关于并发执行及返回结果对比 (py版)

前言

py的世界里虽有GIL,但是进程，线程的使用还是有一些用武之地的.
本文对比的是

threading
multiprocessing,
concurrent.futures
asyncio(3.5 版本以后的协程)
gevent(常称monkey_patch)

至于源码，有兴趣的，研究研究，还是很有收获的。改天再开篇。
asyncio 是基于yield魔改的，整体的生态还不成熟，常被吐槽, 但据我目前使用来看，还是不错的。

monkey_patch 经过长时间的线上验证，及代码不侵入性，性能还是挺可靠的。

基于并发的考虑，这些都是不错的思路。

threading 及 multiprocessing

这两个的api差不多，要说不太一样的是，multiprocessing可带返回结果，threading返回结果，一般有两种思路是用队列或用类再封装一层

multiprocessing返回结果

def req_multi(url:str, result: dict):
    r = requests.get(url)
    result[url] = r

def main_multi():
    process_manager = multiprocessing.Manager()
    result_dict = process_manager.dict()
    urls = ["http://www.baidu.com", "http://www.zhihu.com"]
    reqs = [multiprocessing.Process(target=req_multi, args=(i, result_dict)) for i in urls]
    [j.start() for j in reqs]
    [j.join() for j in reqs]
    print(result_dict)

结果

![image.png](https://upload-images.jianshu.io/upload_images/1500770-b608536e103201be.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)

threading返回结果

queue的方式

q = queue.Queue()

def req_threading(url: str):
    r = requests.get(url)
    q.put({url: r})

def main_threading_queue():
    urls = ["http://www.baidu.com", "http://www.zhihu.com"]
    results = [threading.Thread(target=req_threading, args=(i,)) for i in urls]
    [j.start() for j in results]
    [k.join() for k in results]
    while q:
        print(q.get())

class封装的方式

class MainThread(threading.Thread):
    def __init__(self, fn_name: str, url: list):
        super(MainThread, self).__init__()
        self.fn_name = fn_name
        self.url = url
        self.result = {}

    def run(self):
        for i in self.url:
            r = requests.get(i)
            self.result[self.fn_name] = r

异步的方式import concurrent.futures

def main_future():
    urls = ["http://www.baidu.com", "http://www.zhihu.com"]
    pool = concurrent.futures.ProcessPoolExecutor(max_workers=2)
    results = [pool.submit(req_futrue, i) for i in urls]
    # results = [pool.map(req_futrue, urls)]
    r = [i.result(timeout=10) for i in  results]
    print(r)

asyncio

import gevent
from gevent import socket
# from gevent import monkey; monkey.patch_all()
import time
start_time = time.time()


async def main_gevnet():

    urls = ["http://www.baidu.com", "http://www.baidu.com"]
    # jobs_1 = [gevent.spawn(req_1, i )for i in urls]
    # jobs_2 = [gevent.spawn(req_2, i )for i in urls]
    # for j in jobs_1:
    #     j.start()
    #     j.join()
    # for k in jobs_2:
    #     k.start()
    #     k.join()
    job_1 = req_1("http://www.baidu.com")
    job_2 = req_2("http://www.baidu.com")

import asyncio
for i in range(100):
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main_gevnet())
print(time.time() - start_time)

gevent

import gevent
from gevent import socket
# from gevent import monkey; monkey.patch_all()
import time
start_time = time.time()


async def main_gevnet():

    urls = ["http://www.baidu.com", "http://www.baidu.com"]
    jobs_1 = [gevent.spawn(req_1, i )for i in urls]
    jobs_2 = [gevent.spawn(req_2, i )for i in urls]
    for j in jobs_1:
        j.start()
        j.join()
    for k in jobs_2:
        k.start()
        k.join()
    # job_1 = req_1("http://www.baidu.com")
    # job_2 = req_2("http://www.baidu.com")