Python爬虫框架Scrapy实例代码

# -*- coding: utf-8 -*-import scrapyclass TencentItem(scrapy.Item):  # 职位名  positionname = scrapy.Field()  # 详情连接  positionlink = scrapy.Field()  # 职位类别  positionType = scrapy.Field()  # 招聘人数  peopleNum = scrapy.Field()  # 工作地点  workLocation = scrapy.Field()  # 发布时间  publishTime = scrapy.Field()

# tencentPostion为爬虫名，tencent.com为爬虫作用范围scrapy genspider tencentPostion "tencent.com"

# -*- coding: utf-8 -*-import scrapyfrom tencent.items import TencentItemclass TencentpositionSpider(scrapy.Spider):  """  功能：爬取腾讯社招信息  """  # 爬虫名  name = "tencentPosition"  # 爬虫作用范围  allowed_domains = ["tencent.com"]  url = "http://hr.tencent.com/position.php?&start="  offset = 0  # 起始url  start_urls = [url + str(offset)]  def parse(self, response):    for each in response.xpath("//tr[@class='even'] | //tr[@class='odd']"):      # 初始化模型对象      item = TencentItem()      # 职位名称      item['positionname'] = each.xpath("./td[1]/a/text()").extract()[0]      # 详情连接      item['positionlink'] = each.xpath("./td[1]/a/@href").extract()[0]      # 职位类别      item['positionType'] = each.xpath("./td[2]/text()").extract()[0]      # 招聘人数      item['peopleNum'] = each.xpath("./td[3]/text()").extract()[0]      # 工作地点      item['workLocation'] = each.xpath("./td[4]/text()").extract()[0]      # 发布时间      item['publishTime'] = each.xpath("./td[5]/text()").extract()[0]      yield item    if self.offset < 1680:      self.offset += 10    # 每次处理完一页的数据之后，重新发送下一页页面请求    # self.offset自增10，同时拼接为新的url，并调用回调函数self.parse处理Response    yield scrapy.Request(self.url + str(self.offset), callback = self.parse)

# -*- coding: utf-8 -*-import jsonclass TencentPipeline(object):　　"""     功能：保存item数据   """  def __init__(self):    self.filename = open("tencent.json", "w")  def process_item(self, item, spider):    text = json.dumps(dict(item), ensure_ascii = False) + ",/n"    self.filename.write(text.encode("utf-8"))    return item  def close_spider(self, spider):    self.filename.close()

# 设置请求头部，添加urlDEFAULT_REQUEST_HEADERS = {  "User-Agent" : "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;",  'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8'}# 设置item——pipelinesITEM_PIPELINES = {  'tencent.pipelines.TencentPipeline': 300,}

# tencentPosition为爬虫名scrapy crwal tencentPosition

# 创建项目scrapy startproject TencentSpider# 进入项目目录下，创建爬虫文件scrapy genspider -t crawl tencent tencent.comitem等文件写法不变，主要是爬虫文件的编写# -*- coding:utf-8 -*-import scrapy# 导入CrawlSpider类和Rulefrom scrapy.spiders import CrawlSpider, Rule# 导入链接规则匹配类，用来提取符合规则的连接from scrapy.linkextractors import LinkExtractorfrom TencentSpider.items import TencentItemclass TencentSpider(CrawlSpider):  name = "tencent"  allow_domains = ["hr.tencent.com"]  start_urls = ["http://hr.tencent.com/position.php?&start=0#a"]  # Response里链接的提取规则，返回的符合匹配规则的链接匹配对象的列表  pagelink = LinkExtractor(allow=("start=/d+"))  rules = [    # 获取这个列表里的链接，依次发送请求，并且继续跟进，调用指定回调函数处理    Rule(pagelink, callback = "parseTencent", follow = True)  ]  # 指定的回调函数  def parseTencent(self, response):    for each in response.xpath("//tr[@class='even'] | //tr[@class='odd']"):      item = TencentItem()      # 职位名称      item['positionname'] = each.xpath("./td[1]/a/text()").extract()[0]      # 详情连接      item['positionlink'] = each.xpath("./td[1]/a/@href").extract()[0]      # 职位类别      item['positionType'] = each.xpath("./td[2]/text()").extract()[0]      # 招聘人数      item['peopleNum'] = each.xpath("./td[3]/text()").extract()[0]      # 工作地点      item['workLocation'] = each.xpath("./td[4]/text()").extract()[0]      # 发布时间      item['publishTime'] = each.xpath("./td[5]/text()").extract()[0]      yield item