Merging main

Author: Ken Lippold

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = hydroserverpy
-version = 1.7.0b4
+version = 1.6.2
 description = A Python client for managing HydroServer data
 long_description_content_type = text/markdown
 long_description = file: README.md

src/hydroserverpy/api/services/iam/workspace.py

@@ -87,15 +87,15 @@ def add_collaborator(
         )
 
     def edit_collaborator_role(
-        self, uid: Union[UUID, str], email: EmailStr, role: Union["Role", UUID, str]
+        self, uid: Union[UUID, str], email: EmailStr, role: Union["Role", UUID, str], role_id: UUID
     ) -> "Collaborator":
         """Edit the role of a collaborator in a workspace."""
 
         path = f"/{self.client.base_route}/{self.model.get_route()}/{str(uid)}/collaborators"
         headers = {"Content-type": "application/json"}
         body = {
             "email": email,
-            "roleId": normalize_uuid(role)
+            "roleId": normalize_uuid(role if role is not ... else role_id)
         }
 
         response = self.client.request(
@@ -165,6 +165,7 @@ def update_api_key(
         uid: Union[UUID, str],
         api_key_id: Union[UUID, str],
         role: Union["Role", UUID, str] = ...,
+        role_id: UUID = ...,
         name: str = ...,
         description: Optional[str] = ...,
         is_active: bool = ...,
@@ -175,7 +176,7 @@ def update_api_key(
         path = f"/{self.client.base_route}/{self.model.get_route()}/{str(uid)}/api-keys/{api_key_id}"
         headers = {"Content-type": "application/json"}
         body = {
-            "roleId": normalize_uuid(role),
+            "roleId": normalize_uuid(role if role is not ... else role_id),
             "name": name,
             "description": description,
             "isActive": is_active,

src/hydroserverpy/api/services/sta/datastream.py

@@ -149,10 +149,15 @@ def update(
         name: str = ...,
         description: str = ...,
         thing: Union["Thing", UUID, str] = ...,
+        thing_id: UUID = ...,
         sensor: Union["Sensor", UUID, str] = ...,
+        sensor_id: UUID = ...,
         observed_property: Union["ObservedProperty", UUID, str] = ...,
+        observed_property_id: UUID = ...,
         processing_level: Union["ProcessingLevel", UUID, str] = ...,
+        processing_level_id: UUID = ...,
         unit: Union["Unit", UUID, str] = ...,
+        unit_id: UUID = ...,
         observation_type: str = ...,
         result_type: str = ...,
         sampled_medium: str = ...,
@@ -180,11 +185,15 @@ def update(
         body = {
             "name": name,
             "description": description,
-            "thingId": normalize_uuid(thing),
-            "sensorId": normalize_uuid(sensor),
-            "observedPropertyId": normalize_uuid(observed_property),
-            "processingLevelId": normalize_uuid(processing_level),
-            "unitId": normalize_uuid(unit),
+            "thingId": normalize_uuid(thing if thing is not ... else thing_id),
+            "sensorId": normalize_uuid(sensor if sensor is not ... else sensor_id),
+            "observedPropertyId": normalize_uuid(
+                observed_property if observed_property is not ... else observed_property_id
+            ),
+            "processingLevelId": normalize_uuid(
+                processing_level if processing_level is not ... else processing_level_id
+            ),
+            "unitId": normalize_uuid(unit if unit is not ... else unit_id),
             "observationType": observation_type,
             "resultType": result_type,
             "sampledMedium": sampled_medium,

src/hydroserverpy/etl/loaders/hydroserver_loader.py

@@ -28,8 +28,13 @@ def load(self, data: pd.DataFrame, task: Task) -> None:
         begin_date = self.earliest_begin_date(task)
         new_data = data[data["timestamp"] > begin_date]
         for col in new_data.columns.difference(["timestamp"]):
+            datastream = self.client.datastreams.get(
+                uid=str(col)
+            )
+            ds_cutoff = datastream.phenomenon_end_time
             df = (
                 new_data[["timestamp", col]]
+                .loc[lambda d: d["timestamp"] > ds_cutoff if ds_cutoff else True]
                 .rename(columns={col: "value"})
                 .dropna(subset=["value"])
             )
@@ -67,7 +72,6 @@ def load(self, data: pd.DataFrame, task: Task) -> None:
                             start,
                             end - 1,
                         )
-                        break
                     raise
 
     def _fetch_earliest_begin(