CODEWITHSUNDEEP
pythonmultithreadingconcurrent.futures
jhonatan teixeira
jhonatan teixeira

Reputation: 800

Python concurrent.futures performance difference with little change

i got the following code:

from concurrent.futures import ThreadPoolExecutor, wait
import datetime

def calculate_mass(mass):
    for _ in range(10000):
        gravity = 9.8
        weight = mass * gravity


def perform_calculations():
    with ThreadPoolExecutor(3) as pool:
        pool.map(calculate_mass, range(1000))

if __name__ == '__main__':
    start = datetime.datetime.now()
    perform_calculations()
    end = datetime.datetime.now()

    print((end - start).total_seconds())

it takes 1.6467 seconds to execute on a core i7 3th generation with 8gb ram (dell notebook)

if change the this line 

weight = mass * gravity

to

return mass * gravity

all of a sudden it takes 0.059083 seconds to complete.

Does anyone knows why that happens?

edit: I guess i'm getting tired. i didnt notice the loop was ending. my bad guys

Upvotes: 0

Views: 31

Answers (1)

Logan
Logan

Reputation: 316

With the line:

for _ in range(10000):
    gravity = 9.8
    weight = mass * gravity

It is iterating through the for loop 10,000 times. Which will take time.

However when you change it to:

for _ in range(10000):
    gravity = 9.8
    return mass * gravity

It is instead returning the value of mass * gravity after only 1 iteration through the for loop.

Upvotes: 1

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