cpython/Lib/test/sortperf.py
Tim Peters 7ea39b135a New test "+sort", tacking 10 random floats on to the end of a sorted
array.  Our samplesort special-cases the snot out of this, running about
12x faster than *sort.  The experimental mergesort runs it about 8x
faster than *sort without special-casing, but should really do better
than that (when merging runs of different lengths, right now it only
does something clever about finding where the second run begins in
the first and where the first run ends in the second, and that's more
of a temp-memory optimization).
2002-07-21 17:37:03 +00:00

163 lines
4.4 KiB
Python

"""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: 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
# 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()