- # Rather than create an array of many hundred items and pick randomly
- # from it, just pick a number up to the total number of potential
- # items, then pick randomly from that, and partition the whole range
- # into chunks. This also avoids the slight problem that the index
- # contains more rows (for languages) for some items than others.
- # XXX ought to cache this (in the index?) if possible
- total = 0
- partitions = []
- for table_name in table_names:
- count = self.session.query(self.indexed_tables[table_name]).count()
- total += count
- partitions.append((table_name, count))
-
- n = random.randint(1, total)
- while n > partitions[0][1]:
- n -= partitions[0][1]
- partitions.pop(0)
-
- return self.lookup(unicode(n), valid_types=[ partitions[0][0] ])
+ # Pick a random table, then pick a random item from it. Small tables
+ # like Type will have an unnatural bias. The alternative is that a
+ # simple search for "random" will do some eight queries, counting the
+ # rows in every single indexed table, and that's awful.
+ # XXX Can we improve on this, reasonably?
+ table_name = random.choice(table_names)
+ count = self.session.query(self.indexed_tables[table_name]).count()
+ id, = self.session.query(self.indexed_tables[table_name].id) \
+ .offset(random.randint(0, count - 1)) \
+ .first()
+
+ return self.lookup(unicode(id), valid_types=[table_name])