oceanum.datamesh.Datasource#

pydantic model oceanum.datamesh.Datasource[source]#

Datasource

field coordinates: Dict[Coordinates, str] = {}#

Coordinates in datasource, referenced by standard coordinate keys. The dictionary keys map to coordinates variables in the datasource.

Ensemble: “e”
Rasterband: “b”
Category: “c”
Quantile: “q”
Season: “s”
Month: “m”
Time: “t”
Vertical: “z”
Northing: “y”
Easting: “x”
Station: “s” (Locations assumed stationary, datasource with a multigeometry indexed by station coordinate)
Geometry: “g” (Abstract coordinate - a 2 or 3D geometry that defines a feature location)
Frequency: “f”
Direction: “d”
Other 1: “i” (any other arbitrary coordinate)
Other 2: “j” (any other arbitrary coordinate)
Other 3: “k” (any other arbitrary coordinate)

Example {“t”:”time”,”x”:”longitude”,”y”:”latitude”}

field created: datetime | None = datetime.datetime(2026, 4, 23, 19, 21, 8, 358383, tzinfo=datetime.timezone.utc)#: Time when the datasource was first created

field dataschema: Schema | None = Schema(attrs={}, dims={}, coords={}, data_vars={}) (alias 'schema')#: Datasource schema

field description: str | None = ''#

Description of datasource

Constraints:

max_length = 1500

field details: AnyHttpUrl | None = None#: URL to further details about the datasource

field driver: str [Required]#

field driver_args: dict | None = {} (alias 'args')#: Driver arguments for datasource. These are driver dependent.

field expires: datetime | None = None#: Time when the datasource expires and should get automatically deleted

field geom: Annotated[Point | MultiPoint | Polygon, _GeometryAnnotation] | None = None#: Valid shapely or geoJSON geometry describing the spatial extent of the datasource

field id: str [Required]#

Unique ID for the datasource

Constraints:

min_length = 3
max_length = 80
pattern = ^[a-z0-9-_]+$

Validated by:

validate_id

field info: dict | None = {}#: Additional datasource descriptive metadata

field labels: list | None = []#: Metadata labels related to the datasource. A given label can only be owned by one organisation.

field modified: datetime | None = datetime.datetime(2026, 4, 23, 19, 21, 8, 358351, tzinfo=datetime.timezone.utc)#: Last time datasource was modified

field name: str [Required]#

Human readable name for the datasource

Constraints:

max_length = 128

field parameters: dict | None = {}#: Additional parameters for accessing datasource

field parchive: Annotated[timedelta, BeforeValidator(func=parse_period, json_schema_input_type=PydanticUndefined)] | None = None#: Duration of a rolling archive (time before present). Must be a valid ISO8601 interval string or None.

field pforecast: Annotated[timedelta, BeforeValidator(func=parse_period, json_schema_input_type=PydanticUndefined)] | None = None#: Duration of a forecast horizon (time after present). Must be a valid ISO8601 interval string or None.

field tags: list | None = []#: Metadata keyword tags related to the datasource

field tend: datetime | None = None#: Latest time in datasource. Must be a valid ISO8601 datetime string

field tstart: datetime | None = None#: Earliest time in datasource. Must be a valid ISO8601 datetime string

model_post_init(context: Any, /) → None#

This function is meant to behave like a BaseModel method to initialize private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

self – The BaseModel instance.
context – The context.

validator validate_id » id [source]#

property attributes#: Datasource global attributes. Note that these are None (undefined) for a summary dataset.

property bounds#

Bounding box of datasource geographical extent

Type:: list[float]

property geometry#

property variables#: Datasource variables. Note that these are None (undefined) for a summary dataset.

Table of Contents

oceanum.datamesh.Datasource#