ZoningSystemMetaData

class caf.base.zoning.ZoningSystemMetaData(*, name, shapefile_id_col=None, shapefile_path=None, extra_columns=None)

Bases: BaseConfig

Class to store metadata relating to zoning systems in normits_demand.

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.
name
shapefile_id_col
shapefile_path
extra_columns

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)
from_yaml(text)	Parse class attributes from YAML text.
json(*[, include, exclude, by_alias, ...])
load_yaml(path)	Read YAML file and load the data using from_yaml.
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, ...])
save_yaml(path[, datetime_comment, ...])	Write data from self to a YAML file.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
to_yaml()	Convert attributes from self to YAML string.
update_forward_refs(**localns)
validate(value)
write_example(path_, /[, comment_])	Write examples to a config file.

Attributes Documentation

Parameters:

• name (str | None)

• shapefile_id_col (str | None)

• shapefile_path (Path | None)

• extra_columns (list[str] | None)

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.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields = {'extra_columns': FieldInfo(annotation=Union[list[str], NoneType], required=False, default=None), 'name': FieldInfo(annotation=Union[str, NoneType], required=True), 'shapefile_id_col': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'shapefile_path': FieldInfo(annotation=Union[Path, NoneType], required=False, default=None)}

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

name: str | None

shapefile_id_col: str | None

shapefile_path: Path | None

extra_columns: list[str] | None