1.爬取豆瓣前250部电影

由于电豆瓣电影中一共存在250部电影，需要进行分页，每隔25进行一次分页截取。

# 构造分页数字列表
page_indexs = range(0, 250, 25)

headers表头为：

headers={
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 UBrowser/6.2.4098.3 Safari/537.36',
    'Cookie': 'douban-fav-remind=1; bid=xV3mzxZaZxE; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1558577880%2C%22https%3A%2F%2Fwww.baidu.com%2Flink%3Furl%3DV45iHCRmrzprwRNYFC4Tj2b6lo3J1MbSYFIzkgsyd9EERM6EE6OIaTGDe9z7NaJj%26wd%3D%26eqid%3Db8eae7580058b189000000025ce602d1%22%5D; _pk_id.100001.4cf6=cf9fd67f-eed2-4398-a10d-333daee6b8b7.1558577880.1.1558577880.1558577880.; _pk_ses.100001.4cf6=*; __utma=30149280.1353623796.1524120262.1556333363.1558577881.8; __utmb=30149280.0.10.1558577881; __utmc=30149280; __utmz=30149280.1558577881.8.7.utmcsr=baidu|utmccn=(organic)|utmcmd=organic; __utma=223695111.2144420921.1558577881.1558577881.1558577881.1; __utmb=223695111.0.10.1558577881; __utmc=223695111; __utmz=223695111.1558577881.1.1.utmcsr=baidu|utmccn=(organic)|utmcmd=organic'
}

信息都存在于div.info中，使用response读取数据，以列表形式读取存储到lists，其中包括了name,year,country,category,star,people_num的信息 。其中详细的演员信息需要单独读取。

def get_movie_list(url,headers):
    soup = requests.get(url,headers=headers)
    response = BeautifulSoup(soup.text,'lxml')
    lists = response.select('div.info')
    datas = []
    for list in lists:
        sing_url =list.select('a')[0].get('href')
        name =list.select('div.hd .title')[0].text
        type_list = list.select('div.bd p')[0].text.strip('').split('...')[-1].replace(' ','').split('/')
        year =''.join(type_list[0].split())
        country = ''.join(type_list[1].split())
        category = ''.join(type_list[2].split())
        star = list.select('div.bd .star .rating_num')[0].text.replace(' ','')
        people_num = list.select('div.bd .star span:nth-of-type(4)')[0].text.split('人')[0]
        data = get_detail_movie(sing_url,name,year,country,category,star,people_num,headers)
        datas.append(data)
    for info in datas:
        if '导' in info['year']:continue
        else:
            print(info)
            mv_mysql.save_data(info)

其中get_detail_movie函数用来单独读取演员信息。

def get_detail_movie(movie_url,name,year,country,category,star,people_num,headers):
    response = requests.get(movie_url,headers = headers)
    soup = BeautifulSoup(response.text,'lxml')
    # daoyan =soup.select('#info > span:nth-of-type(1) > span.attrs')[0].text
    yanyuan =[]
    for i in soup.select('#info > span.actor > span.attrs'):
        yanyuan.append(i.text.replace('/',''))

    list1 =str(yanyuan).replace('[','').replace("'",'').split(' ')
    yanyuan = ' '.join(list1)
    data ={'name':name,
           'year':year,
           'country':country,
           'category':category,
           'star':star,
           'people_num':people_num,
           # 'daoyan':daoyan,
           'yanyuan':yanyuan
           }
    return data

对于信息本文采用mysql数据库存储，采用pymysql，安装比较简单。

import pymysql

首先需要连接到MYSQL数据库中。

#连接MYSQL数据库
db = pymysql.connect("host","usr","password","database" )
cursor = db.cursor()

其中host我选择是自己的主机，usr是你登录mysql数据库用户名，password你的密码，database是你数据库名。
在数据库中建表

def creat_table():
    cursor.execute("DROP TABLE IF EXISTS DBDY_250")
    sql = '''CREATE TABLE DBDY_250(
               name text(5000),
               year VARCHAR(1000),
               country text(5000),
               category text(5000),
               star VARCHAR(1000),
               people_num VARCHAR(1000),
               # daoyan text(5000),
               yanyuan text(5000)
            );'''
    cursor.execute(sql)
    return

建立的表中，表名为DBDY_250，存储爬取到的数据：

#存储爬取到的数据
def save_data(data_dict):
    sql = '''INSERT INTO DBDY_250(name,year,country,category,star,people_num,yanyuan) VALUES(%s,%s,%s,%s,%s,%s,%s)'''
    value_tup = (data_dict['name']
                 ,data_dict['year']
                 ,data_dict['country']
                 ,data_dict['category']
                 ,data_dict['star']
                 ,data_dict['people_num']
                 # ,data_dict['daoyan']
                 ,data_dict['yanyuan']
                 )
    try:
        cursor.execute(sql,value_tup)
        db.commit()
    except:
        print('数据库写入失败')
    return

爬取到的文件格式如下：

后续爬取信息会进行数据分析，可视化分析，可以期待一下。需要代码的在评论区留言哦!谢谢，记得点赞哦。