def line_profile(items):
"""A context manager which prints a line-by-line profile for the given functions, modules, or
module names while execution is in its context.
Example:
with line_profile(__name__, Class.some_function, some_module):
do_something()
"""
from line_profiler import LineProfiler
prof = LineProfiler()
for item in items:
if inspect.isfunction(item):
prof.add_function(item)
elif inspect.ismodule(item):
prof.add_module(item)
elif isinstance(item, str):
prof.add_module(sys.modules[str])
else:
raise TypeError(
'Inputs must be functions, modules, or module names')
prof.enable()
yield
prof.disable()
prof.print_stats()
def profile_list_serialization(serializer, child_serializer, instances_list):
if os.environ.get('CI', None) != 'true' or not LineProfiler:
return
profile = LineProfiler(serializer.instances_list, child_serializer.instances_list)
profile.enable()
serializer.to_representation(instances_list)
profile.disable()
profile.print_stats()
def profile_list_deserialization(serializer, child_serializer, data_list):
if os.environ.get('CI', None) != 'true' or not LineProfiler:
return
profile = LineProfiler(serializer.to_internal_value, child_serializer.to_internal_value)
profile.enable()
serializer.to_internal_value(data_list)
profile.disable()
profile.print_stats()
def profile_list_deserialization(serializer, child_serializer, data_list):
if os.environ.get('CI', None) != 'true' or not LineProfiler:
return
profile = LineProfiler(serializer.to_internal_value,
child_serializer.to_internal_value)
profile.enable()
serializer.to_internal_value(data_list)
profile.disable()
profile.print_stats()
def profile_list_serialization(serializer, child_serializer, instances_list):
if os.environ.get('CI', None) != 'true' or not LineProfiler:
return
profile = LineProfiler(serializer.instances_list,
child_serializer.instances_list)
profile.enable()
serializer.to_representation(instances_list)
profile.disable()
profile.print_stats()
def profileTimeLine(func, args, kw_args):
from line_profiler import LineProfiler
prf = LineProfiler(func)
# from . import util; prf.add_function(util.loadYml) # you may add more functions
prf.enable()
func(*args, **kw_args)
prf.disable()
prf.dump_stats('lpstats')
with open('lineprofstats.txt', 'w') as flw:
prf.print_stats(flw)
def test_enable_profile_all(self):
lp = LineProfiler()
lp.enable_profile_all()
lp.enable()
value = f(10)
lp.disable()
self.assertEqual(value, f(10))
self.assertEqual(len(lp.code_map.keys()), 1)
self.assertEqual(len(lp.code_map[f.__code__]), 2)
def profile_on(fcn_names=None):
if fcn_names and HAS_LINE_PROFILER:
pr = LineProfiler()
for fcn_name in fcn_names:
pr.add_function(fcn_name)
pr.enable()
return pr
pr = cProfile.Profile()
pr.enable()
return pr
def profile_on(fcn_names=None):
if fcn_names and HAS_LINE_PROFILER:
pr = LineProfiler()
for fcn_name in fcn_names:
pr.add_function(fcn_name)
pr.enable()
return pr
pr = cProfile.Profile()
pr.enable()
return pr
def process(cell_id):
if strtobool(get_param(DbName.COMMON, 'profile')[0]):
print('cell id : {}'.format(cell_id))
pr = LineProfiler()
rtg = RdfToGcnf(cell_id)
pr.add_function(rtg.create_gcn_file)
pr.enable()
rtg.create_gcn_file()
pr.disable()
pr.print_stats()
del rtg
else:
rtg = RdfToGcnf(cell_id)
rtg.create_gcn_file()
del rtg
def line(
cls_runner: tp.Type[Perf],
pattern_func: str,
) -> None:
runner = cls_runner()
for name in runner.iter_function_names(pattern_func):
f = getattr(runner, name)
profiler = LineProfiler()
if not runner.meta:
raise NotImplementedError('must define runner.meta')
profiler.add_function(runner.meta[name].line_target)
profiler.enable()
f()
profiler.disable()
profiler.print_stats()
def main():
profiler = cProfile.Profile()
profiler.enable()
function_runner('original_method')
function_runner('step_one')
function_runner('step_two')
function_runner('step_three')
function_runner('step_four')
function_runner('step_five')
function_runner('step_six')
function_runner('step_seven')
function_runner('step_eight')
function_runner('step_nine')
function_runner('current')
profiler.disable()
profiler.dump_stats('function_event.stats')
line_profiler = LineProfiler(CurrentFunctionContainer().current)
line_profiler.enable()
function_runner('current')
line_profiler.disable()
line_profiler.dump_stats('function_event.line_stats')
line_profiler.print_stats()
print 'Original', timeit.timeit(
lambda: function_runner('original_method'), number=7)
print 'One', timeit.timeit(
lambda: function_runner('step_one'), number=7)
print 'Two', timeit.timeit(
lambda: function_runner('step_two'), number=7)
print 'Three', timeit.timeit(
lambda: function_runner('step_three'), number=7)
print 'Four', timeit.timeit(
lambda: function_runner('step_four'), number=7)
print 'Five', timeit.timeit(
lambda: function_runner('step_five'), number=7)
print 'Six', timeit.timeit(
lambda: function_runner('step_six'), number=7)
print 'Seven', timeit.timeit(
lambda: function_runner('step_seven'), number=7)
print 'Eight', timeit.timeit(
lambda: function_runner('step_eight'), number=7)
print 'Nine', timeit.timeit(
lambda: function_runner('step_nine'), number=7)
print 'Current', timeit.timeit(
lambda: function_runner('current'), number=7)
def run_profiling(args):
lprofiler = LineProfiler()
monitor_fuctions = [
api.problem.submit_key, api.problem.get_unlocked_pids,
api.problem.get_solved_pids, api.problem.get_all_problems,
api.problem.get_solved_problems, api.stats.get_score,
api.cache.memoize, api.autogen.grade_problem_instance,
api.autogen.get_problem_instance, api.autogen.get_number_of_instances
]
for func in monitor_fuctions:
lprofiler.add_function(func)
lprofiler.enable()
if args.stack:
profiler = Profiler(use_signal=False)
profiler.start()
for func, a, kw in operations:
func(*a, **kw)
if args.stack:
profiler.stop()
lprofiler.disable()
if args.print:
print(profiler.output_text(unicode=True, color=True))
lprofiler.print_stats()
output = open(args.output, "w")
if args.stack:
output.write(profiler.output_text(unicode=True))
if args.output_html is not None:
output_html = open(args.output_html, "w")
output_html.write(profiler.output_html())
output_html.close()
print("Wrote test info to " + args.output_html)
lprofiler.print_stats(output)
output.close()
print("Wrote test info to " + args.output)
def run_profiling(args):
lprofiler = LineProfiler()
monitor_fuctions = [api.problem.submit_key, api.problem.get_unlocked_pids, api.problem.get_solved_pids,
api.problem.get_all_problems, api.problem.get_solved_problems, api.stats.get_score,
api.cache.memoize, api.autogen.grade_problem_instance, api.autogen.get_problem_instance,
api.autogen.get_number_of_instances]
for func in monitor_fuctions:
lprofiler.add_function(func)
lprofiler.enable()
if args.stack:
profiler = Profiler(use_signal=False)
profiler.start()
for func, a, kw in operations:
func(*a, **kw)
if args.stack:
profiler.stop()
lprofiler.disable()
if args.print:
print(profiler.output_text(unicode=True, color=True))
lprofiler.print_stats()
output = open(args.output, "w")
if args.stack:
output.write(profiler.output_text(unicode=True))
if args.output_html is not None:
output_html = open(args.output_html, "w")
output_html.write(profiler.output_html())
output_html.close()
print("Wrote test info to " + args.output_html)
lprofiler.print_stats(output)
output.close()
print("Wrote test info to " + args.output)
def _perf_hot_spot():
try:
from line_profiler import LineProfiler
except ImportError:
print(
'WARNING: Unable to import line_profiler, skipping '
'detailed performance checking',
file=stderr)
return
for comp_c_f in COMP_VERT_C_F:
# Generate a random net.
with FixedSeed(0x4711):
nets, Model, Comp = _gen(1, comp_c_f)
net = nets[0]
model = Model()
# Attach the profiler.
profiler = LineProfiler()
profiler.add_function(Comp.forward)
profiler.add_function(Comp.backward)
profiler.enable()
# Run the network forwards and backwards to accumulate statistics.
gradient = model.gradient()
for _ in range(32):
net.forward(model)
net.backward(model, gradient=gradient)
profiler.print_stats()
sanity = False
if sanity:
from .fdiff import fdiff_check
fdiff_check(model, net)
grid[:, -10:, :] = fdtd.PML(name="pml_yhigh")
# z boundaries
grid[:, :, 0] = fdtd.PeriodicBoundary(name="zbounds")
# objects
grid[11:32, 30:84, 0:1] = fdtd.AnisotropicObject(permittivity=2.5,
name="object")
print(grid)
print(f"courant number: {grid.courant_number}")
# create and enable profiler
profiler = LineProfiler()
profiler.add_function(grid.update_E)
profiler.enable()
# run simulation
grid.run(50, progress_bar=False)
# print profiler summary
profiler.print_stats()
## Plots
# Fields
if True:
fig, axes = plt.subplots(2, 3, squeeze=False)
titles = ["Ex: xy", "Ey: xy", "Ez: xy", "Hx: xy", "Hy: xy", "Hz: xy"]
fields = bd.stack([
class SpecialTestRunner(SpecialTest):
"""
Test runner, calls the specified test under specified profiler
Mode = None - no profiler, "c" - cProfile, "l" - LineProfiler, "h" - hotshot
"""
def __init__(self, test, mode=None):
super(SpecialTestRunner, self).__init__()
self.mode = mode
self.test = test
self.profiler = None
def setup(self):
if self.mode == 'c':
import cProfile
self.profiler = cProfile.Profile()
elif self.mode == 'l':
from line_profiler import LineProfiler
self.profiler = LineProfiler()
elif self.mode == 'h':
import hotshot
self.info['name'] = 'special.prof'
self.profiler = hotshot.Profile(self.info['name'])
self.test.setup()
def run(self):
if self.mode == 'c':
self.profiler.enable()
elif self.mode == 'l':
self.profiler.enable_by_count()
self.profiler.add_function(Handler.handle)
self.profiler.add_function(Condition.check_string_match)
self.profiler.add_function(Condition.check_function)
self.profiler.add_function(Condition.check_list)
t = Timer()
# Run itself
if self.mode == 'h':
self.profiler.runcall(self.test.run)
else:
self.test.run()
print('Test time: %s' % t.delta())
if self.mode == 'c':
import pstats
import StringIO
self.profiler.disable()
sio = StringIO.StringIO()
ps = pstats.Stats(self.profiler, stream=sio).sort_stats('time')
ps.print_stats()
print(sio.getvalue())
elif self.mode == 'h':
import hotshot.stats
print('Processing results...')
self.profiler.close()
name = self.info['name']
stats = hotshot.stats.load(name)
stats.strip_dirs()
stats.sort_stats('time', 'calls')
stats.print_stats(50)
print('Run "hotshot2calltree -o %s.out %s" to generate the cachegrind file' % (name, name))
elif self.mode == 'l':
self.profiler.disable()
self.profiler.print_stats()
import sys
sys.path.append('/home/preclineu/andmar/sfw/nispat/nispat')
from trendsurf import estimate
from line_profiler import LineProfiler
from bayesreg import BLR
# with test covariates
wdir = '/home/preclineu/andmar/py.sandbox/unittests'
maskfile = os.path.join(wdir, 'mask.nii.gz')
datafile = os.path.join(wdir, 'spect_data2_first5.nii.gz')
basis = os.path.join(wdir, 'bfs/icp_basis_s8.nii.gz')
lp = LineProfiler(BLR.loglik)
lp.add_function(BLR.dloglik)
lp.add_function(BLR.post)
lp.enable()
estimate(datafile, maskfile, basis)
lp.disable()
lp.print_stats()
# to profile, can also put the following code in trendsurf.py
# lp = LineProfiler(BLR.loglik)
# lp = LineProfiler(BLR.dloglik)
# lp.add_function(BLR.post)
# lp.enable()
# hyp[i, :] = breg.estimate(hyp0, Phi, Yz[:, i])
# lp.disable()
# lp.print_stats()
class SpecialTestRunner(SpecialTest):
"""
Test runner, calls the specified test under specified profiler
Mode = None - no profiler, "c" - cProfile, "l" - LineProfiler, "h" - hotshot
"""
def __init__(self, test, mode=None):
super(SpecialTestRunner, self).__init__()
self.mode = mode
self.test = test
self.profiler = None
def setup(self):
if self.mode == 'c':
import cProfile
self.profiler = cProfile.Profile()
elif self.mode == 'l':
from line_profiler import LineProfiler
self.profiler = LineProfiler()
elif self.mode == 'h':
import hotshot
self.info['name'] = 'special.prof'
self.profiler = hotshot.Profile(self.info['name'])
self.test.setup()
def run(self):
if self.mode == 'c':
self.profiler.enable()
elif self.mode == 'l':
self.profiler.enable_by_count()
self.profiler.add_function(Handler.handle)
self.profiler.add_function(Condition.check_string_match)
self.profiler.add_function(Condition.check_function)
self.profiler.add_function(Condition.check_list)
t = Timer()
# Run itself
if self.mode == 'h':
self.profiler.runcall(self.test.run)
else:
self.test.run()
print('Test time: %s' % t.delta())
if self.mode == 'c':
import pstats
import StringIO
self.profiler.disable()
sio = StringIO.StringIO()
ps = pstats.Stats(self.profiler, stream=sio).sort_stats('time')
ps.print_stats()
print(sio.getvalue())
elif self.mode == 'h':
import hotshot.stats
print('Processing results...')
self.profiler.close()
name = self.info['name']
stats = hotshot.stats.load(name)
stats.strip_dirs()
stats.sort_stats('time', 'calls')
stats.print_stats(50)
print(
'Run "hotshot2calltree -o %s.out %s" to generate the cachegrind file'
% (name, name))
elif self.mode == 'l':
self.profiler.disable()
self.profiler.print_stats()
29 return True
30
31 1 2.0 2.0 0.0 return False
"""
"""
O(N*(N/2))
"""
def contains_duplicates(vec: np.ndarray) -> bool:
vec_len: int = np.alen(vec)
for i in range(vec_len - 1):
i_scalar = vec[i]
for j in range(i + 1, vec_len):
if i_scalar == vec[j]:
return True
return False
if __name__ == '__main__':
vec = np.arange(1, 10001)
p = LineProfiler(contains_duplicates)
p.enable()
# %time -> Wall time: 6.5 s
contains_duplicates(vec)
p.print_stats()
count = 1
for i in range(num):
count *= i + 1
return count
if __name__ == '__main__':
num = 10000
lp = LineProfiler()
lp.add_function(test) # 添加被测试函数
lp_wrapper = lp(myFunc)
lp_wrapper(num)
lp.print_stats()
lp2 = LineProfiler(test)
lp2.enable() # 开始性能分析
test()
lp2.disable() # 停止性能分析
lp2.print_stats()
# ### line_profiler
# PyPI: https://pypi.org/project/line_profiler/
# 可以统计每行代码的执行次数和执行时间等，时间单位为微秒；
#
# ### 结果说明
# - Total Time： 测试代码的总运行时间
# - File： 代码文件的地址
# - Function： 函数的行号
# - Line： 每行代码的行号
# - Hits： 每行代码的运行次数
# - Time： 每行代码的运行时间
