runctx method of cProfile module.

[sachinladhad]

Define two functions f1 and f2 such that, f1 returns a list of squares of first 200000 natural numbers using list comprehension. f2 returns a generator that computes squares of first 200000 natural numbers. Perform profiling of both the functions and which portions of a function consume more time for computing. Hint : Make use of runctx method of cProfile module.

Below is the code but it is not working properly (incorrect result)
Anyone can help me

import pstats, cProfile

def f1(n1):
    f= [i**2 for i in range(1,n1)]
    return f

def f2(n2):
    g = (x**2 for x in range(1,n2))
    return g

cProfile.runctx("f1(n1)", globals(), {'n1':200001}, "Profile1.prof")
cProfile.runctx("f2(n2)", globals(), {'n2':200001}, "Profile2.prof")

s1 = pstats.Stats("Profile1.prof")
s1.strip_dirs().sort_stats("time").print_stats()    

s2 = pstats.Stats("Profile2.prof")
s2.strip_dirs().sort_stats("time").print_stats()