def evaluate_delta(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs to evaluate-delta")
(old, new) = args.remainder
vargs = vars_of_args(args)
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
env = {}
ident = re.compile('(\w+)$')
for r in compare_stats(args, old_stats.stats, new_stats.stats):
if r.name.startswith("time.") or '.time.' in r.name:
continue
m = re.search(ident, r.name)
if m:
i = m.groups()[0]
if args.verbose:
print("%s => %s" % (i, r.delta))
env[i] = r.delta
try:
if eval(args.evaluate_delta, env):
return 0
else:
print("evaluate-delta condition failed: '%s'" %
args.evaluate_delta)
return 1
except Exception as e:
print(e)
return 1
def evaluate_delta(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs to evaluate-delta")
(old, new) = args.remainder
vargs = vars_of_args(args)
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
env = {}
ident = re.compile('(\w+)$')
for r in compare_stats(args, old_stats.stats, new_stats.stats):
if r.name.startswith("time.") or '.time.' in r.name:
continue
m = re.search(ident, r.name)
if m:
i = m.groups()[0]
if args.verbose:
print("%s => %s" % (i, r.delta))
env[i] = r.delta
try:
if eval(args.evaluate_delta, env):
return 0
else:
print("evaluate-delta condition failed: '%s'" %
args.evaluate_delta)
return 1
except Exception as e:
print(e)
return 1
def load_paired_stats_dirs(args):
assert (len(args.remainder) == 2)
paired_stats = []
mod = args.select_module
stat = args.select_stat
xt = args.exclude_timers
(old, new) = args.remainder
for p in sorted(os.listdir(old)):
full_old = os.path.join(old, p)
full_new = os.path.join(new, p)
if not (os.path.exists(full_old) and os.path.isdir(full_old)
and os.path.exists(full_new) and os.path.isdir(full_new)):
continue
old_stats = load_stats_dir(full_old,
select_module=mod,
select_stat=stat,
exclude_timers=xt)
new_stats = load_stats_dir(full_new,
select_module=mod,
select_stat=stat,
exclude_timers=xt)
if len(old_stats) == 0 or len(new_stats) == 0:
continue
paired_stats.append((p, (old_stats, new_stats)))
return paired_stats
def compare_stats_dirs(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs")
vargs = vars_of_args(args)
(old, new) = args.remainder
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
return write_comparison(args, old_stats.stats, new_stats.stats)
def compare_stats_dirs(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs")
vargs = vars_of_args(args)
(old, new) = args.remainder
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
return write_comparison(args, old_stats.stats, new_stats.stats)
def compare_stats_dirs(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs")
(old, new) = args.remainder
old_stats = merge_all_jobstats(load_stats_dir(
old, select_module=args.select_module),
select_module=args.select_module,
group_by_module=args.group_by_module)
new_stats = merge_all_jobstats(load_stats_dir(
new, select_module=args.select_module),
select_module=args.select_module,
group_by_module=args.group_by_module)
return write_comparison(args, old_stats.stats, new_stats.stats)
def evaluate(args):
if len(args.remainder) != 1:
raise ValueError("Expected exactly 1 stats-dir to evaluate against")
d = args.remainder[0]
vargs = vars_of_args(args)
merged = merge_all_jobstats(load_stats_dir(d, **vargs), **vargs)
env = {}
ident = re.compile('(\w+)$')
for (k, v) in merged.stats.items():
if k.startswith("time.") or '.time.' in k:
continue
m = re.search(ident, k)
if m:
i = m.groups()[0]
if args.verbose:
print("%s => %s" % (i, v))
env[i] = v
try:
if eval(args.evaluate, env):
return 0
else:
print("evaluate condition failed: '%s'" % args.evaluate)
return 1
except Exception as e:
print(e)
return 1
def load_paired_stats_dirs(args):
assert(len(args.remainder) == 2)
paired_stats = []
(old, new) = args.remainder
for p in sorted(os.listdir(old)):
full_old = os.path.join(old, p)
full_new = os.path.join(new, p)
if not (os.path.exists(full_old) and os.path.isdir(full_old) and
os.path.exists(full_new) and os.path.isdir(full_new)):
continue
old_stats = load_stats_dir(full_old, **vars(args))
new_stats = load_stats_dir(full_new, **vars(args))
if len(old_stats) == 0 or len(new_stats) == 0:
continue
paired_stats.append((p, (old_stats, new_stats)))
return paired_stats
def load_paired_stats_dirs(args):
assert (len(args.remainder) == 2)
paired_stats = []
(old, new) = args.remainder
for p in sorted(os.listdir(old)):
full_old = os.path.join(old, p)
full_new = os.path.join(new, p)
if not (os.path.exists(full_old) and os.path.isdir(full_old)
and os.path.exists(full_new) and os.path.isdir(full_new)):
continue
old_stats = load_stats_dir(full_old, **vars(args))
new_stats = load_stats_dir(full_new, **vars(args))
if len(old_stats) == 0 or len(new_stats) == 0:
continue
paired_stats.append((p, (old_stats, new_stats)))
return paired_stats
def write_lnt_values(args):
for d in args.remainder:
stats = load_stats_dir(d,
select_module=args.select_module,
select_stat=args.select_stat,
exclude_timers=args.exclude_timers)
merged = merge_all_jobstats(stats,
select_module=args.select_module,
group_by_module=args.group_by_module)
j = merged.to_lnt_test_obj(args)
if args.lnt_submit is None:
json.dump(j, args.output, indent=4)
else:
url = args.lnt_submit
print "\nsubmitting to LNT server: " + url
json_report = {'input_data': json.dumps(j), 'commit': '1'}
data = urllib.urlencode(json_report)
response_str = urllib2.urlopen(urllib2.Request(url, data))
response = json.loads(response_str.read())
print "### response:"
print response
if 'success' in response:
print "server response:\tSuccess"
else:
print "server response:\tError"
print "error:\t", response['error']
sys.exit(1)
def set_csv_baseline(args):
existing = None
if os.path.exists(args.set_csv_baseline):
with open(args.set_csv_baseline, "r") as f:
existing = read_stats_dict_from_csv(f)
print("updating %d baseline entries in %s" %
(len(existing), args.set_csv_baseline))
else:
print "making new baseline " + args.set_csv_baseline
fieldnames = ["epoch", "name", "value"]
with open(args.set_csv_baseline, "wb") as f:
out = csv.DictWriter(f,
fieldnames,
dialect='excel-tab',
quoting=csv.QUOTE_NONNUMERIC)
sel = args.select_module
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, select_module=sel)),
select_module=sel,
group_by_module=args.group_by_module)
changed = 0
newepoch = int(time.time())
for name in sorted(m.stats.keys()):
epoch = newepoch
value = m.stats[name]
if existing is not None:
if name not in existing:
continue
(epoch, value,
chg) = update_epoch_value(existing, name, epoch, value)
changed += chg
out.writerow(dict(epoch=int(epoch), name=name, value=int(value)))
if existing is not None:
print "changed %d entries in baseline" % changed
return 0
def evaluate(args):
if len(args.remainder) != 1:
raise ValueError("Expected exactly 1 stats-dir to evaluate against")
d = args.remainder[0]
vargs = vars_of_args(args)
merged = merge_all_jobstats(load_stats_dir(d, **vargs), **vargs)
env = {}
ident = re.compile('(\w+)$')
for (k, v) in merged.stats.items():
if k.startswith("time.") or '.time.' in k:
continue
m = re.search(ident, k)
if m:
i = m.groups()[0]
if args.verbose:
print("%s => %s" % (i, v))
env[i] = v
try:
if eval(args.evaluate, env):
return 0
else:
print("evaluate condition failed: '%s'" % args.evaluate)
return 1
except Exception as e:
print(e)
return 1
def write_catapult_trace(args):
allstats = []
for path in args.remainder:
allstats += load_stats_dir(path,
select_module=args.select_module,
select_stat=args.select_stat,
exclude_timers=args.exclude_timers)
json.dump([s.to_catapult_trace_obj() for s in allstats], args.output)
def write_catapult_trace(args):
allstats = []
vargs = vars_of_args(args)
for path in args.remainder:
allstats += load_stats_dir(path, **vargs)
allstats.sort(key=attrgetter('start_usec'))
for i in range(len(allstats)):
allstats[i].jobid = i
json.dump([s.to_catapult_trace_obj() for s in allstats], args.output)
def write_catapult_trace(args):
allstats = []
vargs = vars_of_args(args)
for path in args.remainder:
allstats += load_stats_dir(path, **vargs)
allstats.sort(key=attrgetter('start_usec'))
for i in range(len(allstats)):
allstats[i].jobid = i
json.dump([s.to_catapult_trace_obj() for s in allstats], args.output)
def compare_stats_dirs(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs")
vargs = vars(args)
if args.select_stats_from_csv_baseline is not None:
b = read_stats_dict_from_csv(args.select_stats_from_csv_baseline)
if args.group_by_module:
pat = re.compile('^\w+\.')
vargs['select_stat'] = set(re.sub(pat, '', k) for k in b.keys())
else:
vargs['select_stat'] = b.keys()
(old, new) = args.remainder
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
return write_comparison(args, old_stats.stats, new_stats.stats)
def compare_to_csv_baseline(args):
old_stats = read_stats_dict_from_csv(args.compare_to_csv_baseline)
m = merge_all_jobstats(
(s for d in args.remainder for s in load_stats_dir(d, **vars(args))),
**vars(args))
old_stats = dict((k, v) for (k, (_, v)) in old_stats.items())
new_stats = m.stats
return write_comparison(args, old_stats, new_stats)
def compare_stats_dirs(args):
if len(args.remainder) != 2:
raise ValueError("Expected exactly 2 stats-dirs")
vargs = vars(args)
if args.select_stats_from_csv_baseline is not None:
b = read_stats_dict_from_csv(args.select_stats_from_csv_baseline)
if args.group_by_module:
pat = re.compile('^\w+\.')
vargs['select_stat'] = set(re.sub(pat, '', k) for k in b.keys())
else:
vargs['select_stat'] = b.keys()
(old, new) = args.remainder
old_stats = merge_all_jobstats(load_stats_dir(old, **vargs), **vargs)
new_stats = merge_all_jobstats(load_stats_dir(new, **vargs), **vargs)
return write_comparison(args, old_stats.stats, new_stats.stats)
def compare_to_csv_baseline(args):
old_stats = read_stats_dict_from_csv(args.compare_to_csv_baseline,
select_stat=args.select_stat)
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, **vars(args))),
**vars(args))
old_stats = dict((k, v) for (k, (_, v)) in old_stats.items())
new_stats = m.stats
return write_comparison(args, old_stats, new_stats)
def compare_to_csv_baseline(args):
old_stats = read_stats_dict_from_csv(args.compare_to_csv_baseline)
sel = args.select_module
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, select_module=sel)),
select_module=sel,
group_by_module=args.group_by_module)
old_stats = dict((k, v) for (k, (_, v)) in old_stats.items())
new_stats = m.stats
return write_comparison(args, old_stats, new_stats)
def compare_to_csv_baseline(args):
vargs = vars_of_args(args)
with io.open(args.compare_to_csv_baseline, 'r', encoding='utf-8') as f:
old_stats = read_stats_dict_from_csv(f,
select_stat=vargs['select_stat'])
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, **vargs)), **vargs)
old_stats = dict((k, v) for (k, (_, v)) in old_stats.items())
new_stats = m.stats
return write_comparison(args, old_stats, new_stats)
def show_incrementality(args):
fieldnames = ["incrementality", "name"]
out = csv.DictWriter(args.output, fieldnames, dialect='excel-tab')
out.writeheader()
for path in args.remainder:
stats = load_stats_dir(path, **vars(args))
for s in stats:
if s.is_driver_job():
pct = s.incrementality_percentage()
out.writerow(dict(name=os.path.basename(path),
incrementality=pct))
def show_incrementality(args):
fieldnames = ["incrementality", "name"]
out = csv.DictWriter(args.output, fieldnames, dialect='excel-tab')
out.writeheader()
for path in args.remainder:
stats = load_stats_dir(path, **vars(args))
for s in stats:
if s.is_driver_job():
pct = s.incrementality_percentage()
out.writerow(
dict(name=os.path.basename(path), incrementality=pct))
def set_csv_baseline(args):
existing = None
vargs = vars_of_args(args)
if os.path.exists(args.set_csv_baseline):
with io.open(args.set_csv_baseline,
"r",
encoding='utf-8',
newline='\n') as f:
ss = vargs['select_stat']
existing = read_stats_dict_from_csv(f, select_stat=ss)
print("updating %d baseline entries in %s" %
(len(existing), args.set_csv_baseline))
else:
print("making new baseline " + args.set_csv_baseline)
fieldnames = ["epoch", "name", "value"]
def _open(path):
if sys.version_info[0] < 3:
return open(path, 'wb')
return io.open(path, "w", encoding='utf-8', newline='\n')
with _open(args.set_csv_baseline) as f:
out = csv.DictWriter(f,
fieldnames,
dialect='excel-tab',
quoting=csv.QUOTE_NONNUMERIC)
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, **vargs)), **vargs)
if m is None:
print("no stats found")
return 1
changed = 0
newepoch = int(time.time())
for name in sorted(m.stats.keys()):
epoch = newepoch
value = m.stats[name]
if existing is not None:
if name not in existing:
continue
(epoch, value,
chg) = update_epoch_value(existing, name, epoch, value)
changed += chg
out.writerow(dict(epoch=int(epoch), name=name, value=int(value)))
if existing is not None:
print("changed %d entries in baseline" % changed)
return 0
def write_lnt_values(args):
for d in args.remainder:
stats = load_stats_dir(d, **vars(args))
merged = merge_all_jobstats(stats, **vars(args))
j = merged.to_lnt_test_obj(args)
if args.lnt_submit is None:
json.dump(j, args.output, indent=4)
else:
url = args.lnt_submit
print "\nsubmitting to LNT server: " + url
json_report = {'input_data': json.dumps(j), 'commit': '1'}
data = urllib.urlencode(json_report)
response_str = urllib2.urlopen(urllib2.Request(url, data))
response = json.loads(response_str.read())
print "### response:"
print response
if 'success' in response:
print "server response:\tSuccess"
else:
print "server response:\tError"
print "error:\t", response['error']
sys.exit(1)
def set_csv_baseline(args):
existing = None
vargs = vars_of_args(args)
if os.path.exists(args.set_csv_baseline):
with open(args.set_csv_baseline, "r") as f:
ss = vargs['select_stat']
existing = read_stats_dict_from_csv(f, select_stat=ss)
print ("updating %d baseline entries in %s" %
(len(existing), args.set_csv_baseline))
else:
print "making new baseline " + args.set_csv_baseline
fieldnames = ["epoch", "name", "value"]
with open(args.set_csv_baseline, "wb") as f:
out = csv.DictWriter(f, fieldnames, dialect='excel-tab',
quoting=csv.QUOTE_NONNUMERIC)
m = merge_all_jobstats((s for d in args.remainder
for s in load_stats_dir(d, **vargs)),
**vargs)
if m is None:
print "no stats found"
return 1
changed = 0
newepoch = int(time.time())
for name in sorted(m.stats.keys()):
epoch = newepoch
value = m.stats[name]
if existing is not None:
if name not in existing:
continue
(epoch, value, chg) = update_epoch_value(existing, name,
epoch, value)
changed += chg
out.writerow(dict(epoch=int(epoch),
name=name,
value=int(value)))
if existing is not None:
print "changed %d entries in baseline" % changed
return 0
def write_lnt_values(args):
vargs = vars_of_args(args)
for d in args.remainder:
stats = load_stats_dir(d, **vargs)
merged = merge_all_jobstats(stats, **vargs)
j = merged.to_lnt_test_obj(args)
if args.lnt_submit is None:
json.dump(j, args.output, indent=4)
else:
url = args.lnt_submit
print("\nsubmitting to LNT server: " + url)
json_report = {'input_data': json.dumps(j), 'commit': '1'}
data = urllib.urlencode(json_report)
response_str = URLOpen(Request(url, data))
response = json.loads(response_str.read())
print("### response:")
print(response)
if 'success' in response:
print("server response:\tSuccess")
else:
print("server response:\tError")
print("error:\t", response['error'])
sys.exit(1)
def write_catapult_trace(args):
allstats = []
vargs = vars_of_args(args)
for path in args.remainder:
allstats += load_stats_dir(path, **vargs)
json.dump([s.to_catapult_trace_obj() for s in allstats], args.output)
def write_catapult_trace(args):
allstats = []
for path in args.remainder:
allstats += load_stats_dir(path, **vars(args))
json.dump([s.to_catapult_trace_obj() for s in allstats], args.output)
