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], diagnostics_from: AmdarDiagnosticCmpSource = AmdarDiagnosticCmpSource.EVALUATION, save_harmonised_data: bool = True, diagnostic_validation: DiagnosticValidationConfig | None = None)[source]#

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)])

  • diagnostics_from (Annotated[AmdarDiagnosticCmpSource, FieldInfo(annotation=NoneType, required=False, default=<AmdarDiagnosticCmpSource.EVALUATION: 'evaluation'>, description='Which data (thus diagnostics) should be amdar data be compared against', frozen=True)])

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

  • diagnostic_validation (Annotated[DiagnosticValidationConfig | None, FieldInfo(annotation=NoneType, required=False, default=None, description='Diagnostic validation configuration', frozen=True)])

__init__(**data: Any) → None[source]#

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_diagnostic_validation_conditions()

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, ensure_ascii, ...])

!!! 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, extra, ...])

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

diagnostics_from

save_harmonised_data

diagnostic_validation

data_dir

data_source