def Stats(*args):
print 'Report generating functions are in the "pstats" module\a'
python类Stats()的实例源码
def main():
usage = "profile.py [-o output_file_path] [-s sort] scriptfile [arg] ..."
parser = OptionParser(usage=usage)
parser.allow_interspersed_args = False
parser.add_option('-o', '--outfile', dest="outfile",
help="Save stats to <outfile>", default=None)
parser.add_option('-s', '--sort', dest="sort",
help="Sort order when printing to stdout, based on pstats.Stats class",
default=-1)
if not sys.argv[1:]:
parser.print_usage()
sys.exit(2)
(options, args) = parser.parse_args()
sys.argv[:] = args
if len(args) > 0:
progname = args[0]
sys.path.insert(0, os.path.dirname(progname))
with open(progname, 'rb') as fp:
code = compile(fp.read(), progname, 'exec')
globs = {
'__file__': progname,
'__name__': '__main__',
'__package__': None,
}
runctx(code, globs, None, options.outfile, options.sort)
else:
parser.print_usage()
return parser
# When invoked as main program, invoke the profiler on a script
def load(self):
# The timer selected by the profiler should never be used, so make
# sure it doesn't work:
p = Profile()
p.get_time = _brokentimer
log = hotshot.log.LogReader(self._logfn)
taccum = 0
for event in log:
what, (filename, lineno, funcname), tdelta = event
if tdelta > 0:
taccum += tdelta
# We multiply taccum to convert from the microseconds we
# have to the seconds that the profile/pstats module work
# with; this allows the numbers to have some basis in
# reality (ignoring calibration issues for now).
if what == ENTER:
frame = self.new_frame(filename, lineno, funcname)
p.trace_dispatch_call(frame, taccum * .000001)
taccum = 0
elif what == EXIT:
frame = self.pop_frame()
p.trace_dispatch_return(frame, taccum * .000001)
taccum = 0
# no further work for line events
assert not self._stack
return pstats.Stats(p)
def print_stats(self, sort=-1):
import pstats
pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()
def __init__(self, *filename):
import pstats
try:
self.stats = pstats.Stats(*filename)
except ValueError:
if PYTHON_3:
sys.stderr.write('error: failed to load %s\n' % ', '.join(filename))
sys.exit(1)
import hotshot.stats
self.stats = hotshot.stats.load(filename[0])
self.profile = Profile()
self.function_ids = {}
def profile(num_elements=100000, parser="lxml"):
filehandle = tempfile.NamedTemporaryFile()
filename = filehandle.name
data = rdoc(num_elements)
vars = dict(bs4=bs4, data=data, parser=parser)
cProfile.runctx('bs4.BeautifulSoup(data, parser)' , vars, vars, filename)
stats = pstats.Stats(filename)
# stats.strip_dirs()
stats.sort_stats("cumulative")
stats.print_stats('_html5lib|bs4', 50)
def __call__(self, environ, start_response):
response_body = []
def catching_start_response(status, headers, exc_info=None):
start_response(status, headers, exc_info)
return response_body.append
def runapp():
appiter = self._app(environ, catching_start_response)
response_body.extend(appiter)
if hasattr(appiter, 'close'):
appiter.close()
p = Profile()
start = time.time()
p.runcall(runapp)
body = b''.join(response_body)
elapsed = time.time() - start
if self._profile_dir is not None:
prof_filename = os.path.join(self._profile_dir,
'%s.%s.%06dms.%d.prof' % (
environ['REQUEST_METHOD'],
environ.get('PATH_INFO').strip(
'/').replace('/', '.') or 'root',
elapsed * 1000.0,
time.time()
))
p.dump_stats(prof_filename)
else:
stats = Stats(p, stream=self._stream)
stats.sort_stats(*self._sort_by)
self._stream.write('-' * 80)
self._stream.write('\nPATH: %r\n' % environ.get('PATH_INFO'))
stats.print_stats(*self._restrictions)
self._stream.write('-' * 80 + '\n\n')
return [body]
def __call__(self, environ, start_response):
response_body = []
def catching_start_response(status, headers, exc_info=None):
start_response(status, headers, exc_info)
return response_body.append
def runapp():
appiter = self._app(environ, catching_start_response)
response_body.extend(appiter)
if hasattr(appiter, 'close'):
appiter.close()
p = Profile()
start = time.time()
p.runcall(runapp)
body = b''.join(response_body)
elapsed = time.time() - start
if self._profile_dir is not None:
prof_filename = os.path.join(self._profile_dir,
'%s.%s.%06dms.%d.prof' % (
environ['REQUEST_METHOD'],
environ.get('PATH_INFO').strip(
'/').replace('/', '.') or 'root',
elapsed * 1000.0,
time.time()
))
p.dump_stats(prof_filename)
else:
stats = Stats(p, stream=self._stream)
stats.sort_stats(*self._sort_by)
self._stream.write('-' * 80)
self._stream.write('\nPATH: %r\n' % environ.get('PATH_INFO'))
stats.print_stats(*self._restrictions)
self._stream.write('-' * 80 + '\n\n')
return [body]
def __call__(self, environ, start_response):
response_body = []
def catching_start_response(status, headers, exc_info=None):
start_response(status, headers, exc_info)
return response_body.append
def runapp():
appiter = self._app(environ, catching_start_response)
response_body.extend(appiter)
if hasattr(appiter, 'close'):
appiter.close()
p = Profile()
start = time.time()
p.runcall(runapp)
body = b''.join(response_body)
elapsed = time.time() - start
if self._profile_dir is not None:
prof_filename = os.path.join(self._profile_dir,
'%s.%s.%06dms.%d.prof' % (
environ['REQUEST_METHOD'],
environ.get('PATH_INFO').strip(
'/').replace('/', '.') or 'root',
elapsed * 1000.0,
time.time()
))
p.dump_stats(prof_filename)
else:
stats = Stats(p, stream=self._stream)
stats.sort_stats(*self._sort_by)
self._stream.write('-' * 80)
self._stream.write('\nPATH: %r\n' % environ.get('PATH_INFO'))
stats.print_stats(*self._restrictions)
self._stream.write('-' * 80 + '\n\n')
return [body]
def profile(num_elements=100000, parser="lxml"):
filehandle = tempfile.NamedTemporaryFile()
filename = filehandle.name
data = rdoc(num_elements)
vars = dict(bs4=bs4, data=data, parser=parser)
cProfile.runctx('bs4.BeautifulSoup(data, parser)' , vars, vars, filename)
stats = pstats.Stats(filename)
# stats.strip_dirs()
stats.sort_stats("cumulative")
stats.print_stats('_html5lib|bs4', 50)
def __call__(self, environ, start_response):
response_body = []
def catching_start_response(status, headers, exc_info=None):
start_response(status, headers, exc_info)
return response_body.append
def runapp():
appiter = self._app(environ, catching_start_response)
response_body.extend(appiter)
if hasattr(appiter, 'close'):
appiter.close()
p = Profile()
start = time.time()
p.runcall(runapp)
body = b''.join(response_body)
elapsed = time.time() - start
if self._profile_dir is not None:
prof_filename = os.path.join(self._profile_dir,
'%s.%s.%06dms.%d.prof' % (
environ['REQUEST_METHOD'],
environ.get('PATH_INFO').strip(
'/').replace('/', '.') or 'root',
elapsed * 1000.0,
time.time()
))
p.dump_stats(prof_filename)
else:
stats = Stats(p, stream=self._stream)
stats.sort_stats(*self._sort_by)
self._stream.write('-' * 80)
self._stream.write('\nPATH: %r\n' % environ.get('PATH_INFO'))
stats.print_stats(*self._restrictions)
self._stream.write('-' * 80 + '\n\n')
return [body]
def profile(num_elements=100000, parser="lxml"):
filehandle = tempfile.NamedTemporaryFile()
filename = filehandle.name
data = rdoc(num_elements)
vars = dict(bs4=bs4, data=data, parser=parser)
cProfile.runctx('bs4.BeautifulSoup(data, parser)' , vars, vars, filename)
stats = pstats.Stats(filename)
# stats.strip_dirs()
stats.sort_stats("cumulative")
stats.print_stats('_html5lib|bs4', 50)
def _run_profiler(function, *args, **kwargs):
"""Run a profiler on the specified function."""
profiler = cProfile.Profile()
profiler.enable()
result = function(*args, **kwargs)
profiler.disable()
stats = pstats.Stats(profiler).sort_stats('cumtime')
stats.print_stats()
return result
def profile(num_elements=100000, parser="lxml"):
filehandle = tempfile.NamedTemporaryFile()
filename = filehandle.name
data = rdoc(num_elements)
vars = dict(bs4=bs4, data=data, parser=parser)
cProfile.runctx('bs4.BeautifulSoup(data, parser)' , vars, vars, filename)
stats = pstats.Stats(filename)
# stats.strip_dirs()
stats.sort_stats("cumulative")
stats.print_stats('_html5lib|bs4', 50)
def main(parser):
opt = parser.parse_args()
if opt['torch']:
with torch.autograd.profiler.profile() as prof:
TrainLoop(parser).train()
print(prof.total_average())
sort_cpu = sorted(prof.key_averages(), key=lambda k: k.cpu_time)
sort_cuda = sorted(prof.key_averages(), key=lambda k: k.cuda_time)
def cpu():
for e in sort_cpu:
print(e)
def cuda():
for e in sort_cuda:
print(e)
cpu()
if opt['debug']:
print('`cpu()` prints out cpu-sorted list, '
'`cuda()` prints cuda-sorted list')
pdb.set_trace()
else:
pr = cProfile.Profile()
pr.enable()
TrainLoop(parser).train()
pr.disable()
s = io.StringIO()
sortby = 'cumulative'
ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
ps.print_stats()
print(s.getvalue())
if opt['debug']:
pdb.set_trace()
def profile(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
profiler = cProfile.Profile()
try:
return profiler.runcall(func, *args, **kwargs)
finally:
stats = pstats.Stats(profiler)
stats.strip_dirs()
stats.sort_stats('tottime')
stats.print_stats()
return wrapper
def profile_execute(self, pstat_file=None):
pr = cProfile.Profile()
pr.enable()
exec_node_group(self)
pr.disable()
if pstat_file is not None:
pr.dump_stats(pstat_file)
s = io.StringIO()
sortby = 'cumulative'
ps = pstats.Stats(pr, stream=s)
ps.strip_dirs()
ps.sort_stats(sortby)
ps.print_stats()
text_name = self.name + " Profile"
if text_name in bpy.data.texts:
text = bpy.data.texts[text_name]
else:
text = bpy.data.texts.new(text_name)
text.from_string(s.getvalue())
def __call__(self, environ, start_response):
response_body = []
def catching_start_response(status, headers, exc_info=None):
start_response(status, headers, exc_info)
return response_body.append
def runapp():
appiter = self._app(environ, catching_start_response)
response_body.extend(appiter)
if hasattr(appiter, 'close'):
appiter.close()
p = Profile()
start = time.time()
p.runcall(runapp)
body = b''.join(response_body)
elapsed = time.time() - start
if self._profile_dir is not None:
prof_filename = os.path.join(self._profile_dir,
'%s.%s.%06dms.%d.prof' % (
environ['REQUEST_METHOD'],
environ.get('PATH_INFO').strip(
'/').replace('/', '.') or 'root',
elapsed * 1000.0,
time.time()
))
p.dump_stats(prof_filename)
else:
stats = Stats(p, stream=self._stream)
stats.sort_stats(*self._sort_by)
self._stream.write('-' * 80)
self._stream.write('\nPATH: %r\n' % environ.get('PATH_INFO'))
stats.print_stats(*self._restrictions)
self._stream.write('-' * 80 + '\n\n')
return [body]
def run_profiled(self, coeff_file=None, kgrid_tp="coarse", write_outputs=True):
profiler = cProfile.Profile()
profiler.runcall(lambda: self.run(coeff_file, kgrid_tp=kgrid_tp,
write_outputs=write_outputs))
stats = Stats(profiler, stream=STDOUT)
stats.strip_dirs()
stats.sort_stats('cumulative')
stats.print_stats(15) # only print the top 10 (10 slowest functions)
