Automation

*,
__typename: Literal['Trigger'] = 'Trigger',
id: typing.Annotated[str, Strict(strict=True)],
createdAt: datetime.datetime,
updatedAt: datetime.datetime | None = None,
name: str,
description: str | None,
enabled: bool,
scope: typing.Annotated[wandb.automations.scopes._ArtifactSequenceScope | wandb.automations.scopes._ArtifactPortfolioScope | wandb.automations.scopes.ProjectScope, BeforeValidator(func=<function parse_scope>, json_schema_input_type=PydanticUndefined)],
event: wandb.automations.events.SavedEvent,
action: typing.Annotated[wandb.automations.actions.SavedLaunchJobAction | wandb.automations.actions.SavedNotificationAction | wandb.automations.actions.SavedWebhookAction | wandb.automations.actions.SavedNoOpAction, BeforeValidator(func=<function parse_saved_action>, json_schema_input_type=PydanticUndefined)]

Description

A local instance of a saved W&B automation that supports editing.

Args

• __typename:
• id:
• createdAt:
• updatedAt:
• name:
• description:
• enabled:
• scope:
• event:
• action:

Methods

method construct

_fields_set: 'set[str] | None' = None, **values: 'Any'

Arguments

• _fields_set:
• values:

method copy

self, *,
include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
update: 'Dict[str, Any] | None' = None,
deep: 'bool' = False

Returns a copy of the model.

!!! warning “Deprecated” This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Arguments

• include: Optional set or mapping specifying which fields to include in the copied model.
• exclude: Optional set or mapping specifying which fields to exclude in the copied model.
• update: Optional dictionary of field-value pairs to override field values in the copied model.
• deep: If True, the values of fields that are Pydantic models will be deep-copied.

method dict

self, *,
include: 'IncEx | None' = None,
exclude: 'IncEx | None' = None,
by_alias: 'bool' = False,
exclude_unset: 'bool' = False,
exclude_defaults: 'bool' = False,
exclude_none: 'bool' = False

Arguments

• include:
• exclude:
• by_alias:
• exclude_unset:
• exclude_defaults:
• exclude_none:

method from_orm

obj: 'Any'

Arguments

• obj:

method json

self, *,
include: 'IncEx | None' = None,
exclude: 'IncEx | None' = None,
by_alias: 'bool' = False,
exclude_unset: 'bool' = False,
exclude_defaults: 'bool' = False,
exclude_none: 'bool' = False,
encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
models_as_dict: 'bool' = PydanticUndefined, **dumps_kwargs: 'Any'

Arguments

• include:
• exclude:
• by_alias:
• exclude_unset:
• exclude_defaults:
• exclude_none:
• encoder:
• models_as_dict:
• dumps_kwargs:

method model_construct

_fields_set: 'set[str] | None' = None, **values: 'Any'

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Arguments

• _fields_set: A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.
• values: Trusted or pre-validated data dictionary.

method model_copy

self, *,
update: 'Mapping[str, Any] | None' = None,
deep: 'bool' = False

!!! abstract “Usage Documentation” model_copy

Returns a copy of the model.

!!! note The underlying instance’s [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Arguments

• update: Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
• deep: Set to True to make a deep copy of the model.

method model_dump

self, *,
mode: 'str' = 'json', **kwargs: 'Any'

!!! abstract “Usage Documentation” model_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Arguments

• mode: The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.
• kwargs:

method model_dump_json

self, *,
indent: 'int | None' = None, **kwargs: 'Any'

!!! abstract “Usage Documentation” model_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Arguments

• indent: Indentation to use in the JSON output. If None is passed, the output will be compact.
• kwargs:

method model_json_schema

by_alias: 'bool' = True,
ref_template: 'str' = '#/$defs/{model}',
schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
mode: 'JsonSchemaMode' = 'validation'

Generates a JSON schema for a model class.

Arguments

• by_alias: Whether to use attribute aliases or not.
• ref_template: The reference template.
• schema_generator: To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications
• mode: The mode in which to generate the schema.

method model_parametrized_name

params: 'tuple[type[Any], ...]'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Arguments

• params: Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Raises

• TypeError: Raised when trying to generate concrete names for non-generic models.

method model_post_init

self,
context: 'Any', /

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Arguments

• context:

method model_rebuild

*,
force: 'bool' = False,
raise_errors: 'bool' = True,
_parent_namespace_depth: 'int' = 2,
_types_namespace: 'MappingNamespace | None' = None

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Arguments

• force: Whether to force the rebuilding of the model schema, defaults to False.
• raise_errors: Whether to raise errors, defaults to True.
• _parent_namespace_depth: The depth level of the parent namespace, defaults to 2.
• _types_namespace: The types namespace, defaults to None.

method model_validate

obj: 'Any', *,
strict: 'bool | None' = None,
from_attributes: 'bool | None' = None,
context: 'Any | None' = None,
by_alias: 'bool | None' = None,
by_name: 'bool | None' = None

Validate a pydantic model instance.

Arguments

• obj: The object to validate.
• strict: Whether to enforce types strictly.
• from_attributes: Whether to extract data from object attributes.
• context: Additional context to pass to the validator.
• by_alias: Whether to use the field’s alias when validating against the provided input data.
• by_name: Whether to use the field’s name when validating against the provided input data.

Raises

• ValidationError: If the object could not be validated.

method model_validate_json

json_data: 'str | bytes | bytearray', *,
strict: 'bool | None' = None,
context: 'Any | None' = None,
by_alias: 'bool | None' = None,
by_name: 'bool | None' = None

!!! abstract “Usage Documentation” JSON Parsing

Validate the given JSON data against the Pydantic model.

Arguments

• json_data: The JSON data to validate.
• strict: Whether to enforce types strictly.
• context: Extra variables to pass to the validator.
• by_alias: Whether to use the field’s alias when validating against the provided input data.
• by_name: Whether to use the field’s name when validating against the provided input data.

Raises

• ValidationError: If json_data is not a JSON string or the object could not be validated.

method model_validate_strings

obj: 'Any', *,
strict: 'bool | None' = None,
context: 'Any | None' = None,
by_alias: 'bool | None' = None,
by_name: 'bool | None' = None

Validate the given object with string data against the Pydantic model.

Arguments

• obj: The object containing string data to validate.
• strict: Whether to enforce types strictly.
• context: Extra variables to pass to the validator.
• by_alias: Whether to use the field’s alias when validating against the provided input data.
• by_name: Whether to use the field’s name when validating against the provided input data.

method parse_file

path: 'str | Path', *,
content_type: 'str | None' = None,
encoding: 'str' = 'utf8',
proto: 'DeprecatedParseProtocol | None' = None,
allow_pickle: 'bool' = False

Arguments

• path:
• content_type:
• encoding:
• proto:
• allow_pickle:

method parse_obj

obj: 'Any'

Arguments

• obj:

method parse_raw

b: 'str | bytes', *,
content_type: 'str | None' = None,
encoding: 'str' = 'utf8',
proto: 'DeprecatedParseProtocol | None' = None,
allow_pickle: 'bool' = False

Arguments

• b:
• content_type:
• encoding:
• proto:
• allow_pickle:

method schema

by_alias: 'bool' = True,
ref_template: 'str' = '#/$defs/{model}'

Arguments

• by_alias:
• ref_template:

method schema_json

*,
by_alias: 'bool' = True,
ref_template: 'str' = '#/$defs/{model}', **dumps_kwargs: 'Any'

Arguments

• by_alias:
• ref_template:
• dumps_kwargs:

method update_forward_refs

**localns: 'Any'

Arguments

• localns:

method validate

value: 'Any'

Arguments

• value: