爬取博客园文章列表

爬取博客园文章列表，假设页面的URL是https://www.cnblogs.com/loaderman

要求：使用requests获取页面信息，用XPath / re 做数据提取 获取每个博客里的标题，描述，链接地址，日期等保存到 json 文件内

示例：

# -*- coding:utf-8 -*-

import urllib2import jsonfrom lxml import etree

url = "https://www.cnblogs.com/loaderman/"headers = {"User-Agent": "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;"}

request = urllib2.Request(url, headers=headers)

html = urllib2.urlopen(request).read()# 响应返回的是字符串，解析为HTML DOM模式 text = etree.HTML(html)

text = etree.HTML(html)# 返回所有结点位置，contains()模糊查询方法，第一个参数是要匹配的标签，第二个参数是标签名部分内容node_list = text.xpath('//div[contains(@class, "post")]')print (node_list)items = {}for each in node_list:    print (each)    title = each.xpath(".//h2/a[@class='postTitle2']/text()")[0]    detailUrl = each.xpath(".//a[@class='postTitle2']/@href")[0]    content = each.xpath(".//div[@class='c_b_p_desc']/text()")[0]    date = each.xpath(".//p[@class='postfoot']/text()")[0]

    items = {        "title": title,        "image": detailUrl,        "content": content,        "date": date,

    }

    with open("loaderman.json", "a") as f:        f.write(json.dumps(items, ensure_ascii=False).encode("utf-8") + "\n")

效果：

多线程爬虫案例

Queue是python中的标准库，可以直接import Queue引用;队列是线程间最常用的交换数据的形式

python下多线程的思考

对于资源，加锁是个重要的环节。因为python原生的list,dict等，都是not thread safe的。而Queue，是线程安全的，因此在满足使用条件下，建议使用队列

• 初始化：class Queue.Queue(maxsize) FIFO 先进先出

• 包中的常用方法:

  Queue.qsize() 返回队列的大小

  Queue.empty() 如果队列为空，返回True,反之False

  Queue.full() 如果队列满了，返回True,反之False

  Queue.full 与 maxsize 大小对应

  Queue.get([block[, timeout]])获取队列，timeout等待时间

• 创建一个“队列”对象

  import Queue

  myqueue = Queue.Queue(maxsize = 10)

• 将一个值放入队列中

  myqueue.put(10)

• 将一个值从队列中取出

  myqueue.get()

示意图：

# -*- coding:utf-8 -*-

# 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 jsonimport 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 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;"}

    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 = "https://www.cnblogs.com/loaderman/default.html?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(@class, "post")]')        print (node_list)        items = {}        for each in node_list:            print (each)            title = each.xpath(".//h2/a[@class='postTitle2']/text()")[0]            detailUrl = each.xpath(".//a[@class='postTitle2']/@href")[0]            content = each.xpath(".//div[@class='c_b_p_desc']/text()")[0]            date = each.xpath(".//p[@class='postfoot']/text()")[0]

            items = {                "title": title,                "image": detailUrl,                "content": content,                "date": date,

            }

            with open("loadermanThread.json", "a") as f:                f.write(json.dumps(items, ensure_ascii=False).encode("utf-8") + "\n")

CRAWL_EXIT = FalsePARSE_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()

效果：

完

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