爬虫——scrapy框架爬取多个页面电影的二级子页面的详细信息

需求：

• scrapy框架，爬取某电影网页面的每个电影的一级页面的名字
• https://www.55xia.com/
• 爬取每部电影二级页面的详细信息
• 使用代理ip
• 保存日志文件
• 存为csv文件

总结：

1、xpath解析使用extract()的各种情况分析
https://blog.youkuaiyun.com/nzjdsds/article/details/77278400

2、xpath用法注意的点：

div[not(contains(@class,"col-xs-12"))]

class属性不包括"col-xs-12"的div标签
https://blog.youkuaiyun.com/caorya/article/details/81839928?utm_source=blogxgwz1

3、二次解析时，用meta参数字典格式传递第一次解析的参数值。

 # meta 传递第二次解析函数
 yield scrapy.Request(url=url, callback=self.parse_detail, meta={'item': item})

4、存为csv文件：

import csv
csv.writer
writerow

https://blog.youkuaiyun.com/qq_40243365/article/details/83003161

5、空行加参数newline='',

self.f=open('./movie.csv','w',newline='', encoding='utf-8')

6、伪装UA，保存日志，编码格式
settings里设置

USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.75 Safari/537.36'
FEED_EXPORT_ENCODING = 'utf-8-sig'
LOG_LEVEL = 'ERROR'
LOG_FILE = 'log.txt'
ROBOTSTXT_OBEY = False

7、代理ip中间件

class MyMiddleware(object):
    def process_request(self, request, spider):
        request.meta['proxy'] = 'https://157.230.150.101:8080'

settings设置：

DOWNLOADER_MIDDLEWARES = {
   'movie.middlewares.MyMiddleware': 543,
}

代码：

movieinfo.py

import scrapy
from movie.items import MovieItem


class MovieinfoSpider(scrapy.Spider):
    name = 'movieinfo'
    # allowed_domains = ['www.movie.com']
    start_urls = ['https://www.55xia.com/movie']
    page = 1
    base_url = 'https://www.55xia.com/movie/?page={}'

    # 解析二级子页面
    def parse_detail(self, response):

        # 导演可能不止一人，不用extract_first（），拼接成字符串
        directors = response.xpath(
            '/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[1]/td[2]//a/text()').extract()
        directors = " ".join(directors)
        movieType = response.xpath(
            '/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[4]/td[2]/a/text()').extract_first()
        area = response.xpath(
            '/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[5]/td[2]//text()').extract_first()
        time = response.xpath(
            '/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[7]/td[2]//text()').extract_first()
        score = response.xpath(
            '/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[9]/td[2]//a/text()').extract_first()

        # 取出meta的item
        item = response.meta['item']
        print('二级子页面:', item['name'])

        item['directors'] = directors
        item['movieType'] = movieType
        item['area'] = area
        item['time'] = time
        item['score'] = score
        yield item

    def parse(self, response):
        """
        获取超链接
        导演，编剧，主演，类型，地区，语言，上映时间，别名，评分
        :param response:
        :return:
        """
        div_list = response.xpath('/html/body/div[1]/div[1]/div[2]/div[not(contains(@class,"col-xs-12"))]')
        for div in div_list:
            name = div.xpath('./div/div/h1/a/text()').extract_first()

            print('已找到:',name)

            url = div.xpath('.//div[@class="meta"]/h1/a/@href').extract_first()
            url = "https:" + url
            # 实例化item对象并存储
            item = MovieItem()
            item['name'] = name
            # meta 传递第二次解析函数
            yield scrapy.Request(url=url, callback=self.parse_detail, meta={'item': item})

        # 完成每页之后开始下一页
        if self.page < 3:
            self.page += 1
            new_url=self.base_url.format(self.page)
            yield scrapy.Request(url=new_url, callback=self.parse)

items.py

import scrapy


class MovieItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    name = scrapy.Field()
    directors = scrapy.Field()
    movieType = scrapy.Field()
    area = scrapy.Field()
    time = scrapy.Field()
    score = scrapy.Field()

middleware.py

class MyMiddleware(object):
    def process_request(self, request, spider):
        request.meta['proxy'] = 'https://157.230.150.101:8080'

pipelines.py

import csv


class MoviePipeline(object):

    def open_spider(self, spider):
        print('开始存储')
        self.f=open('./movie.csv','w',newline='', encoding='utf-8')
        self.writer= csv.writer(self.f)
        self.writer.writerow(['name','directors','movieType','area','time','score'])

    def process_item(self, item, spider):
        print('正在写入')
        self.writer.writerow([item['name'],item['directors'],item['movieType'],item['area'],item['time'],item['score']])
        return item

    def close_spider(self, spider):
        self.f.close()
        print('保存完成')

结果：

附加：

Excel和CSV格式文件的不同之处
https://blog.youkuaiyun.com/weixin_39198406/article/details/78705016

crawlspider可以改进：

crawlspider更加高效，直接写个正则，可以提取页面符合规则的所有url，直接解析。

• 创建工程scrapy startproject 工程名
• cd 该文件夹
• 创建爬虫文件 scrapy genspider -t crawl 爬虫文件名 网址
• 主要是rule比较牛

  rules = (
        Rule(LinkExtractor(allow=r'/movie/\?page=\d+'), callback='parse_item', follow=False),
    )

import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule


class TtSpider(CrawlSpider):
    name = 'tt'
    # allowed_domains = ['www.baidu.com']
    start_urls = ['https://www.55xia.com/movie']

    rules = (
        Rule(LinkExtractor(allow=r'/movie/\?page=\d+'), callback='parse_item', follow=False),
    )
    '''
    LinkExtractor(allow=r'Items/') 实例化一个链接提取器的对象，根据allow的正则表达式来提取指定内容。
    Rule（）实例化一个规则解析器对象，对Link提取的链接发起请求，获取链接对应的页面内容，交给callback解析
    follow 表示是否在提取到的url链接页面再次以相同规则提取，
    scrapy 最后会去重
    # follow=True 所有的页面数据。
    '''

    def parse_item(self, response):
        # i = {}
        #i['domain_id'] = response.xpath('//input[@id="sid"]/@value').extract()
        #i['name'] = response.xpath('//div[@id="name"]').extract()
        #i['description'] = response.xpath('//div[@id="description"]').extract()
        # return i
        '''
        print(response)打印的是提取器提取到的链接，但是可以直接response.xpath解析链接指向的页面！
        :param response:
        :return:
        '''
        title=response.xpath('/html/body/div[1]/div[1]/div[2]/div[1]/div/div/h1/a/text()').extract_first()
        print(title)