blob: 3938c40e51dae8c393a7b8ab8fcb9bca5f2896a5 [file] [log] [blame]
#!/usr/bin/env python
# Copyright 2015 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Print statistics about the rate of commits to a repository."""
import datetime
import itertools
import json
import math
import urllib
import urllib2
_BASE_URL = 'https://chromium.googlesource.com/'
# Can be up to 10,000.
_REVISION_COUNT = 1000
_REPOSITORIES = [
'chromium/src',
'angle/angle',
'skia',
'v8/v8',
]
def Pairwise(iterable):
"""s -> (s0,s1), (s1,s2), (s2, s3), ..."""
a, b = itertools.tee(iterable)
next(b, None)
return itertools.izip(a, b)
def Percentile(data, percentile):
"""Find a percentile of a list of values.
Parameters:
data: A sorted list of values.
percentile: The percentile to look up, from 0.0 to 1.0.
Returns:
The percentile.
Raises:
ValueError: If data is empty.
"""
if not data:
raise ValueError()
k = (len(data) - 1) * percentile
f = math.floor(k)
c = math.ceil(k)
if f == c:
return data[int(k)]
return data[int(f)] * (c - k) + data[int(c)] * (k - f)
def CommitTimes(repository, revision_count):
parameters = urllib.urlencode((('n', revision_count), ('format', 'JSON')))
url = '%s/%s/+log?%s' % (_BASE_URL, urllib.quote(repository), parameters)
data = json.loads(''.join(urllib2.urlopen(url).read().splitlines()[1:]))
commit_times = []
for revision in data['log']:
commit_time_string = revision['committer']['time']
commit_time = datetime.datetime.strptime(
commit_time_string, '%a %b %d %H:%M:%S %Y')
commit_times.append(commit_time)
return commit_times
def main():
for repository in _REPOSITORIES:
commit_times = CommitTimes(repository, _REVISION_COUNT)
commit_durations = []
for time1, time2 in Pairwise(commit_times):
commit_durations.append((time1 - time2).total_seconds())
commit_durations.sort()
print 'REPOSITORY:', repository
print 'Start Date:', min(commit_times)
print ' End Date:', max(commit_times)
print ' Duration:', max(commit_times) - min(commit_times)
print ' n:', len(commit_times)
for p in (0.00, 0.05, 0.25, 0.50, 0.75, 0.95, 1.00):
percentile = Percentile(commit_durations, p)
print '%3d%% commit duration:' % (p * 100), '%6ds' % percentile
mean = math.fsum(commit_durations) / len(commit_durations)
print ' Min commit duration:', '%6ds' % min(commit_durations)
print 'Mean commit duration:', '%6ds' % mean
print ' Max commit duration:', '%6ds' % max(commit_durations)
print
if __name__ == '__main__':
main()