python使用多进程提高运行效率

单进程的执行结果

如图：

 

 测试代码：

from knight_util.util import KnightUtil
import time
m1 = KnightUtil().mysql_()


def tk_(user_id):
    sql = '''SELECT token, client_code FROM sso.user_session WHERE user_id={} AND status='ENABLED';'''.format(user_id)
    m1.execute(sql)
    platform_dict = {}
    for data in m1.fetchall():
        platform_dict.update({data[1]: "{}".format(data[0])})
    print(platform_dict)


if __name__ == '__main__':
    start_time = time.time()
    for i in range(100):
        tk_(2397)
    stop_time = time.time()
    print('代码运行时间为:{}'.format(stop_time - start_time))

 

 

多进程的执行结果

如图：

 

 测试代码：

from knight_util.util import KnightUtil
from multiprocessing import Pool
import time
m1 = KnightUtil().mysql_()


def tk_(user_id):
    sql = '''SELECT token, client_code FROM sso.user_session WHERE user_id={} AND status='ENABLED';'''.format(user_id)
    m1.execute(sql)
    platform_dict = {}
    for data in m1.fetchall():
        platform_dict.update({data[1]: "{}".format(data[0])})
    print(platform_dict)


if __name__ == '__main__':
    start_time = time.time()
    pool = Pool(10)
    for i in range(100):
        pool.apply_async(tk_, args=(2397,))
    pool.close()
    pool.join()
    stop_time = time.time()
    print('代码运行时间为:{}'.format(stop_time - start_time))