to avoid one round trip.
        """
        assert self.workflows_service, "workflow service not initialized"
        assert self.namespace, "workflow namespace not defined"
        assert self.name, "workflow name not defined"
        # we always need to do a get prior to updating to get the resource version to update in the first place
        # https://github.com/argoproj/argo-workflows/pull/5465#discussion_r597797052

        template = self.build()
        try:
            curr = self.get()
            template.metadata.resource_version = curr.metadata.resource_version
        except NotFound:
            return self.create()
        return self.workflows_service.update_cron_workflow(
            self.name,
            UpdateCronWorkflowRequest(cron_workflow=template),  # type: ignore
            namespace=self.namespace,
        )

    def lint(self) -> TWorkflow:
        """Lints the CronWorkflow using the Argo cluster."""
        assert self.workflows_service, "workflow service not initialized"
        assert self.namespace, "workflow namespace not defined"
        return self.workflows_service.lint_cron_workflow(
            LintCronWorkflowRequest(cron_workflow=self.build()),  # type: ignore
            namespace=self.namespace,
        )

    def build(self) -> TWorkflow:
        """Builds the CronWorkflow and its components into an Argo schema CronWorkflow object."""
        self = self._dispatch_hooks()

        model_workflow = cast(_ModelWorkflow, super().build())
        model_cron_workflow = _ModelCronWorkflow(
            metadata=model_workflow.metadata,
            spec=CronWorkflowSpec(
                workflow_spec=model_workflow.spec,
            ),
        )

        return _CronWorkflowModelMapper.build_model(CronWorkflow, self, model_cron_workflow)

    @classmethod
    def _from_model(cls, model: BaseModel) -> ModelMapperMixin:
        """Parse from given model to cls's type."""
        assert isinstance(model, _ModelCronWorkflow)
        hera_cron_workflow = cls()

        for attr, annotation in cls._get_all_annotations().items():
            if mappers := get_annotated_metadata(annotation, ModelMapperMixin.ModelMapper):
                if len(mappers) != 1:
                    raise ValueError("Expected only one ModelMapper")

                if mappers[0].model_path:
                    value = None

                    if (
                        isinstance(mappers[0], _CronWorkflowModelMapper)
                        or isinstance(mappers[0], _WorkflowModelMapper)
                        and mappers[0].model_path[0] == "metadata"
                    ):
                        value = _get_model_attr(model, mappers[0].model_path)

                    elif isinstance(mappers[0], _WorkflowModelMapper) and mappers[0].model_path[0] == "spec":
                        # We map "spec.workflow_spec" from the model CronWorkflow to "spec" for Hera's Workflow (used
                        # as the parent class of Hera's CronWorkflow)
                        value = _get_model_attr(model.spec.workflow_spec, mappers[0].model_path[1:])

                    if value is not None:
                        setattr(hera_cron_workflow, attr, value)

        return hera_cron_workflow

    @classmethod
    def from_dict(cls, model_dict: Dict) -> ModelMapperMixin:
        """Create a CronWorkflow from a CronWorkflow contained in a dict.

        Examples:
            >>> my_cron_workflow = CronWorkflow(name="my-cron-wf")
            >>> my_cron_workflow == CronWorkflow.from_dict(my_cron_workflow.to_dict())
            True
        """
        return cls._from_dict(model_dict, _ModelCronWorkflow)

    @classmethod
    def from_yaml(cls, yaml_str: str) -> ModelMapperMixin:
        """Create a CronWorkflow from a CronWorkflow contained in a YAML string.

        Examples:
            >>> my_cron_workflow = CronWorkflow.from_yaml(yaml_str)
        """
        return cls._from_yaml(yaml_str, _ModelCronWorkflow)

    @classmethod
    def from_file(cls, yaml_file: Union[Path, str]) -> ModelMapperMixin:
        """Create a CronWorkflow from a CronWorkflow contained in a YAML file.

        Examples:
            >>> yaml_file = Path(...)
            >>> my_workflow_template = CronWorkflow.from_file(yaml_file)
        """
        return cls._from_file(yaml_file, _ModelCronWorkflow)

    def get_workflow_link(self) -> str:
        """Returns the workflow link for the workflow."""
        assert self.workflows_service is not None, "Cannot fetch a cron workflow link without a service"
        assert self.name is not None, "Cannot fetch a cron workflow link without a cron workflow name"
        return self.workflows_service.get_cron_workflow_link(self.name)

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

api_version class-attribute instance-attribute

api_version = None

archive_logs class-attribute instance-attribute

archive_logs = None

arguments class-attribute instance-attribute

arguments = None

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact_repository_ref class-attribute instance-attribute

artifact_repository_ref = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

concurrency_policy class-attribute instance-attribute

concurrency_policy = None

creation_timestamp class-attribute instance-attribute

creation_timestamp = None

cron_status class-attribute instance-attribute

cron_status = None

cron_suspend class-attribute instance-attribute

cron_suspend = None

deletion_grace_period_seconds class-attribute instance-attribute

deletion_grace_period_seconds = None

deletion_timestamp class-attribute instance-attribute

deletion_timestamp = None

dns_config class-attribute instance-attribute

dns_config = None

dns_policy class-attribute instance-attribute

dns_policy = None

entrypoint class-attribute instance-attribute

entrypoint = None

executor class-attribute instance-attribute

executor = None

failed_jobs_history_limit class-attribute instance-attribute

failed_jobs_history_limit = None

finalizers class-attribute instance-attribute

finalizers = None

generate_name class-attribute instance-attribute

generate_name = None

generation class-attribute instance-attribute

generation = None

hooks class-attribute instance-attribute

hooks = None

host_aliases class-attribute instance-attribute

host_aliases = None

host_network class-attribute instance-attribute

host_network = None

image_pull_secrets class-attribute instance-attribute

image_pull_secrets = None

kind class-attribute instance-attribute

kind = None

labels class-attribute instance-attribute

labels = None

managed_fields class-attribute instance-attribute

managed_fields = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

namespace class-attribute instance-attribute

namespace = None

node_selector class-attribute instance-attribute

node_selector = None

on_exit class-attribute instance-attribute

on_exit = None

owner_references class-attribute instance-attribute

owner_references = None

parallelism class-attribute instance-attribute

parallelism = None

pod_disruption_budget class-attribute instance-attribute

pod_disruption_budget = None

pod_gc class-attribute instance-attribute

pod_gc = None

pod_metadata class-attribute instance-attribute

pod_metadata = None

pod_priority class-attribute instance-attribute

pod_priority = None

pod_priority_class_name class-attribute instance-attribute

pod_priority_class_name = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

resource_version class-attribute instance-attribute

resource_version = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

schedule class-attribute instance-attribute

schedule = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

schedules class-attribute instance-attribute

schedules = None

security_context class-attribute instance-attribute

security_context = None

self_link class-attribute instance-attribute

self_link = None

service_account_name class-attribute instance-attribute

service_account_name = None

shutdown class-attribute instance-attribute

shutdown = None

starting_deadline_seconds class-attribute instance-attribute

starting_deadline_seconds = None

status class-attribute instance-attribute

status = None

stop_strategy class-attribute instance-attribute

stop_strategy = None

successful_jobs_history_limit class-attribute instance-attribute

successful_jobs_history_limit = None

suspend class-attribute instance-attribute

suspend = None

synchronization class-attribute instance-attribute

synchronization = None

template_defaults class-attribute instance-attribute

template_defaults = None

templates class-attribute instance-attribute

templates = []

timezone class-attribute instance-attribute

timezone = None

tolerations class-attribute instance-attribute

tolerations = None

ttl_strategy class-attribute instance-attribute

ttl_strategy = None

uid class-attribute instance-attribute

uid = None

volume_claim_gc class-attribute instance-attribute

volume_claim_gc = None

volume_claim_templates class-attribute instance-attribute

volume_claim_templates = None

volumes class-attribute instance-attribute

volumes = None

when class-attribute instance-attribute

when = None

workflow_metadata class-attribute instance-attribute

workflow_metadata = None

workflow_template_ref class-attribute instance-attribute

workflow_template_ref = None

workflows_service class-attribute instance-attribute

workflows_service = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Container

The Container template type defines a container to run on Argo.

The container generally consists of running a Docker container remotely, which is configured via fields such as command (the command to run to start the container), args (arguments for the container), working_dir (for setting the active working directory relative to container execution), etc.

Source code in src/hera/workflows/container.py

class Container(
    EnvIOMixin,
    ContainerMixin,
    TemplateMixin,
    ResourceMixin,
    VolumeMountMixin,
    CallableTemplateMixin,
):
    """The Container template type defines a container to run on Argo.

    The container generally consists of running a Docker container remotely, which is configured via fields such as
    `command` (the command to run to start the container), `args` (arguments for the container), `working_dir` (for
    setting the active working directory relative to container execution), etc.
    """

    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    working_dir: Optional[str] = None

    def _build_container(self) -> _ModelContainer:
        """Builds the generated `Container` representation."""
        assert self.image
        return _ModelContainer(
            args=self.args,
            command=self.command,
            env=self._build_env(),
            env_from=self._build_env_from(),
            image=self.image,
            image_pull_policy=self._build_image_pull_policy(),
            lifecycle=self.lifecycle,
            liveness_probe=self.liveness_probe,
            ports=self.ports,
            readiness_probe=self.readiness_probe,
            resize_policy=self.resize_policy,
            resources=self._build_resources(),
            restart_policy=self.restart_policy,
            security_context=self.security_context,
            startup_probe=self.startup_probe,
            stdin=self.stdin,
            stdin_once=self.stdin_once,
            termination_message_path=self.termination_message_path,
            termination_message_policy=self.termination_message_policy,
            tty=self.tty,
            volume_devices=self.volume_devices,
            volume_mounts=self._build_volume_mounts(),
            working_dir=self.working_dir,
        )

    def _build_template(self) -> _ModelTemplate:
        """Builds the generated `Template` representation of the container."""
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container=self._build_container(),
            daemon=self.daemon,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
            volumes=self._build_volumes(),
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

args class-attribute instance-attribute

args = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

command class-attribute instance-attribute

command = None

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

DAG

A DAG template invocator is used to define Task dependencies as an acyclic graph.

DAG implements the contextmanager interface so allows usage of with, under which any hera.workflows.task.Task objects instantiated will be added to the DAG’s list of Tasks.

Examples:

>>> @script()
>>> def foo() -> None:
>>>     print(42)
>>>
>>> with DAG(...) as dag:
>>>     foo()

Source code in src/hera/workflows/dag.py

class DAG(
    IOMixin,
    TemplateMixin,
    CallableTemplateMixin,
    ContextMixin,
):
    """A DAG template invocator is used to define Task dependencies as an acyclic graph.

    DAG implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.task.Task` objects instantiated will be added to the DAG's list of Tasks.

    Examples:
        >>> @script()
        >>> def foo() -> None:
        >>>     print(42)
        >>>
        >>> with DAG(...) as dag:
        >>>     foo()
    """

    fail_fast: Optional[bool] = None
    target: Optional[str] = None
    tasks: List[Union[Task, DAGTask]] = []

    _node_names = PrivateAttr(default_factory=set)
    _current_task_depends: Set[str] = PrivateAttr(set())

    def _add_sub(self, node: Any):
        if not isinstance(node, Task):
            raise InvalidType(type(node))
        if node.name in self._node_names:
            raise NodeNameConflict(f"Found multiple Task nodes with name: {node.name}")
        self._node_names.add(node.name)
        self.tasks.append(node)

    def _build_template(self) -> _ModelTemplate:
        """Builds the auto-generated `Template` representation of the `DAG`."""
        tasks = []
        for task in self.tasks:
            if isinstance(task, Task):
                tasks.append(task._build_dag_task())
            else:
                tasks.append(task)
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            daemon=self.daemon,
            dag=_ModelDAGTemplate(fail_fast=self.fail_fast, target=self.target, tasks=tasks),
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

synchronization class-attribute instance-attribute

synchronization = None

target class-attribute instance-attribute

target = None

tasks class-attribute instance-attribute

tasks = []

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

ModelMapper

Source code in src/hera/workflows/_meta_mixins.py

class ModelMapper:
    def __init__(self, model_path: str, hera_builder: Optional[Callable] = None):
        self.model_path = []
        self.builder = hera_builder

        if not model_path:
            # Allows overriding parent attribute annotations to remove the mapping
            return

        self.model_path = model_path.split(".")
        curr_class: Type[BaseModel] = self._get_model_class()
        for key in self.model_path:
            fields = get_fields(curr_class)
            if key not in fields:
                raise ValueError(f"Model key '{key}' does not exist in class {curr_class}")
            curr_class = fields[key].outer_type_  # type: ignore

    @classmethod
    def _get_model_class(cls) -> Type[BaseModel]:
        raise NotImplementedError

    @classmethod
    def build_model(
        cls, hera_class: Type[ModelMapperMixin], hera_obj: ModelMapperMixin, model: TWorkflow
    ) -> TWorkflow:
        assert isinstance(hera_obj, ModelMapperMixin)

        for attr, annotation in hera_class._get_all_annotations().items():
            if mappers := get_annotated_metadata(annotation, ModelMapperMixin.ModelMapper):
                if len(mappers) != 1:
                    raise ValueError("Expected only one ModelMapper")

                # Value comes from builder function if it exists on hera_obj, otherwise directly from the attr
                value = (
                    getattr(hera_obj, mappers[0].builder.__name__)()
                    if mappers[0].builder is not None
                    else getattr(hera_obj, attr)
                )
                if value is not None:
                    _set_model_attr(model, mappers[0].model_path, value)

        return model

builder instance-attribute

builder = hera_builder

model_path instance-attribute

model_path = split('.')

build_model classmethod

build_model(hera_class, hera_obj, model)

Source code in src/hera/workflows/_meta_mixins.py

@classmethod
def build_model(
    cls, hera_class: Type[ModelMapperMixin], hera_obj: ModelMapperMixin, model: TWorkflow
) -> TWorkflow:
    assert isinstance(hera_obj, ModelMapperMixin)

    for attr, annotation in hera_class._get_all_annotations().items():
        if mappers := get_annotated_metadata(annotation, ModelMapperMixin.ModelMapper):
            if len(mappers) != 1:
                raise ValueError("Expected only one ModelMapper")

            # Value comes from builder function if it exists on hera_obj, otherwise directly from the attr
            value = (
                getattr(hera_obj, mappers[0].builder.__name__)()
                if mappers[0].builder is not None
                else getattr(hera_obj, attr)
            )
            if value is not None:
                _set_model_attr(model, mappers[0].model_path, value)

    return model

Script

A Script acts as a wrapper around a container.

In Hera this defaults to a “python:3.9” image specified by global_config.image, which runs a python source specified by Script.source.

Source code in src/hera/workflows/script.py

class Script(
    EnvIOMixin,
    CallableTemplateMixin,
    ContainerMixin,
    TemplateMixin,
    ResourceMixin,
    VolumeMountMixin,
):
    """A Script acts as a wrapper around a container.

    In Hera this defaults to a "python:3.9" image specified by global_config.image, which runs a python source
    specified by `Script.source`.
    """

    container_name: Optional[str] = None
    args: Optional[List[str]] = None
    command: Optional[List[str]] = None
    lifecycle: Optional[Lifecycle] = None
    security_context: Optional[SecurityContext] = None
    source: Optional[Union[Callable, str]] = None
    working_dir: Optional[str] = None
    add_cwd_to_sys_path: Optional[bool] = None
    constructor: Optional[Union[str, ScriptConstructor]] = None

    @validator("constructor", always=True)
    @classmethod
    def _set_constructor(cls, v):
        if v is None:
            # TODO: In the future we can insert
            # detection code here to determine
            # the best constructor to use.
            v = InlineScriptConstructor()
        if isinstance(v, ScriptConstructor):
            return v
        assert isinstance(v, str)
        if v.lower() == "inline":
            return InlineScriptConstructor()
        elif v.lower() == "runner":
            return RunnerScriptConstructor()
        raise ValueError(f"Unknown constructor {v}")

    @validator("command", always=True)
    @classmethod
    def _set_command(cls, v):
        return v or global_config.script_command

    @validator("add_cwd_to_sys_path", always=True)
    @classmethod
    def _set_add_cwd_to_sys_path(cls, v):
        if v is None:
            return True

    @root_validator
    @classmethod
    def _constructor_validate(cls, values):
        constructor = values.get("constructor")
        assert isinstance(constructor, ScriptConstructor)
        return constructor.transform_values(cls, values)

    def _build_template(self) -> _ModelTemplate:
        assert isinstance(self.constructor, ScriptConstructor)

        return self.constructor.transform_template_post_build(
            self,
            _ModelTemplate(
                active_deadline_seconds=self.active_deadline_seconds,
                affinity=self.affinity,
                archive_location=self.archive_location,
                automount_service_account_token=self.automount_service_account_token,
                daemon=self.daemon,
                executor=self.executor,
                fail_fast=self.fail_fast,
                host_aliases=self.host_aliases,
                init_containers=self._build_init_containers(),
                inputs=self._build_inputs(),
                memoize=self.memoize,
                metadata=self._build_metadata(),
                metrics=self._build_metrics(),
                name=self.name,
                node_selector=self.node_selector,
                outputs=self._build_outputs(),
                parallelism=self.parallelism,
                plugin=self.plugin,
                pod_spec_patch=self.pod_spec_patch,
                priority=self.priority,
                priority_class_name=self.priority_class_name,
                retry_strategy=self.retry_strategy,
                scheduler_name=self.scheduler_name,
                script=self._build_script(),
                security_context=self.pod_security_context,
                service_account_name=self.service_account_name,
                sidecars=self._build_sidecars(),
                synchronization=self.synchronization,
                timeout=self.timeout,
                tolerations=self.tolerations,
                volumes=self._build_volumes(),
            ),
        )

    def _build_script(self) -> _ModelScriptTemplate:
        assert isinstance(self.constructor, ScriptConstructor)
        if _output_annotations_used(cast(Callable, self.source)) and isinstance(
            self.constructor, RunnerScriptConstructor
        ):
            if not self.constructor.outputs_directory:
                self.constructor.outputs_directory = self.constructor.DEFAULT_HERA_OUTPUTS_DIRECTORY
            if self.constructor.volume_for_outputs is not None:
                if self.constructor.volume_for_outputs.mount_path is None:
                    self.constructor.volume_for_outputs.mount_path = self.constructor.outputs_directory
                self._create_hera_outputs_volume(self.constructor.volume_for_outputs)
        assert self.image
        return self.constructor.transform_script_template_post_build(
            self,
            _ModelScriptTemplate(
                args=self.args,
                command=self.command,
                env=self._build_env(),
                env_from=self._build_env_from(),
                image=self.image,
                # `image_pull_policy` in script wants a string not an `ImagePullPolicy` object
                image_pull_policy=self._build_image_pull_policy(),
                lifecycle=self.lifecycle,
                liveness_probe=self.liveness_probe,
                name=self.container_name,
                ports=self.ports,
                readiness_probe=self.readiness_probe,
                resize_policy=self.resize_policy,
                resources=self._build_resources(),
                restart_policy=self.restart_policy,
                security_context=self.security_context,
                source=self.constructor.generate_source(self),
                startup_probe=self.startup_probe,
                stdin=self.stdin,
                stdin_once=self.stdin_once,
                termination_message_path=self.termination_message_path,
                termination_message_policy=self.termination_message_policy,
                tty=self.tty,
                volume_devices=self.volume_devices,
                volume_mounts=self._build_volume_mounts(),
                working_dir=self.working_dir,
            ),
        )

    def _build_inputs(self) -> Optional[ModelInputs]:
        inputs = super()._build_inputs()
        func_parameters: List[Parameter] = []
        func_artifacts: List[Artifact] = []
        if callable(self.source):
            func_parameters, func_artifacts = _get_inputs_from_callable(self.source)

        return cast(Optional[ModelInputs], self._aggregate_callable_io(inputs, func_parameters, func_artifacts, False))

    def _build_outputs(self) -> Optional[ModelOutputs]:
        outputs = super()._build_outputs()

        if not callable(self.source):
            return outputs

        outputs_directory = None
        if isinstance(self.constructor, RunnerScriptConstructor):
            outputs_directory = self.constructor.outputs_directory or self.constructor.DEFAULT_HERA_OUTPUTS_DIRECTORY

        out_parameters, out_artifacts = _get_outputs_from_return_annotation(self.source, outputs_directory)
        func_parameters, func_artifacts = _get_outputs_from_parameter_annotations(self.source, outputs_directory)
        func_parameters.extend(out_parameters)
        func_artifacts.extend(out_artifacts)

        return cast(
            Optional[ModelOutputs], self._aggregate_callable_io(outputs, func_parameters, func_artifacts, True)
        )

    def _aggregate_callable_io(
        self,
        current_io: Optional[Union[ModelInputs, ModelOutputs]],
        func_parameters: List[Parameter],
        func_artifacts: List[Artifact],
        output: bool,
    ) -> Union[ModelOutputs, ModelInputs, None]:
        """Aggregate the Inputs/Outputs with parameters and artifacts extracted from a callable."""
        if not func_parameters and not func_artifacts:
            return current_io
        if current_io is None:
            if output:
                return ModelOutputs(
                    parameters=[p.as_output() for p in func_parameters] or None,
                    artifacts=[a._build_artifact() for a in func_artifacts] or None,
                )

            return ModelInputs(
                parameters=[p.as_input() for p in func_parameters] or None,
                artifacts=[a._build_artifact() for a in func_artifacts] or None,
            )

        seen_params = {p.name for p in current_io.parameters or []}
        seen_artifacts = {a.name for a in current_io.artifacts or []}

        for param in func_parameters:
            if param.name not in seen_params and param.name not in seen_artifacts:
                if current_io.parameters is None:
                    current_io.parameters = []
                if output:
                    current_io.parameters.append(param.as_output())
                else:
                    current_io.parameters.append(param.as_input())

        for artifact in func_artifacts:
            if artifact.name not in seen_artifacts:
                if current_io.artifacts is None:
                    current_io.artifacts = []
                current_io.artifacts.append(artifact._build_artifact())

        return current_io

    def _create_hera_outputs_volume(self, volume: _BaseVolume) -> None:
        """Add given volume to the script template for the automatic saving of the hera outputs."""
        assert isinstance(self.constructor, RunnerScriptConstructor)

        if self.volumes is None:
            self.volumes = []
        elif isinstance(self.volumes, Sequence):
            self.volumes = list(self.volumes)
        elif not isinstance(self.volumes, list):
            self.volumes = [self.volumes]

        if volume not in self.volumes:
            self.volumes.append(volume)

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

add_cwd_to_sys_path class-attribute instance-attribute

add_cwd_to_sys_path = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

args class-attribute instance-attribute

args = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

command class-attribute instance-attribute

command = None

constructor class-attribute instance-attribute

constructor = None

container_name class-attribute instance-attribute

container_name = None

daemon class-attribute instance-attribute

daemon = None

env class-attribute instance-attribute

env = None

env_from class-attribute instance-attribute

env_from = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

image class-attribute instance-attribute

image = None

image_pull_policy class-attribute instance-attribute

image_pull_policy = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

lifecycle class-attribute instance-attribute

lifecycle = None

liveness_probe class-attribute instance-attribute

liveness_probe = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

ports class-attribute instance-attribute

ports = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

readiness_probe class-attribute instance-attribute

readiness_probe = None

resize_policy class-attribute instance-attribute

resize_policy = None

resources class-attribute instance-attribute

resources = None

restart_policy class-attribute instance-attribute

restart_policy = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

security_context class-attribute instance-attribute

security_context = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

source class-attribute instance-attribute

source = None

startup_probe class-attribute instance-attribute

startup_probe = None

stdin class-attribute instance-attribute

stdin = None

stdin_once class-attribute instance-attribute

stdin_once = None

synchronization class-attribute instance-attribute

synchronization = None

termination_message_path class-attribute instance-attribute

termination_message_path = None

termination_message_policy class-attribute instance-attribute

termination_message_policy = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

tty class-attribute instance-attribute

tty = None

volume_devices class-attribute instance-attribute

volume_devices = None

volume_mounts class-attribute instance-attribute

volume_mounts = None

volumes class-attribute instance-attribute

volumes = None

working_dir class-attribute instance-attribute

working_dir = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

Steps

A Steps template invocator is used to define a sequence of steps which can run sequentially or in parallel.

Steps implements the contextmanager interface so allows usage of with, under which any hera.workflows.steps.Step objects instantiated will be added to the Steps’ list of sub_steps.

• Step and Parallel objects initialised within a Steps context will be added to the list of sub_steps in the order they are initialised.
• All Step objects initialised within a Parallel context will run in parallel.

Source code in src/hera/workflows/steps.py

class Steps(
    IOMixin,
    TemplateMixin,
    CallableTemplateMixin,
    ContextMixin,
):
    """A Steps template invocator is used to define a sequence of steps which can run sequentially or in parallel.

    Steps implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.steps.Step` objects instantiated will be added to the Steps' list of sub_steps.

    * Step and Parallel objects initialised within a Steps context will be added to the list of sub_steps
    in the order they are initialised.
    * All Step objects initialised within a Parallel context will run in parallel.
    """

    _node_names = PrivateAttr(default_factory=set)

    sub_steps: List[
        Union[
            Step,
            Parallel,
            List[Step],
            _ModelWorkflowStep,
            List[_ModelWorkflowStep],
        ]
    ] = []

    def _build_steps(self) -> Optional[List[ParallelSteps]]:
        steps = []
        for workflow_step in self.sub_steps:
            if isinstance(workflow_step, Steppable):
                steps.append(ParallelSteps(__root__=workflow_step._build_step()))
            elif isinstance(workflow_step, _ModelWorkflowStep):
                steps.append(ParallelSteps(__root__=[workflow_step]))
            elif isinstance(workflow_step, List):
                substeps = []
                for s in workflow_step:
                    if isinstance(s, Step):
                        substeps.append(s._build_as_workflow_step())
                    elif isinstance(s, _ModelWorkflowStep):
                        substeps.append(s)
                    else:
                        raise InvalidType(type(s))
                steps.append(ParallelSteps(__root__=substeps))
            else:
                raise InvalidType(type(workflow_step))

        return steps or None

    def _add_sub(self, node: Any):
        if not isinstance(node, (Step, Parallel)):
            raise InvalidType(type(node))
        if isinstance(node, Step):
            if node.name in self._node_names:
                raise NodeNameConflict(f"Found multiple Step nodes with name: {node.name}")
            self._node_names.add(node.name)
        if isinstance(node, Parallel):
            node._node_names = self._node_names
        self.sub_steps.append(node)

    def parallel(self) -> Parallel:
        """Returns a Parallel object which can be used in a sub-context manager."""
        return Parallel()

    def _build_template(self) -> _ModelTemplate:
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            container=None,
            container_set=None,
            daemon=self.daemon,
            dag=None,
            data=None,
            executor=self.executor,
            fail_fast=self.fail_fast,
            http=None,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            resource=None,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            script=None,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            steps=self._build_steps(),
            suspend=None,
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

sub_steps class-attribute instance-attribute

sub_steps = []

synchronization class-attribute instance-attribute

synchronization = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

parallel

parallel()

Returns a Parallel object which can be used in a sub-context manager.

Source code in src/hera/workflows/steps.py

def parallel(self) -> Parallel:
    """Returns a Parallel object which can be used in a sub-context manager."""
    return Parallel()

add_template_set

add_template_set(template_set)

Add the templates stored in the template_set to this Workflow.

Source code in src/hera/workflows/workflow.py

def add_template_set(self, template_set: TemplateSet) -> None:
    """Add the templates stored in the template_set to this Workflow."""
    for template in template_set.templates:
        self._add_sub(template)

build

build()

Builds the CronWorkflow and its components into an Argo schema CronWorkflow object.

Source code in src/hera/workflows/cron_workflow.py

def build(self) -> TWorkflow:
    """Builds the CronWorkflow and its components into an Argo schema CronWorkflow object."""
    self = self._dispatch_hooks()

    model_workflow = cast(_ModelWorkflow, super().build())
    model_cron_workflow = _ModelCronWorkflow(
        metadata=model_workflow.metadata,
        spec=CronWorkflowSpec(
            workflow_spec=model_workflow.spec,
        ),
    )

    return _CronWorkflowModelMapper.build_model(CronWorkflow, self, model_cron_workflow)

container

container(**container_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Container)  # type: ignore
def container(self, **container_kwargs) -> Callable:
    self._check_if_enabled("container")
    from hera.workflows.container import Container

    def container_decorator(func: Callable[FuncIns, FuncR]) -> Callable:
        name = container_kwargs.pop("name", func.__name__.replace("_", "-"))

        signature = inspect.signature(func)
        func_inputs = signature.parameters
        inputs = []
        if len(func_inputs) >= 1:
            input_arg = list(func_inputs.values())[0].annotation
            if issubclass(input_arg, (InputV1, InputV2)):
                inputs = input_arg._get_inputs(add_missing_path=True)

        func_return = signature.return_annotation
        outputs = []
        if func_return and issubclass(func_return, (OutputV1, OutputV2)):
            outputs = func_return._get_outputs(add_missing_path=True)

        # Open context to add `Container` object automatically
        with self:
            container_template = Container(
                name=name,
                inputs=inputs,
                outputs=outputs,
                **container_kwargs,
            )

        @functools.wraps(func)
        def container_call_wrapper(*args, **kwargs) -> Union[FuncR, Step, Task, None]:
            """Invokes a CallableTemplateMixin's `__call__` method using the given SubNode (Step or Task) args/kwargs."""
            if _context.declaring:
                subnode_name = kwargs.pop("name", None)
                if not subnode_name:
                    try:
                        # ignore decorator function assignment
                        subnode_name = varname()
                    except ImproperUseError:
                        # Template is being used without variable assignment (so use function name or provided name)
                        subnode_name = container_template.name  # type: ignore

                    assert isinstance(subnode_name, str)
                    subnode_name = subnode_name.replace("_", "-")

                return self._create_subnode(subnode_name, func, container_template, *args, **kwargs)

            if _context.pieces:
                return container_template.__call__(*args, **kwargs)
            return func(*args)

        # Set the template name to the inferred name
        container_call_wrapper.template_name = name  # type: ignore

        return container_call_wrapper

    return container_decorator

create

create()

Creates the CronWorkflow on the Argo cluster.

Source code in src/hera/workflows/cron_workflow.py

def create(self) -> TWorkflow:  # type: ignore
    """Creates the CronWorkflow on the Argo cluster."""
    assert self.workflows_service, "workflow service not initialized"
    assert self.namespace, "workflow namespace not defined"

    wf = self.workflows_service.create_cron_workflow(
        CreateCronWorkflowRequest(cron_workflow=self.build()),  # type: ignore
        namespace=self.namespace,
    )
    # set the name on the object so that we can do a get/update later
    self.name = wf.metadata.name
    return wf

dag

dag(**dag_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(DAG)  # type: ignore
def dag(self, **dag_kwargs) -> Callable:
    self._check_if_enabled("dag")

    from hera.workflows.dag import DAG

    return self._construct_invocator_decorator(DAG, **dag_kwargs)

from_dict classmethod

from_dict(model_dict)

Create a CronWorkflow from a CronWorkflow contained in a dict.

Examples:

>>> my_cron_workflow = CronWorkflow(name="my-cron-wf")
>>> my_cron_workflow == CronWorkflow.from_dict(my_cron_workflow.to_dict())
True

Source code in src/hera/workflows/cron_workflow.py

@classmethod
def from_dict(cls, model_dict: Dict) -> ModelMapperMixin:
    """Create a CronWorkflow from a CronWorkflow contained in a dict.

    Examples:
        >>> my_cron_workflow = CronWorkflow(name="my-cron-wf")
        >>> my_cron_workflow == CronWorkflow.from_dict(my_cron_workflow.to_dict())
        True
    """
    return cls._from_dict(model_dict, _ModelCronWorkflow)

from_file classmethod

from_file(yaml_file)

Create a CronWorkflow from a CronWorkflow contained in a YAML file.

Examples:

>>> yaml_file = Path(...)
>>> my_workflow_template = CronWorkflow.from_file(yaml_file)

Source code in src/hera/workflows/cron_workflow.py

@classmethod
def from_file(cls, yaml_file: Union[Path, str]) -> ModelMapperMixin:
    """Create a CronWorkflow from a CronWorkflow contained in a YAML file.

    Examples:
        >>> yaml_file = Path(...)
        >>> my_workflow_template = CronWorkflow.from_file(yaml_file)
    """
    return cls._from_file(yaml_file, _ModelCronWorkflow)

from_yaml classmethod

from_yaml(yaml_str)

Create a CronWorkflow from a CronWorkflow contained in a YAML string.

Examples:

>>> my_cron_workflow = CronWorkflow.from_yaml(yaml_str)

Source code in src/hera/workflows/cron_workflow.py

@classmethod
def from_yaml(cls, yaml_str: str) -> ModelMapperMixin:
    """Create a CronWorkflow from a CronWorkflow contained in a YAML string.

    Examples:
        >>> my_cron_workflow = CronWorkflow.from_yaml(yaml_str)
    """
    return cls._from_yaml(yaml_str, _ModelCronWorkflow)

get

get()

Attempts to get a cron workflow based on the parameters of this template e.g. name + namespace.

Source code in src/hera/workflows/cron_workflow.py

def get(self) -> TWorkflow:
    """Attempts to get a cron workflow based on the parameters of this template e.g. name + namespace."""
    assert self.workflows_service, "workflow service not initialized"
    assert self.namespace, "workflow namespace not defined"
    assert self.name, "workflow name not defined"
    return self.workflows_service.get_cron_workflow(name=self.name, namespace=self.namespace)

get_parameter

get_parameter(name)

Attempts to find and return a Parameter of the specified name.

Source code in src/hera/workflows/workflow.py

def get_parameter(self, name: str) -> Parameter:
    """Attempts to find and return a `Parameter` of the specified name."""
    arguments = self._build_arguments()
    if arguments is None:
        raise KeyError("Workflow has no arguments set")
    if arguments.parameters is None:
        raise KeyError("Workflow has no argument parameters set")

    parameters = arguments.parameters
    if next((p for p in parameters if p.name == name), None) is None:
        raise KeyError(f"`{name}` is not a valid workflow parameter")
    return Parameter(name=name, value=f"{{{{workflow.parameters.{name}}}}}")

get_workflow_link

get_workflow_link()

Returns the workflow link for the workflow.

Source code in src/hera/workflows/cron_workflow.py

def get_workflow_link(self) -> str:
    """Returns the workflow link for the workflow."""
    assert self.workflows_service is not None, "Cannot fetch a cron workflow link without a service"
    assert self.name is not None, "Cannot fetch a cron workflow link without a cron workflow name"
    return self.workflows_service.get_cron_workflow_link(self.name)

lint

lint()

Lints the CronWorkflow using the Argo cluster.

Source code in src/hera/workflows/cron_workflow.py

def lint(self) -> TWorkflow:
    """Lints the CronWorkflow using the Argo cluster."""
    assert self.workflows_service, "workflow service not initialized"
    assert self.namespace, "workflow namespace not defined"
    return self.workflows_service.lint_cron_workflow(
        LintCronWorkflowRequest(cron_workflow=self.build()),  # type: ignore
        namespace=self.namespace,
    )

script

script(**script_kwargs)

A decorator that wraps a function into a Script object.

Using this decorator users can define a function that will be executed as a script in a container. Once the Script is returned users can use it as they generally use a Script e.g. as a callable inside a DAG or Steps. Note that invoking the function will result in the template associated with the script to be added to the workflow context, so users do not have to worry about that.

Parameters

**script_kwargs Keyword arguments to be passed to the Script object.

Returns:

Callable Function wrapper that holds a Script and allows the function to be called to create a Step or Task if in a Steps or DAG context.

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Script)  # type: ignore
def script(self, **script_kwargs) -> Callable:
    """A decorator that wraps a function into a Script object.

    Using this decorator users can define a function that will be executed as a script in a container. Once the
    `Script` is returned users can use it as they generally use a `Script` e.g. as a callable inside a DAG or Steps.
    Note that invoking the function will result in the template associated with the script to be added to the
    workflow context, so users do not have to worry about that.

    Parameters
    ----------
    **script_kwargs
        Keyword arguments to be passed to the Script object.

    Returns:
    -------
    Callable
        Function wrapper that holds a `Script` and allows the function to be called to create a Step or Task if
        in a Steps or DAG context.
    """
    self._check_if_enabled("script")

    from hera.workflows.script import RunnerScriptConstructor, Script

    def script_decorator(func: Callable[FuncIns, FuncR]) -> Callable:
        """The internal decorator function.

        Parameters
        ----------
        func: Callable
            Function to wrap.

        Returns:
        -------
        Callable
            Callable that calls the `Script` object `__call__` method when in a Steps or DAG context,
            otherwise calls function itself.
        """
        # instance methods are wrapped in `staticmethod`. Hera can capture that type and extract the underlying
        # function for remote submission since it does not depend on any class or instance attributes, so it is
        # submittable
        if isinstance(func, staticmethod):
            source: Callable = func.__func__
        else:
            source = func

        # take the client-provided `name` if it is submitted, pop the name for otherwise there will be two
        # kwargs called `name`
        # otherwise populate the `name` from the function name
        name = script_kwargs.pop("name", source.__name__.replace("_", "-"))

        if "constructor" not in script_kwargs and "constructor" not in global_config._get_class_defaults(Script):
            script_kwargs["constructor"] = RunnerScriptConstructor()

        signature = inspect.signature(func)
        func_inputs = signature.parameters
        if len(func_inputs) > 1:
            raise SyntaxError("script decorator must be used with a single `Input` arg, or no args.")

        if len(func_inputs) == 1:
            func_input = list(func_inputs.values())[0].annotation
            if not issubclass(func_input, (InputV1, InputV2)):
                raise SyntaxError("script decorator must be used with a single `Input` arg, or no args.")

        # Open (Workflow) context to add `Script` object automatically
        with self:
            script_template = Script(name=name, source=source, **script_kwargs)

        if not isinstance(script_template.constructor, RunnerScriptConstructor):
            raise ValueError(f"Script '{name}' must use RunnerScriptConstructor")

        @functools.wraps(func)
        def script_call_wrapper(*args, **kwargs) -> Union[FuncR, Step, Task, None]:
            """Invokes a CallableTemplateMixin's `__call__` method using the given SubNode (Step or Task) args/kwargs."""
            if _context.declaring:
                subnode_name = kwargs.pop("name", None)
                if not subnode_name:
                    try:
                        # ignore decorator function assignment
                        subnode_name = varname()
                    except ImproperUseError:
                        # Template is being used without variable assignment (so use function name or provided name)
                        subnode_name = script_template.name  # type: ignore

                    assert isinstance(subnode_name, str)
                    subnode_name = subnode_name.replace("_", "-")

                return self._create_subnode(subnode_name, func, script_template, *args, **kwargs)

            if _context.pieces:
                return script_template.__call__(*args, **kwargs)

            return func(*args)

        # Set the wrapped function to the original function so that we can use it later
        script_call_wrapper.wrapped_function = func  # type: ignore
        # Set the template name to the inferred name
        script_call_wrapper.template_name = name  # type: ignore

        return script_call_wrapper

    return script_decorator

set_entrypoint

set_entrypoint(func)

Decorator function to set entrypoint.

Source code in src/hera/workflows/workflow.py

def set_entrypoint(self, func: Callable[P, T]) -> Callable[P, T]:
    """Decorator function to set entrypoint."""
    if not hasattr(func, "template_name"):
        raise SyntaxError("`set_entrypoint` decorator must be above template decorator")

    if self.entrypoint is not None:
        if self.entrypoint == func.template_name:
            return func

        logging.warning(f"entrypoint is being reassigned from {self.entrypoint} to {func.template_name}")

    self.entrypoint = func.template_name  # type: ignore
    return func

steps

steps(**steps_kwargs)

Source code in src/hera/workflows/_meta_mixins.py

@_add_type_hints(Steps)  # type: ignore
def steps(self, **steps_kwargs) -> Callable:
    self._check_if_enabled("steps")

    from hera.workflows.steps import Steps

    return self._construct_invocator_decorator(Steps, **steps_kwargs)

to_dict

to_dict()

Builds the Workflow as an Argo schema Workflow object and returns it as a dictionary.

Source code in src/hera/workflows/workflow.py

def to_dict(self) -> Any:
    """Builds the Workflow as an Argo schema Workflow object and returns it as a dictionary."""
    return self.build().dict(exclude_none=True, by_alias=True)

to_file

to_file(output_directory='.', name='', *args, **kwargs)

Writes the Workflow as an Argo schema Workflow object to a YAML file and returns the path to the file.

Parameters:

Name	Type	Description	Default
output_directory	Union[Path, str]	The directory to write the file to. Defaults to the current working directory.	'.'
name	str	The name of the file to write without the file extension. Defaults to the Workflow’s name or a generated name.	''
*args		Additional arguments to pass to yaml.dump.	()
**kwargs		Additional keyword arguments to pass to yaml.dump.	{}

Source code in src/hera/workflows/workflow.py

def to_file(self, output_directory: Union[Path, str] = ".", name: str = "", *args, **kwargs) -> Path:
    """Writes the Workflow as an Argo schema Workflow object to a YAML file and returns the path to the file.

    Args:
        output_directory: The directory to write the file to. Defaults to the current working directory.
        name: The name of the file to write without the file extension.  Defaults to the Workflow's name or a
              generated name.
        *args: Additional arguments to pass to `yaml.dump`.
        **kwargs: Additional keyword arguments to pass to `yaml.dump`.
    """
    workflow_name = self.name or (self.generate_name or "workflow").rstrip("-")
    name = name or workflow_name
    output_directory = Path(output_directory)
    output_path = Path(output_directory) / f"{name}.yaml"
    output_directory.mkdir(parents=True, exist_ok=True)
    output_path.write_text(self.to_yaml(*args, **kwargs))
    return output_path.absolute()

to_yaml

to_yaml(*args, **kwargs)

Builds the Workflow as an Argo schema Workflow object and returns it as yaml string.

Source code in src/hera/workflows/workflow.py

def to_yaml(self, *args, **kwargs) -> str:
    """Builds the Workflow as an Argo schema Workflow object and returns it as yaml string."""

    def human_readable_ordering(kv: tuple) -> int:
        """Key ordering function for ordering in a more human-readable fashion.

        Ordering is:
        1. "name" keys always first (if present)
        2. Primitives (not dicts/lists)
        3. lists
        4. dict
        """
        k, v = kv
        if k == "name" and isinstance(v, str):
            return 0
        if not isinstance(v, (dict, list)):
            return 1
        if isinstance(v, list):
            return 2
        return 3

    def order_dict(d: dict) -> dict[str, Any]:
        """Recursively orders `d` by the custom_ordering function by inserting them into a copy of the dict in order."""
        d_copy: dict[str, Any] = dict()
        for k, v in sorted(d.items(), key=lambda x: (human_readable_ordering(x), x[0])):
            if isinstance(v, dict):
                d_copy[k] = order_dict(v)
            elif isinstance(v, list):
                if v and isinstance(v[0], dict):
                    d_copy[k] = [order_dict(i) if isinstance(i, dict) else i for i in v]
                elif v and isinstance(v[0], list):
                    d_copy[k] = [[order_dict(i) for i in sublist] for sublist in v]
                else:
                    d_copy[k] = v
            else:
                d_copy[k] = v
        return d_copy

    human_ordered_dict = order_dict(self.to_dict())
    return _yaml.dump(human_ordered_dict, *args, **kwargs)

update

update()

Attempts to perform a workflow template update based on the parameters of this template.

Note that this creates the template if it does not exist. In addition, this performs a get prior to updating to get the resource version to update in the first place. If you know the template does not exist ahead of time, it is more efficient to use create() directly to avoid one round trip.

Source code in src/hera/workflows/cron_workflow.py

def update(self) -> TWorkflow:
    """Attempts to perform a workflow template update based on the parameters of this template.

    Note that this creates the template if it does not exist. In addition, this performs
    a get prior to updating to get the resource version to update in the first place. If you know the template
    does not exist ahead of time, it is more efficient to use `create()` directly to avoid one round trip.
    """
    assert self.workflows_service, "workflow service not initialized"
    assert self.namespace, "workflow namespace not defined"
    assert self.name, "workflow name not defined"
    # we always need to do a get prior to updating to get the resource version to update in the first place
    # https://github.com/argoproj/argo-workflows/pull/5465#discussion_r597797052

    template = self.build()
    try:
        curr = self.get()
        template.metadata.resource_version = curr.metadata.resource_version
    except NotFound:
        return self.create()
    return self.workflows_service.update_cron_workflow(
        self.name,
        UpdateCronWorkflowRequest(cron_workflow=template),  # type: ignore
        namespace=self.namespace,
    )

wait

wait(poll_interval=5)

Waits for the Workflow to complete execution.

Parameters

poll_interval: int = 5 The interval in seconds to poll the workflow status.

Source code in src/hera/workflows/workflow.py

def wait(self, poll_interval: int = 5) -> TWorkflow:
    """Waits for the Workflow to complete execution.

    Parameters
    ----------
    poll_interval: int = 5
        The interval in seconds to poll the workflow status.
    """
    assert self.workflows_service is not None, "workflow service not initialized"
    assert self.namespace is not None, "workflow namespace not defined"
    assert self.name is not None, "workflow name not defined"

    # here we use the sleep interval to wait for the workflow post creation. This is to address a potential
    # race conditions such as:
    # 1. Argo server says "workflow was accepted" but the workflow is not yet created
    # 2. Hera wants to verify the status of the workflow, but it's not yet defined because it's not created
    # 3. Argo finally creates the workflow
    # 4. Hera throws an `AssertionError` because the phase assertion fails
    time.sleep(poll_interval)
    wf = self.workflows_service.get_workflow(self.name, namespace=self.namespace)
    assert wf.metadata.name is not None, f"workflow name not defined for workflow {self.name}"

    assert wf.status is not None, f"workflow status not defined for workflow {wf.metadata.name}"
    assert wf.status.phase is not None, f"workflow phase not defined for workflow status {wf.status}"
    status = WorkflowStatus.from_argo_status(wf.status.phase)

    # keep polling for workflow status until completed, at the interval dictated by the user
    while status == WorkflowStatus.running:
        time.sleep(poll_interval)
        wf = self.workflows_service.get_workflow(wf.metadata.name, namespace=self.namespace)
        assert wf.status is not None, f"workflow status not defined for workflow {wf.metadata.name}"
        assert wf.status.phase is not None, f"workflow phase not defined for workflow status {wf.status}"
        status = WorkflowStatus.from_argo_status(wf.status.phase)
    return wf

DAG

A DAG template invocator is used to define Task dependencies as an acyclic graph.

DAG implements the contextmanager interface so allows usage of with, under which any hera.workflows.task.Task objects instantiated will be added to the DAG’s list of Tasks.

Examples:

>>> @script()
>>> def foo() -> None:
>>>     print(42)
>>>
>>> with DAG(...) as dag:
>>>     foo()

Source code in src/hera/workflows/dag.py

class DAG(
    IOMixin,
    TemplateMixin,
    CallableTemplateMixin,
    ContextMixin,
):
    """A DAG template invocator is used to define Task dependencies as an acyclic graph.

    DAG implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.task.Task` objects instantiated will be added to the DAG's list of Tasks.

    Examples:
        >>> @script()
        >>> def foo() -> None:
        >>>     print(42)
        >>>
        >>> with DAG(...) as dag:
        >>>     foo()
    """

    fail_fast: Optional[bool] = None
    target: Optional[str] = None
    tasks: List[Union[Task, DAGTask]] = []

    _node_names = PrivateAttr(default_factory=set)
    _current_task_depends: Set[str] = PrivateAttr(set())

    def _add_sub(self, node: Any):
        if not isinstance(node, Task):
            raise InvalidType(type(node))
        if node.name in self._node_names:
            raise NodeNameConflict(f"Found multiple Task nodes with name: {node.name}")
        self._node_names.add(node.name)
        self.tasks.append(node)

    def _build_template(self) -> _ModelTemplate:
        """Builds the auto-generated `Template` representation of the `DAG`."""
        tasks = []
        for task in self.tasks:
            if isinstance(task, Task):
                tasks.append(task._build_dag_task())
            else:
                tasks.append(task)
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            daemon=self.daemon,
            dag=_ModelDAGTemplate(fail_fast=self.fail_fast, target=self.target, tasks=tasks),
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

synchronization class-attribute instance-attribute

synchronization = None

target class-attribute instance-attribute

target = None

tasks class-attribute instance-attribute

tasks = []

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

Data

Data implements the Argo data template representation.

Data can be used to indicate that some data, identified by a source, should be processed via the specified transformations. The transformations field can be either expressed via a pure str or via a hera.expr, which transpiles the expression into a statement that can be processed by Argo.

Source code in src/hera/workflows/data.py

class Data(TemplateMixin, IOMixin, CallableTemplateMixin):
    """`Data` implements the Argo data template representation.

    Data can be used to indicate that some data, identified by a `source`, should be processed via the specified
    `transformations`. The `transformations` field can be either expressed via a pure `str` or via a `hera.expr`,
    which transpiles the expression into a statement that can be processed by Argo.
    """

    source: Union[m.DataSource, m.ArtifactPaths, Artifact]
    transformations: List[Union[str, Node]] = []

    def _build_source(self) -> m.DataSource:
        """Builds the generated `DataSource`."""
        if isinstance(self.source, m.DataSource):
            return self.source
        elif isinstance(self.source, m.ArtifactPaths):
            return m.DataSource(artifact_paths=self.source)
        return m.DataSource(artifact_paths=self.source._build_artifact_paths())

    def _build_data(self) -> m.Data:
        """Builds the generated `Data` template."""
        return m.Data(
            source=self._build_source(),
            transformation=list(map(lambda expr: m.TransformationStep(expression=str(expr)), self.transformations)),
        )

    def _build_template(self) -> m.Template:
        """Builds the generated `Template` from the fields of `Data`."""
        return m.Template(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            data=self._build_data(),
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            outputs=self._build_outputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            name=self.name,
            node_selector=self.node_selector,
            plugin=self.plugin,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

source instance-attribute

source

synchronization class-attribute instance-attribute

synchronization = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

transformations class-attribute instance-attribute

transformations = []

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

DownwardAPIVolume

Representation of a volume passed via the downward API.

Source code in src/hera/workflows/volume.py

class DownwardAPIVolume(_BaseVolume, _ModelDownwardAPIVolumeSource):
    """Representation of a volume passed via the downward API."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            downward_api=_ModelDownwardAPIVolumeSource(default_mode=self.default_mode, items=self.items),
        )

default_mode class-attribute instance-attribute

default_mode = None

items class-attribute instance-attribute

items = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

EmptyDirVolume

Representation of an empty dir volume from K8s.

Source code in src/hera/workflows/volume.py

class EmptyDirVolume(_BaseVolume, _ModelEmptyDirVolumeSource):
    """Representation of an empty dir volume from K8s."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name, empty_dir=_ModelEmptyDirVolumeSource(medium=self.medium, size_limit=self.size_limit)
        )

medium class-attribute instance-attribute

medium = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

size_limit class-attribute instance-attribute

size_limit = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Env

A variable implementation that can expose a plain value or value from input as an env variable.

Source code in src/hera/workflows/env.py

class Env(_BaseEnv):
    """A variable implementation that can expose a plain `value` or `value from input` as an env variable."""

    value: Optional[Any] = None
    """the value of the environment variable"""

    value_from_input: Optional[Union[str, Parameter]] = None
    """an optional `str` or `Parameter` representation of the origin of the environment variable value"""

    @staticmethod
    def _sanitise_param_for_argo(v: str) -> str:
        """Sanitizes the given `v` value into one that satisfies Argo's parameter rules.

        Argo has some strict parameter validation. To satisfy, we replace all ._ with a dash,
        take only first 32 characters from a-zA-Z0-9-, and append md5 digest of the original string.
        """
        # NOTE move this to some general purpose utils?
        replaced_dashes = v.translate(str.maketrans({e: "-" for e in "_."}))  # type: ignore
        legit_set = string.ascii_letters + string.digits + "-"
        legit_prefix = "".join(islice((c for c in replaced_dashes if c in legit_set), 32))
        hash_suffix = hashlib.md5(v.encode("utf-8")).hexdigest()
        return f"{legit_prefix}-{hash_suffix}"

    @root_validator(pre=True)
    @classmethod
    def _check_values(cls, values):
        """Validates that only one of `value` or `value_from_input` is specified."""
        if values.get("value") is not None and values.get("value_from_input") is not None:
            raise ValueError("cannot specify both `value` and `value_from_input`")

        return values

    @property
    def param_name(self) -> str:
        """Returns the parameter name of the environment variable, conditioned on the use of `value_from_input`."""
        if not self.value_from_input:
            raise ValueError(
                "Unexpected use of `param_name` - without `value_from_input`, no param should be generated"
            )
        return Env._sanitise_param_for_argo(self.name)

    def build(self) -> _ModelEnvVar:
        """Constructs and returns the Argo environment specification."""
        if self.value_from_input is not None:
            self.value = f"{{{{inputs.parameters.{self.param_name}}}}}"
        elif isinstance(self.value, str):
            self.value = self.value
        else:
            self.value = json.dumps(self.value)
        return _ModelEnvVar(name=self.name, value=self.value)

name instance-attribute

name

the name of the environment variable. This is universally required irrespective of the type of env variable

param_name property

param_name

Returns the parameter name of the environment variable, conditioned on the use of value_from_input.

value class-attribute instance-attribute

value = None

the value of the environment variable

value_from_input class-attribute instance-attribute

value_from_input = None

an optional str or Parameter representation of the origin of the environment variable value

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Constructs and returns the Argo environment specification.

Source code in src/hera/workflows/env.py

def build(self) -> _ModelEnvVar:
    """Constructs and returns the Argo environment specification."""
    if self.value_from_input is not None:
        self.value = f"{{{{inputs.parameters.{self.param_name}}}}}"
    elif isinstance(self.value, str):
        self.value = self.value
    else:
        self.value = json.dumps(self.value)
    return _ModelEnvVar(name=self.name, value=self.value)

EphemeralVolume

Representation of a volume that uses ephemeral storage shared with the K8s node a pod is scheduled on.

Source code in src/hera/workflows/volume.py

class EphemeralVolume(_BaseVolume, _ModelEphemeralVolumeSource):
    """Representation of a volume that uses ephemeral storage shared with the K8s node a pod is scheduled on."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name, ephemeral=_ModelEphemeralVolumeSource(volume_claim_template=self.volume_claim_template)
        )

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

volume_claim_template class-attribute instance-attribute

volume_claim_template = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

ExistingVolume

ExistingVolume is a representation of an existing volume in K8s.

The existing volume is mounted based on the supplied claim name. This tells K8s that the specified persistent volume claim should be used to mount a volume to a pod.

Source code in src/hera/workflows/volume.py

class ExistingVolume(_BaseVolume, _ModelPersistentVolumeClaimVolumeSource):
    """`ExistingVolume` is a representation of an existing volume in K8s.

    The existing volume is mounted based on the supplied claim name. This tells K8s that the specified persistent
    volume claim should be used to mount a volume to a pod.
    """

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            persistent_volume_claim=_ModelPersistentVolumeClaimVolumeSource(
                claim_name=self.claim_name, read_only=self.read_only
            ),
        )

claim_name instance-attribute

claim_name

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

FCVolume

An FV volume representation.

Source code in src/hera/workflows/volume.py

class FCVolume(_BaseVolume, _ModelFCVolumeSource):
    """An FV volume representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            fc=_ModelFCVolumeSource(
                fs_type=self.fs_type,
                lun=self.lun,
                read_only=self.read_only,
                target_ww_ns=self.target_ww_ns,
                wwids=self.wwids,
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

lun class-attribute instance-attribute

lun = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

target_ww_ns class-attribute instance-attribute

target_ww_ns = None

wwids class-attribute instance-attribute

wwids = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

FieldEnv

FieldEnv is an environment variable whose origin is in a field specification.

The field path specification points to a particular field within the workflow/container YAML specification. For instance, if there’s a YAML that has 3 fields like so

name: abc
spec:
  a: 42

then a reference to the field a must be encoded as spec.a in order for the value of 42 to be extracted and set as an environment variable.

Source code in src/hera/workflows/env.py

class FieldEnv(_BaseEnv):
    """`FieldEnv` is an environment variable whose origin is in a field specification.

    The field path specification points to a particular field within the workflow/container YAML specification. For
    instance, if there's a YAML that has 3 fields like so
    ```
    name: abc
    spec:
      a: 42
    ```
    then a reference to the field a must be encoded as `spec.a` in order for the value of `42` to be extracted and set
    as an environment variable.
    """

    field_path: str
    """the path to the field whose value should be extracted into an environment variable"""

    api_version: Optional[str] = None
    """optionally, an API version specification. This defaults to the Hera global config `api_version`"""

    @validator("api_version")
    @classmethod
    def _check_api_version(cls, v):
        """Checks whether the `api_version` field is set and uses the global config `api_version` if not."""
        if v is None:
            return global_config.api_version
        return v

    def build(self) -> _ModelEnvVar:
        """Constructs and returns the Argo environment specification."""
        return _ModelEnvVar(
            name=self.name,
            value_from=_ModelEnvVarSource(
                field_ref=_ModelObjectFieldSelector(
                    field_path=self.field_path,
                    api_version=self.api_version,
                )
            ),
        )

api_version class-attribute instance-attribute

api_version = None

optionally, an API version specification. This defaults to the Hera global config api_version

field_path instance-attribute

field_path

the path to the field whose value should be extracted into an environment variable

name instance-attribute

name

the name of the environment variable. This is universally required irrespective of the type of env variable

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Constructs and returns the Argo environment specification.

Source code in src/hera/workflows/env.py

def build(self) -> _ModelEnvVar:
    """Constructs and returns the Argo environment specification."""
    return _ModelEnvVar(
        name=self.name,
        value_from=_ModelEnvVarSource(
            field_ref=_ModelObjectFieldSelector(
                field_path=self.field_path,
                api_version=self.api_version,
            )
        ),
    )

FlexVolume

A Flex volume representation.

Source code in src/hera/workflows/volume.py

class FlexVolume(_BaseVolume, _ModelFlexVolumeSource):
    """A Flex volume representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            flex_volume=_ModelFlexVolumeSource(
                driver=self.driver,
                fs_type=self.fs_type,
                options=self.options,
                read_only=self.read_only,
                secret_ref=self.secret_ref,
            ),
        )

driver instance-attribute

driver

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

options class-attribute instance-attribute

options = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_ref class-attribute instance-attribute

secret_ref = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

FlockerVolume

A Flocker volume representation.

Source code in src/hera/workflows/volume.py

class FlockerVolume(_BaseVolume, _ModelFlockerVolumeSource):
    """A Flocker volume representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            flocker=_ModelFlockerVolumeSource(dataset_name=self.dataset_name, dataset_uuid=self.dataset_uuid),
        )

dataset_name class-attribute instance-attribute

dataset_name = None

dataset_uuid class-attribute instance-attribute

dataset_uuid = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

GCEPersistentDiskVolume

A representation of a Google Cloud Compute Enginer persistent disk.

Notes

The volume must exist on GCE before a request to mount it to a pod is performed.

Source code in src/hera/workflows/volume.py

class GCEPersistentDiskVolume(_BaseVolume, _ModelGCEPersistentDiskVolumeSource):
    """A representation of a Google Cloud Compute Enginer persistent disk.

    Notes:
        The volume must exist on GCE before a request to mount it to a pod is performed.
    """

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            gce_persistent_disk=_ModelGCEPersistentDiskVolumeSource(
                fs_type=self.fs_type, partition=self.partition, pd_name=self.pd_name, read_only=self.read_only
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

partition class-attribute instance-attribute

partition = None

pd_name instance-attribute

pd_name

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

GCSArtifact

An artifact sourced from Google Cloud Storage.

Source code in src/hera/workflows/artifact.py

class GCSArtifact(_ModelGCSArtifact, Artifact):
    """An artifact sourced from Google Cloud Storage."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.gcs = _ModelGCSArtifact(
            bucket=self.bucket,
            key=self.key,
            service_account_key_secret=self.service_account_key_secret,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + ["bucket", "key", "service_account_key_secret"]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

bucket class-attribute instance-attribute

bucket = None

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

key instance-attribute

key

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

service_account_key_secret class-attribute instance-attribute

service_account_key_secret = None

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

Gauge

Gauge metric component used to record intervals based on the given value.

Notes

See https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics

Source code in src/hera/workflows/metrics.py

class Gauge(_BaseMetric, _ModelGauge):
    """Gauge metric component used to record intervals based on the given value.

    Notes:
        See [https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics](https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics)
    """

    realtime: bool
    value: str

    def _build_metric(self) -> _ModelPrometheus:
        return _ModelPrometheus(
            counter=None,
            gauge=_ModelGauge(realtime=self.realtime, value=self.value),
            help=self.help,
            histogram=None,
            labels=self._build_labels(),
            name=self.name,
            when=self.when,
        )

help instance-attribute

help

labels class-attribute instance-attribute

labels = None

name instance-attribute

name

operation class-attribute instance-attribute

operation = None

realtime instance-attribute

realtime

value instance-attribute

value

when class-attribute instance-attribute

when = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

GitArtifact

An artifact sourced from GitHub.

Source code in src/hera/workflows/artifact.py

class GitArtifact(_ModelGitArtifact, Artifact):
    """An artifact sourced from GitHub."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.git = _ModelGitArtifact(
            branch=self.branch,
            depth=self.depth,
            disable_submodules=self.disable_submodules,
            fetch=self.fetch,
            insecure_ignore_host_key=self.insecure_ignore_host_key,
            password_secret=self.password_secret,
            repo=self.repo,
            revision=self.revision,
            single_branch=self.single_branch,
            ssh_private_key_secret=self.ssh_private_key_secret,
            username_secret=self.username_secret,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + [
            "branch",
            "depth",
            "disable_submodules",
            "fetch",
            "insecure_ignore_host_key",
            "password_secret",
            "repo",
            "revision",
            "single_branch",
            "ssh_private_key_secret",
            "username_secret",
        ]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

branch class-attribute instance-attribute

branch = None

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

depth class-attribute instance-attribute

depth = None

disable_submodules class-attribute instance-attribute

disable_submodules = None

fetch class-attribute instance-attribute

fetch = None

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

insecure_ignore_host_key class-attribute instance-attribute

insecure_ignore_host_key = None

insecure_skip_tls class-attribute instance-attribute

insecure_skip_tls = None

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

password_secret class-attribute instance-attribute

password_secret = None

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

repo instance-attribute

repo

revision class-attribute instance-attribute

revision = None

single_branch class-attribute instance-attribute

single_branch = None

ssh_private_key_secret class-attribute instance-attribute

ssh_private_key_secret = None

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

username_secret class-attribute instance-attribute

username_secret = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

GitRepoVolume

A representation of a Git repo that can be mounted as a volume.

Source code in src/hera/workflows/volume.py

class GitRepoVolume(_BaseVolume, _ModelGitRepoVolumeSource):
    """A representation of a Git repo that can be mounted as a volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            git_repo=_ModelGitRepoVolumeSource(
                directory=self.directory, repository=self.repository, revision=self.revision
            ),
        )

directory class-attribute instance-attribute

directory = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

repository instance-attribute

repository

revision class-attribute instance-attribute

revision = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

GlusterfsVolume

A representation for a Gluster filesystem volume.

Source code in src/hera/workflows/volume.py

class GlusterfsVolume(_BaseVolume, _ModelGlusterfsVolumeSource):
    """A representation for a Gluster filesystem volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            glusterfs=_ModelGlusterfsVolumeSource(endpoints=self.endpoints, path=self.path, read_only=self.read_only),
        )

endpoints instance-attribute

endpoints

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

path instance-attribute

path

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

HDFSArtifact

A Hadoop File System artifact.

Note that HDFSArtifact does not inherit from the auto-generated HDFSArtifact because there’s a conflict in path with the base class Artifact. Here, we redefine the HDFS path to hdfs_path to differentiate between the parent class and the child class path.

Source code in src/hera/workflows/artifact.py

class HDFSArtifact(Artifact):
    """A Hadoop File System artifact.

    Note that `HDFSArtifact` does not inherit from the auto-generated `HDFSArtifact` because there's a
    conflict in `path` with the base class `Artifact`. Here, we redefine the HDFS `path` to `hdfs_path` to
    differentiate between the parent class and the child class `path`.
    """

    hdfs_path: str
    addresses: Optional[List[str]] = None
    force: Optional[bool] = None
    hdfs_user: Optional[str]
    krb_c_cache_secret: Optional[SecretKeySelector] = None
    krb_config_config_map: Optional[ConfigMapKeySelector] = None
    krb_keytab_secret: Optional[SecretKeySelector] = None
    krb_realm: Optional[str] = None
    krb_service_principal_name: Optional[str] = None
    krb_username: Optional[str] = None

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.hdfs = _ModelHDFSArtifact(
            addresses=self.addresses,
            force=self.force,
            hdfs_user=self.hdfs_user,
            krb_c_cache_secret=self.krb_c_cache_secret,
            krb_config_config_map=self.krb_config_config_map,
            krb_keytab_secret=self.krb_keytab_secret,
            krb_realm=self.krb_realm,
            krb_service_principal_name=self.krb_service_principal_name,
            krb_username=self.krb_username,
            path=self.hdfs_path,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + [
            "addresses",
            "force",
            "hdfs_path",
            "hdfs_user",
            "krb_c_cache_secret",
            "krb_config_config_map",
            "krb_keytab_secret",
            "krb_realm",
            "krb_service_principal_name",
            "krb_username",
        ]

addresses class-attribute instance-attribute

addresses = None

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

force class-attribute instance-attribute

force = None

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

hdfs_path instance-attribute

hdfs_path

hdfs_user instance-attribute

hdfs_user

krb_c_cache_secret class-attribute instance-attribute

krb_c_cache_secret = None

krb_config_config_map class-attribute instance-attribute

krb_config_config_map = None

krb_keytab_secret class-attribute instance-attribute

krb_keytab_secret = None

krb_realm class-attribute instance-attribute

krb_realm = None

krb_service_principal_name class-attribute instance-attribute

krb_service_principal_name = None

krb_username class-attribute instance-attribute

krb_username = None

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

HTTP

HTTP is an implementation of the HTTP template that supports executing HTTP actions in a step/task.

Source code in src/hera/workflows/http_template.py

class HTTP(TemplateMixin, IOMixin, CallableTemplateMixin):
    """`HTTP` is an implementation of the HTTP template that supports executing HTTP actions in a step/task."""

    url: str
    body: Optional[str] = None
    body_from: Optional[HTTPBodySource] = None
    headers: Optional[List[HTTPHeader]] = None
    insecure_skip_verify: Optional[bool] = None
    method: Optional[str] = None
    success_condition: Optional[str] = None
    timeout_seconds: Optional[int] = None

    def _build_http_template(self) -> _ModelHTTP:
        """Builds the generated HTTP sub-template."""
        return _ModelHTTP(
            url=self.url,
            body=self.body,
            body_from=self.body_from,
            headers=self.headers,
            insecure_skip_verify=self.insecure_skip_verify,
            method=self.method,
            success_condition=self.success_condition,
            timeout_seconds=self.timeout_seconds,
        )

    def _build_template(self) -> _ModelTemplate:
        """Builds the HTTP generated `Template`."""
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            http=self._build_http_template(),
            init_containers=self._build_init_containers(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            inputs=self._build_inputs(),
            outputs=self._build_outputs(),
            name=self.name,
            node_selector=self.node_selector,
            plugin=self.plugin,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

body class-attribute instance-attribute

body = None

body_from class-attribute instance-attribute

body_from = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

headers class-attribute instance-attribute

headers = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

insecure_skip_verify class-attribute instance-attribute

insecure_skip_verify = None

labels class-attribute instance-attribute

labels = None

memoize class-attribute instance-attribute

memoize = None

method class-attribute instance-attribute

method = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

sidecars class-attribute instance-attribute

sidecars = None

success_condition class-attribute instance-attribute

success_condition = None

synchronization class-attribute instance-attribute

synchronization = None

timeout class-attribute instance-attribute

timeout = None

timeout_seconds class-attribute instance-attribute

timeout_seconds = None

tolerations class-attribute instance-attribute

tolerations = None

url instance-attribute

url

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

HTTPArtifact

An artifact sourced from an HTTP URL.

Source code in src/hera/workflows/artifact.py

class HTTPArtifact(_ModelHTTPArtifact, Artifact):
    """An artifact sourced from an HTTP URL."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.http = _ModelHTTPArtifact(
            auth=self.auth,
            headers=self.headers,
            url=self.url,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + ["auth", "headers", "url"]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

auth class-attribute instance-attribute

auth = None

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

headers class-attribute instance-attribute

headers = None

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

url instance-attribute

url

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

Histogram

Histogram metric that records the value at the specified bucket intervals.

Notes

See https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics

Source code in src/hera/workflows/metrics.py

class Histogram(_BaseMetric):
    """Histogram metric that records the value at the specified bucket intervals.

    Notes:
        See [https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics](https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics)
    """

    buckets: List[Union[float, _ModelAmount]]  # type: ignore
    value: str

    def _build_buckets(self) -> List[_ModelAmount]:
        return [_ModelAmount(__root__=bucket) if isinstance(bucket, float) else bucket for bucket in self.buckets]

    def _build_metric(self) -> _ModelPrometheus:
        return _ModelPrometheus(
            counter=None,
            gauge=None,
            help=self.help,
            histogram=_ModelHistogram(
                buckets=self._build_buckets(),
                value=self.value,
            ),
            labels=self._build_labels(),
            name=self.name,
            when=self.when,
        )

buckets instance-attribute

buckets

help instance-attribute

help

labels class-attribute instance-attribute

labels = None

name instance-attribute

name

value instance-attribute

value

when class-attribute instance-attribute

when = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

HostPathVolume

Representation for a volume that can be mounted from a host path/node location.

Source code in src/hera/workflows/volume.py

class HostPathVolume(_BaseVolume, _ModelHostPathVolumeSource):
    """Representation for a volume that can be mounted from a host path/node location."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(name=self.name, host_path=_ModelHostPathVolumeSource(path=self.path, type=self.type))

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

path instance-attribute

path

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

type class-attribute instance-attribute

type = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

ISCSIVolume

Representation of ISCSI volume.

Source code in src/hera/workflows/volume.py

class ISCSIVolume(_BaseVolume, _ModelISCSIVolumeSource):
    """Representation of ISCSI volume."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            iscsi=_ModelISCSIVolumeSource(
                chap_auth_discovery=self.chap_auth_discovery,
                chap_auth_session=self.chap_auth_discovery,
                fs_type=self.fs_type,
                initiator_name=self.initiator_name,
                iqn=self.iqn,
                iscsi_interface=self.iscsi_interface,
                lun=self.lun,
                portals=self.portals,
                read_only=self.read_only,
                secret_ref=self.secret_ref,
                target_portal=self.target_portal,
            ),
        )

chap_auth_discovery class-attribute instance-attribute

chap_auth_discovery = None

chap_auth_session class-attribute instance-attribute

chap_auth_session = None

fs_type class-attribute instance-attribute

fs_type = None

initiator_name class-attribute instance-attribute

initiator_name = None

iqn instance-attribute

iqn

iscsi_interface class-attribute instance-attribute

iscsi_interface = None

lun instance-attribute

lun

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

portals class-attribute instance-attribute

portals = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_ref class-attribute instance-attribute

secret_ref = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

target_portal instance-attribute

target_portal

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

InlineScriptConstructor

InlineScriptConstructor is a script constructor that submits a script as a source to Argo.

This script constructor is focused on taking a Python script/function “as is” for remote execution. The constructor processes the script to infer what parameters it needs to deserialize so the script can execute. The submitted script will contain prefixes such as new imports, e.g. import os, import json, etc. and will contain the necessary json.loads calls to deserialize the parameters so they are usable by the script just like a normal Python script/function.

Source code in src/hera/workflows/script.py

class InlineScriptConstructor(ScriptConstructor):
    """`InlineScriptConstructor` is a script constructor that submits a script as a `source` to Argo.

    This script constructor is focused on taking a Python script/function "as is" for remote execution. The
    constructor processes the script to infer what parameters it needs to deserialize so the script can execute.
    The submitted script will contain prefixes such as new imports, e.g. `import os`, `import json`, etc. and
    will contain the necessary `json.loads` calls to deserialize the parameters so they are usable by the script just
    like a normal Python script/function.
    """

    add_cwd_to_sys_path: Optional[bool] = None

    @staticmethod
    def _roundtrip(source):
        tree = ast.parse(source)
        if hasattr(ast, "unparse"):
            return ast.unparse(tree)
        return ast.unparse(tree)

    def _get_param_script_portion(self, instance: Script) -> str:
        """Constructs and returns a script that loads the parameters of the specified arguments.

        Since Argo passes parameters through `{{input.parameters.name}}` it can be very cumbersome for users to
        manage that. This creates a script that automatically imports json and loads/adds code to interpret
        each independent argument into the script.

        Returns:
        -------
        str
            The string representation of the script to load.
        """
        inputs = instance._build_inputs()
        assert inputs
        extract = "import json\n"
        for param in sorted(inputs.parameters or [], key=lambda x: x.name):
            # Hera does not know what the content of the `InputFrom` is, coming from another task. In some cases
            # non-JSON encoded strings are returned, which fail the loads, but they can be used as plain strings
            # which is why this captures that in an except. This is only used for `InputFrom` cases as the extra
            # payload of the script is not necessary when regular input is set on the task via `func_params`
            if param.value_from is None:
                extract += f"""try: {param.name} = json.loads(r'''{{{{inputs.parameters.{param.name}}}}}''')\n"""
                extract += f"""except: {param.name} = r'''{{{{inputs.parameters.{param.name}}}}}'''\n"""
        return textwrap.dedent(extract) if extract != "import json\n" else ""

    def generate_source(self, instance: Script) -> str:
        """Assembles and returns a script representation of the given function.

        This also assembles any extra script material prefixed to the string source.
        The script is expected to be a callable function the client is interested in submitting
        for execution on Argo and the `script_extra` material represents the parameter loading part obtained, likely,
        through `get_param_script_portion`.

        Returns:
        -------
        str
            Final formatted script.
        """
        if not callable(instance.source):
            assert isinstance(instance.source, str)
            return instance.source
        args = inspect.getfullargspec(instance.source).args
        script = ""
        # Argo will save the script as a file and run it with cmd:
        # - python /argo/staging/script
        # However, this prevents the script from importing modules in its cwd,
        # since it's looking for files relative to the script path.
        # We fix this by appending the cwd path to sys:
        if instance.add_cwd_to_sys_path or self.add_cwd_to_sys_path:
            script = "import os\nimport sys\nsys.path.append(os.getcwd())\n"

        script_extra = self._get_param_script_portion(instance) if args else None
        if script_extra:
            script += copy.deepcopy(script_extra)
            script += "\n"

        # We use ast parse/unparse to get the source code of the function
        # in order to have consistent looking functions and getting rid of any comments
        # parsing issues.
        # See https://github.com/argoproj-labs/hera/issues/572
        content = self._roundtrip(textwrap.dedent(inspect.getsource(instance.source))).splitlines()
        for i, line in enumerate(content):
            if line.startswith("def") or line.startswith("async def"):
                break

        s = "\n".join(content[i + 1 :])
        script += textwrap.dedent(s)
        return textwrap.dedent(script)

add_cwd_to_sys_path class-attribute instance-attribute

add_cwd_to_sys_path = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

generate_source

generate_source(instance)

Assembles and returns a script representation of the given function.

This also assembles any extra script material prefixed to the string source. The script is expected to be a callable function the client is interested in submitting for execution on Argo and the script_extra material represents the parameter loading part obtained, likely, through get_param_script_portion.

Returns:

str Final formatted script.

Source code in src/hera/workflows/script.py

def generate_source(self, instance: Script) -> str:
    """Assembles and returns a script representation of the given function.

    This also assembles any extra script material prefixed to the string source.
    The script is expected to be a callable function the client is interested in submitting
    for execution on Argo and the `script_extra` material represents the parameter loading part obtained, likely,
    through `get_param_script_portion`.

    Returns:
    -------
    str
        Final formatted script.
    """
    if not callable(instance.source):
        assert isinstance(instance.source, str)
        return instance.source
    args = inspect.getfullargspec(instance.source).args
    script = ""
    # Argo will save the script as a file and run it with cmd:
    # - python /argo/staging/script
    # However, this prevents the script from importing modules in its cwd,
    # since it's looking for files relative to the script path.
    # We fix this by appending the cwd path to sys:
    if instance.add_cwd_to_sys_path or self.add_cwd_to_sys_path:
        script = "import os\nimport sys\nsys.path.append(os.getcwd())\n"

    script_extra = self._get_param_script_portion(instance) if args else None
    if script_extra:
        script += copy.deepcopy(script_extra)
        script += "\n"

    # We use ast parse/unparse to get the source code of the function
    # in order to have consistent looking functions and getting rid of any comments
    # parsing issues.
    # See https://github.com/argoproj-labs/hera/issues/572
    content = self._roundtrip(textwrap.dedent(inspect.getsource(instance.source))).splitlines()
    for i, line in enumerate(content):
        if line.startswith("def") or line.startswith("async def"):
            break

    s = "\n".join(content[i + 1 :])
    script += textwrap.dedent(s)
    return textwrap.dedent(script)

transform_script_template_post_build

transform_script_template_post_build(instance, script)

A hook to transform the generated script template.

Source code in src/hera/workflows/script.py

def transform_script_template_post_build(
    self, instance: "Script", script: _ModelScriptTemplate
) -> _ModelScriptTemplate:
    """A hook to transform the generated script template."""
    return script

transform_template_post_build

transform_template_post_build(instance, template)

A hook to transform the generated template.

Source code in src/hera/workflows/script.py

def transform_template_post_build(self, instance: "Script", template: _ModelTemplate) -> _ModelTemplate:
    """A hook to transform the generated template."""
    return template

transform_values

transform_values(cls, values)

A function that will be invoked by the root validator of the Script class.

Source code in src/hera/workflows/script.py

def transform_values(self, cls: Type["Script"], values: Any) -> Any:
    """A function that will be invoked by the root validator of the Script class."""
    return values

Input

Input model usable by the Hera Runner.

Input is a Pydantic model which users can create a subclass of. When a subclass of Input is used as a function parameter type, Hera will take the fields of the user’s subclass to create template input parameters and artifacts. See the example for the script_pydantic_io experimental feature.

Source code in src/hera/workflows/io/v1.py

class Input(InputMixin, BaseModel):
    """Input model usable by the Hera Runner.

    Input is a Pydantic model which users can create a subclass of. When a subclass
    of Input is used as a function parameter type, Hera will take the fields of the
    user's subclass to create template input parameters and artifacts. See the example
    for the script_pydantic_io experimental feature.
    """

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

InvalidDispatchType

Exception raised when Hera attempts to dispatch a hook and it fails to do so.

Source code in src/hera/workflows/exceptions.py

class InvalidDispatchType(WorkflowsException):
    """Exception raised when Hera attempts to dispatch a hook and it fails to do so."""

    ...

InvalidTemplateCall

Exception raised when an invalid template call is performed.

Source code in src/hera/workflows/exceptions.py

class InvalidTemplateCall(WorkflowsException):
    """Exception raised when an invalid template call is performed."""

    ...

InvalidType

Exception raised when an invalid type is submitted to a Hera object’s field or functionality.

Source code in src/hera/workflows/exceptions.py

class InvalidType(WorkflowsException):
    """Exception raised when an invalid type is submitted to a Hera object's field or functionality."""

    ...

Metric

Prometheus metric that can be used at the workflow or task/template level.

Notes

See https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics

Source code in src/hera/workflows/metrics.py

class Metric(_BaseMetric):
    """Prometheus metric that can be used at the workflow or task/template level.

    Notes:
        See [https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics](https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics)
    """

    counter: Optional[Counter] = None
    gauge: Optional[Gauge] = None
    histogram: Optional[Histogram] = None

    def _build_metric(self) -> _ModelPrometheus:
        return _ModelPrometheus(
            counter=_ModelCounter(value=self.counter.value) if self.counter else None,
            gauge=_ModelGauge(realtime=self.gauge.realtime, value=self.gauge.value) if self.gauge else None,
            help=self.help,
            histogram=_ModelHistogram(
                buckets=self.histogram._build_buckets(),
                value=self.histogram.value,
            )
            if self.histogram
            else None,
            labels=self._build_labels(),
            name=self.name,
            when=self.when,
        )

counter class-attribute instance-attribute

counter = None

gauge class-attribute instance-attribute

gauge = None

help instance-attribute

help

histogram class-attribute instance-attribute

histogram = None

labels class-attribute instance-attribute

labels = None

name instance-attribute

name

when class-attribute instance-attribute

when = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Metrics

A collection of Prometheus metrics.

Notes

See https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics

Source code in src/hera/workflows/metrics.py

class Metrics(BaseMixin):
    """A collection of Prometheus metrics.

    Notes:
        See [https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics](https://argoproj.github.io/argo-workflows/metrics/#grafana-dashboard-for-argo-controller-metrics)
    """

    metrics: List[Metric]

    def _build_metrics(self) -> List[_ModelPrometheus]:
        return [metric._build_metric() for metric in self.metrics]

metrics instance-attribute

metrics

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

NFSVolume

A network file system volume representation.

Source code in src/hera/workflows/volume.py

class NFSVolume(_BaseVolume, _ModelNFSVolumeSource):
    """A network file system volume representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name, nfs=_ModelNFSVolumeSource(server=self.server, path=self.path, read_only=self.read_only)
        )

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

path instance-attribute

path

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

server instance-attribute

server

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

NodeNameConflict

Exception raised when multiple Task/Step are found with the same name.

Source code in src/hera/workflows/exceptions.py

class NodeNameConflict(WorkflowsException):
    """Exception raised when multiple Task/Step are found with the same name."""

    ...

NoneArchiveStrategy

NoneArchiveStrategy indicates artifacts should skip serialization.

Source code in src/hera/workflows/archive.py

class NoneArchiveStrategy(ArchiveStrategy):
    """`NoneArchiveStrategy` indicates artifacts should skip serialization."""

    def _build_archive_strategy(self) -> _ModelArchiveStrategy:
        return _ModelArchiveStrategy(none=_ModelNoneStrategy())

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

OSSArtifact

An artifact sourced from OSS.

Source code in src/hera/workflows/artifact.py

class OSSArtifact(_ModelOSSArtifact, Artifact):
    """An artifact sourced from OSS."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.oss = _ModelOSSArtifact(
            access_key_secret=self.access_key_secret,
            bucket=self.bucket,
            create_bucket_if_not_present=self.create_bucket_if_not_present,
            endpoint=self.endpoint,
            key=self.key,
            lifecycle_rule=self.lifecycle_rule,
            secret_key_secret=self.secret_key_secret,
            security_token=self.security_token,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + [
            "access_key_secret",
            "bucket",
            "create_bucket_if_not_present",
            "endpoint",
            "key",
            "lifecycle_rule",
            "secret_key_secret",
            "security_token",
        ]

access_key_secret class-attribute instance-attribute

access_key_secret = None

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

bucket class-attribute instance-attribute

bucket = None

create_bucket_if_not_present class-attribute instance-attribute

create_bucket_if_not_present = None

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

endpoint class-attribute instance-attribute

endpoint = None

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

key instance-attribute

key

lifecycle_rule class-attribute instance-attribute

lifecycle_rule = None

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

secret_key_secret class-attribute instance-attribute

secret_key_secret = None

security_token class-attribute instance-attribute

security_token = None

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

use_sdk_creds class-attribute instance-attribute

use_sdk_creds = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

Operator

Operator is a representation of mathematical comparison symbols.

This can be used on tasks that execute conditionally based on the output of another task.

Notes

The task that outputs its result needs to do so using stdout. See examples for a sample workflow.

Source code in src/hera/workflows/operator.py

class Operator(Enum):
    """Operator is a representation of mathematical comparison symbols.

    This can be used on tasks that execute conditionally based on the output of another task.

    Notes:
        The task that outputs its result needs to do so using stdout. See `examples` for a sample workflow.
    """

    does_not_exist = "DoesNotExist"
    exists = "Exists"
    gt = "Gt"
    in_ = "In"
    lt = "Lt"
    not_in = "NotIn"

    equals = "=="
    greater = ">"
    less = "<"
    greater_equal = ">="
    less_equal = "<="
    not_equal = "!="
    or_ = "||"
    and_ = "&&"
    starts_with = "=~"

    def __str__(self) -> str:
        """Assembles the `value` representation of the enum and returns it as a string."""
        return str(self.value)

and_ class-attribute instance-attribute

and_ = '&&'

does_not_exist class-attribute instance-attribute

does_not_exist = 'DoesNotExist'

equals class-attribute instance-attribute

equals = '=='

exists class-attribute instance-attribute

exists = 'Exists'

greater class-attribute instance-attribute

greater = '>'

greater_equal class-attribute instance-attribute

greater_equal = '>='

gt class-attribute instance-attribute

gt = 'Gt'

in_ class-attribute instance-attribute

in_ = 'In'

less class-attribute instance-attribute

less = '<'

less_equal class-attribute instance-attribute

less_equal = '<='

lt class-attribute instance-attribute

lt = 'Lt'

not_equal class-attribute instance-attribute

not_equal = '!='

not_in class-attribute instance-attribute

not_in = 'NotIn'

or_ class-attribute instance-attribute

or_ = '||'

starts_with class-attribute instance-attribute

starts_with = '=~'

Output

Output model usable by the Hera Runner.

Output is a Pydantic model which users can create a subclass of. When a subclass of Output is used as a function return type, Hera will take the fields of the user’s subclass to create template output parameters and artifacts. See the example for the script_pydantic_io experimental feature.

Source code in src/hera/workflows/io/v1.py

class Output(OutputMixin, BaseModel):
    """Output model usable by the Hera Runner.

    Output is a Pydantic model which users can create a subclass of. When a subclass
    of Output is used as a function return type, Hera will take the fields of the
    user's subclass to create template output parameters and artifacts. See the example
    for the script_pydantic_io experimental feature.
    """

    exit_code: int = 0
    result: Any = None

exit_code class-attribute instance-attribute

exit_code = 0

result class-attribute instance-attribute

result = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Parallel

Parallel is used to add a list of steps which will run in parallel.

Parallel implements the contextmanager interface so allows usage of with, under which any hera.workflows.steps.Step objects instantiated will be added to Parallel’s list of sub_steps.

Source code in src/hera/workflows/steps.py

class Parallel(
    ContextMixin,
    SubNodeMixin,
):
    """Parallel is used to add a list of steps which will run in parallel.

    Parallel implements the contextmanager interface so allows usage of `with`, under which any
    `hera.workflows.steps.Step` objects instantiated will be added to Parallel's list of sub_steps.
    """

    sub_steps: List[Union[Step, _ModelWorkflowStep]] = []

    _node_names = PrivateAttr(default_factory=set)

    def _add_sub(self, node: Any):
        if not isinstance(node, Step):
            raise InvalidType(type(node))
        if node.name in self._node_names:
            raise NodeNameConflict(f"Found multiple Steps named: {node.name}")
        self._node_names.add(node.name)
        self.sub_steps.append(node)

    def _build_step(self) -> List[_ModelWorkflowStep]:
        steps = []
        for step in self.sub_steps:
            if isinstance(step, Step):
                steps.append(step._build_as_workflow_step())
            elif isinstance(step, _ModelWorkflowStep):
                steps.append(step)
            else:
                raise InvalidType(type(step))
        return steps

sub_steps class-attribute instance-attribute

sub_steps = []

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

Parameter

A Parameter is used to pass values in and out of templates.

They are to declare input and output parameters in the case of templates, and are used for Steps and Tasks to assign values.

Source code in src/hera/workflows/parameter.py

class Parameter(_ModelParameter):
    """A `Parameter` is used to pass values in and out of templates.

    They are to declare input and output parameters in the case of templates, and are used
    for Steps and Tasks to assign values.
    """

    name: Optional[str] = None  # type: ignore

    output: Optional[bool] = False
    """used to specify parameter as an output in function signature annotations"""

    def _check_name(self):
        if not self.name:
            raise ValueError("name cannot be `None` or empty when used")

    # `MISSING` is the default value so that `Parameter` serialization understands the difference between a
    # missing value and a value of `None`, as set by a user. With this, when something sets a value of `None` it is
    # taken as a proper `None`. By comparison, if a user does not set a value, it is taken as `MISSING` and therefore
    # not serialized. This happens because the values if turned into an _actual_ `None` by `serialize` and therefore
    # Pydantic will not include it in the YAML that is passed to Argo
    value: Optional[Any] = MISSING
    default: Optional[Any] = MISSING

    @root_validator(pre=True, allow_reuse=True)
    def _check_values(cls, values):
        if values.get("value") is not None and values.get("value_from") is not None:
            raise ValueError("Cannot specify both `value` and `value_from` when instantiating `Parameter`")

        values["value"] = serialize(values.get("value", MISSING))
        values["default"] = serialize(values.get("default", MISSING))
        if values.get("enum", []):
            # We don't need to set "enum" in values to "MISSING" if there are no values
            # as it's a list of values. The values themselves should be serialized.
            values["enum"] = [serialize(v) for v in values.get("enum")]

        return values

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input parameter annotations."""
        return ["enum", "description", "default", "name", "value", "value_from"]

    def __str__(self):
        """Represent the parameter as a string by pointing to its value.

        This is useful in situations where we want to concatenate string values such as
        Task.args=["echo", wf.get_parameter("message")].
        """
        if self.value is None:
            raise ValueError("Cannot represent `Parameter` as string as `value` is not set")
        return self.value

    @classmethod
    def from_model(cls, model: _ModelParameter) -> Parameter:
        """Creates a `Parameter` from a `Parameter` model without running validation."""
        return cls.construct(**model.dict())

    def with_name(self, name: str) -> Parameter:
        """Returns a copy of the parameter with the name set to the value."""
        p = self.copy(deep=True)
        p.name = name
        return p

    def as_input(self) -> _ModelParameter:
        """Assembles the parameter for use as an input of a template."""
        self._check_name()
        assert self.name
        return _ModelParameter(
            name=self.name,
            description=self.description,
            default=self.default,
            enum=self.enum,
            value=self.value,
            value_from=self.value_from,
        )

    def as_argument(self) -> _ModelParameter:
        """Assembles the parameter for use as an argument of a step or a task."""
        # Setting a default value when used as an argument is a no-op so we exclude it as it would get overwritten by
        # `value` or `value_from` (one of which is required)
        # Overwrite ref: https://github.com/argoproj/argo-workflows/blob/781675ddcf6f1138d697cb9c71dae484daa0548b/workflow/common/util.go#L126-L139
        # One of value/value_from required ref: https://github.com/argoproj/argo-workflows/blob/ab178bb0b36a5ce34b4c1302cf4855879a0e8cf5/workflow/validate/validate.go#L794-L798
        self._check_name()
        assert self.name
        return _ModelParameter(
            name=self.name,
            global_name=self.global_name,
            description=self.description,
            enum=self.enum,
            value=self.value,
            value_from=self.value_from,
        )

    def as_output(self) -> _ModelParameter:
        """Assembles the parameter for use as an output of a template."""
        # Only `value` and `value_from` are valid here
        # see https://github.com/argoproj/argo-workflows/blob/e3254eca115c9dd358e55d16c6a3d41403c29cae/workflow/validate/validate.go#L1067
        self._check_name()
        assert self.name
        return _ModelParameter(
            name=self.name,
            global_name=self.global_name,
            description=self.description,
            value=self.value,
            value_from=self.value_from,
        )

default class-attribute instance-attribute

default = MISSING

description class-attribute instance-attribute

description = None

enum class-attribute instance-attribute

enum = None

global_name class-attribute instance-attribute

global_name = None

name class-attribute instance-attribute

name = None

output class-attribute instance-attribute

output = False

used to specify parameter as an output in function signature annotations

value class-attribute instance-attribute

value = MISSING

value_from class-attribute instance-attribute

value_from = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_argument

as_argument()

Assembles the parameter for use as an argument of a step or a task.

Source code in src/hera/workflows/parameter.py

def as_argument(self) -> _ModelParameter:
    """Assembles the parameter for use as an argument of a step or a task."""
    # Setting a default value when used as an argument is a no-op so we exclude it as it would get overwritten by
    # `value` or `value_from` (one of which is required)
    # Overwrite ref: https://github.com/argoproj/argo-workflows/blob/781675ddcf6f1138d697cb9c71dae484daa0548b/workflow/common/util.go#L126-L139
    # One of value/value_from required ref: https://github.com/argoproj/argo-workflows/blob/ab178bb0b36a5ce34b4c1302cf4855879a0e8cf5/workflow/validate/validate.go#L794-L798
    self._check_name()
    assert self.name
    return _ModelParameter(
        name=self.name,
        global_name=self.global_name,
        description=self.description,
        enum=self.enum,
        value=self.value,
        value_from=self.value_from,
    )

as_input

as_input()

Assembles the parameter for use as an input of a template.

Source code in src/hera/workflows/parameter.py

def as_input(self) -> _ModelParameter:
    """Assembles the parameter for use as an input of a template."""
    self._check_name()
    assert self.name
    return _ModelParameter(
        name=self.name,
        description=self.description,
        default=self.default,
        enum=self.enum,
        value=self.value,
        value_from=self.value_from,
    )

as_output

as_output()

Assembles the parameter for use as an output of a template.

Source code in src/hera/workflows/parameter.py

def as_output(self) -> _ModelParameter:
    """Assembles the parameter for use as an output of a template."""
    # Only `value` and `value_from` are valid here
    # see https://github.com/argoproj/argo-workflows/blob/e3254eca115c9dd358e55d16c6a3d41403c29cae/workflow/validate/validate.go#L1067
    self._check_name()
    assert self.name
    return _ModelParameter(
        name=self.name,
        global_name=self.global_name,
        description=self.description,
        value=self.value,
        value_from=self.value_from,
    )

from_model classmethod

from_model(model)

Creates a Parameter from a Parameter model without running validation.

Source code in src/hera/workflows/parameter.py

@classmethod
def from_model(cls, model: _ModelParameter) -> Parameter:
    """Creates a `Parameter` from a `Parameter` model without running validation."""
    return cls.construct(**model.dict())

with_name

with_name(name)

Returns a copy of the parameter with the name set to the value.

Source code in src/hera/workflows/parameter.py

def with_name(self, name: str) -> Parameter:
    """Returns a copy of the parameter with the name set to the value."""
    p = self.copy(deep=True)
    p.name = name
    return p

PhotonPersistentDiskVolume

A Photon Persisten Disk representation.

Source code in src/hera/workflows/volume.py

class PhotonPersistentDiskVolume(_BaseVolume, _ModelPhotonPersistentDiskVolumeSource):
    """A Photon Persisten Disk representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            photon_persistent_disk=_ModelPhotonPersistentDiskVolumeSource(fs_type=self.fs_type, pd_id=self.pd_id),
        )

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

pd_id instance-attribute

pd_id

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

PortworxVolume

PortworxVolume represents a Portworx volume to mount to a container.

Source code in src/hera/workflows/volume.py

class PortworxVolume(_BaseVolume, _ModelPortworxVolumeSource):
    """`PortworxVolume` represents a Portworx volume to mount to a container."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            portworx_volume=_ModelPortworxVolumeSource(
                fs_type=self.fs_type, read_only=self.read_only, volume_id=self.volume_id
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

volume_id instance-attribute

volume_id

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

ProjectedVolume

ProjectedVolume represents a projected volume to mount to a container.

Source code in src/hera/workflows/volume.py

class ProjectedVolume(_BaseVolume, _ModelProjectedVolumeSource):
    """`ProjectedVolume` represents a projected volume to mount to a container."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name, projected=_ModelProjectedVolumeSource(default_mode=self.default_mode, sources=self.sources)
        )

default_mode class-attribute instance-attribute

default_mode = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

sources class-attribute instance-attribute

sources = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

QuobyteVolume

QuobyteVolume represents a Quobyte volume to mount to a container.

Source code in src/hera/workflows/volume.py

class QuobyteVolume(_BaseVolume, _ModelQuobyteVolumeSource):
    """`QuobyteVolume` represents a Quobyte volume to mount to a container."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            quobyte=_ModelQuobyteVolumeSource(
                group=self.group,
                read_only=self.read_only,
                registry=self.registry,
                tenant=self.tenant,
                user=self.user,
                volume=self.volume,
            ),
        )

group class-attribute instance-attribute

group = None

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

registry instance-attribute

registry

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

tenant class-attribute instance-attribute

tenant = None

user class-attribute instance-attribute

user = None

volume instance-attribute

volume

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

RBDVolume

An RDB volume representation.

Source code in src/hera/workflows/volume.py

class RBDVolume(_BaseVolume, _ModelRBDVolumeSource):
    """An RDB volume representation."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            rbd=_ModelRBDVolumeSource(
                fs_type=self.fs_type,
                image=self.image,
                keyring=self.keyring,
                monitors=self.monitors,
                pool=self.pool,
                read_only=self.read_only,
                secret_ref=self.secret_ref,
                user=self.user,
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

image instance-attribute

image

keyring class-attribute instance-attribute

keyring = None

monitors instance-attribute

monitors

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

pool class-attribute instance-attribute

pool = None

read_only class-attribute instance-attribute

read_only = None

recursive_read_only class-attribute instance-attribute

recursive_read_only = None

secret_ref class-attribute instance-attribute

secret_ref = None

sub_path class-attribute instance-attribute

sub_path = None

sub_path_expr class-attribute instance-attribute

sub_path_expr = None

user class-attribute instance-attribute

user = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

RawArtifact

A raw bytes artifact representation.

Source code in src/hera/workflows/artifact.py

class RawArtifact(_ModelRawArtifact, Artifact):
    """A raw bytes artifact representation."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.raw = _ModelRawArtifact(data=self.data)
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + ["data"]

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

data instance-attribute

data

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

Resource

Resource is a representation of a K8s resource that can be created by Argo.

The resource is a callable step that can be invoked in a DAG/Workflow. The resource can create any K8s resource, such as other workflows, workflow templates, daemons, etc, as specified by the manifest field of the resource. The manifest field is a canonical YAML that is submitted to K8s by Argo. Note that the manifest is a union of multiple types. The manifest can be a string, in which case it is assume to be YAML. Otherwise, if it’s a Hera objects, it is automatically converted to the corresponding YAML representation.

Source code in src/hera/workflows/resource.py

class Resource(CallableTemplateMixin, TemplateMixin, SubNodeMixin, IOMixin):
    """`Resource` is a representation of a K8s resource that can be created by Argo.

    The resource is a callable step that can be invoked in a DAG/Workflow. The resource can create any K8s resource,
    such as other workflows, workflow templates, daemons, etc, as specified by the `manifest` field of the resource.
    The manifest field is a canonical YAML that is submitted to K8s by Argo. Note that the manifest is a union of
    multiple types. The manifest can be a string, in which case it is assume to be YAML. Otherwise, if it's a Hera
    objects, it is automatically converted to the corresponding YAML representation.
    """

    action: str
    failure_condition: Optional[str] = None
    flags: Optional[List[str]] = None
    manifest: Optional[Union[str, Workflow, CronWorkflow, WorkflowTemplate]] = None
    manifest_from: Optional[ManifestFrom] = None
    merge_strategy: Optional[str] = None
    set_owner_reference: Optional[bool] = None
    success_condition: Optional[str] = None

    def _build_manifest(self) -> Optional[str]:
        if isinstance(self.manifest, (Workflow, CronWorkflow, WorkflowTemplate)):
            # hack to appease raw yaml string comparison
            return self.manifest.to_yaml().replace("'{{", "{{").replace("}}'", "}}")
        return self.manifest

    def _build_resource_template(self) -> _ModelResourceTemplate:
        return _ModelResourceTemplate(
            action=self.action,
            failure_condition=self.failure_condition,
            flags=self.flags,
            manifest=self._build_manifest(),
            manifest_from=self.manifest_from,
            merge_strategy=self.merge_strategy,
            set_owner_reference=self.set_owner_reference,
            success_condition=self.success_condition,
        )

    def _build_template(self) -> _ModelTemplate:
        return _ModelTemplate(
            active_deadline_seconds=self.active_deadline_seconds,
            affinity=self.affinity,
            archive_location=self.archive_location,
            automount_service_account_token=self.automount_service_account_token,
            daemon=self.daemon,
            executor=self.executor,
            fail_fast=self.fail_fast,
            host_aliases=self.host_aliases,
            init_containers=self._build_init_containers(),
            inputs=self._build_inputs(),
            memoize=self.memoize,
            metadata=self._build_metadata(),
            metrics=self._build_metrics(),
            name=self.name,
            node_selector=self.node_selector,
            outputs=self._build_outputs(),
            parallelism=self.parallelism,
            plugin=self.plugin,
            pod_spec_patch=self.pod_spec_patch,
            priority=self.priority,
            priority_class_name=self.priority_class_name,
            resource=self._build_resource_template(),
            retry_strategy=self.retry_strategy,
            scheduler_name=self.scheduler_name,
            security_context=self.pod_security_context,
            service_account_name=self.service_account_name,
            sidecars=self._build_sidecars(),
            synchronization=self.synchronization,
            timeout=self.timeout,
            tolerations=self.tolerations,
        )

action instance-attribute

action

active_deadline_seconds class-attribute instance-attribute

active_deadline_seconds = None

affinity class-attribute instance-attribute

affinity = None

annotations class-attribute instance-attribute

annotations = None

archive_location class-attribute instance-attribute

archive_location = None

automount_service_account_token class-attribute instance-attribute

automount_service_account_token = None

daemon class-attribute instance-attribute

daemon = None

executor class-attribute instance-attribute

executor = None

fail_fast class-attribute instance-attribute

fail_fast = None

failure_condition class-attribute instance-attribute

failure_condition = None

flags class-attribute instance-attribute

flags = None

host_aliases class-attribute instance-attribute

host_aliases = None

http class-attribute instance-attribute

http = None

init_containers class-attribute instance-attribute

init_containers = None

inputs class-attribute instance-attribute

inputs = None

labels class-attribute instance-attribute

labels = None

manifest class-attribute instance-attribute

manifest = None

manifest_from class-attribute instance-attribute

manifest_from = None

memoize class-attribute instance-attribute

memoize = None

merge_strategy class-attribute instance-attribute

merge_strategy = None

metrics class-attribute instance-attribute

metrics = None

name class-attribute instance-attribute

name = None

node_selector class-attribute instance-attribute

node_selector = None

outputs class-attribute instance-attribute

outputs = None

parallelism class-attribute instance-attribute

parallelism = None

plugin class-attribute instance-attribute

plugin = None

pod_security_context class-attribute instance-attribute

pod_security_context = None

pod_spec_patch class-attribute instance-attribute

pod_spec_patch = None

priority class-attribute instance-attribute

priority = None

priority_class_name class-attribute instance-attribute

priority_class_name = None

retry_strategy class-attribute instance-attribute

retry_strategy = None

scheduler_name class-attribute instance-attribute

scheduler_name = None

service_account_name class-attribute instance-attribute

service_account_name = None

set_owner_reference class-attribute instance-attribute

set_owner_reference = None

sidecars class-attribute instance-attribute

sidecars = None

success_condition class-attribute instance-attribute

success_condition = None

synchronization class-attribute instance-attribute

synchronization = None

timeout class-attribute instance-attribute

timeout = None

tolerations class-attribute instance-attribute

tolerations = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

get_artifact

get_artifact(name)

Finds and returns the artifact with the supplied name.

Note that this method will raise an error if the artifact is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input artifact to find and return.	required

Returns:

Name	Type	Description
Artifact	Artifact	the artifact with the supplied name.

Raises:

Type	Description
KeyError	if the artifact is not found.

Source code in src/hera/workflows/_mixins.py

def get_artifact(self, name: str) -> Artifact:
    """Finds and returns the artifact with the supplied name.

    Note that this method will raise an error if the artifact is not found.

    Args:
        name: name of the input artifact to find and return.

    Returns:
        Artifact: the artifact with the supplied name.

    Raises:
        KeyError: if the artifact is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Artifact {name} not found.")
    if inputs.artifacts is None:
        raise KeyError(f"No artifacts set. Artifact {name} not found.")
    for artifact in inputs.artifacts:
        if artifact.name == name:
            return Artifact(name=name, from_=f"{{{{inputs.artifacts.{artifact.name}}}}}")
    raise KeyError(f"Artifact {name} not found.")

get_parameter

get_parameter(name)

Finds and returns the parameter with the supplied name.

Note that this method will raise an error if the parameter is not found.

Parameters:

Name	Type	Description	Default
name	str	name of the input parameter to find and return.	required

Returns:

Name	Type	Description
Parameter	Parameter	the parameter with the supplied name.

Raises:

Type	Description
KeyError	if the parameter is not found.

Source code in src/hera/workflows/_mixins.py

def get_parameter(self, name: str) -> Parameter:
    """Finds and returns the parameter with the supplied name.

    Note that this method will raise an error if the parameter is not found.

    Args:
        name: name of the input parameter to find and return.

    Returns:
        Parameter: the parameter with the supplied name.

    Raises:
        KeyError: if the parameter is not found.
    """
    inputs = self._build_inputs()
    if inputs is None:
        raise KeyError(f"No inputs set. Parameter {name} not found.")
    if inputs.parameters is None:
        raise KeyError(f"No parameters set. Parameter {name} not found.")
    for p in inputs.parameters:
        if p.name == name:
            param = Parameter.from_model(p)
            param.value = f"{{{{inputs.parameters.{param.name}}}}}"
            return param
    raise KeyError(f"Parameter {name} not found.")

ResourceEnv

ResourceEnv exposes a resource field as an environment variable.

Only resources limits and requests such as limits.cpu, limits.memory, limits.ephemeral-storage, requests.cpu, requests.memory and requests.ephemeral-storage are currently supported.

Source code in src/hera/workflows/env.py

class ResourceEnv(_BaseEnv):
    """`ResourceEnv` exposes a resource field as an environment variable.

    Only resources limits and requests such as `limits.cpu`, `limits.memory`, `limits.ephemeral-storage`,
    `requests.cpu`, `requests.memory` and `requests.ephemeral-storage` are currently supported.
    """

    resource: str
    """the name of the resource to select, such as `limit.cpu`, `limits.memory`, etc."""

    container_name: Optional[str] = None
    """
    a pod can contain multiple containers, so this field helps select the right container whose resources should 
    be exposed as an env variable.
    """

    divisor: Optional[Quantity] = None
    """Specifies the output format of the exposed resources, defaults to `1` on Argo's side"""

    def build(self) -> _ModelEnvVar:
        """Builds the `ResourceEnv` into a Hera auto-generated environment variable model."""
        return _ModelEnvVar(
            name=self.name,
            value_from=_ModelEnvVarSource(
                resource_field_ref=_ModelResourceFieldSelector(
                    container_name=self.container_name,
                    divisor=self.divisor,
                    resource=self.resource,
                )
            ),
        )

container_name class-attribute instance-attribute

container_name = None

a pod can contain multiple containers, so this field helps select the right container whose resources should be exposed as an env variable.

divisor class-attribute instance-attribute

divisor = None

Specifies the output format of the exposed resources, defaults to 1 on Argo’s side

name instance-attribute

name

the name of the environment variable. This is universally required irrespective of the type of env variable

resource instance-attribute

resource

the name of the resource to select, such as limit.cpu, limits.memory, etc.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Builds the ResourceEnv into a Hera auto-generated environment variable model.

Source code in src/hera/workflows/env.py

def build(self) -> _ModelEnvVar:
    """Builds the `ResourceEnv` into a Hera auto-generated environment variable model."""
    return _ModelEnvVar(
        name=self.name,
        value_from=_ModelEnvVarSource(
            resource_field_ref=_ModelResourceFieldSelector(
                container_name=self.container_name,
                divisor=self.divisor,
                resource=self.resource,
            )
        ),
    )

Resources

A representation of a collection of resources that are requested to be consumed by a task for execution.

This follow the K8S definition for resources.

Attributes:

Name	Type	Description
cpu_request	Optional[Union[float, int, str]]	The number of CPUs to request, either as a fraction (millicpu), whole number, or a string.
cpu_limit	Optional[Union[float, int, str]]	The limit of CPUs to request, either as a fraction (millicpu), whole number, or a string.
memory_request	Optional[str]	The amount of memory to request.
memory_limit	Optional[str]	The memory limit of the pod.
ephemeral_request	Optional[str]	The amount of ephemeral storage to request.
ephemeral_limit	Optional[str]	The ephemeral storage limit of the pod.
gpus	Optional[Union[int, str]]	The number of GPUs to request.
gpu_flag	Optional[str]	The GPU flag to use for identifying how many GPUs to mount to a pod. This is dependent on the cloud provider.
custom_resources	Optional[Dict]	Any custom resources to request. This is dependent on the cloud provider.

Notes

Most of the fields that support a union of int and str support either specifying a number for the resource, such as 1 CPU, 2 GPU, etc., a str representation of that numerical resource, such as ‘1’ CPU, ‘2’ GPU, etc., but also supports specifying a to be computed value, such as {{inputs.parameters.cpu_request}}. This means tasks, steps, etc., can be stitched together in a way to have a task/step that computes the resource requirements, and then outputs them to the next step/task.

Source code in src/hera/workflows/resources.py

class Resources(_BaseModel):
    """A representation of a collection of resources that are requested to be consumed by a task for execution.

    This follow the K8S definition for resources.

    Attributes:
        cpu_request: The number of CPUs to request, either as a fraction (millicpu), whole number, or a string.
        cpu_limit: The limit of CPUs to request, either as a fraction (millicpu), whole number, or a string.
        memory_request: The amount of memory to request.
        memory_limit: The memory limit of the pod.
        ephemeral_request: The amount of ephemeral storage to request.
        ephemeral_limit: The ephemeral storage limit of the pod.
        gpus: The number of GPUs to request.
        gpu_flag: The GPU flag to use for identifying how many GPUs to mount to a pod. This is dependent on the cloud provider.
        custom_resources: Any custom resources to request. This is dependent on the cloud provider.

    Notes:
        Most of the fields that support a union of `int` and `str` support either specifying a number for the resource,
        such as 1 CPU, 2 GPU, etc., a `str` representation of that numerical resource, such as '1' CPU, '2' GPU, etc., but
        also supports specifying a *to be computed* value, such as `{{inputs.parameters.cpu_request}}`. This means tasks,
        steps, etc., can be stitched together in a way to have a task/step that *computes* the resource requirements, and
        then `outputs` them to the next step/task.
    """

    cpu_request: Optional[Union[float, int, str]] = None
    cpu_limit: Optional[Union[float, int, str]] = None
    memory_request: Optional[str] = None
    memory_limit: Optional[str] = None
    ephemeral_request: Optional[str] = None
    ephemeral_limit: Optional[str] = None
    gpus: Optional[Union[int, str]] = None
    gpu_flag: Optional[str] = "nvidia.com/gpu"
    custom_resources: Optional[Dict] = None

    @root_validator(pre=True)
    def _check_specs(cls, values):
        cpu_request: Optional[Union[float, int, str]] = values.get("cpu_request")
        cpu_limit: Optional[Union[float, int, str]] = values.get("cpu_limit")
        memory_request: Optional[str] = values.get("memory_request")
        memory_limit: Optional[str] = values.get("memory_limit")
        ephemeral_request: Optional[str] = values.get("ephemeral_request")
        ephemeral_limit: Optional[str] = values.get("ephemeral_limit")

        if memory_request is not None:
            validate_memory_units(memory_request)
        if memory_limit is not None:
            validate_memory_units(memory_limit)
            if memory_request is not None:
                assert convert_memory_units(memory_request) <= convert_memory_units(memory_limit), (
                    "Memory request must be smaller or equal to limit"
                )

        if ephemeral_request is not None:
            validate_storage_units(ephemeral_request)
        if ephemeral_limit is not None:
            validate_storage_units(ephemeral_limit)
            if ephemeral_request is not None:
                assert convert_storage_units(ephemeral_request) <= convert_storage_units(ephemeral_limit), (
                    "Ephemeral request must be smaller or equal to limit"
                )

        if cpu_request is not None and isinstance(cpu_request, (int, float)):
            assert cpu_request >= 0, "CPU request must be positive"
        if cpu_limit is not None and isinstance(cpu_limit, (int, float)):
            assert cpu_limit >= 0, "CPU limit must be positive"
            if cpu_request is not None and isinstance(cpu_request, (int, float)):
                assert cpu_request <= cpu_limit, "CPU request must be smaller or equal to limit"

        if cpu_request is not None and isinstance(cpu_request, str):
            validate_cpu_units(cpu_request)
        if cpu_limit is not None and isinstance(cpu_limit, str):
            validate_cpu_units(cpu_limit)
            if cpu_request is not None and isinstance(cpu_request, str):
                assert convert_cpu_units(cpu_request) <= convert_cpu_units(cpu_limit), (
                    "CPU request must be smaller or equal to limit"
                )

        return values

    def build(self) -> _ModelResourceRequirements:
        """Builds the resource requirements of the pod."""
        resources: Dict = dict()

        if self.cpu_limit is not None:
            resources = _merge_dicts(resources, dict(limits=dict(cpu=str(self.cpu_limit))))

        if self.cpu_request is not None:
            resources = _merge_dicts(resources, dict(requests=dict(cpu=str(self.cpu_request))))

        if self.memory_limit is not None:
            resources = _merge_dicts(resources, dict(limits=dict(memory=self.memory_limit)))

        if self.memory_request is not None:
            resources = _merge_dicts(resources, dict(requests=dict(memory=self.memory_request)))

        if self.ephemeral_limit is not None:
            resources = _merge_dicts(resources, dict(limits={"ephemeral-storage": self.ephemeral_limit}))

        if self.ephemeral_request is not None:
            resources = _merge_dicts(resources, dict(requests={"ephemeral-storage": self.ephemeral_request}))

        if self.gpus is not None:
            resources = _merge_dicts(resources, dict(requests={self.gpu_flag: str(self.gpus)}))
            resources = _merge_dicts(resources, dict(limits={self.gpu_flag: str(self.gpus)}))

        if self.custom_resources:
            resources = _merge_dicts(resources, self.custom_resources)

        return _ModelResourceRequirements(**resources)

cpu_limit class-attribute instance-attribute

cpu_limit = None

cpu_request class-attribute instance-attribute

cpu_request = None

custom_resources class-attribute instance-attribute

custom_resources = None

ephemeral_limit class-attribute instance-attribute

ephemeral_limit = None

ephemeral_request class-attribute instance-attribute

ephemeral_request = None

gpu_flag class-attribute instance-attribute

gpu_flag = 'nvidia.com/gpu'

gpus class-attribute instance-attribute

gpus = None

memory_limit class-attribute instance-attribute

memory_limit = None

memory_request class-attribute instance-attribute

memory_request = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Builds the resource requirements of the pod.

Source code in src/hera/workflows/resources.py

def build(self) -> _ModelResourceRequirements:
    """Builds the resource requirements of the pod."""
    resources: Dict = dict()

    if self.cpu_limit is not None:
        resources = _merge_dicts(resources, dict(limits=dict(cpu=str(self.cpu_limit))))

    if self.cpu_request is not None:
        resources = _merge_dicts(resources, dict(requests=dict(cpu=str(self.cpu_request))))

    if self.memory_limit is not None:
        resources = _merge_dicts(resources, dict(limits=dict(memory=self.memory_limit)))

    if self.memory_request is not None:
        resources = _merge_dicts(resources, dict(requests=dict(memory=self.memory_request)))

    if self.ephemeral_limit is not None:
        resources = _merge_dicts(resources, dict(limits={"ephemeral-storage": self.ephemeral_limit}))

    if self.ephemeral_request is not None:
        resources = _merge_dicts(resources, dict(requests={"ephemeral-storage": self.ephemeral_request}))

    if self.gpus is not None:
        resources = _merge_dicts(resources, dict(requests={self.gpu_flag: str(self.gpus)}))
        resources = _merge_dicts(resources, dict(limits={self.gpu_flag: str(self.gpus)}))

    if self.custom_resources:
        resources = _merge_dicts(resources, self.custom_resources)

    return _ModelResourceRequirements(**resources)

RetryPolicy

An enum that holds options for retry policy.

Source code in src/hera/workflows/retry_strategy.py

class RetryPolicy(Enum):
    """An enum that holds options for retry policy."""

    always = "Always"
    """Retry all failed steps"""

    on_failure = "OnFailure"
    """Retry steps whose main container is marked as failed in Kubernetes"""

    on_error = "OnError"
    """Retry steps that encounter Argo controller errors, or whose init or wait containers fail"""

    on_transient_error = "OnTransientError"
    """Retry steps that encounter errors defined as transient, or errors matching the `TRANSIENT_ERROR_PATTERN`
    environment variable.
    Available in version 3.0 and later.
    """

    def __str__(self) -> str:
        """Assembles the `value` representation of the enum as a string."""
        return str(self.value)

always class-attribute instance-attribute

always = 'Always'

Retry all failed steps

on_error class-attribute instance-attribute

on_error = 'OnError'

Retry steps that encounter Argo controller errors, or whose init or wait containers fail

on_failure class-attribute instance-attribute

on_failure = 'OnFailure'

Retry steps whose main container is marked as failed in Kubernetes

on_transient_error class-attribute instance-attribute

on_transient_error = 'OnTransientError'

Retry steps that encounter errors defined as transient, or errors matching the TRANSIENT_ERROR_PATTERN environment variable. Available in version 3.0 and later.

RetryStrategy

RetryStrategy configures how an Argo job should retry.

Source code in src/hera/workflows/retry_strategy.py

class RetryStrategy(_BaseModel):
    """`RetryStrategy` configures how an Argo job should retry."""

    affinity: Optional[RetryAffinity] = None
    """affinity dictates the affinity of the retried jobs"""

    backoff: Optional[Backoff] = None
    """backoff dictates how long should a job wait for before retrying"""

    expression: Optional[str] = None
    """the expression field supports the expression of complex rules regarding retry behavior"""

    limit: Optional[Union[int, str, IntOrString]] = None
    """the hard numeric limit of how many times a jobs should retry"""

    retry_policy: Optional[Union[str, RetryPolicy]] = None
    """the policy dictates, at a high level, under what conditions should a job retry"""

    @validator("retry_policy", pre=True)
    def _convert_retry_policy(cls, v):
        """Converts the `retry_policy` field into a pure `str` from either `str` already or an enum."""
        if v is None or isinstance(v, str):
            return v

        v = cast(RetryPolicy, v)
        return v.value

    @validator("limit", pre=True)
    def _convert_limit(cls, v) -> Optional[IntOrString]:
        """Converts the `limit` field from the union specification into a `str`."""
        if v is None or isinstance(v, IntOrString):
            return v

        return IntOrString(__root__=v)

    def build(self) -> _ModelRetryStrategy:
        """Builds the generated `RetryStrategy` representation of the retry strategy."""
        return _ModelRetryStrategy(
            affinity=self.affinity,
            backoff=self.backoff,
            expression=self.expression,
            limit=self.limit,  # type: ignore
            retry_policy=str(self.retry_policy) if self.retry_policy is not None else None,
        )

affinity class-attribute instance-attribute

affinity = None

affinity dictates the affinity of the retried jobs

backoff class-attribute instance-attribute

backoff = None

backoff dictates how long should a job wait for before retrying

expression class-attribute instance-attribute

expression = None

the expression field supports the expression of complex rules regarding retry behavior

limit class-attribute instance-attribute

limit = None

the hard numeric limit of how many times a jobs should retry

retry_policy class-attribute instance-attribute

retry_policy = None

the policy dictates, at a high level, under what conditions should a job retry

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

build

build()

Builds the generated RetryStrategy representation of the retry strategy.

Source code in src/hera/workflows/retry_strategy.py

def build(self) -> _ModelRetryStrategy:
    """Builds the generated `RetryStrategy` representation of the retry strategy."""
    return _ModelRetryStrategy(
        affinity=self.affinity,
        backoff=self.backoff,
        expression=self.expression,
        limit=self.limit,  # type: ignore
        retry_policy=str(self.retry_policy) if self.retry_policy is not None else None,
    )

RunnerScriptConstructor

RunnerScriptConstructor is a script constructor that runs a script in a container.

The runner script, also known as “The Hera runner”, takes a script/Python function definition, infers the path to the function (module import), assembles a path to invoke the function, and passes any specified parameters to the function. This helps users “save” on the source space required for submitting a function for remote execution on Argo. Execution within the container requires the executing container to include the file that contains the submitted script. More specifically, the container must be created in some process (e.g. CI), so that it conains the script to run remotely.

Source code in src/hera/workflows/script.py

class RunnerScriptConstructor(ScriptConstructor):
    """`RunnerScriptConstructor` is a script constructor that runs a script in a container.

    The runner script, also known as "The Hera runner", takes a script/Python function definition, infers the path
    to the function (module import), assembles a path to invoke the function, and passes any specified parameters
    to the function. This helps users "save" on the `source` space required for submitting a function for remote
    execution on Argo. Execution within the container *requires* the executing container to include the file that
    contains the submitted script. More specifically, the container must be created in some process (e.g. CI), so that
    it conains the script to run remotely.
    """

    outputs_directory: Optional[str] = None
    """Used for saving outputs when defined using annotations."""

    volume_for_outputs: Optional[_BaseVolume] = None
    """Volume to use if saving outputs when defined using annotations."""

    DEFAULT_HERA_OUTPUTS_DIRECTORY: str = "/tmp/hera-outputs"
    """Used as the default value for when the outputs_directory is not set"""

    pydantic_mode: Optional[Literal[1, 2]] = None
    """Used for selecting the pydantic version used for BaseModels.
    Allows for using pydantic.v1 BaseModels with pydantic v2.
    Defaults to the installed version of Pydantic."""

    @validator("pydantic_mode", always=True)
    def _pydantic_mode(cls, value: Optional[Literal[1, 2]]) -> Optional[Literal[1, 2]]:
        if value and value > _PYDANTIC_VERSION:
            raise ValueError("v2 pydantic mode only available for pydantic>=2")
        return value

    def transform_values(self, cls: Type[Script], values: Any) -> Any:
        """A function that can inspect the Script instance and generate the source field."""
        if not callable(values.get("source")):
            return values

        if values.get("args") is not None:
            raise ValueError("Cannot specify args when callable is True")
        values["args"] = [
            "-m",
            "hera.workflows.runner",
            "-e",
            f"{values['source'].__module__}:{values['source'].__name__}",
        ]

        return values

    def generate_source(self, instance: Script) -> str:
        """A function that can inspect the Script instance and generate the source field."""
        return f"{g.inputs.parameters:$}"

    def transform_script_template_post_build(
        self, instance: "Script", script: _ModelScriptTemplate
    ) -> _ModelScriptTemplate:
        """A hook to transform the generated script template."""
        script_env = []

        if self.outputs_directory:
            script_env.append(EnvVar(name="hera__outputs_directory", value=self.outputs_directory))
        if self.pydantic_mode:
            script_env.append(EnvVar(name="hera__pydantic_mode", value=str(self.pydantic_mode)))
        if _flag_enabled(_SCRIPT_PYDANTIC_IO_FLAG):
            script_env.append(EnvVar(name="hera__script_pydantic_io", value=""))

        if script_env:
            if not script.env:
                # If user did not set any env vars themselves then we need to initialise the list
                script.env = []

            script.env.extend(script_env)

        return script

DEFAULT_HERA_OUTPUTS_DIRECTORY class-attribute instance-attribute

DEFAULT_HERA_OUTPUTS_DIRECTORY = '/tmp/hera-outputs'

Used as the default value for when the outputs_directory is not set

outputs_directory class-attribute instance-attribute

outputs_directory = None

Used for saving outputs when defined using annotations.

pydantic_mode class-attribute instance-attribute

pydantic_mode = None

Used for selecting the pydantic version used for BaseModels. Allows for using pydantic.v1 BaseModels with pydantic v2. Defaults to the installed version of Pydantic.

volume_for_outputs class-attribute instance-attribute

volume_for_outputs = None

Volume to use if saving outputs when defined using annotations.

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

generate_source

generate_source(instance)

A function that can inspect the Script instance and generate the source field.

Source code in src/hera/workflows/script.py

def generate_source(self, instance: Script) -> str:
    """A function that can inspect the Script instance and generate the source field."""
    return f"{g.inputs.parameters:$}"

transform_script_template_post_build

transform_script_template_post_build(instance, script)

A hook to transform the generated script template.

Source code in src/hera/workflows/script.py

def transform_script_template_post_build(
    self, instance: "Script", script: _ModelScriptTemplate
) -> _ModelScriptTemplate:
    """A hook to transform the generated script template."""
    script_env = []

    if self.outputs_directory:
        script_env.append(EnvVar(name="hera__outputs_directory", value=self.outputs_directory))
    if self.pydantic_mode:
        script_env.append(EnvVar(name="hera__pydantic_mode", value=str(self.pydantic_mode)))
    if _flag_enabled(_SCRIPT_PYDANTIC_IO_FLAG):
        script_env.append(EnvVar(name="hera__script_pydantic_io", value=""))

    if script_env:
        if not script.env:
            # If user did not set any env vars themselves then we need to initialise the list
            script.env = []

        script.env.extend(script_env)

    return script

transform_template_post_build

transform_template_post_build(instance, template)

A hook to transform the generated template.

Source code in src/hera/workflows/script.py

def transform_template_post_build(self, instance: "Script", template: _ModelTemplate) -> _ModelTemplate:
    """A hook to transform the generated template."""
    return template

transform_values

transform_values(cls, values)

A function that can inspect the Script instance and generate the source field.

Source code in src/hera/workflows/script.py

def transform_values(self, cls: Type[Script], values: Any) -> Any:
    """A function that can inspect the Script instance and generate the source field."""
    if not callable(values.get("source")):
        return values

    if values.get("args") is not None:
        raise ValueError("Cannot specify args when callable is True")
    values["args"] = [
        "-m",
        "hera.workflows.runner",
        "-e",
        f"{values['source'].__module__}:{values['source'].__name__}",
    ]

    return values

S3Artifact

An artifact sourced from AWS S3.

Source code in src/hera/workflows/artifact.py

class S3Artifact(_ModelS3Artifact, Artifact):
    """An artifact sourced from AWS S3."""

    def _build_artifact(self) -> _ModelArtifact:
        artifact = super()._build_artifact()
        artifact.s3 = _ModelS3Artifact(
            access_key_secret=self.access_key_secret,
            bucket=self.bucket,
            create_bucket_if_not_present=self.create_bucket_if_not_present,
            encryption_options=self.encryption_options,
            endpoint=self.endpoint,
            insecure=self.insecure,
            key=self.key,
            region=self.region,
            role_arn=self.role_arn,
            secret_key_secret=self.secret_key_secret,
            use_sdk_creds=self.use_sdk_creds,
        )
        return artifact

    @classmethod
    def _get_input_attributes(cls):
        """Return the attributes used for input artifact annotations."""
        return super()._get_input_attributes() + [
            "access_key_secret",
            "bucket",
            "create_bucket_if_not_present",
            "encryption_options",
            "endpoint",
            "insecure",
            "key",
            "region",
            "role_arn",
            "secret_key_secret",
            "use_sdk_creds",
        ]

access_key_secret class-attribute instance-attribute

access_key_secret = None

archive class-attribute instance-attribute

archive = None

artifact archiving configuration

archive_logs class-attribute instance-attribute

archive_logs = None

whether to log the archive object

artifact_gc class-attribute instance-attribute

artifact_gc = None

artifact garbage collection configuration

bucket class-attribute instance-attribute

bucket = None

ca_secret class-attribute instance-attribute

ca_secret = None

create_bucket_if_not_present class-attribute instance-attribute

create_bucket_if_not_present = None

deleted class-attribute instance-attribute

deleted = None

whether the artifact is deleted

encryption_options class-attribute instance-attribute

encryption_options = None

endpoint class-attribute instance-attribute

endpoint = None

from_ class-attribute instance-attribute

from_ = None

configures the artifact task/step origin

from_expression class-attribute instance-attribute

from_expression = None

an expression that dictates where to obtain the artifact from

global_name class-attribute instance-attribute

global_name = None

global workflow artifact name

insecure class-attribute instance-attribute

insecure = None

key class-attribute instance-attribute

key = None

loader class-attribute instance-attribute

loader = None

used for input Artifact annotations for determining how to load the data.

Note: A loader value of ‘None’ must be used with an underlying type of ‘str’ or Path-like class.

mode class-attribute instance-attribute

mode = None

mode bits to use on the artifact, must be a value between 0 and 0777 set when loading input artifacts.

name instance-attribute

name

name of the artifact

optional class-attribute instance-attribute

optional = None

whether the Artifact is optional. For an input Artifact, this means it may possibly not exist at the specified path during the template’s runtime. For an output Artifact, it may possibly not be generated during the step/task and available as an output to subsequent steps/tasks.

output class-attribute instance-attribute

output = False

used to specify artifact as an output in function signature annotations

path class-attribute instance-attribute

path = None

path where the artifact should be placed/loaded from

recurse_mode class-attribute instance-attribute

recurse_mode = None

recursion mode when applying the permissions of the artifact if it is an artifact folder

region class-attribute instance-attribute

region = None

role_arn class-attribute instance-attribute

role_arn = None

secret_key_secret class-attribute instance-attribute

secret_key_secret = None

session_token_secret class-attribute instance-attribute

session_token_secret = None

sub_path class-attribute instance-attribute

sub_path = None

allows the specification of an artifact from a subpath within the main source.

use_sdk_creds class-attribute instance-attribute

use_sdk_creds = None

Config

Config class dictates the behavior of the underlying Pydantic model.

See Pydantic documentation for more info.

Source code in src/hera/shared/_pydantic.py

class Config:
    """Config class dictates the behavior of the underlying Pydantic model.

    See Pydantic documentation for more info.
    """

    allow_population_by_field_name = True
    """support populating Hera object fields by their Field alias"""

    allow_mutation = True
    """supports mutating Hera objects post instantiation"""

    use_enum_values = True
    """supports using enums, which are then unpacked to obtain the actual `.value`, on Hera objects"""

    arbitrary_types_allowed = True
    """supports specifying arbitrary types for any field to support Hera object fields processing"""

    smart_union = True
    """uses smart union for matching a field's specified value to the underlying type that's part of a union"""

allow_mutation class-attribute instance-attribute

allow_mutation = True

supports mutating Hera objects post instantiation

allow_population_by_field_name class-attribute instance-attribute

allow_population_by_field_name = True

support populating Hera object fields by their Field alias

arbitrary_types_allowed class-attribute instance-attribute

arbitrary_types_allowed = True

supports specifying arbitrary types for any field to support Hera object fields processing

smart_union class-attribute instance-attribute

smart_union = True

uses smart union for matching a field’s specified value to the underlying type that’s part of a union

use_enum_values class-attribute instance-attribute

use_enum_values = True

supports using enums, which are then unpacked to obtain the actual .value, on Hera objects

as_name

as_name(name)

DEPRECATED, use with_name.

Returns a ‘built’ copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def as_name(self, name: str) -> _ModelArtifact:
    """DEPRECATED, use with_name.

    Returns a 'built' copy of the current artifact, renamed using the specified `name`.
    """
    logger.warning("'as_name' is deprecated, use 'with_name'")
    artifact = self._build_artifact()
    artifact.name = name
    return artifact

with_name

with_name(name)

Returns a copy of the current artifact, renamed using the specified name.

Source code in src/hera/workflows/artifact.py

def with_name(self, name: str) -> Artifact:
    """Returns a copy of the current artifact, renamed using the specified `name`."""
    artifact = self.copy(deep=True)
    artifact.name = name
    return artifact

ScaleIOVolume

ScaleIOVolume represents a ScaleIO volume to mount to the container.

Source code in src/hera/workflows/volume.py

class ScaleIOVolume(_BaseVolume, _ModelScaleIOVolumeSource):
    """`ScaleIOVolume` represents a ScaleIO volume to mount to the container."""

    def _build_volume(self) -> _ModelVolume:
        assert self.name
        return _ModelVolume(
            name=self.name,
            scale_io=_ModelScaleIOVolumeSource(
                fs_type=self.fs_type,
                gateway=self.gateway,
                protection_domain=self.protection_domain,
                read_only=self.read_only,
                secret_ref=self.secret_ref,
                ssl_enabled=self.ssl_enabled,
                storage_mode=self.storage_mode,
                storage_pool=self.storage_pool,
                system=self.system,
                volume_name=self.volume_name,
            ),
        )

fs_type class-attribute instance-attribute

fs_type = None

gateway instance-attribute

gateway

mount_path class-attribute instance-attribute

mount_path = None

mount_propagation class-attribute instance-attribute

mount_propagation = None

name class-attribute instance-attribute

name = None

protection_domain class-attribute instance-attribute

protection_domain = None