在 Python 中利用Pool 进行多处理

import time
from multiprocessing import Pool


def square(x):
print(f"start process:{x}")
square = x * x
print(f"square {x}:{square}")
time.sleep(1)
print(f"end process:{x}")


if __name__ == "__main__":
starttime = time.time()
pool = Pool()
pool.map(square, range(0, 5))
pool.close()
endtime = time.time()
print(f"Time taken {endtime-starttime} seconds")

import time
from multiprocessing import Pool


def square(x):
print(f"start process {x}")
square = x * x
time.sleep(1)
print(f"end process {x}")
return square


if __name__ == "__main__":
pool = Pool()
a = pool.map(square, range(0, 5))
print(a)

from concurrent.futures import ThreadPoolExecutor

def say_hello():
print("Hello")

executor = ThreadPoolExecutor(50)
for i in range(0, 10):
executor.submit(say_hello)

from redis_db import pool
import redis
import random
from concurrent.futures import ThreadPoolExecutor

s = set()
while True:
if len(s) == 1000:
break
num = random.randint(10000, 100000)
s.add(num)
print(s)

con = redis.Redis(
connection_pool=pool
)

try:
con.delete("kill_total", "kill_num", "kill_flag", "kill_user")
con.set("kill_total", 50)
con.set("kill_num", 0)
con.set("kill_flag", 1)
con.expire("kill_flag", 600)

except Exception as e:
print(e)
finally:
del con

executor = ThreadPoolExecutor(200)
def buy():
connection = redis.Redis(
connection_pool=pool
)
pipline = connection.pipline()
try:
if connection.exists("kill_flag") == 1:
pipline.watch("kill_num", "kill_user")
total = pipline.get("kill_total")
num = int(pipline.get("kill_num").decode("utf-8"))
if num < total:
pipline.multi()
pipline.incr("kill_num")
user_id = s.pop()
pipline.rpush("kill_user", user_id)

pipline.execute()
except Exception as e:
print(e)
finally:
if "pipline" in dir():
pipline.reset()
del connection

for i in range(0, 1000):
executor.submit(buy)
print("秒杀活动已经结束")