Performance Measurement in Python: Analyzing Code Execution

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A given problem may be solved by more than one alternative algorithms. Hence, we need to optimize the performance of the solution. Python's timeit module is a useful tool to measure the performance of a Python application.

The timit() function in this module measures execution time of your Python code.

Syntax

timeit.timeit(stmt, setup, timer, number)

Parameters

stmt − code snippet for measurement of performance.
setup − setup details arguments to be passed or variables.
timer − uses default timer, so, it may be skipped.
number − the code will be executed this number of times. The default is 1000000.

Example

The following statement uses list comprehension to return a list of multiple of 2 for each number in the range upto 100.

>>> [n*2 for n in range(100)] [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98, 100, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134, 136, 138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164, 166, 168, 170, 172, 174, 176, 178, 180, 182, 184, 186, 188, 190, 192, 194, 196, 198]

To measure the execution time of the above statement, we use the timeit() function as follows −

>>> from timeit import timeit >>> timeit('[n*2 for n in range(100)]', number=10000) 0.0862189000035869

Compare the execution time with the process of appending the numbers using a for loop.

>>> string = ''' ... numbers=[] ... for n in range(100): ... numbers.append(n*2) ... ''' >>> timeit(string, number=10000) 0.1010853999905521

The result shows that list comprehension is more efficient.

The statement string can contain a Python function to which one or more arguments My be passed as setup code.

We shall find and compare the execution time of a factorial function using a loop with that of its recursive version.

The normal function using for loop is −

def fact(x): fact = 1 for i in range(1, x+1): fact*=i return fact

Definition of recursive factorial.

def rfact(x): if x==1: return 1 else: return x*fact(x-1)

Test these functions to calculate factorial of 10.

print ("Using loop:",fact(10)) print ("Using Recursion",rfact(10)) Result Using loop: 3628800 Using Recursion 3628800

Now we shall find their respective execution time with timeit() function.

import timeit setup1=""" from __main__ import fact x = 10 """ setup2=""" from __main__ import rfact x = 10 """ print ("Performance of factorial function with loop") print(timeit.timeit(stmt = "fact(x)", setup=setup1, number=10000)) print ("Performance of factorial function with Recursion") print(timeit.timeit(stmt = "rfact(x)", setup=setup2, number=10000))

Output

Performance of factorial function with loop
0.00330029999895487
Performance of factorial function with Recursion
0.006506800003990065

The recursive function is slower than the function with loop.

In this way, we can perform performance measurement of Python code.

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