• 多线程爬虫


    爬取糗事百科

    # 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 json
    import time
    
    class ThreadCrawl(threading.Thread):
        def __init__(self, threadName, pageQueue, dataQueue):
            #threading.Thread.__init__(self)
            # 调用父类初始化方法
            super(ThreadCrawl, self).__init__()
            # 线程名
            self.threadName = threadName
            # 页码队列
            self.pageQueue = pageQueue
            # 数据队列
            self.dataQueue = dataQueue
            # 请求报头
            self.headers = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.101 Safari/537.36'}
    
        def run(self):
            print ("启动 " + self.threadName)
            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.pageQueue.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.dataQueue.put(content)
                    #print (len(content))
                except:
                    pass
            print ("结束 " + self.threadName)
    
    class ThreadParse(threading.Thread):
        def __init__(self, threadName, dataQueue, filename, lock):
            super(ThreadParse, self).__init__()
            # 线程名
            self.threadName = threadName
            # 数据队列
            self.dataQueue = dataQueue
            # 保存解析后数据的文件名
            self.filename = filename
            # 锁
            self.lock = lock
    
        def run(self):
            print ("启动" + self.threadName)
            while not PARSE_EXIT:
                try:
                    html = self.dataQueue.get(False)
                    self.parse(html)
                except:
                    pass
            print ("退出" + self.threadName)
    
        def parse(self, html):
            # 解析为HTML DOM
            html = etree.HTML(html)
    
            node_list = html.xpath('//div[contains(@id, "qiushi_tag")]')
    
            for node in node_list:
                # xpath返回的列表,这个列表就这一个参数,用索引方式取出来,用户名
                username = node.xpath('./div/a/@title')[0]
                # 图片连接
                image = node.xpath('.//div[@class="thumb"]//@src')#[0]
                # 取出标签下的内容,段子内容
                content = node.xpath('.//div[@class="content"]/span')[0].text
                # 取出标签里包含的内容,点赞
                zan = node.xpath('.//i')[0].text
                # 评论
                comments = node.xpath('.//i')[1].text
    
                items = {
                    "username" : username,
                    "image" : image,
                    "content" : content,
                    "zan" : zan,
                    "comments" : comments
                }
    
                # with 后面有两个必须执行的操作:__enter__ 和 _exit__
                # 不管里面的操作结果如何,都会执行打开、关闭
                # 打开锁、处理内容、释放锁
                with self.lock:
                    # 写入存储的解析后的数据
                    self.filename.write(json.dumps(items, ensure_ascii = False).encode("utf-8") + "
    ")
    
    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
        threadcrawl = []
        for threadName in crawlList:
            thread = ThreadCrawl(threadName, pageQueue, dataQueue)
            thread.start()
            threadcrawl.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
        threadparse = []
        for threadName in parseList:
            thread = ThreadParse(threadName, dataQueue, filename, lock)
            thread.start()
            threadparse.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 threadcrawl:
            thread.join()
            print ("1")
    
        while not dataQueue.empty():
            pass
    
        global PARSE_EXIT
        PARSE_EXIT = True
    
        for thread in threadparse:
            thread.join()
            print ("2")
    
        with lock:
            # 关闭文件
            filename.close()
        print ("谢谢使用!")
    
    if __name__ == "__main__":
        main()
    

      

    参考链接:https://www.cnblogs.com/derek1184405959/p/8449923.html

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  • 原文地址:https://www.cnblogs.com/iupoint/p/12011085.html
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