#from:https://blog.faradars.org/reduce-memory-usage-and-make-your-python-code-faster-using-generators/
'''generators'''

'''
problem to be solved: in a large list( for example 100,000,000) calculate the cube of even numbers.
'''

import memory_profiler
import time

#ordianary method:
def check_even_list(numbers):
    even = []
    for num in numbers:
        if num % 2 == 0: 
            even.append(num*num)
            
    return even

#using generator
def check_even_gene(numbers):
    for num in numbers:
        if num % 2 == 0:
            yield num * num 
    

    
if __name__ == '__main__':
    n=100_000_000
    #n=100
    m1 = memory_profiler.memory_usage()
    t1 = time.time()
    cubes = check_even_list(range(n))  #ordinary method with using list
    t2 = time.time()
    m2 = memory_profiler.memory_usage()       # breakpoint set here in this line
    time_diff = t2 - t1
    mem_diff = m2[0] - m1[0]
    print(f"It took {time_diff} Secs and {mem_diff} Mb to execute this method with using list.")
    
    
    m3 = memory_profiler.memory_usage()
    t3 = time.time()
    cubes = check_even_gene(range(n))
    t4 = time.time()
    m4 = memory_profiler.memory_usage()
    time_diff = t4 - t3
    mem_diff = m4[0] - m3[0]
    print(f"It took {time_diff} Secs and {mem_diff} Mb to execute this method with using generator.")
   

Output:
It took 27.66528820991516 Secs and 1913.3046875 Mb to execute this method with using list.
It took 1.9990813732147217 Secs and -1912.48828125 Mb to execute this method with using generator.

Output:
It took 0.0 Secs and 0.00390625 Mb to execute this method with using list.
It took 0.0 Secs and 0.0 Mb to execute this method with using generator.
 

(Apr-27-2024, 07:41 AM)akbarza Wrote: the usage of memory is shown as a negative number! why?

del cubes
m3 = ...