|
import time |
|
import random |
|
import math |
|
from itertools import cycle |
|
|
|
def cpu_intensive_task(): |
|
"""随机选择一个CPU密集型任务执行""" |
|
tasks = [ |
|
_calculate_primes, |
|
_matrix_multiplication, |
|
_fibonacci_calculation, |
|
_pi_calculation |
|
] |
|
task = random.choice(tasks) |
|
task() |
|
|
|
def _calculate_primes(): |
|
"""计算质数""" |
|
n = random.randint(100000, 1000000) |
|
sieve = [True] * (n + 1) |
|
sieve[0:2] = [False, False] |
|
for i in range(2, int(math.sqrt(n)) + 1): |
|
if sieve[i]: |
|
sieve[i*i : n+1 : i] = [False] * len(sieve[i*i : n+1 : i]) |
|
|
|
def _matrix_multiplication(): |
|
"""矩阵乘法""" |
|
size = random.randint(100, 300) |
|
matrix = [[random.random() for _ in range(size)] for _ in range(size)] |
|
result = [[0] * size for _ in range(size)] |
|
for i in range(size): |
|
for j in range(size): |
|
for k in range(size): |
|
result[i][j] += matrix[i][k] * matrix[k][j] |
|
|
|
def _fibonacci_calculation(): |
|
"""斐波那契数列计算""" |
|
n = random.randint(300000, 500000) |
|
a, b = 0, 1 |
|
for _ in range(n): |
|
a, b = b, a + b |
|
|
|
def _pi_calculation(): |
|
"""蒙特卡洛法计算π近似值""" |
|
iterations = 10000000 |
|
count = 0 |
|
for _ in range(iterations): |
|
x = random.random() |
|
y = random.random() |
|
if x*x + y*y <= 1: |
|
count += 1 |
|
pi = 4 * count / iterations |
|
|
|
def main(): |
|
try: |
|
|
|
initial_delay = random.randint(5, 15) |
|
time.sleep(initial_delay * 60) |
|
|
|
|
|
intervals = cycle([random.randint(10, 300) for _ in range(50)]) |
|
|
|
while True: |
|
start_time = time.time() |
|
print(f"开始CPU密集型任务 @ {time.strftime('%Y-%m-%d %H:%M:%S')}") |
|
|
|
cpu_intensive_task() |
|
|
|
elapsed = time.time() - start_time |
|
print(f"任务完成，耗时: {elapsed:.2f}秒") |
|
|
|
|
|
delay = next(intervals) |
|
print(f"下次任务将在 {delay} 分钟后执行...") |
|
time.sleep(delay * 60) |
|
|
|
except KeyboardInterrupt: |
|
print("\n任务调度已停止") |
|
|
|
if __name__ == "__main__": |
|
main() |
|
|
