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-rw-r--r--Lib/test/test_heapq.py23
1 files changed, 18 insertions, 5 deletions
diff --git a/Lib/test/test_heapq.py b/Lib/test/test_heapq.py
index 1330f12..7f6d918 100644
--- a/Lib/test/test_heapq.py
+++ b/Lib/test/test_heapq.py
@@ -12,6 +12,20 @@ def check_invariant(heap):
parentpos = (pos-1) >> 1
verify(heap[parentpos] <= item)
+# An iterator returning a heap's elements, smallest-first.
+class heapiter(object):
+ def __init__(self, heap):
+ self.heap = heap
+
+ def next(self):
+ try:
+ return heappop(self.heap)
+ except IndexError:
+ raise StopIteration
+
+ def __iter__(self):
+ return self
+
def test_main():
# 1) Push 100 random numbers and pop them off, verifying all's OK.
heap = []
@@ -47,17 +61,16 @@ def test_main():
check_invariant(heap)
# 5) Less-naive "N-best" algorithm, much faster (if len(data) is big
# enough <wink>) than sorting all of data. However, if we had a max
- # heap instead of a min heap, it would go much faster still via
+ # heap instead of a min heap, it could go faster still via
# heapify'ing all of data (linear time), then doing 10 heappops
# (10 log-time steps).
heap = data[:10]
heapify(heap)
for item in data[10:]:
- if item > heap[0]: # this gets rarer and rarer the longer we run
+ if item > heap[0]: # this gets rarer the longer we run
+ heappop(heap) # we know heap[0] isn't in best 10 anymore
heappush(heap, item)
- heappop(heap)
- heap.sort()
- vereq(heap, data_sorted[-10:])
+ vereq(list(heapiter(heap)), data_sorted[-10:])
# Make user happy
if verbose:
print "All OK"