Python对豆瓣电影Top250并进行数据分析

北山啦

发布于 2022-11-16 18:56:46

4590

发布于 2022-11-16 18:56:46

文章被收录于专栏：北山啦的博客

由于CSDN审核机制，导致原文章无法发出，故修改了相关词汇，并改为两篇问章发布。

数据获取

翻页操作

观察可知，我们只需要修改start参数即可

headers字段

headers中有很多字段，这些字段都有可能会被对方服务器拿过来进行判断是否为爬虫

通过headers中的User-Agent字段来

原理：默认情况下没有User-Agent，而是使用模块默认设置
解决方法：请求之前添加User-Agent即可；更好的方式是使用User-Agent池来解决（收集一堆User-Agent的方式，或者是随机生成User-Agent）

在这里我们只需要添加请求头即可

数据定位

这里我使用的是xpath

# -*- coding: utf-8 -*-
# @Author: Kun
import requests 
from lxml import etree
import pandas as pd
df = []
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4343.0 Safari/537.36',
           'Referer': 'https://movie.douban.com/top250'}
columns = ['排名','电影名称','导演','上映年份','制作国家','类型','评分','评价分数','短评']
def get_data(html):
    xp = etree.HTML(html)
    lis = xp.xpath('//*[@id="content"]/div/div[1]/ol/li')
    for li in lis:
        """排名、标题、导演、演员、"""
        ranks = li.xpath('div/div[1]/em/text()')
        titles = li.xpath('div/div[2]/div[1]/a/span[1]/text()')
        directors = li.xpath('div/div[2]/div[2]/p[1]/text()')[0].strip().replace("\xa0\xa0\xa0","\t").split("\t")
        infos = li.xpath('div/div[2]/div[2]/p[1]/text()')[1].strip().replace('\xa0','').split('/')
        dates,areas,genres = infos[0],infos[1],infos[2]
        ratings = li.xpath('.//div[@class="star"]/span[2]/text()')[0]
        scores = li.xpath('.//div[@class="star"]/span[4]/text()')[0][:-3]
        quotes = li.xpath('.//p[@class="quote"]/span/text()')
        for rank,title,director in zip(ranks,titles,directors):
            if len(quotes) == 0:
                quotes = None
            else:
                quotes = quotes[0]
            df.append([rank,title,director,dates,areas,genres,ratings,scores,quotes])
        d = pd.DataFrame(df,columns=columns)
        d.to_excel('Top250.xlsx',index=False)
for i in range(0,251,25):
    url = "https://movie.douban.com/top250?start={}&filter=".format(str(i))
    res = requests.get(url,headers=headers)
    html = res.text
    get_data(html)

生成的数据保存在Top250.xlsx中。

使用面向对象+线程

# -*- coding: utf-8 -*-
"""
Created on Tue Feb  2 15:19:29 2021

@author: 北山啦
"""
import pandas as pd
import time
import requests
from lxml import etree
from queue import Queue
from threading import Thread, Lock

class Movie():
    def __init__(self):
        self.df = []
        self.headers ={'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4343.0 Safari/537.36',
                       'Referer': 'https://movie.douban.com/top250'}
        self.columns = ['排名','电影名称','导演','上映年份','制作国家','类型','评分','评价分数','短评']
        self.lock = Lock()
        self.url_list = Queue()
    
    def get_url(self):
       url = 'https://movie.douban.com/top250?start={}&filter='
       for i in range(0,250,25):
           self.url_list.put(url.format(str(i)))
    
    def get_html(self):
        while True:
            if not self.url_list.empty():
                url = self.url_list.get()
                resp = requests.get(url,headers=self.headers)
                html = resp.text
                self.xpath_parse(html)
            else:
                break   
    def xpath_parse(self,html):
        xp = etree.HTML(html)
        lis = xp.xpath('//*[@id="content"]/div/div[1]/ol/li')
        for li in lis:
            """排名、标题、导演、演员、"""
            ranks = li.xpath('div/div[1]/em/text()')
            titles = li.xpath('div/div[2]/div[1]/a/span[1]/text()')
            directors = li.xpath('div/div[2]/div[2]/p[1]/text()')[0].strip().replace("\xa0\xa0\xa0","\t").split("\t")
            infos = li.xpath('div/div[2]/div[2]/p[1]/text()')[1].strip().replace('\xa0','').split('/')
            dates,areas,genres = infos[0],infos[1],infos[2]
            ratings = li.xpath('.//div[@class="star"]/span[2]/text()')[0]
            scores = li.xpath('.//div[@class="star"]/span[4]/text()')[0][:-3]
            quotes = li.xpath('.//p[@class="quote"]/span/text()')
            for rank,title,director in zip(ranks,titles,directors):
                if len(quotes) == 0:
                    quotes = None
                else:
                    quotes = quotes[0]
                self.df.append([rank,title,director,dates,areas,genres,ratings,scores,quotes])
            d = pd.DataFrame(self.df,columns=self.columns)
            d.to_excel('douban.xlsx',index=False)
            
            
    def main(self):
        start_time = time.time()
        self.get_url()

        th_list = []
        for i in range(5):
            th = Thread(target=self.get_html)
            th.start()
            th_list.append(th)

        for th in th_list:
            th.join()
        end_time = time.time()
        print(end_time-start_time)
if __name__ == '__main__':
    spider = Movie()
    spider.main()

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原始发表：2022-11-07，如有侵权请联系 cloudcommunity@tencent.com 删除

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