需求和上次一样，只是职位信息和详情内容分开保存到不同的文件，并且获取下一页和详情页的链接方式有改动。

这次用到了CrawlSpider。

class scrapy.spiders.CrawlSpider
它是Spider的派生类，Spider类的设计原则是只爬取start_url列表中的网页，而CrawlSpider类定义了一些规则(rule)来提供跟进link的方便的机制，从爬取的网页中获取link并继续爬取的工作更适合。

items.py

import scrapy


class TencentItem(scrapy.Item):
    position_name = scrapy.Field()
    position_type = scrapy.Field()
    people_number = scrapy.Field()
    work_location = scrapy.Field()
    publish_times = scrapy.Field()
    position_link = scrapy.Field()

class DetailItem(scrapy.Item):
    detailContent = scrapy.Field()

可以看到，items.py里有两个类，分别处理。

tencent_crawl.py

建立这个文件不是scrapy genspider XXX "xxx.com"

而是scrapy genspider -t crawl tencent_crawl "tencent.com"

# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule

from tencent2.items import TencentItem, DetailItem


class TencentCrawlSpider(CrawlSpider):
    name = 'tencent_crawl'
    allowed_domains = ['tencent.com']
    start_urls = ['https://hr.tencent.com/position.php']
    base_url = "https://hr.tencent.com/"

    rules = (
        # 符合规则的url请求返回函数为parse_item，并跟进，response传下去继续匹配
        Rule(LinkExtractor(allow=r'start=\d+'), callback='parse_item', follow=True),
        # 规则的url请求返回函数为detail, 不跟进
        Rule(LinkExtractor(allow=r'position_detail\.php\?id=\d+'), callback='detail', follow=False)
    )
    #回调函数千万不能是parse，因为crawlspider底层是调用了parse，如果覆盖重写parse，运行会报错

    def parse_item(self, response):
        node_list = response.xpath('//tr[@class="even"] | //tr[@class="odd"]')

        for node in node_list:
            item = TencentItem()
            item['position_name'] = node.xpath('./td/a/text()').extract_first()
            item['position_link'] = node.xpath('./td/a/@href').extract_first()
            item['position_type'] = node.xpath('./td[2]/text()').extract_first()
            item['people_number'] = node.xpath('./td[3]/text()').extract_first()
            item['work_location'] = node.xpath('./td[4]/text()').extract_first()
            item['publish_times'] = node.xpath('./td[5]/text()').extract_first()
            yield item

    def detail(self, response):
        item = DetailItem()
        item['detailContent'] = "".join(response.xpath('//ul[@class="squareli"]/li/text()').extract())
        yield item

piplines.py

from tencent2.items import TencentItem
import json
import time


class TencentPipeline(object):
    def open_spider(self, spider):
        self.file = open("tencent.json", "w")
        self.position_num = 0
        self.start_time = time.time()

    def process_item(self, item, spider):
        if isinstance(item, TencentItem):
            self.position_num+=1
            content = json.dumps(dict(item), ensure_ascii=False) + "\n"
            self.file.write(content)
        return item

    def close_spider(self, spider):
        self.end_time = time.time()
        print("----------保存" + str(self.position_num) + "条职位信息数据----------")
        print("共耗时+" + str(self.end_time - self.start_time) + "秒")
        self.file.close()

class DetailPipeline(object):
    def open_spider(self, spider):
        self.file = open("detail.json", "w")
        self.detail_num = 0
        self.start_time = time.time()

    def process_item(self, item, spider):
        if not isinstance(item, TencentItem):
            self.detail_num +=1
            content = json.dumps(dict(item), ensure_ascii=False) + "\n"
            self.file.write(content)
        return item

    def close_spider(self, spider):
        self.end_time = time.time()
        print("----------保存" + str(self.detail_num) + "条职位详情数据----------")
        print("共耗时+" + str(self.end_time - self.start_time) + "秒")
        self.file.close()

在piplines.py文件里同样有两个类，一个是处理职位信息的，一个是处理详情内容的。而通过isinstance(item, TencentItem)这个方法来区别不同item，第一个参数是实例对象，第二个参数是类名，如果相匹配就返回true。

设置settings.py

ITEM_PIPELINES = {
    'tencent2.pipelines.TencentPipeline': 300,
    'tencent2.pipelines.DetailPipeline': 400 ,
}

运行项目：scrapy crawl tencent_crawl

项目源码：https://gitee.com/stefanpy/Scrapy_projects/tree/dev/tencent2