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标题: 《数据采集与预处置惩罚》实验二 网络爬虫低级实践 [打印本页]

作者: 千千梦丶琪    时间: 2024-10-13 21:14
标题: 《数据采集与预处置惩罚》实验二 网络爬虫低级实践
实验二  网络爬虫低级实践

基本题一 显示影片基本信息

一、实验目的与要求

1、明确网络爬虫相干概念及执行流程;
2、纯熟使用requests库、bs4库中的常用方法;
3、掌握独立编写爬虫步伐并获取所需信息的能力。
二、实验题

  访问豆瓣电影Top250(豆瓣电影 Top 250),获取每部电影的中文片名、排名、评分及其对应的链接,按照“排名-中文片名-评分-链接”的格式显示在屏幕上。

说明:
本实验中使用CSS选择器来获取标签,在此演示如何直接在欣赏器获取指定元素的CSS选择器。
例如:要获取《肖申克的救赎》电影的导演,将鼠标移至该电影的导演处,右击鼠标出现。







三、实验代码


import requests
import time
from bs4 import BeautifulSoup
url="https://movie.douban.com/top250?start=0"
for i in range(10):
    url="https://movie.douban.com/top250?start="+ str(i*25)
    print(url)
    headers={
    'User-Agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36'
    ,'Cookie' : 'bid=uF9ux7mK05s; __utmc=30149280; push_noty_num=0; push_doumail_num=0; __gads=ID=a70f4f7daef34c82-22d73b4c7cdc002a:T=1679378544:RT=1679378544:S=ALNI_MbvrIegly9aVzyyg1KUfkj_U8zZNg; __gpi=UID=00000bdc91487ff0:T=1679378544:RT=1679378544:S=ALNI_Mbw-cobhGE0mj6qOVNYu0PLUW6srg; __yadk_uid=vRYo5bQXwbmKrd1enLtfPwbMCx8RdWjm; _pk_ref.100001.8cb4=%5B%22%22%2C%22%22%2C1679384454%2C%22https%3A%2F%2Fcn.bing.com%2F%22%5D; _pk_ses.100001.8cb4=*; ll="118281"; __utma=30149280.1339882974.1679378543.1679378543.1679384467.2; __utmz=30149280.1679384467.2.2.utmcsr=cn.bing.com|utmccn=(referral)|utmcmd=referral|utmcct=/; __utmt=1; __utmb=30149280.1.10.1679384467; dbcl2="268997119:qj6AwkV9IWg"; ck=sfDP; _pk_id.100001.8cb4=2aa0c079c9e490d3.1679379069.2.1679384535.1679379069.'
    }
    data=requests.get(url,headers=headers).content
    soup = BeautifulSoup(data,'lxml')
    name = soup.select('#content > div > div.article > ol > li > div > div.info > div.hd > a > span:nth-child(1)')
    rank=soup.select("#content > div > div.article > ol > li > div > div.pic > em")
    pingfen=soup.select('#content > div > div.article > ol > li > div > div.info > div.bd > div > span.rating_num')
    web=soup.select('#content > div > div.article > ol > li > div > div.info > div.hd > a')
    names_url=[]
    for i in range(len(name)):
        temp= str(rank.get_text())+"--"+str(name.get_text())+"--"+str(pingfen.get_text())+"--"+web['href']
        print(str(temp))
        names_url.append(temp)
print(names_url)







基本题二 Scrapy框架实践

一、实验目的与要求

1、明确网络爬虫相干概念及执行流程;
2、纯熟使用Scrapy框架;
3、掌握独立编写爬虫步伐并获取所需信息的能力。
二、实验题

访问豆瓣电影Top250(豆瓣电影 Top 250),在问题1的基础上,使用Srapy框架获取每部电影的导演、编剧、主演、类型、上映时间、片长、评分人数以及剧情简介等信息,并将获取到的信息保存至当地文件中。
说明:
本实验与第一个实验类似,但又有不同,需要处置惩罚子网页。第一个实验接纳CSS选择器获取标签,本实验通过观察网页源码发现,主页电影信息全在<div class="item">…</div>标签内,而且不同信息的class不同;子网页电影详细信息全在<div id="info">…</div>中。所以为了简化代码,本实验使用Srapy框架获取相应的标签。
三、实验代码





import scrapy
from ..items import DouBanprojectItem

class DoubanprojectSpider(scrapy.Spider):
    name = "DouBanProject"
    allowed_domains = ["movie.douban.cn"]
    pre_urls = ["http://movie.douban.com/"]
    Second_urls = ["https://movie.douban.com/subject/1292052/"]
    index = 25

    pre_url = 'https://movie.douban.com/top250?start='

    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36',
        'Cookie': 'bid=dJvnLS9LSZw; dbcl2="268997517xIMwxecuoM"; ck=_Gt4; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1679986418%2C%22https%3A%2F%2Faccounts.douban.com%2Fpassport%2Flogin%3Fredir%3Dhttps%253A%252F%252Fmovie.douban.com%252Ftop250%253Fstart%253D0%22%5D; _pk_id.100001.4cf6=0c504467b6cba249.1679986418.1.1679986418.1679986418.; __utma=30149280.314202744.1679986418.1679986418.1679986418.1; __utmc=30149280; __utmz=30149280.1679986418.1.1.utmcsr=accounts.douban.com|utmccn=(referral)|utmcmd=referral|utmcct=/passport/login; __utma=223695111.1488601765.1679986418.1679986418.1679986418.1; __utmc=223695111; __utmz=223695111.1679986418.1.1.utmcsr=accounts.douban.com|utmccn=(referral)|utmcmd=referral|utmcct=/passport/login; push_noty_num=0; push_doumail_num=0; __yadk_uid=7XpTBmn419zZXYVbR23RXwxFnykicX94; __gads=ID=d32f3926a8359ffe-221cff7fc4dc00c8:T=1679986420:RT=1679986420:S=ALNI_MZTs_yGwuU--7NrVfPYG23h3f0Pdw; __gpi=UID=00000be25238883c:T=1679986420:RT=1679986420:S=ALNI_MY88r1HJI5u3zUtk_lMeFw4_aa2Lg'

    }

    def start_requests(self):
        new_url = self.pre_url + str(0)
        yield scrapy.Request(url=new_url, headers=self.headers,callback=self.parse)

    def parse(self, response):
        for element in response.xpath('//*[ @ id = "content"]/div/div[1]/ol/li'):
            no = element.xpath('./div/div[1]/em/text()').get()
            name = element.xpath('./div/div[2]/div[1]/a/span[1]/text()').get()
            grade = element.xpath('./div/div[2]/div[2]/div/span[2]/text()').get()
            new_url = element.xpath('./div/div[2]/div[1]/a/@href').get()


            # print(no, name, grade)
           
yield scrapy.Request(url=new_url, headers=self.headers, callback=self.movie)

        if self.index < 250:
            new_url = self.pre_url + str(self.index)
            # https: // movie.douban.com / top250?start = 27
           
self.index += 25
            yield scrapy.Request(url=new_url, headers=self.headers, callback=self.parse)


    # def Second_requests(self):
    #
    #     two_url = self.pre1_url + str(0)
    #     yield scrapy.Request(url=two_url, headers=self.headers, callback=self.movie)

   
def movie(self, response):
        # response.xpath('//*[@id="content"]/h1/span[1]'):
       
daoyan = response.xpath('//*[@id="info"]/span[1]/span[2]/a/text()').get()
        biaoju = response.xpath('//*[@id="info"]/span[2]/span[2]/a/text()').get()
        zhuyan = response.xpath('//*[@id="info"]/span[3]/span[2]/span/a/text()').get()
        leixing = response.xpath('//*[@id="info"]/span/text()').get()
        shangyintime = response.xpath('//*[@id="info"]/span[10]/text()').get()
        pianchang = response.xpath('//*[@id="info"]/span[13]/text()').get()
        pingfenRshu = response.xpath('//*[@id="interest_sectl"]/div[1]/div[2]/div/div[2]/a/text()').get()
        juqingjiejia = response.xpath('//*[@id="link-report-intra"]/span[1]/span/text()').get()
        print(daoyan, biaoju, zhuyan, leixing, shangyintime, pianchang, pingfenRshu, juqingjiejia)
        item = DouBanprojectItem()

        # item['no'] = no
        # item['name'] = name
       
item['daoyan'] = daoyan
        item['biaoju'] = biaoju
        item['zhuyan'] = zhuyan
        item['shangyintime'] = shangyintime
        item['pianchang'] = pianchang
        item['pianchang'] = pianchang
        item['pingfenRshu'] = pingfenRshu
        item['juqingjiejia'] = juqingjiejia
        yield item







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