Revert "S1 extraction fixes - PR Re-opened"

src/openeo_gfmap/fetching/generic.py

@@ -1,10 +1,10 @@
 """ Generic extraction of features, supporting VITO backend.
 """
 
-from typing import Callable, Optional
+from functools import partial
+from typing import Callable
 
 import openeo
-from openeo.rest import OpenEoApiError
 
 from openeo_gfmap.backend import Backend, BackendContext
 from openeo_gfmap.fetching import CollectionFetcher, FetchType, _log
@@ -28,18 +28,15 @@
     "vapour-pressure": "AGERA5-VAPOUR",
     "wind-speed": "AGERA5-WIND",
 }
-KNOWN_UNTEMPORAL_COLLECTIONS = ["COPERNICUS_30"]
 
 
-def _get_generic_fetcher(
-    collection_name: str, fetch_type: FetchType, backend: Backend
-) -> Callable:
-    band_mapping: Optional[dict] = None
-
+def _get_generic_fetcher(collection_name: str, fetch_type: FetchType) -> Callable:
     if collection_name == "COPERNICUS_30":
-        band_mapping = BASE_DEM_MAPPING
+        BASE_MAPPING = BASE_DEM_MAPPING
     elif collection_name == "AGERA5":
-        band_mapping = BASE_WEATHER_MAPPING
+        BASE_MAPPING = BASE_WEATHER_MAPPING
+    else:
+        raise Exception("Please choose a valid collection.")
 
     def generic_default_fetcher(
         connection: openeo.Connection,
@@ -48,34 +45,23 @@ def generic_default_fetcher(
         bands: list,
         **params,
     ) -> openeo.DataCube:
-        if band_mapping is not None:
-            bands = convert_band_names(bands, band_mapping)
+        bands = convert_band_names(bands, BASE_MAPPING)
 
-        if (collection_name in KNOWN_UNTEMPORAL_COLLECTIONS) and (
-            temporal_extent is not None
-        ):
+        if (collection_name == "COPERNICUS_30") and (temporal_extent is not None):
             _log.warning(
-                "Ignoring the temporal extent provided by the user as the collection %s is known to be untemporal.",
-                collection_name,
+                "User set-up non None temporal extent for DEM collection. Ignoring it."
             )
             temporal_extent = None
 
-        try:
-            cube = _load_collection(
-                connection,
-                bands,
-                collection_name,
-                spatial_extent,
-                temporal_extent,
-                fetch_type,
-                **params,
-            )
-        except OpenEoApiError as e:
-            if "CollectionNotFound" in str(e):
-                raise ValueError(
-                    f"Collection {collection_name} not found in the selected backend {backend.value}."
-                ) from e
-            raise e
+        cube = _load_collection(
+            connection,
+            bands,
+            collection_name,
+            spatial_extent,
+            temporal_extent,
+            fetch_type,
+            **params,
+        )
 
         # # Apply if the collection is a GeoJSON Feature collection
         # if isinstance(spatial_extent, GeoJSON):
@@ -90,11 +76,12 @@ def _get_generic_processor(collection_name: str, fetch_type: FetchType) -> Calla
     """Builds the preprocessing function from the collection name as it stored
     in the target backend.
     """
-    band_mapping: Optional[dict] = None
     if collection_name == "COPERNICUS_30":
-        band_mapping = BASE_DEM_MAPPING
+        BASE_MAPPING = BASE_DEM_MAPPING
     elif collection_name == "AGERA5":
-        band_mapping = BASE_WEATHER_MAPPING
+        BASE_MAPPING = BASE_WEATHER_MAPPING
+    else:
+        raise Exception("Please choose a valid collection.")
 
     def generic_default_processor(cube: openeo.DataCube, **params):
         """Default collection preprocessing method for generic datasets.
@@ -112,14 +99,51 @@ def generic_default_processor(cube: openeo.DataCube, **params):
         if collection_name == "COPERNICUS_30":
             cube = cube.min_time()
 
-        if band_mapping is not None:
-            cube = rename_bands(cube, band_mapping)
+        cube = rename_bands(cube, BASE_MAPPING)
 
         return cube
 
     return generic_default_processor
 
 
+OTHER_BACKEND_MAP = {
+    "AGERA5": {
+        Backend.TERRASCOPE: {
+            "fetch": partial(_get_generic_fetcher, collection_name="AGERA5"),
+            "preprocessor": partial(_get_generic_processor, collection_name="AGERA5"),
+        },
+        Backend.CDSE: {
+            "fetch": partial(_get_generic_fetcher, collection_name="AGERA5"),
+            "preprocessor": partial(_get_generic_processor, collection_name="AGERA5"),
+        },
+        Backend.FED: {
+            "fetch": partial(_get_generic_fetcher, collection_name="AGERA5"),
+            "preprocessor": partial(_get_generic_processor, collection_name="AGERA5"),
+        },
+    },
+    "COPERNICUS_30": {
+        Backend.TERRASCOPE: {
+            "fetch": partial(_get_generic_fetcher, collection_name="COPERNICUS_30"),
+            "preprocessor": partial(
+                _get_generic_processor, collection_name="COPERNICUS_30"
+            ),
+        },
+        Backend.CDSE: {
+            "fetch": partial(_get_generic_fetcher, collection_name="COPERNICUS_30"),
+            "preprocessor": partial(
+                _get_generic_processor, collection_name="COPERNICUS_30"
+            ),
+        },
+        Backend.FED: {
+            "fetch": partial(_get_generic_fetcher, collection_name="COPERNICUS_30"),
+            "preprocessor": partial(
+                _get_generic_processor, collection_name="COPERNICUS_30"
+            ),
+        },
+    },
+}
+
+
 def build_generic_extractor(
     backend_context: BackendContext,
     bands: list,
@@ -128,7 +152,13 @@ def build_generic_extractor(
     **params,
 ) -> CollectionFetcher:
     """Creates a generic extractor adapted to the given backend. Currently only tested with VITO backend"""
-    fetcher = _get_generic_fetcher(collection_name, fetch_type, backend_context.backend)
-    preprocessor = _get_generic_processor(collection_name, fetch_type)
+    backend_functions = OTHER_BACKEND_MAP.get(collection_name).get(
+        backend_context.backend
+    )
+
+    fetcher, preprocessor = (
+        backend_functions["fetch"](fetch_type=fetch_type),
+        backend_functions["preprocessor"](fetch_type=fetch_type),
+    )
 
     return CollectionFetcher(backend_context, bands, fetcher, preprocessor, **params)

src/openeo_gfmap/fetching/s1.py

@@ -67,14 +67,16 @@ def s1_grd_fetch_default(
         """
         bands = convert_band_names(bands, BASE_SENTINEL1_GRD_MAPPING)
 
+        load_collection_parameters = params.get("load_collection", {})
+
         cube = _load_collection(
             connection,
             bands,
             collection_name,
             spatial_extent,
             temporal_extent,
             fetch_type,
-            **params,
+            **load_collection_parameters,
         )
 
         if fetch_type is not FetchType.POINT and isinstance(spatial_extent, GeoJSON):