Quickfix for global stats with model v2

.pyproject_generation/pyproject_custom.toml

@@ -1,6 +1,6 @@
 [project]
 name = "metldata"
-version = "2.0.0"
+version = "2.0.1"
 description = "metldata - A framework for handling metadata based on ETL, CQRS, and event sourcing."
 dependencies = [
     "hexkit[akafka,mongodb] >=3, <4",

README.md

@@ -58,21 +58,21 @@ We recommend using the provided Docker container.
 
 A pre-build version is available at [docker hub](https://hub.docker.com/repository/docker/ghga/metldata):
 ```bash
-docker pull ghga/metldata:2.0.0
+docker pull ghga/metldata:2.0.1
 ```
 
 Or you can build the container yourself from the [`./Dockerfile`](./Dockerfile):
 ```bash
 # Execute in the repo's root dir:
-docker build -t ghga/metldata:2.0.0 .
+docker build -t ghga/metldata:2.0.1 .
 ```
 
 For production-ready deployment, we recommend using Kubernetes, however,
 for simple use cases, you could execute the service using docker
 on a single server:
 ```bash
 # The entrypoint is preconfigured:
-docker run -p 8080:8080 ghga/metldata:2.0.0 --help
+docker run -p 8080:8080 ghga/metldata:2.0.1 --help
 ```
 
 If you prefer not to use containers, you may install the service from source:

pyproject.toml

@@ -21,7 +21,7 @@ classifiers = [
     "Intended Audience :: Developers",
 ]
 name = "metldata"
-version = "2.0.0"
+version = "2.0.1"
 description = "metldata - A framework for handling metadata based on ETL, CQRS, and event sourcing."
 dependencies = [
     "hexkit[akafka,mongodb] >=3, <4",

src/metldata/load/stats.py

@@ -32,15 +32,20 @@
 STATS_COLLECTION_NAME = "stats"
 
 
+# the following should be made configurable
+
+
 def get_stat_slot(resource_class: str) -> str | None:
     """Get the name of the slot that shall be used as grouping key."""
     if resource_class.endswith("File"):
         return "format"
-    if resource_class.endswith("Protocol"):
+    if resource_class.endswith("Protocol"):  # v1
         return "type"
-    if resource_class.endswith("Individual"):
-        return "sex"
-    return None
+    return {
+        "Individual": "sex",
+        "Sample": "type",
+        "ExperimentMethod": "instrument_model",  # v2
+    }.get(resource_class)
 
 
 async def create_stats_using_aggregator(