couple tweaks

Makefile

@@ -75,7 +75,7 @@ install-frontend:
 
 .PHONY: model
 model: install-backend	
-	$(RUN) gen-pydantic --pydantic-version 2 --extra-fields ignore $(SCHEMADIR)/model.yaml > $(SCHEMADIR)/model.py
+	$(RUN) gen-pydantic --pydantic-version 2 --extra-fields allow $(SCHEMADIR)/model.yaml > $(SCHEMADIR)/model.py
 	$(RUN) gen-typescript $(SCHEMADIR)/model.yaml > frontend/src/api/model.ts
 	make format
 

backend/src/monarch_py/datamodels/model.py

@@ -19,7 +19,7 @@ class ConfiguredBaseModel(BaseModel):
     model_config = ConfigDict(
         validate_assignment=True,
         validate_default=True,
-        extra="ignore",
+        extra="allow",
         arbitrary_types_allowed=True,
         use_enum_values=True,
     )

backend/src/monarch_py/datamodels/solr.py

@@ -67,7 +67,7 @@ def add_filter_query(self, filter_query):
 
     def query_string(self):
         return urllib.parse.urlencode(
-            {self._solrize(k): self._solrize(v) for k, v in self.dict().items() if v is not None},
+            {self._solrize(k): self._solrize(v) for k, v in self..model_dump().items() if v is not None},
             doseq=True,
         )
 

backend/src/monarch_py/utils/utils.py

@@ -114,7 +114,7 @@ def to_json(obj: Union[ConfiguredBaseModel, Dict, List[ConfiguredBaseModel]], fi
     elif isinstance(obj, dict):
         json_value = json.dumps(obj, indent=4)
     elif isinstance(obj, list):
-        json_value = json.dumps({"items": [o.dict() for o in obj]}, indent=4)
+        json_value = json.dumps({"items": [o.model_dump() for o in obj]}, indent=4)
     if file:
         with open(file, "w") as f:
             f.write(json_value)
@@ -135,8 +135,8 @@ def to_tsv(obj: ConfiguredBaseModel, file: str) -> str:
             headers = get_headers_from_obj(obj)
             rows = []
         else:
-            headers = obj.items[0].dict().keys()
-            rows = [list(item.dict().values()) for item in obj.items]
+            headers = obj.items[0].model_dump().keys()
+            rows = [list(item.model_dump().values()) for item in obj.items]
     else:
         console.print(f"\n[bold red]{FMT_INPUT_ERROR_MSG}[/]\n")
         raise typer.Exit(1)
@@ -200,7 +200,7 @@ def to_yaml(obj: ConfiguredBaseModel, file: str):
     if isinstance(obj, Entity):
         yaml.dump(obj.model_dump(), fh, indent=4)
     elif isinstance(obj, Results) or isinstance(obj, HistoPheno) or isinstance(obj, AssociationCountList):
-        yaml.dump([item.dict() for item in obj.items], fh, indent=4)
+        yaml.dump([item.model_dump() for item in obj.items], fh, indent=4)
     else:
         console.print(f"\n[bold red]{FMT_INPUT_ERROR_MSG}[/]\n")
         raise typer.Exit(1)

backend/tests/fixtures/phenotype_explorer_compare.py

@@ -5,8 +5,8 @@
 def phenotype_explorer_compare():
     return {
         "subject_termset": {
-            "MP:0010771": {"id": "MP:0010771", "label": "integument phenotype (MPO)"},
             "MP:0002169": {"id": "MP:0002169", "label": "no abnormal phenotype detected (MPO)"},
+            "MP:0010771": {"id": "MP:0010771", "label": "integument phenotype (MPO)"},
         },
         "object_termset": {"HP:0004325": {"id": "HP:0004325", "label": "Decreased body weight (HPO)"}},
         "subject_best_matches": {
@@ -69,16 +69,16 @@ def phenotype_explorer_compare():
             "HP:0004325": {
                 "match_source": "HP:0004325",
                 "match_source_label": "Decreased body weight (HPO)",
-                "match_target": "MP:0010771",
-                "match_target_label": "integument phenotype (MPO)",
+                "match_target": "MP:0002169",
+                "match_target_label": "no abnormal phenotype detected (MPO)",
                 "score": 1.4431977534690428,
                 "match_subsumer": None,
                 "match_subsumer_label": None,
                 "similarity": {
                     "subject_id": "HP:0004325",
                     "subject_label": None,
                     "subject_source": None,
-                    "object_id": "MP:0010771",
+                    "object_id": "MP:0002169",
                     "object_label": None,
                     "object_source": None,
                     "ancestor_id": "UPHENO:0001003",
@@ -87,10 +87,10 @@ def phenotype_explorer_compare():
                     "object_information_content": None,
                     "subject_information_content": None,
                     "ancestor_information_content": 1.4431977534690428,
-                    "jaccard_similarity": 0.3333333333333333,
+                    "jaccard_similarity": 0.16216216216216217,
                     "cosine_similarity": None,
                     "dice_similarity": None,
-                    "phenodigm_score": 0.6935891563620457,
+                    "phenodigm_score": 0.48376861011243283,
                 },
             }
         },

backend/tests/unit/test_solr_parsers.py

@@ -47,9 +47,7 @@ def test_parse_histopheno(histopheno_response, histopheno, node):
     histopheno_response["response"]["numFound"] = histopheno_response["response"].pop("num_found")
     solr_response = SolrQueryResult(**histopheno_response)
     parsed = parse_histopheno(solr_response, subject_closure=Node(**node).id).model_dump()
-    assert (
-        parsed == histopheno
-    ), f"Parsed result is not as expected. Difference: {dict_diff(parsed, histopheno)}"
+    assert parsed == histopheno, f"Parsed result is not as expected. Difference: {dict_diff(parsed, histopheno)}"
 
 
 def test_parse_search(search_response, search):
@@ -63,15 +61,11 @@ def test_parse_autocomplete(autocomplete_response, autocomplete):
     autocomplete_response["response"]["numFound"] = autocomplete_response["response"].pop("num_found")
     solr_response = SolrQueryResult(**autocomplete_response)
     parsed = parse_autocomplete(solr_response).model_dump()
-    assert (
-        parsed == autocomplete
-    ), f"Parsed result is not as expected. Difference: {dict_diff(parsed, autocomplete)}"
+    assert parsed == autocomplete, f"Parsed result is not as expected. Difference: {dict_diff(parsed, autocomplete)}"
 
 
 def test_parse_mappings(mapping_response, mappings):
     mapping_response["response"]["numFound"] = mapping_response["response"].pop("num_found")
     solr_response = SolrQueryResult(**mapping_response)
     parsed = parse_mappings(solr_response).model_dump()
-    assert (
-        parsed == mappings
-    ), f"Parsed result is not as expected. Difference: {dict_diff(parsed, mappings)}"
+    assert parsed == mappings, f"Parsed result is not as expected. Difference: {dict_diff(parsed, mappings)}"

backend/tests/unit/test_solr_queries.py

@@ -33,7 +33,7 @@ def test_build_association_query(
         direct=direct,
         facet_fields=facet_fields,
         facet_queries=facet_queries,
-    ).dict()
+    ).model_dump()
     expected = association_query_direct if direct else association_query_indirect
     if facet_fields:
         expected["facet_fields"] = facet_fields
@@ -91,30 +91,30 @@ def test_build_association_multiple_objects():
 
 
 def test_build_association_counts_query(association_counts_query, node):
-    query = build_association_counts_query(entity=Node(**node).id).dict()
+    query = build_association_counts_query(entity=Node(**node).id).model_dump()
     expected = association_counts_query
     assert compare_dicts(query, expected), f"Query is not as expected. Difference: {dict_diff(query, expected)}"
 
 
 def test_build_histopheno_query(histopheno_query):
-    query = build_histopheno_query("MONDO:0020121").dict()
+    query = build_histopheno_query("MONDO:0020121").model_dump()
     expected = histopheno_query
     assert compare_dicts(query, expected), f"Query is not as expected. Difference: {dict_diff(query, expected)}"
 
 
 def test_build_search_query(search_query):
-    query = build_search_query(q="fanconi").dict()
+    query = build_search_query(q="fanconi").model_dump()
     expected = search_query
     assert compare_dicts(query, expected), f"Query is not as expected. Difference: {dict_diff(query, expected)}"
 
 
 def test_build_autocomplete_query(autocomplete_query):
-    query = build_autocomplete_query(q="fanc").dict()
+    query = build_autocomplete_query(q="fanc").model_dump()
     expected = autocomplete_query
     assert compare_dicts(query, expected), f"Query is not as expected. Difference: {dict_diff(query, expected)}"
 
 
 def test_build_mappings_query(mapping_query):
-    query = build_mapping_query(entity_id=["MONDO:0020121"]).dict()
+    query = build_mapping_query(entity_id=["MONDO:0020121"]).model_dump()
     expected = mapping_query
     assert compare_dicts(query, expected), f"Query is not as expected. Difference: {dict_diff(query, expected)}"

frontend/fixtures/phenotype-explorer-compare.json

@@ -1,12 +1,12 @@
 {
   "subject_termset": {
-    "MP:0010771": {
-      "id": "MP:0010771",
-      "label": "integument phenotype (MPO)"
-    },
     "MP:0002169": {
       "id": "MP:0002169",
       "label": "no abnormal phenotype detected (MPO)"
+    },
+    "MP:0010771": {
+      "id": "MP:0010771",
+      "label": "integument phenotype (MPO)"
     }
   },
   "object_termset": {
@@ -75,16 +75,16 @@
     "HP:0004325": {
       "match_source": "HP:0004325",
       "match_source_label": "Decreased body weight (HPO)",
-      "match_target": "MP:0010771",
-      "match_target_label": "integument phenotype (MPO)",
+      "match_target": "MP:0002169",
+      "match_target_label": "no abnormal phenotype detected (MPO)",
       "score": 1.4431977534690428,
       "match_subsumer": null,
       "match_subsumer_label": null,
       "similarity": {
         "subject_id": "HP:0004325",
         "subject_label": null,
         "subject_source": null,
-        "object_id": "MP:0010771",
+        "object_id": "MP:0002169",
         "object_label": null,
         "object_source": null,
         "ancestor_id": "UPHENO:0001003",
@@ -93,10 +93,10 @@
         "object_information_content": null,
         "subject_information_content": null,
         "ancestor_information_content": 1.4431977534690428,
-        "jaccard_similarity": 0.3333333333333333,
+        "jaccard_similarity": 0.16216216216216217,
         "cosine_similarity": null,
         "dice_similarity": null,
-        "phenodigm_score": 0.6935891563620457
+        "phenodigm_score": 0.48376861011243283
       }
     }
   },