def print_summary(args, printer=sys.stdout.write):
time_range = get_time_range(args)
timed_producer = prof.timed_trace_producer()
timed_samples = []
count_per_tp = defaultdict(lambda: 0)
count = 0
min_time = None
max_time = None
class CpuTimeRange:
def __init__(self):
self.min = None
self.max = None
def update(self, time):
if self.min is None or time < self.min:
self.min = time
if self.max is None or time > self.max:
self.max = time
cpu_time_ranges = defaultdict(CpuTimeRange)
with get_trace_reader(args) as reader:
for t in reader.get_traces():
if t.time in time_range:
cpu_time_ranges[t.cpu].update(t.time)
count += 1
count_per_tp[t.tp] += 1
if not min_time:
min_time = t.time
else:
min_time = min(min_time, t.time)
if not max_time:
max_time = t.time
else:
max_time = max(max_time, t.time)
if args.timed:
timed = timed_producer(t)
if timed:
timed_samples.append(timed)
if args.timed:
timed_samples.extend((timed_producer.finish()))
if count == 0:
print("No samples")
return
print("Collected %d samples spanning %s" %
(count, prof.format_time(max_time - min_time)))
print("\nTime ranges:\n")
for cpu, r in sorted(list(cpu_time_ranges.items()),
key=lambda c_r: c_r[1].min):
print(" CPU 0x%02d: %s - %s = %10s" % (cpu, trace.format_time(
r.min), trace.format_time(r.max), prof.format_time(r.max - r.min)))
max_name_len = reduce(max,
[len(tp.name) for tp in iter(count_per_tp.keys())])
format = " %%-%ds %%8s" % (max_name_len)
print("\nTracepoint statistics:\n")
print(format % ("name", "count"))
print(format % ("----", "-----"))
for tp, count in sorted(iter(count_per_tp.items()),
key=lambda tp_count: tp_count[0].name):
print(format % (tp.name, count))
if args.timed:
format = " %-20s %8s %8s %8s %8s %8s %8s %8s %15s"
print("\nTimed tracepoints [ms]:\n")
timed_samples = [
t for t in timed_samples if t.time_range.intersection(time_range)
]
if not timed_samples:
print(" None")
else:
print(format % ("name", "count", "min", "50%", "90%", "99%",
"99.9%", "max", "total"))
print(format % ("----", "-----", "---", "---", "---", "---",
"-----", "---", "-----"))
for name, traces in get_timed_traces_per_function(
timed_samples).items():
samples = sorted(
list((t.time_range.intersection(time_range).length()
for t in traces)))
print(format %
(name, len(samples),
format_duration(get_percentile(samples, 0)),
format_duration(get_percentile(samples, 0.5)),
format_duration(get_percentile(samples, 0.9)),
format_duration(get_percentile(samples, 0.99)),
format_duration(get_percentile(samples, 0.999)),
format_duration(get_percentile(
samples, 1)), format_duration(sum(samples))))
print()
def print_summary(args, printer=sys.stdout.write):
time_range = get_time_range(args)
timed_producer = prof.timed_trace_producer()
timed_samples = []
count_per_tp = defaultdict(lambda: 0)
count = 0
min_time = None
max_time = None
with get_trace_reader(args) as reader:
for t in reader.get_traces():
if t.time in time_range:
count += 1
count_per_tp[t.tp] += 1
if not min_time:
min_time = t.time
else:
min_time = min(min_time, t.time)
max_time = max(max_time, t.time)
if args.timed:
timed = timed_producer(t)
if timed:
timed_samples.append(timed)
if args.timed:
timed_samples.extend((timed_producer.finish()))
if count == 0:
print "No samples"
return
print "Collected %d samples spanning %s" % (count, prof.format_time(max_time - min_time))
max_name_len = reduce(max, map(lambda tp: len(tp.name), count_per_tp.iterkeys()))
format = " %%-%ds %%8s" % (max_name_len)
print "\nTracepoint statistics:\n"
print format % ("name", "count")
print format % ("----", "-----")
for tp, count in sorted(count_per_tp.iteritems(), key=lambda (tp, count): tp.name):
print format % (tp.name, count)
if args.timed:
format = " %-20s %8s %8s %8s %8s %8s %8s %8s %15s"
print "\nTimed tracepoints [ms]:\n"
timed_samples = filter(lambda t: t.time_range.intersection(time_range), timed_samples)
if not timed_samples:
print " None"
else:
print format % ("name", "count", "min", "50%", "90%", "99%", "99.9%", "max", "total")
print format % ("----", "-----", "---", "---", "---", "---", "-----", "---", "-----")
for name, traces in get_timed_traces_per_function(timed_samples).iteritems():
samples = sorted(list((t.time_range.intersection(time_range).length() for t in traces)))
print format % (
name,
len(samples),
format_duration(get_percentile(samples, 0)),
format_duration(get_percentile(samples, 0.5)),
format_duration(get_percentile(samples, 0.9)),
format_duration(get_percentile(samples, 0.99)),
format_duration(get_percentile(samples, 0.999)),
format_duration(get_percentile(samples, 1)),
format_duration(sum(samples)))
print