文章目录

• 需求：
• 总结：
• 代码：
• • movieinfo.py
  • items.py
  • middleware.py
  • pipelines.py
• 结果：
• 附加：
• crawlspider可以改进：

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.csdn.net/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.csdn.net/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.csdn.net/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.csdn.net/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)