adp.ingest.dataclasses.IngestSettings

class adp.ingest.dataclasses.IngestSettings(*, keys: List[str] | None = None, select: List[str] | None = None, exclude: List[str] | None = None, max_depth: int | None = None, datatypes: List[DataType] | None = None, maskings: List[Masking] | None = None, append_type: AppendTypeEnum | None = None, merge_type: MergeTypeEnum | None = None, delete_null_keys: bool | None = False, silver_type: SilverTypeEnum = SilverTypeEnum.merge_and_delete, type_escalation_mode: TypeEscalationModeEnum = TypeEscalationModeEnum.strict, default_datatype: DefaultDataTypeEnum = DefaultDataTypeEnum.infer, can_rewrite_history: bool = False, ignore_missing_columns: bool = False, columns_to_lowercase: bool = True, persist_storage_level: PersistStorageLevelEnum | None = PersistStorageLevelEnum.off_heap, unpersist_blocking: bool = False, spark_config: Dict[str, Any] | None = None)

__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.

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
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

keys_underscored
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.
keys
select
exclude
max_depth
datatypes
maskings
append_type
merge_type
delete_null_keys
silver_type
type_escalation_mode
default_datatype
can_rewrite_history
ignore_missing_columns
columns_to_lowercase
persist_storage_level
unpersist_blocking
spark_config

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].