def test_given_a_text_column_when_profiler_is_applied_with_high_level_analysis_then_it_finishes_quick(
):
# given
if not os.path.exists(TARGET_PROFILE_REPORT_FOLDER):
os.makedirs(TARGET_PROFILE_REPORT_FOLDER)
profile = LineProfiler()
source_data = generate_data()
expected_execution_time = 4 # benchmarked: (first-time) 46.694923639297485, (cached) 5.918392 seconds
# when: using default method (joblib Parallel) for parallelisation
start_execution_time = time()
profile_wrapper = profile(grammar_check_score)
for each in source_data:
profile_wrapper(each)
actual_execution_time = time() - start_execution_time
output_filename = f'{TARGET_PROFILE_REPORT_FOLDER}/grammar_check_score-' \
f'{datetime.now().strftime("%d-%m-%Y-%H-%M-%S")}-' \
f'{shorten_sha(git_current_head_sha())}'
with open(f'{output_filename}.txt', 'w') as file:
with redirect_stdout(file):
profile.print_stats()
profile.dump_stats(f'{output_filename}.lprof')
# then
assert actual_execution_time <= expected_execution_time, \
f"Expected duration: {expected_execution_time}, Actual duration: {actual_execution_time}. " \
f"Slow down by: {abs(actual_execution_time - expected_execution_time)} seconds. " \
f"We have crossed the benchmark limit after a speed up via commit 51a8952."
def test_given_a_text_column_when_profiler_is_applied_with_high_level_analysis_then_it_finishes_quick():
# given
TARGET_PROFILE_REPORT_FOLDER = '.cprofile/'
if not os.path.exists(TARGET_PROFILE_REPORT_FOLDER):
os.makedirs(TARGET_PROFILE_REPORT_FOLDER)
profile = LineProfiler()
source_data = generate_data()
expected_execution_time = 32 # benchmarked: (first-time) 31.051079034805298, (cached) 0.918392 seconds
# when: using default method (joblib Parallel) for parallelisation
start_execution_time = time()
profile_wrapper = profile(spelling_quality_score)
for each in source_data:
profile_wrapper(each)
end_execution_time = time()
actual_execution_time = end_execution_time - start_execution_time
short_sha = shorten_sha(git_current_head_sha())
output_filename = f'{TARGET_PROFILE_REPORT_FOLDER}/spelling_quality_check-' \
f'{datetime.now().strftime("%d-%m-%Y-%H-%M-%S")}-{short_sha}'
with open(f'{output_filename}.txt', 'w') as file:
with redirect_stdout(file):
profile.print_stats()
profile.dump_stats(f'{output_filename}.lprof')
# then
assert actual_execution_time <= expected_execution_time, \
f"Expected duration: {expected_execution_time}, Actual duration: {actual_execution_time}." \
f"Slow down by: {abs(actual_execution_time - expected_execution_time)} seconds." \
f"We are cross the benchmark limit after a speed up after commit a81ed70."
def assert_benchmark(expected_execution_time: float, target_function,
profile_filename_prefix: str, commit_id: str):
# given
if not os.path.exists(TARGET_PROFILE_REPORT_FOLDER):
os.makedirs(TARGET_PROFILE_REPORT_FOLDER)
profile = LineProfiler()
source_data = generate_data()
# when: using default method (joblib Parallel) for parallelisation
start_execution_time = time()
profile_wrapper = profile(target_function)
for each in source_data:
profile_wrapper(each)
actual_execution_time = time() - start_execution_time
output_filename = f'{TARGET_PROFILE_REPORT_FOLDER}/{profile_filename_prefix}-' \
f'{datetime.now().strftime("%d-%m-%Y-%H-%M-%S")}-' \
f'{shorten_sha(git_current_head_sha())}'
with open(f'{output_filename}.txt', 'w') as file:
with redirect_stdout(file):
profile.print_stats()
profile.dump_stats(f'{output_filename}.lprof')
# then
assert actual_execution_time <= expected_execution_time, \
f"Expected duration: {expected_execution_time}, Actual duration: {actual_execution_time}. " \
f"Slow down by: {abs(actual_execution_time - expected_execution_time)} seconds. " \
f"We have crossed the benchmark limit after a speed up via commit {commit_id}."
def decorator(*args, **kwargs):
# line-profiler==3.0.2
profiler = LineProfiler()
try:
profiler.add_function(func)
profiler.enable_by_count()
return func(*args, **kwargs)
finally:
profiler.dump_stats('/var/log/{}.lprof'.format(time.time()))
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 wrapper(*args, **kwargs):
profiler = LineProfiler()
profiler.add_function(fn)
try:
for f in follow:
profiler.add_function(f)
profiler.enable_by_count()
return fn(*args, **kwargs)
finally:
profiler.print_stats(output_unit=1)
profiler.dump_stats(report)
def wrapper(*args, **kwargs):
if not hasattr(wrapper, 'cnt'):
wrapper.cnt = 1
else:
wrapper.cnt += 1
if not (max_cnt >= 0 and wrapper.cnt > max_cnt) and not sys._getframe().f_back.f_code.co_name == func.__name__:
prof = LineProfiler()
try:
return prof(func)(*args, **kwargs)
finally:
prof.dump_stats(filename)
else:
return func(*args, **kwargs)
def wrapper(*args, **kwargs):
# Don't profile if debugging is off (PROD server mode)
if DEBUG:
logger.error('Line Profiling (@profile_this_by_line) ' + func.__name__ + '() to ' + stats_filename + '.')
profiler = LineProfiler()
profiled_func = profiler(func)
try:
retval = profiled_func(*args, **kwargs)
finally:
# profiler.print_stats()
profiler.dump_stats(stats_filename)
else:
logger.error('Line Profiling (@profile_this_by_line) attempted on ' + func.__name__ + '() while in production mode. Profiling Bypassed.')
retval = func(*args, **kwargs)
return retval
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)
# Test and profile TimeHistogram
#
# Copyright (C) 2010-2012 Huang Xin
#
# See LICENSE.TXT that came with this file.
#import cProfile,pstats
from line_profiler import LineProfiler
import TimeHistogram
def run():
psth = TimeHistogram.PSTHAverage(
'/home/chrox/dev/plexon_data/c04-stim-timing-8ms-rand-1.plx')
psth.get_data()
if __name__ == '__main__':
#cProfile.run('psth.get_data()','hist_profile')
#p = pstats.Stats('hist_profile')
#p.sort_stats('cumulative')
#p.print_stats()
profile = LineProfiler()
profile.add_function(run)
profile.add_function(TimeHistogram.PSTHAverage._process_unit)
profile.run('run()')
profile.print_stats()
profile.dump_stats("hist_profile.lprof")
properties[i].append(objects[j].moments_hu())
properties[i].append(objects[j].image())
properties[i].append(objects[j].label)
properties[i].append(objects[j].major_axis_length())
properties[i].append(objects[j].max_intensity())
properties[i].append(objects[j].mean_intensity())
properties[i].append(objects[j].min_intensity())
properties[i].append(objects[j].minor_axis_length())
properties[i].append(objects[j].moments())
properties[i].append(objects[j].moments_normalized())
properties[i].append(objects[j].orientation())
properties[i].append(objects[j].perimeter())
properties[i].append(objects[j].solidity())
properties[i].append(objects[j].weighted_moments_central())
properties[i].append(objects[j].weighted_centroid())
properties[i].append(objects[j].weighted_moments_hu())
properties[i].append(objects[j].weighted_moments())
properties[i].append(objects[j].weighted_moments_normalized())
return properties, prop_names
if __name__ == '__main__':
image = io.imread('test-image.png')
green = image[..., 1].copy()
lp = LineProfiler()
lp.add_function(object_features)
lp.run('intensity_object_features(green, 100)')
lp.print_stats()
lp.dump_stats('profile.lprof')
print(__file__)
unstrobed_word = pu.GetExtEvents(data,
event='unstrobed_word',
online=False)
print "found %d unstrobed word events in which 10 events are:" % (len(
unstrobed_word['value']))
indices = np.arange(0, len(unstrobed_word['value']),
len(unstrobed_word['value']) / 10)
for value, timestamp in zip(unstrobed_word['value'][indices],
unstrobed_word['timestamp'][indices]):
binary_value = bin(value)
print "unstrobed word:%s t=%f" % (binary_value, timestamp)
if __name__ == "__main__":
#run()
profile = LineProfiler()
profile.add_function(run)
profile.add_function(PlexUtil.GetExtEvents)
profile.add_function(reconstruct_word)
profile.run('run()')
profile.print_stats()
profile.dump_stats("testPlexFile_profile.lprof")
#cProfile.run('run()','PlexFile_profile')
#p = pstats.Stats('testPlexFile_profile.lprof')
#p.sort_stats('cumulative')
#p.print_stats()
#print h.heap()
for timestamp in bit_2_events[-5:]:
print "unstrobed bit 2 t=%f" % timestamp
print "found %d bit 3 events. Last 5 events are:" %(len(bit_3_events))
for timestamp in bit_3_events[-5:]:
print "unstrobed bit 3 t=%f" % timestamp
unstrobed_word = pu.GetExtEvents(data, event='unstrobed_word', online=False)
print "found %d unstrobed word events in which 10 events are:" %(len(unstrobed_word['value']))
indices = np.arange(0,len(unstrobed_word['value']),len(unstrobed_word['value'])/10)
for value,timestamp in zip(unstrobed_word['value'][indices],unstrobed_word['timestamp'][indices]) :
binary_value = bin(value)
print "unstrobed word:%s t=%f" % (binary_value,timestamp)
if __name__ == "__main__":
#run()
profile = LineProfiler()
profile.add_function(run)
profile.add_function(PlexUtil.GetExtEvents)
profile.add_function(reconstruct_word)
profile.run('run()')
profile.print_stats()
profile.dump_stats("testPlexFile_profile.lprof")
#cProfile.run('run()','PlexFile_profile')
#p = pstats.Stats('testPlexFile_profile.lprof')
#p.sort_stats('cumulative')
#p.print_stats()
#print h.heap()
# Test and profile TimeHistogram
#
# Copyright (C) 2010-2012 Huang Xin
#
# See LICENSE.TXT that came with this file.
#import cProfile,pstats
from line_profiler import LineProfiler
import TimeHistogram
def run():
psth = TimeHistogram.PSTHAverage('/home/chrox/dev/plexon_data/c04-stim-timing-8ms-rand-1.plx')
psth.get_data()
if __name__ == '__main__':
#cProfile.run('psth.get_data()','hist_profile')
#p = pstats.Stats('hist_profile')
#p.sort_stats('cumulative')
#p.print_stats()
profile = LineProfiler()
profile.add_function(run)
profile.add_function(TimeHistogram.PSTHAverage._process_unit)
profile.run('run()')
profile.print_stats()
profile.dump_stats("hist_profile.lprof")
# -- coding = 'utf-8' --
# Author Kylin
# Python Version 3.7.3
# OS macOS
import line_profiler
from line_profiler import LineProfiler
import random
def do_something(numbers):
s = sum(numbers)
l = [numbers[i] / 43 for i in range(len(numbers))]
numbers = [random.randint(1, 100) for i in range(1000)]
lp = LineProfiler() # 实例化对象
lp_wrapper = lp(do_something) # 封装想要处理的函数
lp_wrapper(numbers) # 传入参数
lp.print_stats() # 查看LineProfiler的状态，显示各阶段的运行时间】
# 保存
# profile结果保存到test.lp
lp.dump_stats("test.lp")
# 重新载入
# 载入二进制文件
lstats = line_profiler.load_stats("test.lp")
# 打印到标准输出
line_profiler.show_text(lstats.timings, lstats.unit)
