✨(backend) search user on her email and name

Compute Trigram similarity on user's name, and sum it up
with existing one based on user's email.

This approach is inspired by Contact search feature, which
computes a Trigram similarity score on first name and last
name, to sum up their scores.

With a similarity score influenced by both email and name,
API results would reflect both email and name user's attributes.

As we sum up similarities, I increased the similarity threshold.
Its value is empirical, and was finetuned to avoid breaking
existing tests. Please note, the updated value is closer to the
threshold used to search contacts.

Email or Name can be None. Summing two similarity scores with
one of them None, results in a None total score. To mitigate
this issue, I added a default empty string value, to replace
None values. Thus, the similarity score on this default empty
string value is equal to 0 and not to None anymore.

src/backend/core/api/viewsets.py

@@ -2,6 +2,7 @@
 
 from django.contrib.postgres.search import TrigramSimilarity
 from django.db.models import Func, Max, OuterRef, Prefetch, Q, Subquery, Value
+from django.db.models.functions import Coalesce
 
 from rest_framework import (
     decorators,
@@ -18,9 +19,7 @@ from core import models
 
 from . import permissions, serializers
 
-EMAIL_SIMILARITY_THRESHOLD = 0.01
-# TrigramSimilarity threshold is lower for searching email than for names,
-# to improve matching results
+SIMILARITY_THRESHOLD = 0.04
 
 
 class NestedGenericViewSet(viewsets.GenericViewSet):
@@ -212,13 +211,21 @@ class UserViewSet(
             if query := self.request.GET.get("q", ""):
                 similarity = Max(
                     TrigramSimilarity(
-                        Func("identities__email", function="unaccent"),
+                        Coalesce(
+                            Func("identities__email", function="unaccent"), Value("")
+                        ),
+                        Func(Value(query), function="unaccent"),
+                    )
+                    + TrigramSimilarity(
+                        Coalesce(
+                            Func("identities__name", function="unaccent"), Value("")
+                        ),
                         Func(Value(query), function="unaccent"),
                     )
                 )
                 queryset = (
                     queryset.annotate(similarity=similarity)
-                    .filter(similarity__gte=EMAIL_SIMILARITY_THRESHOLD)
+                    .filter(similarity__gte=SIMILARITY_THRESHOLD)
                     .order_by("-similarity")
                 )