allow random addon sort to be used with promoted filter (#15469)

docs/topics/api/addons.rst

@@ -54,7 +54,7 @@ This endpoint allows you to search through public add-ons.
          downloads  Number of weekly downloads, descending.
            hotness  Hotness (average number of users progression), descending.
             random  Random ordering. Only available when no search query is
-                    passed and when filtering to only return recommended add-ons.
+                    passed and when filtering to only return promoted add-ons.
             rating  Bayesian rating, descending.
        recommended  Recommended add-ons above non-recommend add-ons. Only
                     available combined with another sort - ignored on its own.
@@ -66,14 +66,11 @@ This endpoint allows you to search through public add-ons.
              users  Average number of daily users, descending.
     ==============  ==========================================================
 
-    The new default behavior is to sort by relevance if a search query (``q``)
+    The default behavior is to sort by relevance if a search query (``q``)
     is present; otherwise place recommended add-ons first, then non recommended
     add-ons, then sorted by average daily users, descending. (``sort=recommended,users``).
     This is the default on AMO dev server.
 
-    The default on AMO production currently is to sort by relevance if a search
-    query (``q``) is present; otherwise sort by number of weekly downloads, descending.
-
     You can combine multiple parameters by separating them with a comma.
     For instance, to sort search results by downloads and then by creation
     date, use ``sort=downloads,created``. The only exception is the ``random``

src/olympia/search/filters.py

@@ -915,7 +915,8 @@ class SortingFilter(BaseFilterBackend):
                 raise serializers.ValidationError(
                     'The "random" "sort" parameter can not be combined.')
 
-            # Second, for perf reasons it's only available when the 'featured'
+            # Second, for perf reasons it's only available when the 'featured',
+            # 'promoted'
             # or 'recommended' param is present (to limit the number of
             # documents we'll have to apply the random score to) and a search
             # query is absent (to prevent clashing with the score functions
@@ -924,6 +925,7 @@ class SortingFilter(BaseFilterBackend):
 
                 is_random_sort_available = (
                     (AddonFeaturedQueryParam.query_param in request.GET or
+                     AddonPromotedQueryParam.query_param in request.GET or
                      AddonRecommendedQueryParam.query_param in request.GET) and
                     not search_query_param
                 )
@@ -940,7 +942,8 @@ class SortingFilter(BaseFilterBackend):
                 else:
                     raise serializers.ValidationError(
                         'The "sort" parameter "random" can only be specified '
-                        'when the "featured" or "recommended" parameter is '
+                        'when the "featured", "promoted", or "recommended" '
+                        'parameter is '
                         'also present, and the "q" parameter absent.')
 
             # Sorting by relevance only makes sense with a query string

src/olympia/search/tests/test_filters.py

@@ -492,7 +492,8 @@ class TestSortingFilter(FilterTestsBase):
 
     def test_sort_random_restrictions(self):
         expected = ('The "sort" parameter "random" can only be specified when '
-                    'the "featured" or "recommended" parameter is also '
+                    'the "featured", "promoted", or "recommended" parameter '
+                    'is also '
                     'present, and the "q" parameter absent.')
 
         with self.assertRaises(serializers.ValidationError) as context:
@@ -504,6 +505,11 @@ class TestSortingFilter(FilterTestsBase):
                 data={'q': 'something', 'featured': 'true', 'sort': 'random'})
         assert context.exception.detail == [expected]
 
+        with self.assertRaises(serializers.ValidationError) as context:
+            self._filter(
+                data={'q': 'something', 'promoted': 'line', 'sort': 'random'})
+        assert context.exception.detail == [expected]
+
         with self.assertRaises(serializers.ValidationError) as context:
             self._filter(
                 data={'q': 'something', 'recommended': 'true',
@@ -523,13 +529,24 @@ class TestSortingFilter(FilterTestsBase):
 
     @freeze_time('2020-02-27')
     def test_sort_random(self):
+        qs = self._filter(data={'promoted': 'recommended', 'sort': 'random'})
+        # Note: this test does not call AddonPromotedQueryParam so it won't
+        # apply the recommended filtering. That's tested below in
+        # TestCombinedFilter.test_filter_promoted_sort_random
+        assert qs['sort'] == ['_score']
+        assert qs['query']['function_score']['functions'] == [
+            {'random_score': {'seed': 737482}}
+        ]
+
+    @freeze_time('2020-02-28')
+    def test_sort_random_recommended(self):
         qs = self._filter(data={'recommended': 'true', 'sort': 'random'})
         # Note: this test does not call AddonRecommendedQueryParam so it won't
         # apply the recommended filtering. That's tested below in
         # TestCombinedFilter.test_filter_recommended_sort_random
         assert qs['sort'] == ['_score']
         assert qs['query']['function_score']['functions'] == [
-            {'random_score': {'seed': 737482}}
+            {'random_score': {'seed': 737483}}
         ]
 
     def test_sort_recommended_only(self):
@@ -1079,6 +1096,24 @@ class TestCombinedFilter(FilterTestsBase):
             {'random_score': {'seed': 737481}}
         ]
 
+    @freeze_time('2020-02-26')
+    def test_filter_promoted_sort_random(self):
+        qs = self._filter(data={'promoted': 'verified', 'sort': 'random'})
+        bool_ = qs['query']['bool']
+
+        assert 'must_not' not in bool_
+
+        filter_ = bool_['filter']
+        assert {'terms': {'status': amo.REVIEWED_STATUSES}} in filter_
+        assert {'exists': {'field': 'current_version'}} in filter_
+        assert {'term': {'is_disabled': False}} in filter_
+
+        assert qs['sort'] == ['_score']
+
+        assert bool_['must'][0]['function_score']['functions'] == [
+            {'random_score': {'seed': 737481}}
+        ]
+
     @freeze_time('2020-02-26')
     def test_filter_recommended_sort_random(self):
         qs = self._filter(data={'recommended': 'true', 'sort': 'random'})