Simplify doing run_udf on VectorCube

Just use standard method instead of cumbersome PGNode hacking.
Related to #278

Author: soxofaan

CHANGELOG.md

@@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added `Connection.describe_process()` to retrieve and show a single process
 - Added `DataCube.flatten_dimensions()` and `DataCube.unflatten_dimension` 
   ([Open-EO/openeo-processes#308](https://github.com/Open-EO/openeo-processes/issues/308), [Open-EO/openeo-processes#316](https://github.com/Open-EO/openeo-processes/pull/316))
+- Added `VectorCube.run_udf` (to avoid non-standard `process_with_node(UDF(...))` usage)
 
 ### Changed
 

openeo/internal/graph_building.py

@@ -145,11 +145,9 @@ class UDF(PGNode):
     A 'run_udf' process graph node. This is offered as a convenient way to construct run_udf processes.
     """
 
-    def __init__(self, code: str, runtime: str, data=None, version: str = None, context: Dict = None):
-        # TODO: avoid local import: make `THIS` more general than DataCube-specific?
-        from openeo.rest.datacube import THIS
+    def __init__(self, code: str, runtime: str, data, version: str = None, context: Dict = None):
         arguments = {
-            "data": data or THIS,
+            "data": data,
             "udf": code,
             "runtime": runtime
         }

openeo/rest/vectorcube.py

@@ -1,13 +1,12 @@
-import json
 import pathlib
-from typing import Union, Optional
 import typing
+from typing import Union, Optional
 
-from openeo.internal.graph_building import PGNode, _FromNodeMixin
+from openeo.internal.graph_building import PGNode
 from openeo.metadata import CollectionMetadata
-from openeo.rest._datacube import _ProcessGraphAbstraction, THIS
+from openeo.rest._datacube import _ProcessGraphAbstraction
 from openeo.rest.job import RESTJob
-from openeo.util import legacy_alias
+from openeo.util import legacy_alias, dict_no_none
 
 if hasattr(typing, 'TYPE_CHECKING') and typing.TYPE_CHECKING:
     # Imports for type checking only (circular import issue at runtime). `hasattr` is Python 3.5 workaround #210
@@ -45,23 +44,14 @@ def process(
         pg = self._build_pgnode(process_id=process_id, arguments=arguments, namespace=namespace, **kwargs)
         return VectorCube(graph=pg, connection=self._connection, metadata=metadata or self.metadata)
 
-    def process_with_node(self, pg: PGNode, metadata: CollectionMetadata = None) -> 'VectorCube':
-        """
-        Generic helper to create a new DataCube by applying a process (given as process graph node)
-
-        :param pg: process graph node (containing process id and arguments)
-        :param metadata: (optional) metadata to override original cube metadata (e.g. when reducing dimensions)
-        :return: new DataCube instance
-        """
-        arguments = pg.arguments
-        for k, v in arguments.items():
-            # TODO: it's against intended flow to resolve THIS and _FromNodeMixin at this point (should be done before building PGNode)
-            if v is THIS:
-                v = self
-            if isinstance(v, _FromNodeMixin):
-                arguments[k] = {"from_node": v.from_node()}
-        # TODO: deep copy `self.metadata` instead of using same instance?
-        return VectorCube(graph=pg, connection=self._connection, metadata=metadata or self.metadata)
+    def run_udf(
+            self, udf: str, runtime: str, version: Optional[str] = None, context: Optional[dict] = None
+    ) -> "VectorCube":
+        return self.process(
+            process_id="run_udf",
+            data=self, udf=udf, runtime=runtime,
+            arguments=dict_no_none({"version": version, "context": context}),
+        )
 
     def save_result(self, format: str = "GeoJson", options: dict = None):
         return self.process(

tests/rest/datacube/test_vectorcube.py

@@ -1,13 +1,7 @@
-import pytest
-from openeo.internal.graph_building import PGNode
-from openeo.rest.connection import Connection
-import openeo
-
-
 def test_raster_to_vector(con100):
     img = con100.load_collection("S2")
     vector_cube = img.raster_to_vector()
-    vector_cube_tranformed = vector_cube.process_with_node(openeo.UDF("python source code", "Python"))
+    vector_cube_tranformed = vector_cube.run_udf(udf="python source code", runtime="Python")
 
     assert vector_cube_tranformed.flat_graph() == {
         'loadcollection1': {