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comparison async_multi_threads/main.py @ 69:551d9fc0a2ba

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Updated wrong names.
author June Park <parkjune1995@gmail.com>
date Thu, 25 Dec 2025 20:07:46 -0800
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68:70ca1d99f3fd 69:551d9fc0a2ba
1 # You are required to implement a production-level code live, using concurrency. Complete within 60 minutes. Suppose you are developing a simple concurrent counter that can correctly update the count in a multi-threaded environment. The initial count value is 0. Ensure it executes in 100 threads, where each thread increments the counter by 1 every second for 10 seconds. Calculate the final count after parallel execution.
2 #
3 # Input: None
4 #
5 # Output: An integer representing the final count.
6 #
7 # Constraints:
8 #
9 # The code must use multi-threading or multi-processing techniques.
10 # Ensure thread safety.
11
12
13 # - 100 threads
14 # - each tread update counter by 1 everyseconds by 10 seconds
15 from threading import Lock
16 from time import sleep
17 from concurrent.futures import ThreadPoolExecutor
18
19
20 SLEEP_IN_SECONDS = 1
21 EXECUTION_TIME_IN_SECONDS = 3
22 NUMS_THREADS = 100
23
24 class Counter:
25
26 def __init__(self):
27 self._value = 0
28 self.lock = Lock()
29
30 def get(self):
31 return self._value
32
33 def increment(self):
34 with self.lock:
35 value = self.get()
36 sleep(0.01)
37 self._value = value + 1
38
39 def worker(counter: Counter):
40 for _ in range(EXECUTION_TIME_IN_SECONDS):
41 counter.increment()
42 sleep(SLEEP_IN_SECONDS)
43
44 def main():
45 counter = Counter()
46 with ThreadPoolExecutor(max_workers=NUMS_THREADS) as executor:
47 for _ in range(NUMS_THREADS):
48 executor.submit(worker, counter)
49 print(counter.get())
50
51 main()