renumbering chapters >= 19

19-concurrency/primes/threads.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+
+"""
+threads.py: shows that Python threads are slower than
+sequential code for CPU-intensive work.
+"""
+
+import os
+import sys
+from queue import SimpleQueue
+from time import perf_counter
+from typing import NamedTuple
+from threading import Thread
+
+from primes import is_prime, NUMBERS
+
+class PrimeResult(NamedTuple):  # <3>
+    n: int
+    prime: bool
+    elapsed: float
+
+JobQueue = SimpleQueue[int]
+ResultQueue = SimpleQueue[PrimeResult]
+
+def check(n: int) -> PrimeResult:
+    t0 = perf_counter()
+    res = is_prime(n)
+    return PrimeResult(n, res, perf_counter() - t0)
+
+def worker(jobs: JobQueue, results: ResultQueue) -> None:
+    while n := jobs.get():
+        results.put(check(n))
+
+def main() -> None:
+    if len(sys.argv) < 2:  # <1>
+        workers = os.cpu_count() or 1  # make mypy happy
+    else:
+        workers = int(sys.argv[1])
+
+    print(f'Checking {len(NUMBERS)} numbers with {workers} threads:')
+
+    jobs: JobQueue = SimpleQueue() # <2>
+    results: ResultQueue = SimpleQueue()
+    t0 = perf_counter()
+
+    for n in NUMBERS:  # <3>
+        jobs.put(n)
+
+    for _ in range(workers):
+        proc = Thread(target=worker, args=(jobs, results))  # <4>
+        proc.start()  # <5>
+        jobs.put(0)  # <6>
+
+    while True:
+        n, prime, elapsed = results.get()  # <7>
+        label = 'P' if prime else ' '
+        print(f'{n:16}  {label} {elapsed:9.6f}s')
+        if jobs.empty():  # <8>
+            break
+
+    elapsed = perf_counter() - t0
+    print(f'Total time: {elapsed:.2f}s')
+
+if __name__ == '__main__':
+    main()