fixup! Issue #391/#651 add docs, changelog, review tweaks

Author: soxofaan

docs/datacube_construction.rst

@@ -229,7 +229,7 @@ in a single entity that can be used to create or run batch jobs. For example:
 Moreover, it is not necessary to explicitly create such a
 :py:class:`~openeo.rest.multiresult.MultiResult` object,
 as the :py:meth:`Connection.create_job() <openeo.rest.connection.Connection.create_job>` method
-directly support passing multiple data cube objects in a list,
+directly supports passing multiple data cube objects in a list,
 which will be automatically grouped as a multi-result:
 
 .. code-block:: python
@@ -241,7 +241,8 @@ which will be automatically grouped as a multi-result:
 
 .. important::
 
-    Only a single :py:class:`~openeo.rest.connection.Connection` can be in play when working with multiple results.
+    Only a single :py:class:`~openeo.rest.connection.Connection` can be in play
+    when grouping multiple results like this.
     As everything is to be merged in a single process graph
     to be sent to a single backend,
     it is not possible to mix cubes created from different connections.

openeo/rest/_testing.py

@@ -3,7 +3,7 @@
 import collections
 import json
 import re
-from typing import Callable, Iterable, Iterator, Optional, Sequence, Union
+from typing import Callable, Iterable, Iterator, Optional, Sequence, Tuple, Union
 
 from openeo import Connection, DataCube
 from openeo.rest.vectorcube import VectorCube
@@ -92,12 +92,36 @@ def at_url(cls, root_url: str, *, requests_mock, capabilities: Optional[dict] =
         connection = Connection(root_url)
         return cls(requests_mock=requests_mock, connection=connection)
 
-    def setup_collection(self, collection_id: str):
+    def setup_collection(
+        self,
+        collection_id: str,
+        *,
+        temporal: Union[bool, Tuple[str, str]] = True,
+        bands: Sequence[str] = ("B1", "B2", "B3"),
+    ):
         # TODO: also mock `/collections` overview
+        # TODO: option to override cube_dimensions as a whole, or override dimension names
+        cube_dimensions = {
+            "x": {"type": "spatial"},
+            "y": {"type": "spatial"},
+        }
+
+        if temporal:
+            cube_dimensions["t"] = {
+                "type": "temporal",
+                "extent": temporal if isinstance(temporal, tuple) else [None, None],
+            }
+        if bands:
+            cube_dimensions["bands"] = {"type": "bands", "values": list(bands)}
+
         self._requests_mock.get(
             self.connection.build_url(f"/collections/{collection_id}"),
             # TODO: add more metadata?
-            json={"id": collection_id},
+            json={
+                "id": collection_id,
+                # define temporal  and band dim
+                "cube:dimensions": {"t": {"type": "temporal"}, "bands": {"type": "bands"}},
+            },
         )
         return self
 

tests/rest/test_connection.py

@@ -3802,3 +3802,41 @@ def test_create_job_with_mixed_connections(self, con120, dummy_backend, another_
 
         with pytest.raises(OpenEoClientException, match="Mixing different connections"):
             other_connection.create_job([save1, save2])
+
+    def test_create_job_intermediate_resultst(self, con120, dummy_backend):
+        cube = con120.load_collection("S2")
+        save1 = cube.save_result(format="GTiff")
+        reduced = cube.reduce_temporal("mean")
+        save2 = reduced.save_result(format="GTiff")
+        con120.create_job([save1, save2])
+        assert dummy_backend.get_batch_pg() == {
+            "loadcollection1": {
+                "process_id": "load_collection",
+                "arguments": {"id": "S2", "spatial_extent": None, "temporal_extent": None},
+            },
+            "saveresult1": {
+                "process_id": "save_result",
+                "arguments": {"data": {"from_node": "loadcollection1"}, "format": "GTiff", "options": {}},
+            },
+            "reducedimension1": {
+                "process_id": "reduce_dimension",
+                "arguments": {
+                    "data": {"from_node": "loadcollection1"},
+                    "dimension": "t",
+                    "reducer": {
+                        "process_graph": {
+                            "mean1": {
+                                "arguments": {"data": {"from_parameter": "data"}},
+                                "process_id": "mean",
+                                "result": True,
+                            }
+                        }
+                    },
+                },
+            },
+            "saveresult2": {
+                "process_id": "save_result",
+                "arguments": {"data": {"from_node": "reducedimension1"}, "format": "GTiff", "options": {}},
+                "result": True,
+            },
+        }