1、单进程多线程模式

# #!/usr/bin/env python
# # -*- coding:utf-8 -*-

import time
import logging
import requests
import threading
from concurrent import futures

# download_url = 'http://192.168.188.110:8081//workspace/record_download/polls/82003533467_18b305da-e313-11e8-aa39-00163e0a6bde.mp3'
# download_url = 'http://192.168.188.110:8081//workspace/record_download/polls/test.log'
download_url = 'http://192.168.188.110:8081//workspace/record_download/polls/9921_057128214999_18210532807_20181113110420_00163e104dbfbb8b11e8e6f0d0990876(3).wav'
workers = 1000
mutex = threading.Lock()
session = requests.Session()
contain = {'average_cost':0,'min_cost':0,'max_cost':0,'hit_count':0}


def handle(cost):
    with mutex:
        min_cost = contain['min_cost']
        max_cost = contain['max_cost']
        hit_count = contain['hit_count']
        average_cost = contain['average_cost']
        if min_cost == 0:
            contain['min_cost'] = cost
        if min_cost > cost:
            contain['min_cost'] = cost
        if max_cost < cost:
            contain['max_cost'] = cost
        average_cost = (average_cost*hit_count + cost) / (hit_count + 1)
        hit_count +=1
        contain['average_cost'] = average_cost
        contain['hit_count'] = hit_count
    logging.info(contain)

def download_one():
    while True:
        try:
            stime = time.time()
            request = requests.Request(method='GET', url=download_url,)
            prep = session.prepare_request(request)
            response = session.send(prep, timeout=100)
            etime = time.time()
            # print(response.content)
            logging.info('thread[%s] status[%s] cost[%s]',threading.current_thread().ident,
                         response.status_code,etime-stime)
            handle(float(etime-stime))
        except Exception as e:
            logging.error(e)
            print(e)

def main():
    with futures.ThreadPoolExecutor(workers) as executor:
        for i in range(workers):
            executor.submit(download_one)

if __name__ == '__main__':
    logging.basicConfig(filename="client.log", level=logging.INFO,
                        format="%(asctime)s  [%(filename)s:%(lineno)d] %(message)s", datefmt="%m/%d/%Y %H:%M:%S [%A]")
    main()

2、多进程多线程模式

# #!/usr/bin/env python
# # -*- coding:utf-8 -*-

import os
import time
import logging
import requests
import threading
from multiprocessing import Lock,Manager
from concurrent import futures


download_url = 'http://192.168.188.105:8888'
workers = 250
cpu_count = 4

session = requests.Session()

def handle(cost,mutex,contain):
    with mutex:
        min_cost = contain['min_cost']
        max_cost = contain['max_cost']
        hit_count = contain['hit_count']
        average_cost = contain['average_cost']
        if min_cost == 0:
            contain['min_cost'] = cost
        if min_cost > cost:
            contain['min_cost'] = cost
        if max_cost < cost:
            contain['max_cost'] = cost
        average_cost = (average_cost*hit_count + cost) / (hit_count + 1)
        hit_count +=1
        contain['average_cost'] = average_cost
        contain['hit_count'] = hit_count
    logging.info(contain)

def download_one(mutex,contain):
    while True:
        try:
            stime = time.time()
            request = requests.Request(method='GET', url=download_url,)
            prep = session.prepare_request(request)
            response = session.send(prep, timeout=50)
            etime = time.time()
            print(response.status_code)
            logging.info('process[%s] thread[%s] status[%s] cost[%s]',os.getpid(),threading.current_thread().ident,
                         response.status_code,etime-stime)
            handle(float(etime-stime),mutex,contain)
            # time.sleep(1)
        except Exception as e:
            logging.error(e)
            print(e)

def new_thread_pool(mutex,contain):
    with futures.ThreadPoolExecutor(workers) as executor:
        for i in range(workers):
            executor.submit(download_one,mutex,contain)

def subprocess():
    manager = Manager()
    mutex = manager.Lock()
    contain = manager.dict({'average_cost': 0, 'min_cost': 0, 'max_cost': 0, 'hit_count': 0})

    with futures.ProcessPoolExecutor(cpu_count) as executor:
        for i in range(cpu_count):
            executor.submit(new_thread_pool,mutex,contain)

if __name__ == '__main__':
    logging.basicConfig(filename="client.log", level=logging.INFO,
                        format="%(asctime)s  [%(filename)s:%(lineno)d] %(message)s", datefmt="%m/%d/%Y %H:%M:%S [%A]")
    subprocess()

#!/usr/bin/env python3

import time
import urllib.request
import threading
from time import sleep

# 性能测试页面
PERF_TEST_URL = "目标域名"

# 配置:模拟运行状态
THREAD_NUM = 1200            # 并发线程总数
ONE_WORKER_NUM = 100        # 每个线程的循环次数
LOOP_SLEEP = 0.1            # 每次请求时间间隔(秒)

# 出错数
ERROR_NUM = 0

#具体的处理函数，负责处理单个任务
def doWork(index):
    t = threading.currentThread()
    try:
        html = urllib.request.urlopen(PERF_TEST_URL).read()
    except Exception as e:
        print(e)
        global ERROR_NUM
        ERROR_NUM += 1

def working():
    t = threading.currentThread()
    # print( "["+t.name+"] Sub Thread Begin" )
    i = 0
    while i < ONE_WORKER_NUM:
        i += 1
        doWork(i)
        sleep(LOOP_SLEEP)
    # print( "["+t.name+"] Sub Thread End" )

def main():

    t1 = time.time()

    Threads = []

    # 创建线程
    for i in range(THREAD_NUM):
        t = threading.Thread(target=working, name="T"+str(i))
        t.setDaemon(True)
        Threads.append(t)

    for t in Threads:
        t.start()

    for t in Threads:
        t.join()

    print( "main thread end" )

    t2 = time.time()

    print( "========================================" )
    print( "URL:", PERF_TEST_URL )
    print( "任务数量:", THREAD_NUM, "*", ONE_WORKER_NUM, "=", THREAD_NUM*ONE_WORKER_NUM )
    print( "总耗时(秒):", t2-t1 )
    print( "每次请求耗时(秒):", (t2-t1) / (THREAD_NUM*ONE_WORKER_NUM) )
    print( "每秒承载请求数:", 1 / ((t2-t1) / (THREAD_NUM*ONE_WORKER_NUM)) )
    print( "错误数量:", ERROR_NUM )

if __name__ == "__main__":
    main()

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