flask线程池用法
1.线程池的用法
- 在写任务调度的时候，难免遇到使用多线程、多进程、线程池、进程池的场景 ，
from flask import Flask
from time import sleep
from concurrent.futures import ThreadPoolExecutor
# DOCS https://docs.python.org/3/library/concurrent.futures.html#concurrent.futures.ThreadPoolExecutor
executor = ThreadPoolExecutor(2)
app = Flask(__name__)
@app.route('/jobs')
def run_jobs():
# 通过submit函数提交执行的函数到线程池中，submit函数立即返回，不阻塞
executor.submit(long_task, 'hello', 123)
return 'long task running.'
def long_task(arg1, arg2):
print("args: %s %s!" % (arg1, arg2))
sleep(5)
print("Task is done!")
if __name__ == '__main__':
app.run()
2.thread的用法
import time
from threading import Thread
def async_fun(f):
def inner_fun(*args, **kwargs):
t = Thread(target=f, args=args, kwargs=kwargs)
t.start()
return inner_fun
@async_fun
def test_a():
time.sleep(10)
print("test a run")
def test_b():
test_a()
print("test b run")
test_b()
3.flask开启多线程支持
1)threaded : 多线程支持，默认为False，即不开启多线程;
app.run(threaded=True)
2)processes：进程数量，默认为1.
app.run(processes=True)
ps：多进程或多线程只能选择一个，不能同时开启
使用示例：
app.run(host=myaddr,port=myport,debug=False,threaded=True) ### threaded开启以后 不需要等队列 threaded=True
#或者
#app.run(host=myaddr,port=myport,debug=False,processes=3) ### processes=N 进程数量，默认为1个
3.设置守护线程
import time
import threading
def test():
while True:
print threading.currentThread()
time.sleep(1)
if __name__ == '__main__':
t1 = threading.Thread(target=test)
t1.setDaemon(True) # python2.7设置
t1.start()
----------------------------------------------------------
# python 3.7实现
t1 = threading.Thread(target=ppp, args=(), daemon=True)
t1.start()
相关链接
https://www.cxyzjd.com/article/xiaoyu_wu/102820384
https://www.jb51.net/article/212169.htm
https://cloud.tencent.com/developer/article/1572261