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profiler.py
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profiler.py
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#profile memory
global global_profile_memory
global global_memory_tracker
global_profile_memory = False
#create the tracker object
global_memory_tracker = None
try:
from pympler import tracker, asizeof
except ImportError:
global_profile_memory = False
# try:
# from memory_profiler import profile
# except ImportError:
# pass
if global_profile_memory:
pass
# try:
# from guppy import hpy
# global_hp = hpy()
# except ImportError:
# global_profile_memory = False
#
#import pympler
#
# try:
# from memory_profiler import profile
# except ImportError:
# global_profile_memory = False
#set up cProfile
#and the do_cprofile wrapper
try:
import cProfile as pp
except (ImportError, AttributeError):
import profile as pp
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
from random import randint
import pstats
def do_cprofile(func):
def profiled_func(*args, **kwargs):
profile = pp.Profile()
try:
# if global_profile_memory:
# # global_hp.setref()
# global_memory_tracker = tracker.SummaryTracker()
profile.enable()
result = func(*args, **kwargs)
profile.disable()
return result
finally:
print("\nFunction: " + str(func.__name__))
if global_profile_memory and global_memory_tracker:
global_memory_tracker.print_diff()
# if global_profile_memory:
# h = global_hp.heap()
# print("\nMemory usage:")
# print(h)
#
# print("\nBy id:")
# print(h.byid)
# print(h.byvia)
# print(h.byrcs)
# print(h.referents)
#
# print("\nreferents[0]:")
# print(h.referents[0].byid)
# print(h.referents[0].byvia)
# print(h.referents[0].byrcs)
# print(h.referents[0].referents)
s = StringIO()
sortby = 'time'
ps = pstats.Stats(profile, stream = s).sort_stats(sortby)
ps.print_stats()
print("Time usage:")
time_table = str(s.getvalue()).split("\n")
for i in range(25):
if i >= len(time_table):
break
if time_table[i].strip() == "":
continue
print(time_table[i])
print("")
return profiled_func
class Profiler(object):
profiler = None
function_name = ""
f = None
@classmethod
def get_profiler(cls):
return Profiler.profiler
def __init__(self, f):
Profiler.profiler = pp.Profile()
Profiler.f = f
def func(self, *args, **kwargs):
Profiler.profiler.enable()
if global_profile_memory:
global_hp.setref()
result = Profiler.f(*args, **kwargs)
Profiler.function_name = str(Profiler.f.__name__)
Profiler.profiler.disable()
# if randint(0, self.freq) == 0:
# self.print_profiler(function_name)
return result
@classmethod
def print_profiler(self):
if Profiler.function_name == "":
return
print("\nFunction: " + Profiler.function_name)
if global_profile_memory:
h = global_hp.heap()
print("\nMemory usage:")
print(h)
print("\nBy id:")
print(h.byid)
print(h.byvia)
print(h.byrcs)
print(h.referents)
print("\nreferents[0]:")
print(h.referents[0].byid)
print(h.referents[0].byvia)
print(h.referents[0].byrcs)
print(h.referents[0].referents)
s = StringIO()
sortby = 'time'
ps = pstats.Stats(Profiler.profiler, stream = s).sort_stats(sortby)
ps.print_stats()
print("Time usage:")
time_table = str(s.getvalue()).split("\n")
for i in range(25):
if i >= len(time_table):
break
if time_table[i].strip() == "":
continue
print(time_table[i])
print("")
class Profiler1(Profiler):
def __call__(self, *args, **kwargs):
result = super(Profiler1, self).func(*args, **kwargs)
return result
class Profiler2(Profiler):
def __call__(self, *args, **kwargs):
return super(Profiler2, self).func