Scrapy模块的使用

 在爬虫文件中

1.将解析到的页面数据存储至items对象中

2.使用yield关键字将items提交给管道文件进行处理

import scrapy
from scrapy_qiu123.items import ScrapyQiu123Item

class F1Spider(scrapy.Spider):
    name = 'f1'
    # allowed_domains = ['www.qiushibaike.com']
    start_urls = ['https://www.qiushibaike.com/text/']

    def parse(self, response):
        div_list = response.xpath('//div[@id="content-left"]/div')

        for i in div_list:
            # xpath解析到的都是selector对象,可以用extract获取数据
            author = i.xpath('./div/a[2]/h2/text()').extract()[0]
            content = i.xpath('.//div[@class="content"]/span/text()').extract_first()

            # 1将解析到的数据值(author和content)存储到items中
            item = ScrapyQiu123Item()
            item['author'] = author
            item['content'] = content

            # 2将item对象提交给管道
            yield item

  

  在items中

class ScrapyQiu123Item(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    author = scrapy.Field()
    content = scrapy.Field()

3.在管道文件中编写代码完成数据存储

  在pipelines文件中

class ScrapyQiu123Pipeline(object):
    fp = None
    def open_spider(self,spider):
        #整个爬虫过程中,该方法只会在开始爬虫的时候被调用一次
        self.fp = open('./qiubai.text', 'w', encoding='utf-8')

    # 可接收爬虫文件传来的item,并且对item对象中的页面数据进行持久化存储
    # 每当爬虫文件向管道提交一次item,则该方法就会被执行一次
    def process_item(self, item, spider):
        author = item['author']
        content = item['content']

        # 持久化存储
        self.fp.write(author+":"+content+"\n\n\n")
        return item

    def close_spider(self,spider):
        # 整个爬虫过程中,该方法只会在结束爬虫的时候被调用一次
        self.fp.close()

  

  并在setting文件中设置

ITEM_PIPELINES = {
   'scrapy_qiu123.pipelines.ScrapyQiu123Pipeline': 300,
}

4.在终端执行操作

scrapy crawl f1 --nolog

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转载自www.cnblogs.com/zhuzhiwei-2019/p/10909209.html