def get_profile_type(file_path):
(f, mime) = get_file(file_path)
if mime == 'application/octet-stream':
r = nflxprofile_pb2.Profile()
r.ParseFromString(f.read())
f.close()
return ('nflxprofile', r)
elif is_perf_file(f):
f.close()
return ('perf_script', None)
else:
try:
f.seek(0)
r = json.load(f)
f.close()
if isinstance(r, list):
if 'ph' in r[0]:
return ('trace_event', r)
elif 'nodes' in r:
if isinstance(r['nodes'], list):
return ('cpuprofile', r)
raise InvalidFileError('Unknown JSON file.')
except JSONDecodeError:
f.close()
raise InvalidFileError('Unknown file type.')
def parse_nodes(nodes):
profile = nflxprofile_pb2.Profile()
profile.nodes[0].function_name = 'fakenode'
profile.nodes[0].hit_count = 0
for node in nodes:
node_id = node['id']
function_name = node['callFrame']['functionName']
children = node.get('children', None)
hit_count = node.get('hitCount', 0)
profile.nodes[node_id].function_name = function_name
profile.nodes[node_id].hit_count = hit_count
profile.nodes[node_id].libtype = ''
if children:
for child_id in children:
profile.nodes[node_id].children.append(child_id)
return profile.nodes
def nflxprofile_generate_flame_graph(file_path, range_start, range_end):
try:
f = get_file(file_path)
profile = nflxprofile_pb2.Profile()
profile.ParseFromString(f.read())
except TypeError:
abort(500, 'Failed to parse profile.')
finally:
f.close()
start_time = profile.start_time
if range_start is not None:
adjusted_range_start = (math.floor(start_time) + range_start)
if range_end is not None:
adjusted_range_end = (math.floor(start_time) + range_end)
return generate_flame_graph(profile.nodes, 0, profile.samples, profile.time_deltas, start_time, adjusted_range_start, adjusted_range_end, None)
def nflxprofile_generate_differential_flame_graph(file_path, range_start,
range_end):
try:
f = get_file(file_path)
profile = nflxprofile_pb2.Profile()
profile.ParseFromString(f.read())
except TypeError:
abort(500, 'Failed to parse profile.')
finally:
f.close()
start_time = profile.start_time
if range_start is not None:
range_start = (math.floor(start_time) + range_start)
if range_end is not None:
range_end = (math.floor(start_time) + range_end)
return generate_flame_graph([profile], [0], [None], range_start, range_end)
def nflxprofile_readoffsets(file_path):
try:
f = get_file(file_path)
profile = nflxprofile_pb2.Profile()
profile.ParseFromString(f.read())
except TypeError:
abort(500, 'Failed to parse profile.')
finally:
f.close()
offsets = []
current_time = profile.start_time
for delta in profile.time_deltas:
current_time += delta
offsets.append(current_time)
res = collections.namedtuple('offsets', ['start', 'end', 'offsets'])(profile.start_time, profile.end_time, offsets)
return res
