Merge pull request #173 from bento-platform/download-feature

Add CSV renderer for Individuals

chord_metadata_service/patients/api_views.py

@@ -5,7 +5,7 @@
 from .models import Individual
 from .filters import IndividualFilter
 from chord_metadata_service.phenopackets.api_views import BIOSAMPLE_PREFETCH, PHENOPACKET_PREFETCH
-from chord_metadata_service.restapi.api_renderers import FHIRRenderer, PhenopacketsRenderer
+from chord_metadata_service.restapi.api_renderers import FHIRRenderer, PhenopacketsRenderer, IndividualCSVRenderer
 from chord_metadata_service.restapi.pagination import LargeResultsSetPagination
 
 
@@ -24,7 +24,8 @@ class IndividualViewSet(viewsets.ModelViewSet):
     ).order_by("id")
     serializer_class = IndividualSerializer
     pagination_class = LargeResultsSetPagination
-    renderer_classes = (*api_settings.DEFAULT_RENDERER_CLASSES, FHIRRenderer, PhenopacketsRenderer)
+    renderer_classes = (*api_settings.DEFAULT_RENDERER_CLASSES, FHIRRenderer,
+                        PhenopacketsRenderer, IndividualCSVRenderer)
     filter_backends = [DjangoFilterBackend, filters.SearchFilter, filters.OrderingFilter]
     filter_class = IndividualFilter
     ordering_fields = ["id"]

chord_metadata_service/restapi/api_renderers.py

@@ -1,8 +1,11 @@
 import json
+import csv
 from djangorestframework_camel_case.render import CamelCaseJSONRenderer
+from rest_framework.renderers import JSONRenderer
 from rdflib import Graph
 from rdflib.plugin import register, Serializer
-from rest_framework.renderers import JSONRenderer
+from django.http import HttpResponse
+
 from uuid import UUID
 
 from .jsonld_utils import dataset_to_jsonld
@@ -79,3 +82,60 @@ def render(self, data, media_type=None, renderer_context=None):
             g = Graph().parse(data=json.dumps(ld_context_data, cls=UUIDEncoder), format='json-ld')
         rdf_data = g.serialize(format='pretty-xml')
         return rdf_data
+
+
+class IndividualCSVRenderer(JSONRenderer):
+    media_type = 'text/csv'
+    format = 'csv'
+
+    def render(self, data, media_type=None, renderer_context=None):
+        if 'results' in data:
+            individuals = []
+            for individual in data['results']:
+                ind_obj = {
+                    'id': individual['id'],
+                    'sex': individual.get('sex', None),
+                    'date_of_birth': individual.get('date_of_birth', None),
+                    'taxonomy': None,
+                    'karyotypic_sex': individual['karyotypic_sex'],
+                    'race': individual.get('race', None),
+                    'ethnicity': individual.get('ethnicity', None),
+                    'age': None,
+                    'diseases': None,
+                    'created': individual['created'],
+                    'updated': individual['updated']
+                }
+                if 'taxonomy' in individual:
+                    ind_obj['taxonomy'] = individual['taxonomy'].get('label', None)
+                if 'age' in individual:
+                    if 'age' in individual['age']:
+                        ind_obj['age'] = individual['age'].get('age', None)
+                    elif 'start' and 'end' in individual['age']:
+                        ind_obj['age'] = str(
+                            individual['age']['start'].get('age', "NA")
+                            + ' - ' +
+                            individual['age']['end'].get('age', "NA")
+                        )
+                    else:
+                        ind_obj['age'] = None
+                if 'phenopackets' in individual:
+                    all_diseases = []
+                    for phenopacket in individual['phenopackets']:
+                        if 'diseases' in phenopacket:
+                            # use ; because some disease terms might contain , in their label
+                            single_phenopacket_diseases = '; '.join(
+                                [d['term']['label'] for d in phenopacket['diseases']]
+                            )
+                            all_diseases.append(single_phenopacket_diseases)
+                    if all_diseases:
+                        ind_obj['diseases'] = '; '.join(all_diseases)
+                individuals.append(ind_obj)
+            columns = individuals[0].keys()
+            # remove underscore and capitalize column names
+            headers = {key: key.replace('_', ' ').capitalize() for key in individuals[0].keys()}
+            response = HttpResponse(content_type='text/csv')
+            response['Content-Disposition'] = "attachment; filename='export.csv'"
+            dict_writer = csv.DictWriter(response, fieldnames=columns)
+            dict_writer.writerow(headers)
+            dict_writer.writerows(individuals)
+            return response