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아래의 알고리즘 중 한가지를 원하는 프로그래밍 언어로 구현해보세요!

조건

multithreading, multiprocessing 두 방법을 모두 구현해주세요 (비교 목적)
시간이 얼마나 걸렸는지 벤치마크 결과도 기록해주세요
여기를 참고해주세요 : D

Filesystem I/O

import threading
from queue import Queue
import time
import shutil

print_lock = threading.Lock()

def copy_op(file_data):
    with print_lock:
        print("Starting thread : {}".format(threading.current_thread().name))

    mydata = threading.local()
    mydata.ip, mydata.op = next(iter(file_data.items()))

    shutil.copy(mydata.ip, mydata.op)

    with print_lock:
        print("Finished thread : {}".format(threading.current_thread().name))

def process_queue():
    while True:
        file_data = compress_queue.get()
        copy_op(file_data)
        compress_queue.task_done()

compress_queue = Queue()

output_names = [{'v1.mp4' : 'v11.mp4'},{'v2.mp4' : 'v22.mp4'}]

for i in range(2):
    t = threading.Thread(target=process_queue)
    t.daemon = True
    t.start()

start = time.time()

for file_data in output_names:
    compress_queue.put(file_data)

compress_queue.join()

print("Execution time = {0:.5f}".format(time.time() - start))

Network I/O

import threading
from queue import Queue
import requests
import bs4
import time

print_lock = threading.Lock()

def get_url(current_url):

    with print_lock:
        print("\nStarting thread {}".format(threading.current_thread().name))
    res = requests.get(current_url)
    res.raise_for_status()

    current_page = bs4.BeautifulSoup(res.text,"html.parser")
    current_title = current_page.select('title')[0].getText()

    with print_lock:
        print("{}\n".format(threading.current_thread().name))
        print("{}\n".format(current_url))
        print("{}\n".format(current_title))
        print("\nFinished fetching : {}".format(current_url))

def process_queue():
    while True:
        current_url = url_queue.get()
        get_url(current_url)
        url_queue.task_done()

url_queue = Queue()

url_list = ["https://www.google.com"]*5

for i in range(5):
    t = threading.Thread(target=process_queue)
    t.daemon = True
    t.start()

start = time.time()

for current_url in url_list:
    url_queue.put(current_url)

url_queue.join()

print(threading.enumerate())

print("Execution time = {0:.5f}".format(time.time() - start))

CPU bound tasks

import threading
from queue import Queue
import time

list_lock = threading.Lock()

def find_rand(num):
    sum_of_primes = 0

    ix = 2

    while ix <= num:
        if is_prime(ix):
            sum_of_primes += ix
        ix += 1

    sum_primes_list.append(sum_of_primes)

def is_prime(num):
    if num <= 1:
        return False
    elif num <= 3:
        return True
    elif num%2 == 0 or num%3 == 0:
        return False
    i = 5
    while i*i <= num:
        if num%i == 0 or num%(i+2) == 0:
            return False
        i += 6
    return True

def process_queue():
    while True:
        rand_num = min_nums.get()
        find_rand(rand_num)
        min_nums.task_done()

min_nums = Queue()

rand_list = [1000000, 2000000, 3000000]
sum_primes_list = list()

for i in range(2):
    t = threading.Thread(target=process_queue)
    t.daemon = True
    t.start()

start = time.time()

for rand_num in rand_list:
    min_nums.put(rand_num)

min_nums.join()

end_time = time.time()

sum_primes_list.sort()
print(sum_primes_list)

print("Execution time = {0:.5f}".format(end_time - start))

SundayBird / project

[2018.12.09] assignment - concurrent programming #1

Content

Filesystem I/O

Network I/O

CPU bound tasks