feat(company alerts): say if has any regulation computation for month

app/data_access/regulatory_alerts_summary.py

@@ -8,6 +8,9 @@ class AlertsGroup(graphene.ObjectType):
 
 
 class RegulatoryAlertsSummary(graphene.ObjectType):
+    has_any_computation = graphene.Boolean(
+        description="Indique s'il y a des données pour le mois."
+    )
     month = graphene.String(description="Mois correspondant aux données.")
     total_nb_alerts = graphene.Int(
         description="Nombre d'alertes total sur le mois."

app/domain/regulatory_alerts_summary.py

@@ -1,5 +1,6 @@
 from dateutil.relativedelta import relativedelta
 
+from app import db
 from app.data_access.regulation_computation import (
     get_regulation_checks_by_unit,
 )
@@ -8,7 +9,7 @@
     RegulatoryAlertsSummary,
 )
 from app.helpers.submitter_type import SubmitterType
-from app.models import RegulatoryAlert
+from app.models import RegulatoryAlert, RegulationComputation
 from app.models.regulation_check import UnitType, RegulationCheckType
 
 
@@ -50,6 +51,19 @@ def query_alerts(_start_date, _end_date, _user_ids, count_only=True):
     return current_month_alerts, previous_month_alerts_count
 
 
+def has_any_regulation_computation(month, user_ids):
+    start_date = month
+    end_date = month + relativedelta(months=1)
+    db.session.query(
+        RegulationComputation.query.filter(
+            RegulationComputation.user_id.in_(user_ids),
+            RegulationComputation.day >= start_date,
+            RegulationComputation.day < end_date,
+            RegulatoryAlert.submitter_type == SubmitterType.ADMIN,
+        ).exists()
+    ).scalar()
+
+
 def get_regulatory_alerts_summary(month, user_ids, unique_user_id=False):
     current_month_alerts, previous_month_alerts_count = query_alerts_for_month(
         month=month, user_ids=user_ids