案例_(多线程)爬取糗事百科

清疚 2022-05-13 00:56 213阅读 0赞

## 讲解都写在代码注释中了,直接上代码 ##

# 使用了线程库
    import threading
    # 队列
    from queue import Queue
    # 解析库
    from lxml import etree
    # 请求处理
    import requests
    # json处理
    import time
    
    
    class ThreadCrawl(threading.Thread):
        def __init__(self, thread_name, page_queue, data_queue):
            # threading.Thread.__init__(self)
            # 调用父类初始化方法
            super(ThreadCrawl, self).__init__()
            # 线程名
            self.thread_name = thread_name
            # 页码队列
            self.page_queue = page_queue
            # 数据队列
            self.data_queue = data_queue
            # 请求报头
            self.headers = {"User-Agent": "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;"}
    
        def run(self):
            print("启动 " + self.thread_name)
            while not CRAWL_EXIT:
                try:
                    # 取出一个数字，先进先出
                    # 可选参数block，默认值为True
                    # 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
                    # 2. 如果队列为空，block为False的话，就弹出一个Queue.empty()异常，
                    page = self.page_queue.get(False)
                    url = "http://www.qiushibaike.com/8hr/page/" + str(page) + "/"
                    # print url
                    content = requests.get(url, headers=self.headers).text
                    time.sleep(1)
                    self.data_queue.put(content)
                    # print len(content)
                except:
                    pass
            print("结束 " + self.thread_name)
    
    
    class ThreadParse(threading.Thread):
        def __init__(self, thread_name, data_queue):
            super(ThreadParse, self).__init__()
            # 线程名
            self.thread_name = thread_name
            # 数据队列
            self.data_queue = data_queue
    
        def run(self):
            print("启动" + self.thread_name)
            while not PARSE_EXIT:
                try:
                    html = self.data_queue.get(False)
                    self.parse(html)
                except:
                    pass
            print("退出" + self.thread_name)
    
        def parse(self, html):
            selector = etree.HTML(html)
    
            # 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
            # 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)
            node_list = selector.xpath('//div[contains(@id,"qiushi_tag_")]')
    
            for node in node_list:
                # 爬取所有用户名信息
                # 取出标签里的内容,使用.text方法
                user_name = node.xpath('./div[@class="author clearfix"]//h2')[0].text
    
                # 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
                # 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
                duanzi_info = node.xpath('.//div[@class="content"]/span')[0].text.strip()
    
                # 爬取段子的点赞数
                vote_num = node.xpath('.//span[@class="stats-vote"]/i')[0].text
    
                # 爬取评论数
                comment_num = node.xpath('.//span[@class="stats-comments"]//i')[0].text
    
                # 爬取图片链接
                # 属性src的值,所以不需要.text
                img_url = node.xpath('.//div[@class="thumb"]//@src')
                if len(img_url) > 0:
                    img_url = img_url[0]
                else:
                    img_url = "无图片"
    
                self.save_info(user_name, duanzi_info, vote_num, comment_num, img_url)
    
        def save_info(self, user_name, duanzi_info, vote_num, comment_num, img_url):
            """把每条段子的相关信息写进字典"""
            item = {
                "username": user_name,
                "content": duanzi_info,
                "zan": vote_num,
                "comment": comment_num,
                "image_url": img_url
            }
    
            print(item)
    
    
    CRAWL_EXIT = False
    PARSE_EXIT = False
    
    
    def main():
        # 页码的队列，表示20个页面
        pageQueue = Queue(20)
        # 放入1~10的数字，先进先出
        for i in range(1, 21):
            pageQueue.put(i)
    
        # 采集结果(每页的HTML源码)的数据队列，参数为空表示不限制
        dataQueue = Queue()
    
        filename = open("duanzi.json", "a")
        # 创建锁
        lock = threading.Lock()
    
        # 三个采集线程的名字
        crawlList = ["采集线程1号", "采集线程2号", "采集线程3号"]
        # 存储三个采集线程的列表集合
        thread_crawl = []
        for threadName in crawlList:
            thread = ThreadCrawl(threadName, pageQueue, dataQueue)
            thread.start()
            thread_crawl.append(thread)
    
        # 三个解析线程的名字
        parseList = ["解析线程1号", "解析线程2号", "解析线程3号"]
        # 存储三个解析线程
        thread_parse = []
        for threadName in parseList:
            thread = ThreadParse(threadName, dataQueue)
            thread.start()
            thread_parse.append(thread)
    
        # 等待pageQueue队列为空，也就是等待之前的操作执行完毕
        while not pageQueue.empty():
            pass
    
        # 如果pageQueue为空，采集线程退出循环
        global CRAWL_EXIT
        CRAWL_EXIT = True
    
        print("pageQueue为空")
    
        for thread in thread_crawl:
            thread.join()
    
        while not dataQueue.empty():
            pass
    
        global PARSE_EXIT
        PARSE_EXIT = True
    
        for thread in thread_parse:
            thread.join()
    
    
    if __name__ == "__main__":
        main()

## 爬取结果如下: ##

![70][]

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

[70]: /images/20220513/27b052b102744ec191d9c503289b835e.png
[1445380-20180903211901788-1752749014.png]: /images/20220513/93ba4e94b36e4f35b9ba59718d62c04d.png