美文网首页大数据 爬虫Python AI Sql
Scrapy入门案例——腾讯招聘(CrawlSpider升级)

Scrapy入门案例——腾讯招聘(CrawlSpider升级)

作者: 徐同学呀 | 来源:发表于2018-08-03 10:32 被阅读3次

    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

    相关文章

      网友评论

        本文标题:Scrapy入门案例——腾讯招聘(CrawlSpider升级)

        本文链接:https://www.haomeiwen.com/subject/nzcyvftx.html