def is_perf_file(f):
for line in f:
if (line[0] == '#'):
continue
r = event_regexp.search(line)
if r:
return True
return False
def _is_perf_file(file_path):
f = get_file(file_path)
for line in f:
if (line[0] == '#'):
continue
r = event_regexp.search(line)
if r:
f.close()
return True
f.close()
return False
def calculate_profile_range(filename):
start = float("+inf")
end = float("-inf")
index_factor = 100 # save one timestamp per this many lines
file_path = join(config.PROFILE_DIR, filename)
# check for cached times
mtime = getmtime(file_path)
if file_path in stack_times:
if mtime == stack_mtimes[file_path]:
return stack_times[file_path]
f = get_file(file_path)
linenum = -1
stack_index[file_path] = []
for line in f:
linenum += 1
# 1. Skip '#' comments
# 2. Since we're only interested in the event summary lines, skip the
# stack trace lines based on those that start with '\t'. This is a
# performance optimization that avoids using the regexp needlessly,
# and makes a large difference.
if (line[0] == '#' or line[0] == '\t'):
continue
r = event_regexp.search(line)
if (r):
ts = float(r.group(1))
if ((linenum % index_factor) == 0):
stack_index[file_path].append([linenum, ts])
if (ts < start):
start = ts
elif (ts > end):
end = ts
f.close()
times = collections.namedtuple('range', ['start', 'end'])(floor(start),
ceil(end))
stack_times[file_path] = times
stack_mtimes[file_path] = mtime
return times
def perf_generate_flame_graph(filename, range_start=None, range_end=None):
file_path = join(config.PROFILE_DIR, filename)
(f, mime) = get_file(file_path)
# calculate profile file range
r = calculate_profile_range(filename)
start = r.start
end = r.end
# check range. default to full range if not specified.
if (range_end):
if ((start + range_end) > end):
print("ERROR: Bad range, %s -> %s." % (str(start), str(end)))
return abort(416)
else:
end = start + range_end
if (range_start):
start = start + range_start
if (start > end):
print("ERROR: Bad range, %s -> %s." % (str(start), str(end)))
return abort(416)
root = {}
root['c'] = []
root['n'] = "root"
root['l'] = ""
root['v'] = 0
stack = []
ts = -1
comm = ""
# overscan is seconds beyond the time range to keep scanning, which allows
# for some out-of-order samples up to this duration
overscan = 0.1
# determine skip lines
lastline = 0
skiplines = 0
if file_path in stack_index:
for pair in stack_index[file_path]:
if start < pair[1]:
# scanned too far, use last entry
skiplines = lastline
break
lastline = pair[0]
# process perf script output and search for two things:
# - event_regexp: to identify event timestamps
# - idle_regexp: for filtering idle stacks
linenum = -1
for line in f:
linenum += 1
# Performance optimization. Makes a large difference.
if (linenum < skiplines):
continue
# skip comments
if (line[0] == '#'):
continue
# As a performance optimization, skip an event regexp search if the
# line looks like a stack trace based on starting with '\t'. This
# makes a big difference.
r = None
if (line[0] != '\t'):
r = event_regexp.search(line)
if (r):
if (stack):
# process prior stack
stackstr = ""
for pair in stack:
stackstr += pair[0] + ";"
if (idle_regexp.search(stackstr)):
# skip idle
stack = []
elif (ts >= start and ts <= end):
root = add_stack(root, stack, comm)
stack = []
ts = float(r.group(1))
if (ts > end + overscan):
break
r = comm_regexp.search(line)
if (r):
comm = r.group(1).rstrip()
stack.append([comm, ""])
else:
stack.append(["<unknown>", ""])
else:
r = frame_regexp.search(line)
if (r):
name = r.group(1)
# strip instruction offset (+0xfe200...)
c = name.find("+")
if (c > 0):
name = name[:c]
stack.insert(1, [name, r.group(2)])
# last stack
if (ts >= start and ts <= end):
root = add_stack(root, stack, comm)
# close file
f.close()
return root