Switch a datastructure internal to the ORM to be a set, instead of a dictionary.

django/contrib/gis/db/models/sql/query.py

@@ -9,7 +9,7 @@ from django.contrib.gis.geometry.backend import Geometry
 from django.contrib.gis.measure import Area, Distance
 
 
-ALL_TERMS = dict([(x, None) for x in (
+ALL_TERMS = set([
             'bbcontains', 'bboverlaps', 'contained', 'contains',
             'contains_properly', 'coveredby', 'covers', 'crosses', 'disjoint',
             'distance_gt', 'distance_gte', 'distance_lt', 'distance_lte',
@@ -18,7 +18,7 @@ ALL_TERMS = dict([(x, None) for x in (
             'left', 'right', 'overlaps_left', 'overlaps_right',
             'overlaps_above', 'overlaps_below',
             'strictly_above', 'strictly_below'
-            )])
+            ])
 ALL_TERMS.update(sql.constants.QUERY_TERMS)
 
 class GeoQuery(sql.Query):

django/db/models/sql/constants.py

@@ -2,11 +2,11 @@ from collections import namedtuple
 import re
 
 # Valid query types (a dictionary is used for speedy lookups).
-QUERY_TERMS = dict([(x, None) for x in (
+QUERY_TERMS = set([
     'exact', 'iexact', 'contains', 'icontains', 'gt', 'gte', 'lt', 'lte', 'in',
     'startswith', 'istartswith', 'endswith', 'iendswith', 'range', 'year',
     'month', 'day', 'week_day', 'isnull', 'search', 'regex', 'iregex',
-)])
+])
 
 # Size of each "chunk" for get_iterator calls.
 # Larger values are slightly faster at the expense of more storage space.