"""
Performance Module :mod:`analytics.performance`
------------------------------------------------
Main module for performance analyis of the Probrem package
"""
import logging
import time
import numpy as N
measurments = {}
''' A dictionary to keep track of execution times for methods {key=function.__name__ : value=execution time } '''
[docs]def time_analysis(caller):
'''
A decorator function that measures and saves the time of the calling method `caller`
The decorator function is used by adding ::
from analytics.performance import time_analysis
to the module of the caller method and by adding ::
@time_analysis
def methodtomeasure():
...
on the line before the caller function definition
'''
if caller.__name__ not in measurments:
measurments[caller.__name__]=[]
def new_caller(*args):
t_start = time.time() #starting time
r = caller(*args) #execute funtion
t_end = time.time() #end time
measurments[caller.__name__].append((t_end-t_start))
return r
return new_caller
[docs]def displayTimeAnalysis():
''' Displays statistics about the running times of all methods that are decorated with the @time_analysis'''
for (caller,times) in measurments.items():
logging.info('%s() exution time:'%(caller))
logging.info('\tNumber of calls = %s'%(len(times)))
if len(times) != 0:
logging.info('\tTotal = %5e \n\tMean = %5e \n\tVar = %5e \n\tMin = %5e \n\tMax = %5e '%(N.sum(times),N.mean(times),N.var(times),N.min(times),N.max(times)))