benchmarks/bench-parse.py · typeable/aeson

git.iko.soy/typeable/aeson

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1#!/usr/bin/env python

3import os, re, subprocess, sys

5result_re = re.compile(r'^\s*(\d+) good, (\d+\.\d+)s$', re.M)

7def run(count, filename):

8 print ' %s :: %s times' % (filename, count)

9 p = subprocess.Popen(['./AesonParse', str(count), filename],

10 stdout=subprocess.PIPE)

11 output = p.stdout.read()

12 p.wait()

13 m = result_re.search(output)

14 if not m:

15 print >> sys.stderr, 'run gave confusing output!?'

16 sys.stderr.write(output)

17 return

18 else:

19 #sys.stdout.write(output)

20 pass

21 good, elapsed = m.groups()

22 good, elapsed = int(good), float(elapsed)

23 st = os.stat(filename)

24 parses_per_second = good / elapsed

25 mb_per_second = st.st_size * parses_per_second / 1048576

26 print (' %.3f seconds, %d parses/sec, %.3f MB/sec' %

27 (elapsed, parses_per_second, mb_per_second))

28 return parses_per_second, mb_per_second, st.st_size, elapsed

30def runtimes(count, filename, times=1):

31 for i in xrange(times):

32 yield run(count, filename)

34info = '''

35json-data/twitter1.json 60000

36json-data/twitter10.json 13000

37json-data/twitter20.json 7500

38json-data/twitter50.json 2500

39json-data/twitter100.json 1000

40json-data/jp10.json 4000

41json-data/jp50.json 1200

42json-data/jp100.json 700

43'''

45for i in info.strip().splitlines():

46 name, count = i.split()

47 best = sorted(runtimes(int(count), name, times=3), reverse=True)[0]

48 parses_per_second, mb_per_second, size, elapsed = best

49 print ('%.1f KB: %d msg\\/sec (%.1f MB\\/sec)' %

50 (size / 1024.0, int(round(parses_per_second)), mb_per_second))