AmdarConfig

class rojak.orchestrator.configuration.AmdarConfig(*, data_dir: Annotated[Path, AfterValidator(func=_dir_must_exist)], data_source: AmdarDataSource, glob_pattern: str, time_window: Limits[datetime], harmonisation_strategies: list[DiagnosticsAmdarHarmonisationStrategyOptions], save_harmonised_data: bool = True)

Bases: BaseInputDataConfig[AmdarDataSource]

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• data_dir (Annotated[Path, FieldInfo(annotation=NoneType, required=True, description='Path to directory containing the data', frozen=True), AfterValidator(func=~rojak.orchestrator.configuration._dir_must_exist)])

• data_source (Annotated[T, FieldInfo(annotation=NoneType, required=True, description='Where data comes from', frozen=True)])

• glob_pattern (Annotated[str, FieldInfo(annotation=NoneType, required=True, description='Glob pattern to match to get the data files', frozen=True)])

• time_window (Annotated[Limits[datetime], FieldInfo(annotation=NoneType, required=True, description='Time window to extract data for', frozen=True)])

• harmonisation_strategies (Annotated[list[DiagnosticsAmdarHarmonisationStrategyOptions], FieldInfo(annotation=NoneType, required=True, description='List of harmonisation strategies', frozen=True)])

• save_harmonised_data (Annotated[bool, FieldInfo(annotation=NoneType, required=False, default=True, description='Save harmonised data', frozen=True)])

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
check_time_window_increasing()
check_valid_glob_pattern()
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
from_yaml(path)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, include, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
glob_pattern
time_window
harmonisation_strategies
save_harmonised_data
data_dir
data_source