tsdat.config.dataset

Classes

DatasetConfig

Defines the structure and metadata of the dataset produced by a tsdat pipeline.

class tsdat.config.dataset.DatasetConfig

Bases: tsdat.config.utils.YamlModel

Defines the structure and metadata of the dataset produced by a tsdat pipeline.

Also provides methods to support yaml parsing and validation, including generation of json schema.

Parameters

• attrs (GlobalAttributes) – Attributes that pertain to the dataset as a whole.

• coords (Dict[str, Coordinate]) – The dataset’s coordinate variables.

• data_vars (Dict[str, Variable]) – The dataset’s data variables.

attrs :tsdat.config.attributes.GlobalAttributes

coords :Dict[str, tsdat.config.variables.Coordinate]

data_vars :Dict[str, tsdat.config.variables.Variable]

Class Methods

__contains__
__getitem__
set_variable_name_property
time_in_coords
validate_variable_name_uniqueness
variable_names_are_legal

Method Descriptions

__contains__(self, __o: object) → bool

__getitem__(self, name: str) → Union[tsdat.config.variables.Variable, tsdat.config.variables.Coordinate]

classmethod set_variable_name_property(cls, vars: Dict[str, Dict[str, Any]]) → Dict[str, Dict[str, Any]]

classmethod time_in_coords(cls, coords: Dict[str, tsdat.config.variables.Coordinate]) → Dict[str, tsdat.config.variables.Coordinate]

classmethod validate_variable_name_uniqueness(cls, values: Any) → Any

variable_names_are_legal(cls, vars: Dict[str, tsdat.config.variables.Variable], field: pydantic.fields.ModelField) → Dict[str, tsdat.config.variables.Variable]