Profiling to find bottlenecks

Key 2: Identifying application performance bottlenecks.

We should not rely on our intuition on how to optimize application. There are two major ways for logic slowdown; one is CPU time taken, and the second is the wait for results from some other entity. By profiling, we can find out such cases in which we can tweak logic, and language syntax to get better performance on the same hardware. The following code is a showtime decorator that I use to calculate the time taken to call a function. It is simple and effective to get rapid answers:

from datetime import datetime,timedelta
from functools import wraps
import time

def showtime(func):

    @wraps(func)
    def wrap(*args,**kwargs):
        st = time.time() #time clock can be used too
        result = func(*args,**kwargs)
        et = time.time()
        print("%s:%s"%(func.__name__,et-st))
        return result
    return wrap

@showtime
def func_c():
    for i in range(1000):
        for j in range(1000)...