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//usr/lib/python2.4/test/sortperf.py
"""Sort performance test. See main() for command line syntax. See tabulate() for output format. """ import sys import time import random import marshal import tempfile import os td = tempfile.gettempdir() 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: r = random.random result = [r() for i in xrange(n)] try: try: fp = open(fn, "wb") marshal.dump(result, fp) fp.close() fp = None finally: if fp: try: os.unlink(fn) except os.error: pass except IOError, msg: print "can't write", fn, ":", msg else: result = marshal.load(fp) fp.close() # Shuffle it a bit... for i in range(10): i = random.randrange(n) temp = result[:i] del result[:i] temp.reverse() result.extend(temp) del temp assert len(result) == n return result def flush(): sys.stdout.flush() def doit(L): t0 = time.clock() L.sort() t1 = time.clock() print "%6.2f" % (t1-t0), flush() def tabulate(r): """Tabulate sort speed for lists of various sizes. The sizes are 2**i for i in r (the argument, a list). The output displays i, 2**i, and the time to sort arrays of 2**i floating point numbers with the following properties: *sort: random data \sort: descending data /sort: ascending data 3sort: ascending, then 3 random exchanges +sort: ascending, then 10 random at the end %sort: ascending, then randomly replace 1% of the elements w/ random values ~sort: many duplicates =sort: all equal !sort: worst case scenario """ cases = tuple([ch + "sort" for ch in r"*\/3+%~=!"]) fmt = ("%2s %7s" + " %6s"*len(cases)) print fmt % (("i", "2**i") + cases) for i in r: n = 1 << i L = randfloats(n) print "%2d %7d" % (i, n), flush() doit(L) # *sort L.reverse() doit(L) # \sort doit(L) # /sort # Do 3 random exchanges. for dummy in range(3): i1 = random.randrange(n) i2 = random.randrange(n) L[i1], L[i2] = L[i2], L[i1] doit(L) # 3sort # Replace the last 10 with random floats. if n >= 10: L[-10:] = [random.random() for dummy in range(10)] doit(L) # +sort # Replace 1% of the elements at random. for dummy in xrange(n // 100): L[random.randrange(n)] = random.random() doit(L) # %sort # Arrange for lots of duplicates. if n > 4: del L[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 # 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. 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 def main(): """Main program when invoked as a script. One argument: tabulate a single row. Two arguments: tabulate a range (inclusive). Extra arguments are used to seed the random generator. """ # default range (inclusive) k1 = 15 k2 = 20 if sys.argv[1:]: # one argument: single point k1 = k2 = int(sys.argv[1]) if sys.argv[2:]: # two arguments: specify range k2 = int(sys.argv[2]) if sys.argv[3:]: # derive random seed from remaining arguments x = 1 for a in sys.argv[3:]: x = 69069 * x + hash(a) random.seed(x) r = range(k1, k2+1) # include the end point tabulate(r) if __name__ == '__main__': main()