User python serialization mode instead of json

FastAPI uses json serialization by default, which flattens the Allele
sequence location field. To avoid this, use pydantic's serializer with python mode
instead, and return the response directly as a JSON response.

Author: sallybg

src/api/routers/map.py

@@ -1,6 +1,7 @@
 """"Provide mapping router"""
 from cool_seq_tool.schemas import AnnotationLayer
 from fastapi import APIRouter, HTTPException
+from fastapi.responses import JSONResponse
 from requests import HTTPError
 
 from dcd_mapping.align import AlignmentError, BlatNotFoundError, align
@@ -57,12 +58,20 @@ async def map_scoreset(urn: str) -> ScoresetMapping:
         msg = f"BLAT resource could not be acquired: {e}"
         raise HTTPException(status_code=500, detail=msg) from e
     except AlignmentError as e:
-        return ScoresetMapping(metadata=metadata, error_message=str(e).strip("'"))
+        return JSONResponse(
+            content=ScoresetMapping(
+                metadata=metadata, error_message=str(e).strip("'")
+            ).model_dump(exclude_none=True)
+        )
 
     try:
         transcript = await select_transcript(metadata, records, alignment_result)
     except (TxSelectError, KeyError, ValueError) as e:
-        return ScoresetMapping(metadata=metadata, error_message=str(e).strip("'"))
+        return JSONResponse(
+            content=ScoresetMapping(
+                metadata=metadata, error_message=str(e).strip("'")
+            ).model_dump(exclude_none=True)
+        )
     except HTTPError as e:
         msg = f"HTTP error occurred during transcript selection: {e}"
         raise HTTPException(status_code=500, detail=msg) from e
@@ -73,7 +82,11 @@ async def map_scoreset(urn: str) -> ScoresetMapping:
     try:
         vrs_results = vrs_map(metadata, alignment_result, records, transcript, True)
     except VrsMapError as e:
-        return ScoresetMapping(metadata=metadata, error_message=str(e).strip("'"))
+        return JSONResponse(
+            content=ScoresetMapping(
+                metadata=metadata, error_message=str(e).strip("'")
+            ).model_dump(exclude_none=True)
+        )
     if vrs_results is None:
         return ScoresetMapping(
             metadata=metadata,
@@ -83,7 +96,11 @@ async def map_scoreset(urn: str) -> ScoresetMapping:
     try:
         vrs_results = annotate(vrs_results, transcript, metadata, VrsVersion.V_2)
     except Exception as e:
-        return ScoresetMapping(metadata=metadata, error_message=str(e).strip("'"))
+        return JSONResponse(
+            content=ScoresetMapping(
+                metadata=metadata, error_message=str(e).strip("'")
+            ).model_dump(exclude_none=True)
+        )
     if vrs_results is None:
         return ScoresetMapping(
             metadata=metadata,
@@ -118,21 +135,27 @@ async def map_scoreset(urn: str) -> ScoresetMapping:
                 # drop annotation layer from mapping object
                 mapped_scores.append(ScoreAnnotation(**m.model_dump()))
     except Exception as e:
-        return ScoresetMapping(metadata=metadata, error_message=str(e).strip("'"))
+        return JSONResponse(
+            content=ScoresetMapping(
+                metadata=metadata, error_message=str(e).strip("'")
+            ).model_dump(exclude_none=True)
+        )
 
-    return ScoresetMapping(
-        metadata=raw_metadata,
-        computed_protein_reference_sequence=reference_sequences[
-            AnnotationLayer.PROTEIN
-        ]["computed_reference_sequence"],
-        mapped_protein_reference_sequence=reference_sequences[AnnotationLayer.PROTEIN][
-            "mapped_reference_sequence"
-        ],
-        computed_genomic_reference_sequence=reference_sequences[
-            AnnotationLayer.GENOMIC
-        ]["computed_reference_sequence"],
-        mapped_genomic_reference_sequence=reference_sequences[AnnotationLayer.GENOMIC][
-            "mapped_reference_sequence"
-        ],
-        mapped_scores=mapped_scores,
+    return JSONResponse(
+        content=ScoresetMapping(
+            metadata=raw_metadata,
+            computed_protein_reference_sequence=reference_sequences[
+                AnnotationLayer.PROTEIN
+            ]["computed_reference_sequence"],
+            mapped_protein_reference_sequence=reference_sequences[
+                AnnotationLayer.PROTEIN
+            ]["mapped_reference_sequence"],
+            computed_genomic_reference_sequence=reference_sequences[
+                AnnotationLayer.GENOMIC
+            ]["computed_reference_sequence"],
+            mapped_genomic_reference_sequence=reference_sequences[
+                AnnotationLayer.GENOMIC
+            ]["mapped_reference_sequence"],
+            mapped_scores=mapped_scores,
+        ).model_dump(exclude_none=True)
     )