diff --git a/Lib/test/sortperf.py b/Lib/test/sortperf.py index 4ad82a6c8da..546afd5cad9 100644 --- a/Lib/test/sortperf.py +++ b/Lib/test/sortperf.py @@ -10,20 +10,21 @@ import time import random import marshal import tempfile -import operator import os td = tempfile.gettempdir() -def randrange(n): - """Return a random shuffle of range(n).""" +def randfloats(n): + """Return a list of n random floats in [0, 1).""" + # Generating floats is expensive, so this writes them out to a file in + # a temp directory. If the file already exists, it just reads them + # back in and shuffles them a bit. fn = os.path.join(td, "rr%06d" % n) try: fp = open(fn, "rb") except IOError: - result = [] - for i in range(n): - result.append(random.random()) + r = random.random + result = [r() for i in xrange(n)] try: try: fp = open(fn, "wb") @@ -41,18 +42,18 @@ def randrange(n): else: result = marshal.load(fp) fp.close() - ##assert len(result) == n # Shuffle it a bit... for i in range(10): - i = random.randrange(0, n) + i = random.randrange(n) temp = result[:i] del result[:i] temp.reverse() - result[len(result):] = temp + result.extend(temp) del temp + assert len(result) == n return result -def fl(): +def flush(): sys.stdout.flush() def doit(L): @@ -60,7 +61,7 @@ def doit(L): L.sort() t1 = time.clock() print "%6.2f" % (t1-t0), - fl() + flush() def tabulate(r): """Tabulate sort speed for lists of various sizes. @@ -74,33 +75,50 @@ def tabulate(r): \sort: descending data /sort: ascending data ~sort: many duplicates - -sort: all equal + =sort: all equal !sort: worst case scenario """ - cases = ("*sort", "\\sort", "/sort", "~sort", "-sort", "!sort") - fmt = ("%2s %6s" + " %6s"*len(cases)) + cases = ("*sort", "\\sort", "/sort", "~sort", "=sort", "!sort") + fmt = ("%2s %7s" + " %6s"*len(cases)) print fmt % (("i", "2**i") + cases) for i in r: - n = 1< 4: del L[4:] - L = L*(n/4) + L = L * (n // 4) + # Force the elements to be distinct objects, else timings can be + # artificially low. L = map(lambda x: --x, L) doit(L) # ~sort del L - L = map(abs, [-0.5]*n) - doit(L) # -sort - L = range(n/2-1, -1, -1) - L[len(L):] = range(n/2) + + # All equal. Again, force the elements to be distinct objects. + L = map(abs, [-0.5] * n) + doit(L) # =sort + del L + + # This one looks like [3, 2, 1, 0, 0, 1, 2, 3]. It was a bad case + # for an older implementation of quicksort, which used the median + # of the first, last and middle elements as the pivot. It's still + # a worse-than-average case for samplesort, but on the order of a + # measly 5% worse, not a quadratic-time disaster as it was with + # quicksort. + half = n // 2 + L = range(half - 1, -1, -1) + L.extend(range(half)) + # Force to float, so that the timings are comparable. This is + # significantly faster if we leave tham as ints. + L = map(float, L) doit(L) # !sort print @@ -114,7 +132,7 @@ def main(): """ # default range (inclusive) k1 = 15 - k2 = 19 + k2 = 20 if sys.argv[1:]: # one argument: single point k1 = k2 = int(sys.argv[1]) @@ -123,17 +141,10 @@ def main(): k2 = int(sys.argv[2]) if sys.argv[3:]: # derive random seed from remaining arguments - x, y, z = 0, 0, 0 + x = 1 for a in sys.argv[3:]: - h = hash(a) - h, d = divmod(h, 256) - h = h & 0xffffff - x = (x^h^d) & 255 - h = h>>8 - y = (y^h^d) & 255 - h = h>>8 - z = (z^h^d) & 255 - whrandom.seed(x, y, z) + x = 69069 * x + hash(a) + random.seed(x) r = range(k1, k2+1) # include the end point tabulate(r)