# -*- coding: utf-8 -*-
import scrapy
class 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 scrapy
from tencent.items import TencentItem
class 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"
  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 json
class 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url
DEFAULT_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——pipelines
ITEM_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.com
item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Rule
from 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 LinkExtractor
from TencentSpider.items import TencentItem
class TencentSpider(CrawlSpider):
  name = "tencent"
  allow_domains = ["hr.tencent.com"]
  start_urls = ["http://hr.tencent.com/position.php"]
  # 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