案例_(多线线程)爬取糗事百科

谁践踏了优雅 2022-05-14 12:38 241阅读 0赞

1 # 使用了线程库
      2 import threading
      3 # 队列
      4 from queue import Queue
      5 # 解析库
      6 from lxml import etree
      7 # 请求处理
      8 import requests
      9 # json处理
     10 import time
     11 
     12 
     13 class ThreadCrawl(threading.Thread):
     14     def __init__(self, thread_name, page_queue, data_queue):
     15         #threading.Thread.__init__(self)
     16         # 调用父类初始化方法
     17         super(ThreadCrawl, self).__init__()
     18         # 线程名
     19         self.thread_name = thread_name
     20         # 页码队列
     21         self.page_queue = page_queue
     22         # 数据队列
     23         self.data_queue = data_queue
     24         # 请求报头
     25         self.headers = {"User-Agent" : "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;"}
     26 
     27     def run(self):
     28         print("启动 " + self.thread_name)
     29         while not CRAWL_EXIT:
     30             try:
     31                 # 取出一个数字，先进先出
     32                 # 可选参数block，默认值为True
     33                 #1. 如果对列为空，block为True的话，不会结束，会进入阻塞状态，直到队列有新的数据
     34                 #2. 如果队列为空，block为False的话，就弹出一个Queue.empty()异常，
     35                 page = self.page_queue.get(False)
     36                 url = "http://www.qiushibaike.com/8hr/page/" + str(page) +"/"
     37                 #print url
     38                 content = requests.get(url, headers = self.headers).text
     39                 time.sleep(1)
     40                 self.data_queue.put(content)
     41                 #print len(content)
     42             except:
     43                 pass
     44         print("结束 " + self.thread_name)
     45 
     46 class ThreadParse(threading.Thread):
     47     def __init__(self, thread_name, data_queue):
     48         super(ThreadParse, self).__init__()
     49         # 线程名
     50         self.thread_name = thread_name
     51         # 数据队列
     52         self.data_queue = data_queue
     53 
     54     def run(self):
     55         print("启动" + self.thread_name)
     56         while not PARSE_EXIT:
     57             try:
     58                 html = self.data_queue.get(False)
     59                 self.parse(html)
     60             except:
     61                 pass
     62         print("退出" + self.thread_name)
     63 
     64     def parse(self, html):
     65         selector = etree.HTML(html)
     66 
     67         # 返回所有段子的节点位置,contant()模糊查询方法,第一个参数是要匹配的标签,第二个参数是这个标签的部分内容
     68         # 每个节点包括一条完整的段子(用户名,段子内容,点赞,评论等)
     69         node_list = selector.xpath('//div[contains(@id,"qiushi_tag_")]')
     70 
     71         for node in node_list:
     72             # 爬取所有用户名信息
     73             # 取出标签里的内容,使用.text方法
     74             user_name = node.xpath('./div[@class="author clearfix"]//h2')[0].text
     75 
     76             # 爬取段子内容,匹配规则必须加点  不然还是会从整个页面开始匹配
     77             # 注意:如果span标签中有br 在插件中没问题,在代码中会把br也弄进来
     78             duanzi_info = node.xpath('.//div[@class="content"]/span')[0].text.strip()
     79 
     80             # 爬取段子的点赞数
     81             vote_num = node.xpath('.//span[@class="stats-vote"]/i')[0].text
     82 
     83             # 爬取评论数
     84             comment_num = node.xpath('.//span[@class="stats-comments"]//i')[0].text
     85 
     86             # 爬取图片链接
     87             # 属性src的值,所以不需要.text
     88             img_url = node.xpath('.//div[@class="thumb"]//@src')
     89             if len(img_url) > 0:
     90                 img_url = img_url[0]
     91             else:
     92                 img_url = "无图片"
     93 
     94             self.save_info(user_name, duanzi_info, vote_num, comment_num, img_url)
     95 
     96     def save_info(self, user_name, duanzi_info, vote_num, comment_num, img_url):
     97         """把每条段子的相关信息写进字典"""
     98         item = {
     99             "username": user_name,
    100             "content": duanzi_info,
    101             "zan": vote_num,
    102             "comment": comment_num,
    103             "image_url": img_url
    104         }
    105 
    106         print(item)
    107 
    108 
    109 
    110 CRAWL_EXIT = False
    111 PARSE_EXIT = False
    112 
    113 
    114 def main():
    115     # 页码的队列，表示20个页面
    116     pageQueue = Queue(20)
    117     # 放入1~10的数字，先进先出
    118     for i in range(1, 21):
    119         pageQueue.put(i)
    120 
    121     # 采集结果(每页的HTML源码)的数据队列，参数为空表示不限制
    122     dataQueue = Queue()
    123 
    124     filename = open("duanzi.json", "a")
    125     # 创建锁
    126     lock = threading.Lock()
    127 
    128     # 三个采集线程的名字
    129     crawlList = ["采集线程1号", "采集线程2号", "采集线程3号"]
    130     # 存储三个采集线程的列表集合
    131     thread_crawl = []
    132     for threadName in crawlList:
    133         thread = ThreadCrawl(threadName, pageQueue, dataQueue)
    134         thread.start()
    135         thread_crawl.append(thread)
    136 
    137 
    138     # 三个解析线程的名字
    139     parseList = ["解析线程1号","解析线程2号","解析线程3号"]
    140     # 存储三个解析线程
    141     thread_parse = []
    142     for threadName in parseList:
    143         thread = ThreadParse(threadName, dataQueue)
    144         thread.start()
    145         thread_parse.append(thread)
    146 
    147     # 等待pageQueue队列为空，也就是等待之前的操作执行完毕
    148     while not pageQueue.empty():
    149         pass
    150 
    151     # 如果pageQueue为空，采集线程退出循环
    152     global CRAWL_EXIT
    153     CRAWL_EXIT = True
    154 
    155     print("pageQueue为空")
    156 
    157     for thread in thread_crawl:
    158         thread.join()
    159 
    160     while not dataQueue.empty():
    161         pass
    162 
    163     global PARSE_EXIT
    164     PARSE_EXIT = True
    165 
    166     for thread in thread_parse:
    167         thread.join()
    168 
    169 
    170 
    171 if __name__ == "__main__":
    172     main()

# #

## 爬取效果如下: ##

![1445380-20180904224258702-381477299.png][]

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**![1445380-20180903211901788-1752749014.png][]**

[1445380-20180904224258702-381477299.png]: /images/20220514/db705dde26c54350872d8b1f9e653e22.png
[1445380-20180903211901788-1752749014.png]: /images/20220514/b120e0b87eca421491d38286197acad4.png