爬虫多任务、进程、线程

实现多任务的方式

多线程
多进程
协程
多线程+多进程

为什么你能够实现多任务？

并行：同时发起，同时执行，多进程,进程：cpu分配资源
并发：同时发起，单个执行，线程
在pyhton语言中，并不能真正意义上实现多线程，因为Cpython解释器有一个全局的GIL解释器锁, 来保证同一时刻只有一个线程在执行


线程:

是cpu执行的一个基本单元,暂用的资源非常少,并且线程和线程之间的资源是共享的,线程是依赖于进程而存在的,多线程一般适用于I/O密集型操作,线程的执行是无序的
线程的创建和使用

from threading import Thread
import threading,time
data = []
def download_image(url,num):
    """
    下载图片
    :param url:
    :param num:
    :return:
    """
    global data
    time.sleep(2)
    print(url, num)
    data.append(num)

def read_data():
    global data
    for i in data:
        print(i)

if __name__ == '__main__':
    # 获取当前线程的名称：threading.currentThread().name
    print('主线程开始',threading.currentThread().name)

    # 创建一个子线程
    """
    target=None, 线程要执行的目标函数
    name=None, 创建线程的时候指定线程名称
    args=()：为目标函数传参数，对于的是元祖类型(tuple)
    """
    thread_sub1 = Thread(
        target=download_image,
        name='下载线程',
        args=('https://f10.baidu.com/it/u=3931984114,750350835&fm=72',1))
    thread_sub2 = Thread(
        target=read_data,
        name='读取'
    )
    # 是否开启守护进程
    # daemon = False，在主线程结束的时候会检测子线程人物是否结束，
    # 如果子线程的任务没有结束，则会让子线程正常结束任务
    # daemon = True，如果子线程中的任务没有结束会跟主线程一起结束
    # thread_sub1.daemon = True

    # 启动线程
    thread_sub1.start()
    thread_sub1.join()
    thread_sub2.start()


    # join():阻塞，等待子线程中的任务结束再回到主线程中继续执行
    thread_sub2.join()

    print('主线程结束',threading.currentThread().name)


队列

# 队列
import queue
# 创建一个队列，指定最大数据量
dataqueue = queue.Queue(maxsize=40)
for i in range(0,50):
    # 存值,没有存满情况下存值
    if not dataqueue.full():
        dataqueue.put(i)
# 判断是否为空
dataqueue.empty()
# 判断是否存满
dataqueue.full()
# 长度
dataqueue.qsize()
# 取值，FIFO：先进先出，先存的哪个就先取哪个
dataqueue.get()
# li
# 创建线程执行下载任务
for i in range(1, 10):
    taskQueue.put(i)
    threadName = ['下载线程1号','下载线程2号','下载线程3号','下载线程4号']
    crawl_thread = []
    for name in threadName:
        # 创建线程
        thread_crawl = threading.Thread(target=download_page_data,
                         name=name,
                         args=(taskQueue,dataQueue)
                         )
        crawl_thread.append(thread_crawl)
        # 开启线程
        thread_crawl.start()
    # 让所有的爬取线程执行完毕，再回到主线程中继续执行
    for thread in crawl_thread:
        thread.join()
    # 加线程锁
    lock = threading.Lock()
    lock.acquire()  # 加锁
    lock.release()  # 解锁



使用队列做一个简单的爬虫--jobbole

import queue,requests,threading,json
from lxml.html import etree

# 注意：队列是线程之间数据的交换形式，为队列在线程间，是线程安全的
"""
1.创建一个任务队列：存放的是爬取的url地址
2. 创建爬取线程，执行任务下载
3. 创建数据队列，存放爬取线程获取到的页面源码
4.创建解析线程：解析html源码，提取目标数据，数据持久化
"""
# 获取jobbole的文章列表
# http://blog.jobbole.com/all-posts/page/1/
# http://blog.jobbole.com/all-posts/page/2/


def download_page_data(taskQueue,dataQueue):
    """
    执行下载任务
    :param taskQueue: 从任务队列里面取出任务
    :param dataQueue: 将获取到的页面源码存到dataQueue队列中
    :return:
    """
    while not taskQueue.empty():
        page = taskQueue.get()
        print('正在下载'+str(page)+ '页',threading.currentThread().name)
        full_url = 'http://blog.jobbole.com/all-posts/page/{}/'.format(str(page))
        req_header = {
            'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:64.0) Gecko/20100101 Firefox/64.0'
        }
        response = requests.get(full_url,headers=req_header)
        if response.status_code == 200:
            # 将获取到的页面源码存到dataQueue队列里
            dataQueue.put(response.text)
        else:
            taskQueue.put(page)

def parse_data(dataQueue,lock):
    """
    解析数据，从dataQueue中取出的数据进行解析
    :param dataQueue:
    :return:
    """
    while not dataQueue.empty():
        print('正在解析',threading.currentThread().name)
        html = data = dataQueue.get()
        html_element = etree.HTML(html)
        articles = html_element.xpath('//div[@class="post floated-thumb"]')
        for article in articles:
            articleInfo = {}
            # 标题
            articleInfo['title'] = article.xpath('.//a[@class="archive-title"]/text()')[0]
            # 封面
            img_element = article.xpath('.//div[@class="post-thumb"]/a/img')
            if len(img_element) > 0:
                articleInfo['coverImage'] = img_element[0].xpath('./@src')[0]
            else:
                articleInfo['coverImage'] = '暂无图片'
            p_as = article.xpath('.//div[@class="post-meta"]/p[1]//a')
            if len(p_as) >2:
                # tag类型
                articleInfo['tag'] = p_as[1].xpath('./text()')[0]
                # 评论量
                articleInfo['commentNum'] = p_as[2].xpath('./text()')[0]
            else:
                # tag类型
                articleInfo['tag'] = p_as[1].xpath('./text()')[0]
                # 评论量
                articleInfo['commentNum'] = '0'
            # 简介
            articleInfo['content'] = article.xpath('.//span[@class="excerpt"]/p/text()')
            # 时间
            articleInfo['publishTime'] = ''.join(article.xpath('.//div[@class="post-meta"]/p[1]/text()')).replace('\n','').replace(' ','').replace('\r','').replace('.','')# //text（）当前标签下的所有文本，包括子标签
            # lock.acquire() # 加锁
            # with open('jobbole.json','a+',encoding='utf-8') as file:
            #     json_str = json.dumps(articleInfo,ensure_ascii=False) + '\n'
            #     file.write(json_str)
            # lock.release() #解锁
            # print(articleInfo)



if __name__ == '__main__':
    # 创建任务队列
    taskQueue = queue.Queue()
    for i in range(1,10):
        taskQueue.put(i)


    # 创建数据队列
    dataQueue = queue.Queue()

    # 创建线程执行下载任务
    threadName = ['下载线程1号','下载线程2号','下载线程3号','下载线程4号']
    crawl_thread = []
    for name in threadName:
        # 创建线程
        thread_crawl = threading.Thread(target=download_page_data,
                         name=name,
                         args=(taskQueue,dataQueue)
                         )
        crawl_thread.append(thread_crawl)
    # print(crawl_thread)
        # 开启线程
        thread_crawl.start()

    # 让所有的爬取线程执行完毕，再回到主线程中继续执行
    for thread in crawl_thread:
        thread.join()
    # 加线程锁
    lock = threading.Lock()
    # 创建解析线程，从dataQueue队列中取出页面源码进行解析
    threadName = ['解析线程1号', '解析线程2号', '解析线程3号','解析线程4号']
    parse_thread = []
    for name in threadName:
        # 创建线程
        thread_parse = threading.Thread(target=parse_data,
                                        name=name,
                                        args=(dataQueue,lock)
                                        )
        parse_thread.append(thread_crawl)
        # 开启线程
        thread_parse.start()

    # 让所有的爬取线程执行完毕，再回到主线程中继续执行
    for thread in parse_thread:
        thread.join()


线程池

from concurrent.futures import ThreadPoolExecutor
# max_workers:指定线程池中的线程的数量
pool = ThreadPoolExecutor(max_workers=1000)
# 在线程池中添加任务
handler = pool.submit(目标函数,参数)
# 设置回调方法，当某个线程执行结束执行回调结果
handler.add_done_callback(download_data)
def download_done(futures):
    # 返回回调结果
    print(futures.result())
# 同join()
pool.shutdown()


线程池爬虫

from concurrent.futures import ThreadPoolExecutor
import requests,threading,json
from lxml.html import etree

# 线程池的目的：创建一个线程池，里面有指定数量的线程，让线程执行任务
def download_data(page):
    print(page)
    print('正在下载' + str(page) + '页',threading.currentThread().name)
    full_url = 'http://blog.jobbole.com/all-posts/page/{}/'.format(str(page))
    req_header = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:64.0) Gecko/20100101 Firefox/64.0'
    }
    response = requests.get(full_url, headers=req_header)
    if response.status_code == 200:
        # 将获取到的页面源码存到dataQueue队列里
        print('请求成功')
        return response.text,response.status_code

def download_done(futures):
    # 返回回调结果
    print(futures.result())
    # 可以在这里做数据解析
    html = futures.result()[0]
    html_element = etree.HTML(html)
    articles = html_element.xpath('//div[@class="post floated-thumb"]')
    for article in articles:
        articleInfo = {}
        # 标题
        articleInfo['title'] = article.xpath('.//a[@class="archive-title"]/text()')[0]
        # 封面
        img_element = article.xpath('.//div[@class="post-thumb"]/a/img')
        if len(img_element) > 0:
            articleInfo['coverImage'] = img_element[0].xpath('./@src')[0]
        else:
            articleInfo['coverImage'] = '暂无图片'
        p_as = article.xpath('.//div[@class="post-meta"]/p[1]//a')
        if len(p_as) > 2:
            # tag类型
            articleInfo['tag'] = p_as[1].xpath('./text()')[0]
            # 评论量
            articleInfo['commentNum'] = p_as[2].xpath('./text()')[0]
        else:
            # tag类型
            articleInfo['tag'] = p_as[1].xpath('./text()')[0]
            # 评论量
            articleInfo['commentNum'] = '0'
        # 简介
        articleInfo['content'] = article.xpath('.//span[@class="excerpt"]/p/text()')
        # 时间
        articleInfo['publishTime'] = ''.join(article.xpath('.//div[@class="post-meta"]/p[1]/text()')).replace('\n',
                                                                                                              '').replace(
            ' ', '').replace('\r', '').replace('.', '')  # //text（）当前标签下的所有文本，包括子标签

        with open('jobbole.json', 'a+',encoding='utf-8') as file:
            json_str = json.dumps(articleInfo, ensure_ascii=False) + '\n'
            file.write(json_str)


if __name__ == '__main__':
    # 创建线程池
    # max_workers:指定线程池中的线程的数量
    pool = ThreadPoolExecutor(max_workers=10)
    for i in range(1,201):
        # 线程池中添加任务
        handler = pool.submit(download_data,i)
        # 设置回调方法，当某个线程执行结束执行回调结果
        handler.add_done_callback(download_data)
    # 执行shutdown（）内部是执行join（）方法
    pool.shutdown()


进程

队列

from multiprocessing import Process,Queue
import os

#maxsize=-1:设置队列中嫩够存储的最大元素的个数
data_queue = Queue(maxsize=10)

def write_data(num,data_queue):
    print(num)
    #global data_queue
    for i in range(0,num):
        data_queue.put(i)
    print(os.getpid(),data_queue.full())


def read_data(data_queue):
    print('正在读取',os.getpid())
    #global data_queue
    print(data_queue.qsize())
    for i in range(0,data_queue.qsize()):
        print(data_queue.get())


if __name__ == '__main__':

    #os.getpid()获取进程的id
    print('主进程开启',os.getpid())

    #创建子进程
    """
    target=None,:设置进程要执行的函数
    name=None,:设置进程的名称
    args=(), :给进程执行的函数传递参数（tuple类型）
    kwargs={}　:给进程执行的函数传递参数（字典类型）
    """
    process1 = Process(target=write_data,args=(10,data_queue))
    #使用start()启动进程
    process1.start()

    #timeout=5:设置阻塞时间
    process1.join()

    process2 = Process(target=read_data,args=(data_queue,))
    # 使用start()启动进程
    process2.start()

    # timeout=5:设置阻塞时间
    process2.join()

    print('主进程结束',os.getpid())



队列爬虫

"""
1.创建任务队列
2.创建爬取进程,执行爬取任务
3.创建数据队列
4.创建解析线程,解析获取的数据
"""

# 案例网站：世纪家园

# 武汉地区的活动：（第一页数据是静态页面,第二页之后是动态加载的）
# http://date.jiayuan.com/eventslist_new.php?
# page=1&city_id=4201&shop_id=33　（第一页）
# http://date.jiayuan.com/eventslist_new.php?
# page=2&city_id=4201&shop_id=33　（第二页）
#　http://date.jiayuan.com/eventslist_new.php?
# page=3&city_id=4201&shop_id=33　（第三页）
"""
_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; 
jy_refer=www.baidu.com; _gscbrs_1380850711=1; 
PHPSESSID=9202a7e752f801a49a5747832520f1da; 
plat=date_pc; DATE_FROM=daohang; 
SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; 
user_access=1; uv_flag=124.64.18.38; 
DATE_SHOW_LOC=4201; DATE_SHOW_SHOP=33
"""

# http://date.jiayuan.com/eventslist_new.php?
# page=2&city_id=31&shop_id=15
"""
_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; 
jy_refer=www.baidu.com; _gscbrs_1380850711=1; 
PHPSESSID=9202a7e752f801a49a5747832520f1da; 
plat=date_pc; DATE_FROM=daohang; 
SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; 
user_access=1; uv_flag=124.64.18.38; 
DATE_SHOW_LOC=31; DATE_SHOW_SHOP=15
"""
from multiprocessing import Process,Queue
import requests,re,json
from lxml.html import etree
import time

def down_load_page_data(taskQueue,dataQueue):
    """
    执行任务的下载
    :param taskQueue:
    :param dataQueue:
    :return:
    """
    sumTime = 0
    isContinue = True
    while isContinue:
        if not taskQueue.empty():
            sumTime = 0
            url = taskQueue.get()
            response,cur_page = download_page_data(url)
            data_dict = {'data':response.text,'page':cur_page}
            dataQueue.put(data_dict)

            #获取下一页
            if cur_page != 1:
                print('====',cur_page)
                if isinstance(response.json(),list):
                    next_page = cur_page+1
                    next_url = re.sub('page=\d+','page='+str(next_page),url)
                    taskQueue.put(next_url)
                else:
                    print('已获取到'+str(cur_page)+'页','没有数据了',response.json())
                    pass
            elif cur_page == 1:
                next_page = cur_page + 1
                next_url = re.sub('page=\d+', 'page=' + str(next_page), url)
                taskQueue.put(next_url)
        else:
            #数据队列中没有任务了
            time.sleep(0.001)
            sumTime = sumTime + 1
            if sumTime > 5000:
                print('跳出循环')
                isContinue = False
                break

def download_page_data(url):
    """
    下载每一个分页的数据
    :param url: 每一个分页的url地址
    :return:
    """
    #http://date.jiayuan.com/eventslist_new.php?
    # page=1&city_id=4201&shop_id=33
    pattern = re.compile('.*?page=(\d+)&city_id=(\d+)&shop_id=(\d+)')
    result = re.findall(pattern,url)[0]
    cur_page = result[0]
    DATE_SHOW_LOC = result[1]
    DATE_SHOW_SHOP = result[2]
    print(cur_page,DATE_SHOW_SHOP,DATE_SHOW_LOC)
    cookie = """_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; jy_refer=www.baidu.com; _gscbrs_1380850711=1; PHPSESSID=9202a7e752f801a49a5747832520f1da; plat=date_pc; DATE_FROM=daohang; SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; user_access=1; uv_flag=124.64.18.38; DATE_SHOW_LOC=%s; DATE_SHOW_SHOP=%s""" % (DATE_SHOW_LOC,DATE_SHOW_SHOP)
    # print(cookie)

    req_header = {
        'User-Agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36',
        'Cookie':cookie,
        'Referer':'http://date.jiayuan.com/eventslist.php',
    }
    # cookie_dict = {sub_str.split('=')[0]:sub_str.split('=')[1] for sub_str in cookie.split('; ')}
    # print(cookie_dict)
    #cookies(cookiejar object or dict)
    response = requests.get(url,headers=req_header)

    if response.status_code == 200:
        print('第'+cur_page+'页获取成功',DATE_SHOW_SHOP,DATE_SHOW_LOC)
        return response,int(cur_page)


def parse_page_data(dataQueue):
    """
    解析进程解析数据
    :param dataQueue:
    :return:
    """
    while not dataQueue.empty():
        data = dataQueue.get()
        page = data['page']
        html = data['data']
        if page == 1:
            print('解析第一页数据,静态页面')
            html_element = etree.HTML(html)
            hot_active = html_element.xpath('//div[@class="hot_detail fn-clear"]')
            for hot_div in hot_active:
                # 活动详情的url地址
                full_detail_url = 'http://date.jiayuan.com' + hot_div.xpath('.//h2[@class="hot_title"]/a/@href')[0]
                response = download_detail_data(full_detail_url)
                parse_detail_data(response)

            more_active = html_element.xpath('//ul[@class="review_detail fn-clear t-activiUl"]/li')
            for more_li in more_active:
                # 活动详情的url地址
                full_detail_url = 'http://date.jiayuan.com' + more_li.xpath('.//a[@class="review_link"]/@href')[0]
                response = download_detail_data(full_detail_url)
                parse_detail_data(response)
        else:
            print('解析第'+str(page)+'数据','非静态页面')
            #使用json.loads()将json字符串转换为python数据类型
            json_obj = json.loads(html)
            if isinstance(json_obj, list):
                # 是列表,说明得到的是正确的数据,
                print('正在解析数据')
                for sub_dict in json_obj:
                    id = sub_dict['id']
                    #http://date.jiayuan.com/activityreviewdetail.php?id=11706
                    full_detail_url = 'http://date.jiayuan.com/activityreviewdetail.php?id=%s' % id
                    response = download_detail_data(full_detail_url)
                    parse_detail_data(response)

def download_detail_data(url):
    """
    根据活动详情的url地址发起请求
    :param url:
    :return:
    """
    req_header = {
        'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36',
        'Cookie': '_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; jy_refer=www.baidu.com; _gscbrs_1380850711=1; PHPSESSID=9202a7e752f801a49a5747832520f1da; plat=date_pc; DATE_FROM=daohang; SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; user_access=1; uv_flag=124.64.18.38; DATE_SHOW_LOC=50; DATE_SHOW_SHOP=5',
        'Referer': 'http://date.jiayuan.com/eventslist.php',
    }
    response = requests.get(url, headers=req_header)

    if response.status_code == 200:
        print('详情页面获取成功',response.url)
        return response

def parse_detail_data(response):
    """
    解析活动详情
    :param response:
    :return:
    """
    html_element = etree.HTML(response.text)
    # 创建一个字典，存放获取的数据
    item = {}
    # 活动标题
    item['title'] = ''.join(html_element.xpath('//h1[@class="detail_title"]/text()')[0])
    # 活动时间
    item['time'] = ','.join(
        html_element.xpath('//div[@class="detail_right fn-left"]/ul[@class="detail_info"]/li[1]//text()')[0])
    # 活动地址
    item['adress'] = html_element.xpath('//ul[@class="detail_info"]/li[2]/text()')[0]
    # 参加人数
    item['joinnum'] = html_element.xpath('//ul[@class="detail_info"]/li[3]/span[1]/text()')[0]
    # 预约人数
    item['yuyue'] = html_element.xpath('//ul[@class="detail_info"]/li[3]/span[2]/text()')[0]
    # 介绍
    item['intreduces'] = html_element.xpath('//div[@class="detail_act fn-clear"][1]//p[@class="info_word"]/span[1]/text()')[0]
    # 提示
    item['point'] = html_element.xpath('//div[@class="detail_act fn-clear"][2]//p[@class="info_word"]/text()')[0]
    # 体验店介绍
    item['introductionStore'] = ''.join(
        html_element.xpath('//div[@class="detail_act fn-clear"][3]//p[@class="info_word"]/text()'))
    # 图片连接
    item['coverImage'] = html_element.xpath('//div[@class="detail_left fn-left"]/img/@data-original')[0]

    with open('shijijiyua.json','a+') as file:
        json_str = json.dumps(item,ensure_ascii=False)+'\n'
        file.write(json_str)

if __name__ == '__main__':

    #创建任务队列
    taskQueue = Queue()

    #设置起始任务
    taskQueue.put('http://date.jiayuan.com/eventslist_new.php?page=1&city_id=4201&shop_id=33')
    taskQueue.put('http://date.jiayuan.com/eventslist_new.php?page=1&city_id=31&shop_id=15')
    taskQueue.put('http://date.jiayuan.com/eventslist_new.php?page=1&city_id=3702&shop_id=42')
    taskQueue.put('http://date.jiayuan.com/eventslist_new.php?page=1&city_id=50&shop_id=5')

    #创建数据队列
    dataQueue = Queue()

    #创建进程爬取任务

    for i in range(0,3):
        process_crawl = Process(
            target=down_load_page_data,
            args=(taskQueue,dataQueue)
        )
        process_crawl.start()

    time.sleep(10)

    #创建解析进程
    for i in range(0,3):
        process_parse = Process(
            target=parse_page_data,
            args=(dataQueue,)
        )
        process_parse.start()







进程池

from concurrent.futures import ProcessPoolExecutor
import os
"""
def download_page_data(page):

    print(page,os.getpid())

    return '下载完成'+str(page),page

def download_done(futures):
    result = futures.result()
    print(result)
    next_page = int(result[1])+1

    handler = pool.submit(download_page_data,next_page)
    handler.add_done_callback(download_done)

if __name__ == '__main__':
    #创建进程池
    pool = ProcessPoolExecutor(4)
    for page in range(0,200):
        hanlder = pool.submit(download_page_data,page)
        #回调函数的设置,看自己是否需要
        hanlder.add_done_callback(download_done)
    
    #cannot schedule new futures after shutdown
    # pool.shutdown()
"""

#方式二
from multiprocessing import Pool

def download_page_data(page):

    print(page,os.getpid())

    return '下载完成'+str(page),page

def done(futures):

    print(futures)

if __name__ == '__main__':

    #创建进程池
    pool = Pool(4)

    for page in range(0,200):
        # pool.apply_async() 异步非阻塞添加任务
        # pool.apply() 同步的方式添加任务
        # func, 要执行的方法(函数)
        # args=(),给函数传递的参数
        #callback = None,成功的回调
        #error_callback = None,执行错误的回调
        pool.apply_async(download_page_data,args=(page,),callback=done)

    pool.close() #执行close后不可以再添加任务了
    pool.join()


进程池爬虫

from concurrent.futures import ProcessPoolExecutor
import requests
import time,re,json
from lxml.html import etree

def down_load_page_data(url):
    """
    执行任务的下载
    :param url
    :return:
    """
    response,cur_page = download_page_data(url)
    data_dict = {'data':response.text,'page':cur_page}
    #获取下一页
    if cur_page != 1:
        if isinstance(response.json(),list):
            next_page = cur_page+1
            next_url = re.sub('page=\d+','page='+str(next_page),url)
        else:
            print('已获取到'+str(cur_page)+'页','没有数据了',response.json())
            next_url = None
            pass
    elif cur_page == 1:
        next_page = cur_page + 1
        next_url = re.sub('page=\d+', 'page=' + str(next_page), url)

    print('====', cur_page)
    return data_dict,next_url

def download_page_data(url):
    """
    下载每一个分页的数据
    :param url: 每一个分页的url地址
    :return:
    """
    #http://date.jiayuan.com/eventslist_new.php?
    # page=1&city_id=4201&shop_id=33
    pattern = re.compile('.*?page=(\d+)&city_id=(\d+)&shop_id=(\d+)')
    result = re.findall(pattern,url)[0]
    cur_page = result[0]
    DATE_SHOW_LOC = result[1]
    DATE_SHOW_SHOP = result[2]
    print(cur_page,DATE_SHOW_SHOP,DATE_SHOW_LOC)
    cookie = """_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; jy_refer=www.baidu.com; _gscbrs_1380850711=1; PHPSESSID=9202a7e752f801a49a5747832520f1da; plat=date_pc; DATE_FROM=daohang; SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; user_access=1; uv_flag=124.64.18.38; DATE_SHOW_LOC=%s; DATE_SHOW_SHOP=%s""" % (DATE_SHOW_LOC,DATE_SHOW_SHOP)
    # print(cookie)

    req_header = {
        'User-Agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36',
        'Cookie':cookie,
        'Referer':'http://date.jiayuan.com/eventslist.php',
    }
    # cookie_dict = {sub_str.split('=')[0]:sub_str.split('=')[1] for sub_str in cookie.split('; ')}
    # print(cookie_dict)
    #cookies(cookiejar object or dict)
    response = requests.get(url,headers=req_header)

    if response.status_code == 200:
        print('第'+cur_page+'页获取成功',DATE_SHOW_SHOP,DATE_SHOW_LOC)
        return response,int(cur_page)

def parse_page_data(futures):
    """
    step1:获取到下一页的url地址,继续网进程池中添加任务
    strp2:获取到分页的页面源码,进行数据的解析
    :param futures:
    :return:
    """
    result = futures.result()
    data = result[0]
    next_page_url = result[1]
    print(data,next_page_url)

    if next_page_url:
        print('正在天加任务',next_page_url)
        handler = page_pool.submit(down_load_page_data, next_page_url)
        handler.add_done_callback(parse_page_data)

    page = data['page']
    html = data['data']
    # 创建进程池(获取活动详情的页面源码)
    detail_pool = ProcessPoolExecutor(3)

    if page == 1:
        print('解析第一页数据,静态页面')
        html_element = etree.HTML(html)
        hot_active = html_element.xpath('//div[@class="hot_detail fn-clear"]')
        for hot_div in hot_active:
            # 活动详情的url地址
            full_detail_url = 'http://date.jiayuan.com' + hot_div.xpath('.//h2[@class="hot_title"]/a/@href')[0]
            detail_handler = detail_pool.submit(download_detail_data,full_detail_url)
            detail_handler.add_done_callback(parse_detail_data)

        more_active = html_element.xpath('//ul[@class="review_detail fn-clear t-activiUl"]/li')
        for more_li in more_active:
            # 活动详情的url地址
            full_detail_url = 'http://date.jiayuan.com' + more_li.xpath('.//a[@class="review_link"]/@href')[0]
            detail_handler = detail_pool.submit(download_detail_data, full_detail_url)
            detail_handler.add_done_callback(parse_detail_data)

    else:
        print('解析第' + str(page) + '数据', '非静态页面')
        # 使用json.loads()将json字符串转换为python数据类型
        json_obj = json.loads(html)
        if isinstance(json_obj, list):
            # 是列表,说明得到的是正确的数据,
            print('正在解析数据')
            for sub_dict in json_obj:
                id = sub_dict['id']
                # http://date.jiayuan.com/activityreviewdetail.php?id=11706
                full_detail_url = 'http://date.jiayuan.com/activityreviewdetail.php?id=%s' % id
                detail_handler = detail_pool.submit(download_detail_data, full_detail_url)
                detail_handler.add_done_callback(parse_detail_data)

def download_detail_data(url):
    """
    根据活动详情的url地址发起请求
    :param url:
    :return:
    """
    req_header = {
        'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36',
        'Cookie': '_gscu_1380850711=43812116hs5dyy11; accessID=20181222071935501079; jy_refer=www.baidu.com; _gscbrs_1380850711=1; PHPSESSID=9202a7e752f801a49a5747832520f1da; plat=date_pc; DATE_FROM=daohang; SESSION_HASH=61e963462c6b312ee1ffacf151ffaa028477217d; user_access=1; uv_flag=124.64.18.38; DATE_SHOW_LOC=50; DATE_SHOW_SHOP=5',
        'Referer': 'http://date.jiayuan.com/eventslist.php',
    }
    response = requests.get(url, headers=req_header)

    if response.status_code == 200:
        print('详情页面获取成功',response.url)
        return response

def parse_detail_data(futures):
    """
    解析活动详情
    :param response:
    :return:
    """
    response = futures.result()
    html_element = etree.HTML(response.text)
    # 创建一个字典，存放获取的数据
    item = {}
    # 活动标题
    item['title'] = ''.join(html_element.xpath('//h1[@class="detail_title"]/text()')[0])
    # 活动时间
    item['time'] = ','.join(
        html_element.xpath('//div[@class="detail_right fn-left"]/ul[@class="detail_info"]/li[1]//text()')[0])
    # 活动地址
    item['adress'] = html_element.xpath('//ul[@class="detail_info"]/li[2]/text()')[0]
    # 参加人数
    item['joinnum'] = html_element.xpath('//ul[@class="detail_info"]/li[3]/span[1]/text()')[0]
    # 预约人数
    item['yuyue'] = html_element.xpath('//ul[@class="detail_info"]/li[3]/span[2]/text()')[0]
    # 介绍
    item['intreduces'] = html_element.xpath('//div[@class="detail_act fn-clear"][1]//p[@class="info_word"]/span[1]/text()')[0]
    # 提示
    item['point'] = html_element.xpath('//div[@class="detail_act fn-clear"][2]//p[@class="info_word"]/text()')[0]
    # 体验店介绍
    item['introductionStore'] = ''.join(
        html_element.xpath('//div[@class="detail_act fn-clear"][3]//p[@class="info_word"]/text()'))
    # 图片连接
    item['coverImage'] = html_element.xpath('//div[@class="detail_left fn-left"]/img/@data-original')[0]

    with open('shijijiyua.json','a+') as file:
        json_str = json.dumps(item,ensure_ascii=False)+'\n'
        file.write(json_str)

if __name__ == '__main__':

    #创建一个进程池,执行分页任务下载
    page_pool = ProcessPoolExecutor(4)
    start_urls = [
        'http://date.jiayuan.com/eventslist_new.php?page=1&city_id=4201&shop_id=33',
        'http://date.jiayuan.com/eventslist_new.php?page=1&city_id=31&shop_id=15',
        'http://date.jiayuan.com/eventslist_new.php?page=1&city_id=3702&shop_id=42',
        'http://date.jiayuan.com/eventslist_new.php?page=1&city_id=50&shop_id=5',
    ]
    for url in start_urls:
        handler = page_pool.submit(down_load_page_data,url)
        handler.add_done_callback(parse_page_data)