ancestor: optimize _lazyancestorsiter() for contiguous chains

If there's no revision between p1 and current, p1 must be the next revision
to visit. In this case, we can get around the overhead of heappop/push
operations. Note that this is faster than using heapreplace().

'current - p1 == 1' could be generalized as 'all(r not in seen for r in
xrange(p1, current)', but Python is too slow to do such thing.

mercurial/ancestor.py

@@ -283,14 +283,22 b' def _lazyancestorsiter(parentrevs, initr'
                 see(p2)
 
     while visit:
-        current = -nextitem(visit)
+        current = -visit[0]
         if current < stoprev:
             break
         yield current
+        # optimize out heapq operation if p1 is known to be the next highest
+        # revision, which is quite common in linear history.
         p1, p2 = parentrevs(current)
         if p1 not in seen:
-            schedule(visit, -p1)
+            if current - p1 == 1:
+                visit[0] = -p1
+            else:
+                nextitem(visit)
+                schedule(visit, -p1)
             see(p1)
+        else:
+            nextitem(visit)
         if p2 not in seen:
             schedule(visit, -p2)
             see(p2)

tests/test-ancestor.py

@@ -221,6 +221,10 b' def test_lazyancestors():'
     s = genlazyancestors([11, 13], stoprev=12, inclusive=True)
     printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])
 
+    # Contiguous chains: 5->4, 2->1 (where 1 is in seen set), 1->0
+    s = genlazyancestors([10, 1], inclusive=True)
+    printlazyancestors(s, [2, 10, 4, 5, -1, 0, 1])
+
 # The C gca algorithm requires a real repo. These are textual descriptions of
 # DAGs that have been known to be problematic, and, optionally, known pairs
 # of revisions and their expected ancestor list.

tests/test-ancestor.py.out

@@ -22,3 +22,6 b' iteration: [13, 11]'
 % lazy ancestor set for [11, 13], stoprev = 12, inclusive = True
 membership: [13]
 iteration:  [13]
+% lazy ancestor set for [10, 1], stoprev = 0, inclusive = True
+membership: [2, 10, 4, 5, 0, 1]
+iteration:  [10, 5, 4, 2, 1, 0]