Source code for openeo.udf.udf_data



# Note: this module was initially developed under the ``openeo-udf`` project (

from typing import Optional, List, Union

from openeo.udf.feature_collection import FeatureCollection
from openeo.udf.structured_data import StructuredData
from openeo.udf.xarraydatacube import XarrayDataCube

[docs]class UdfData: """ Container for data passed to a user defined function (UDF) """ # TODO: original implementation in `openeo_udf` project had `get_datacube_by_id`, `get_feature_collection_by_id`: is it still useful to provide this? # TODO: original implementation in `openeo_udf` project had `server_context`: is it still useful to provide this? def __init__( self, proj: dict = None, datacube_list: Optional[List[XarrayDataCube]] = None, feature_collection_list: Optional[List[FeatureCollection]] = None, structured_data_list: Optional[List[StructuredData]] = None, user_context: Optional[dict] = None, ): """ The constructor of the UDF argument class that stores all data required by the user defined function. :param proj: A dictionary of form {"proj type string": "projection description"} i. e. {"EPSG":4326} :param datacube_list: A list of data cube objects :param feature_collection_list: A list of VectorTile objects :param structured_data_list: A list of structured data objects """ self.datacube_list = datacube_list self.feature_collection_list = feature_collection_list self.structured_data_list = structured_data_list self.proj = proj self._user_context = user_context or {} def __repr__(self) -> str: fields = " ".join( f"{f}:{getattr(self, f)!r}" for f in ["datacube_list", "feature_collection_list", "structured_data_list"] ) return f"<{type(self).__name__} {fields}>" @property def user_context(self) -> dict: """Return the user context that was passed to the run_udf function""" return self._user_context
[docs] def get_datacube_list(self) -> Union[List[XarrayDataCube], None]: """Get the data cube list""" return self._datacube_list
[docs] def set_datacube_list(self, datacube_list: Union[List[XarrayDataCube], None]): """ Set the data cube list :param datacube_list: A list of data cubes """ self._datacube_list = datacube_list
datacube_list = property(fget=get_datacube_list, fset=set_datacube_list)
[docs] def get_feature_collection_list(self) -> Union[List[FeatureCollection], None]: """get all feature collections as list""" return self._feature_collection_list
def set_feature_collection_list(self, feature_collection_list: Union[List[FeatureCollection], None]): self._feature_collection_list = feature_collection_list feature_collection_list = property(fget=get_feature_collection_list, fset=set_feature_collection_list)
[docs] def get_structured_data_list(self) -> Union[List[StructuredData], None]: """ Get all structured data entries :return: A list of StructuredData objects """ return self._structured_data_list
[docs] def set_structured_data_list(self, structured_data_list: Union[List[StructuredData], None]): """ Set the list of structured data :param structured_data_list: A list of StructuredData objects """ self._structured_data_list = structured_data_list
structured_data_list = property(fget=get_structured_data_list, fset=set_structured_data_list)
[docs] def to_dict(self) -> dict: """ Convert this UdfData object into a dictionary that can be converted into a valid JSON representation """ return { "datacubes": [x.to_dict() for x in self.datacube_list] \ if self.datacube_list else None, "feature_collection_list": [x.to_dict() for x in self.feature_collection_list] \ if self.feature_collection_list else None, "structured_data_list": [x.to_dict() for x in self.structured_data_list] \ if self.structured_data_list else None, "proj": self.proj, "user_context": self.user_context, }
[docs] @classmethod def from_dict(cls, udf_dict: dict) -> "UdfData": """ Create a udf data object from a python dictionary that was created from the JSON definition of the UdfData class :param udf_dict: The dictionary that contains the udf data definition """ datacubes = [XarrayDataCube.from_dict(x) for x in udf_dict.get("datacubes", [])] feature_collection_list = [FeatureCollection.from_dict(x) for x in udf_dict.get("feature_collection_list", [])] structured_data_list = [StructuredData.from_dict(x) for x in udf_dict.get("structured_data_list", [])] udf_data = cls( proj=udf_dict.get("proj"), datacube_list=datacubes, feature_collection_list=feature_collection_list, structured_data_list=structured_data_list, user_context=udf_dict.get("user_context") ) return udf_data