使用requests + Xpath抓取豆瓣电影数据 |
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使用requests + Xpath抓取豆瓣电影数据#
Xpath 即为 XML 路径语言（XML Path Language），它是一种用来确定 XML 文档中某部分位置的语言。 Xpath 基于 XML 的树状结构，提供在数据结构树中找寻节点的能力。起初 Xpath 的提出的初衷是将其作为一个通用的、介于 Xpointer 与 XSL 间的语法模型。但是Xpath 很快的被开发者采用来当作小型查询语言。 获取元素的Xpath信息并获得文本： 这里的“元素的Xpath信息”是需要我们手动获取的，获取方式为： 定位目标元素 在网站上依次点击：右键 > 检查 copy xpath xpath + ‘/text()’ 参考：https://mp.weixin.qq.com/s/zx3_eflBCrrfOqFEWjAUJw import requests from lxml import etree url = 'https://movie.douban.com/subject/26611804/' requests.get(url)如果不加headers，响应状态：418， 正常返回状态应该是 200 418啥意思？就是你爬取的网站有反爬虫机制，我们要向服务器发出爬虫请求，需要添加请求头：headers 如何加请求头headers? 网页右键“检查元素”-Network-Doc 如上图 import requests from lxml import etree url = 'https://movie.douban.com/subject/26611804/' headers ={'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.183 Safari/537.36'} data = requests.get(url, headers = headers).text s = etree.HTML(data)豆瓣电影的名称对应的的xpath为xpath_title，那么title表达为： title = s.xpath('xpath_info/text()') 其中，xpath_info为： //*[@id="content"]/h1/span[1] title = s.xpath('//*[@id="content"]/h1/span[1]/text()')[0] director = s.xpath('//*[@id="info"]/span[1]/span[2]/a/text()') actors = s.xpath('//*[@id="info"]/span[3]/span[2]/a/text()') type1 = s.xpath('//*[@id="info"]/span[5]/text()') type2 = s.xpath('//*[@id="info"]/span[6]/text()') type3 = s.xpath('//*[@id="info"]/span[7]/text()') time = s.xpath('//*[@id="info"]/span[11]/text()') length = s.xpath('//*[@id="info"]/span[13]/text()') score = s.xpath('//*[@id="interest_sectl"]/div[1]/div[2]/strong/text()')[0] print(title, director, actors, type1, type2, type3, time, length, score) 三块广告牌 Three Billboards Outside Ebbing, Missouri ['马丁·麦克唐纳'] ['弗兰西斯·麦克多蒙德', '伍迪·哈里森', '山姆·洛克威尔', '艾比·考尼什', '卢卡斯·赫奇斯', '彼特·丁拉基', '约翰·浩克斯', '卡赖伯·兰德里·琼斯', '凯瑟琳·纽顿', '凯瑞·康顿', '泽利科·伊万内克', '萨玛拉·维文', '克拉克·彼得斯', '尼克·瑟西', '阿曼达·沃伦', '玛拉雅·瑞沃拉·德鲁 ', '布兰登·萨克斯顿', '迈克尔·艾伦·米利甘'] ['剧情'] ['犯罪'] ['官方网站:'] ['2018-03-02(中国大陆)'] ['2017-12-01(美国)'] 8.7 Douban API#https://developers.douban.com/wiki/?title=guide https://github.com/computational-class/douban-api-docs # import requests # # https://movie.douban.com/subject/26611804/ # url = 'https://api.douban.com/v2/movie/subject/26611804?apikey=0b2bdeda43b5688921839c8ecb20399b&start=0&count=20&client=&udid=' # jsonm = requests.get(url).json() jsonm.keys() dict_keys(['msg', 'code', 'request']) jsonm['msg'] 'invalid_credencial2' #jsonm.values() jsonm['rating'] (dict_keys(['schedule_url', 'title', 'aka', 'photos_count', 'languages', 'year', 'tags', 'blooper_urls', 'images', 'trailers', 'popular_reviews', 'videos', 'summary', 'clip_urls', 'do_count', 'comments_count', 'has_ticket', 'ratings_count', 'countries', 'has_video', 'collect_count', 'wish_count', 'writers', 'directors', 'id', 'mainland_pubdate', 'popular_comments', 'episodes_count', 'website', 'clips', 'casts', 'genres', 'reviews_count', 'douban_site', 'alt', 'pubdate', 'trailer_urls', 'mobile_url', 'share_url', 'durations', 'seasons_count', 'photos', 'pubdates', 'subtype', 'current_season', 'has_schedule', 'bloopers', 'collection', 'rating', 'original_title']), {'average': 7.5, 'details': {'1': 206.0, '2': 1590.0, '3': 15843.0, '4': 21556.0, '5': 7558.0}, 'max': 10, 'min': 0, 'stars': '40'}) jsonm['alt'] 'https://movie.douban.com/subject/1764796/' jsonm['casts'][0] {'alt': 'https://movie.douban.com/celebrity/1010548/', 'avatars': {'large': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1436865941.42.jpg', 'medium': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1436865941.42.jpg', 'small': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1436865941.42.jpg'}, 'id': '1010548', 'name': '弗兰西斯·麦克多蒙德', 'name_en': 'Frances McDormand'} jsonm['directors'] [{'alt': 'https://movie.douban.com/celebrity/1000304/', 'avatars': {'large': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1406649730.61.jpg', 'medium': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1406649730.61.jpg', 'small': 'https://img3.doubanio.com/view/celebrity/s_ratio_celebrity/public/p1406649730.61.jpg'}, 'id': '1000304', 'name': '马丁·麦克唐纳', 'name_en': 'Martin McDonagh'}] jsonm['genres'] ['剧情', '犯罪'] 作业：抓取豆瓣电影 Top 250# import requests from bs4 import BeautifulSoup from lxml import etree url0 = 'https://movie.douban.com/top250?start=0&filter=' data = requests.get(url0, headers=headers).text s = etree.HTML(data) //*[@id="content"]/div/div[1]/ol/li[1]/div/div[2]/div[1]/a/span[1] /html/body/div[3]/div[1]/div/div[1]/ol/li[1]/div/div[2]/div[1]/a/span[1] str1 = '//*[@id="content"]/div/div[1]/ol/li[' str2 = ']/div/div[2]/div[1]/a/span[1]/text()' xstr_list = [str1 + str(i+1) +str2 for i in range(25)] [s.xpath(i)[0] for i in xstr_list] ['肖申克的救赎', '霸王别姬', '阿甘正传', '这个杀手不太冷', '泰坦尼克号', '美丽人生', '千与千寻', '辛德勒的名单', '盗梦空间', '忠犬八公的故事', '海上钢琴师', '星际穿越', '楚门的世界', '三傻大闹宝莱坞', '机器人总动员', '放牛班的春天', '大话西游之大圣娶亲', '熔炉', '疯狂动物城', '无间道', '教父', '龙猫', '当幸福来敲门', '怦然心动', '触不可及'] s.xpath('//*[@id="content"]/div/div[1]/ol/li[1]/div/div[2]/div[1]/a/span[1]/text()')[0] '肖申克的救赎' s.xpath('//*[@id="content"]/div/div[1]/ol/li[2]/div/div[2]/div[1]/a/span[1]/text()')[0] '霸王别姬' s.xpath('//*[@id="content"]/div/div[1]/ol/li[3]/div/div[2]/div[1]/a/span[1]/text()')[0] '这个杀手不太冷' import requests from bs4 import BeautifulSoup url0 = 'https://movie.douban.com/top250?start=0&filter=' data = requests.get(url0, headers = headers).text soup = BeautifulSoup(data, 'lxml') movies = soup.find_all('div', {'class', 'info'}) len(movies) 25 movies[0].a['href'] 'https://movie.douban.com/subject/1292052/' movies[0].find('span', {'class', 'title'}).text '肖申克的救赎' movies[0].find('div', {'class', 'star'}) 9.7 2349702人评价 movies[0].find('span', {'class', 'rating_num'}).text '9.7' people_num = movies[0].find('div', {'class', 'star'}).find_all('span')[-1] people_num.text.split('人评价')[0] '2349702' for i in movies: url = i.a['href'] title = i.find('span', {'class', 'title'}).text des = i.find('div', {'class', 'star'}) rating = des.find('span', {'class', 'rating_num'}).text rating_num = des.find_all('span')[-1].text.split('人评价')[0] print(url, title, rating, rating_num) https://movie.douban.com/subject/1292052/ 肖申克的救赎 9.7 2349702 https://movie.douban.com/subject/1291546/ 霸王别姬 9.6 1748540 https://movie.douban.com/subject/1292720/ 阿甘正传 9.5 1769679 https://movie.douban.com/subject/1295644/ 这个杀手不太冷 9.4 1944460 https://movie.douban.com/subject/1292722/ 泰坦尼克号 9.4 1731080 https://movie.douban.com/subject/1292063/ 美丽人生 9.5 1089008 https://movie.douban.com/subject/1291561/ 千与千寻 9.4 1846954 https://movie.douban.com/subject/1295124/ 辛德勒的名单 9.5 903524 https://movie.douban.com/subject/3541415/ 盗梦空间 9.3 1709013 https://movie.douban.com/subject/3011091/ 忠犬八公的故事 9.4 1173854 https://movie.douban.com/subject/1889243/ 星际穿越 9.3 1381846 https://movie.douban.com/subject/1292064/ 楚门的世界 9.3 1297696 https://movie.douban.com/subject/1292001/ 海上钢琴师 9.3 1388360 https://movie.douban.com/subject/3793023/ 三傻大闹宝莱坞 9.2 1560202 https://movie.douban.com/subject/2131459/ 机器人总动员 9.3 1097784 https://movie.douban.com/subject/1291549/ 放牛班的春天 9.3 1081510 https://movie.douban.com/subject/1292213/ 大话西游之大圣娶亲 9.2 1262613 https://movie.douban.com/subject/25662329/ 疯狂动物城 9.2 1526196 https://movie.douban.com/subject/1307914/ 无间道 9.2 1050879 https://movie.douban.com/subject/5912992/ 熔炉 9.3 766645 https://movie.douban.com/subject/1291841/ 教父 9.3 768085 https://movie.douban.com/subject/1849031/ 当幸福来敲门 9.1 1253991 https://movie.douban.com/subject/1291560/ 龙猫 9.2 1045985 https://movie.douban.com/subject/3319755/ 怦然心动 9.1 1482767 https://movie.douban.com/subject/1296141/ 控方证人 9.6 367459 for i in range(0, 250, 25): print('https://movie.douban.com/top250?start=%d&filter='% i) https://movie.douban.com/top250?start=0&filter= https://movie.douban.com/top250?start=25&filter= https://movie.douban.com/top250?start=50&filter= https://movie.douban.com/top250?start=75&filter= https://movie.douban.com/top250?start=100&filter= https://movie.douban.com/top250?start=125&filter= https://movie.douban.com/top250?start=150&filter= https://movie.douban.com/top250?start=175&filter= https://movie.douban.com/top250?start=200&filter= https://movie.douban.com/top250?start=225&filter= import requests from bs4 import BeautifulSoup dat = [] for j in range(0, 250, 25): urli = 'https://movie.douban.com/top250?start=%d&filter='% j print(urli) data = requests.get(urli, headers = headers).text soup = BeautifulSoup(data, 'lxml') movies = soup.find_all('div', {'class', 'info'}) for i in movies: url = i.a['href'] title = i.find('span', {'class', 'title'}).text des = i.find('div', {'class', 'star'}) rating = des.find('span', {'class', 'rating_num'}).text rating_num = des.find_all('span')[-1].text.split('人评价')[0] listi = [url, title, rating, rating_num] dat.append(listi) https://movie.douban.com/top250?start=0&filter= https://movie.douban.com/top250?start=25&filter= https://movie.douban.com/top250?start=50&filter= https://movie.douban.com/top250?start=75&filter= https://movie.douban.com/top250?start=100&filter= https://movie.douban.com/top250?start=125&filter= https://movie.douban.com/top250?start=150&filter= https://movie.douban.com/top250?start=175&filter= https://movie.douban.com/top250?start=200&filter= https://movie.douban.com/top250?start=225&filter= import pandas as pd df = pd.DataFrame(dat, columns = ['url', 'title', 'rating', 'rating_num']) df['rating'] = df.rating.astype(float) df['rating_num'] = df.rating_num.astype(int) df.head() url title rating rating_num 0 https://movie.douban.com/subject/1292052/ 肖申克的救赎 9.7 2349702 1 https://movie.douban.com/subject/1291546/ 霸王别姬 9.6 1748540 2 https://movie.douban.com/subject/1292720/ 阿甘正传 9.5 1769679 3 https://movie.douban.com/subject/1295644/ 这个杀手不太冷 9.4 1944460 4 https://movie.douban.com/subject/1292722/ 泰坦尼克号 9.4 1731080 import matplotlib.pyplot as plt plt.hist(df.rating_num) plt.show() plt.hist(df.rating) plt.show() # viz plt.style.use('ggplot') fig = plt.figure(figsize=(16, 16),facecolor='white') plt.plot(df.rating_num, df.rating, 'bo') for i in df.index: plt.text(df.rating_num[i], df.rating[i], df.title[i], fontsize = df.rating[i], color = 'red', rotation = 45) plt.show() df[df.rating > 9.4] url title rating rating_num 0 https://movie.douban.com/subject/1292052/ 肖申克的救赎 9.6 1004428 1 https://movie.douban.com/subject/1291546/ 霸王别姬 9.5 730274 4 https://movie.douban.com/subject/1292063/ 美丽人生 9.5 469332 41 https://movie.douban.com/subject/1296141/ 控方证人 9.6 108598 alist = [] for i in df.index: alist.append( [df.rating_num[i], df.rating[i], df.title[i] ]) blist =[[df.rating_num[i], df.rating[i], df.title[i] ] for i in df.index] alist [[1021383, 9.5999999999999996, '肖申克的救赎'], [742984, 9.5, '霸王别姬'], [957578, 9.4000000000000004, '这个杀手不太冷'], [814634, 9.4000000000000004, '阿甘正传'], [475813, 9.5, '美丽人生'], [762619, 9.3000000000000007, '千与千寻'], [754309, 9.3000000000000007, '泰坦尼克号'], [433191, 9.4000000000000004, '辛德勒的名单'], [853620, 9.3000000000000007, '盗梦空间'], [559729, 9.3000000000000007, '机器人总动员'], [657670, 9.1999999999999993, '海上钢琴师'], [767473, 9.1999999999999993, '三傻大闹宝莱坞'], [529473, 9.1999999999999993, '忠犬八公的故事'], [513071, 9.1999999999999993, '放牛班的春天'], [561091, 9.1999999999999993, '大话西游之大圣娶亲'], [533017, 9.0999999999999996, '楚门的世界'], [473631, 9.0999999999999996, '龙猫'], [385130, 9.1999999999999993, '教父'], [309138, 9.1999999999999993, '熔炉'], [560855, 9.1999999999999993, '星际穿越'], [299301, 9.1999999999999993, '乱世佳人'], [416073, 9.0999999999999996, '触不可及'], [458107, 9.0, '无间道'], [606767, 8.9000000000000004, '当幸福来敲门'], [337952, 9.0999999999999996, '天堂电影院'], [633995, 8.9000000000000004, '怦然心动'], [190977, 9.4000000000000004, '十二怒汉'], [434420, 9.0, '搏击俱乐部'], [640800, 9.0, '少年派的奇幻漂流'], [260089, 9.1999999999999993, '鬼子来了'], [367866, 9.0999999999999996, '蝙蝠侠：黑暗骑士'], [314885, 9.0999999999999996, '指环王3：王者无敌'], [306344, 9.0999999999999996, '活着'], [369956, 9.0, '天空之城'], [585740, 9.1999999999999993, '疯狂动物城'], [426150, 8.9000000000000004, '罗马假日'], [451703, 8.9000000000000004, '大话西游之月光宝盒'], [554642, 8.9000000000000004, '飞屋环游记'], [249586, 9.0999999999999996, '窃听风暴'], [296760, 9.0999999999999996, '两杆大烟枪'], [111737, 9.5999999999999996, '控方证人'], [301329, 9.0, '飞越疯人院'], [358755, 8.9000000000000004, '闻香识女人'], [393556, 8.9000000000000004, '哈尔的移动城堡'], [196094, 9.3000000000000007, '海豚湾'], [464601, 8.8000000000000007, 'V字仇杀队'], [237421, 9.0999999999999996, '辩护人'], [309071, 9.0, '死亡诗社'], [207619, 9.0999999999999996, '教父2'], [333942, 8.9000000000000004, '美丽心灵'], [296196, 9.0, '指环王2：双塔奇兵'], [331529, 8.9000000000000004, '指环王1：魔戒再现'], [411534, 8.8000000000000007, '情书'], [223469, 9.0999999999999996, '饮食男女'], [517803, 9.0999999999999996, '摔跤吧！爸爸'], [191667, 9.0999999999999996, '美国往事'], [309325, 8.9000000000000004, '狮子王'], [220420, 9.0, '钢琴家'], [520325, 8.6999999999999993, '天使爱美丽'], [205704, 9.0999999999999996, '素媛'], [469032, 8.6999999999999993, '七宗罪'], [153673, 9.1999999999999993, '小鞋子'], [320506, 8.9000000000000004, '被嫌弃的松子的一生'], [375951, 8.8000000000000007, '致命魔术'], [378652, 8.8000000000000007, '看不见的客人'], [251308, 8.9000000000000004, '音乐之声'], [315215, 8.8000000000000007, '勇敢的心'], [523686, 8.6999999999999993, '剪刀手爱德华'], [425844, 8.8000000000000007, '本杰明·巴顿奇事'], [365086, 8.8000000000000007, '低俗小说'], [385562, 8.6999999999999993, '西西里的美丽传说'], [307307, 8.8000000000000007, '黑客帝国'], [262404, 8.9000000000000004, '拯救大兵瑞恩'], [383825, 8.6999999999999993, '沉默的羔羊'], [338488, 8.8000000000000007, '入殓师'], [414361, 8.6999999999999993, '蝴蝶效应'], [677352, 8.6999999999999993, '让子弹飞'], [270494, 8.8000000000000007, '春光乍泄'], [244643, 8.9000000000000004, '玛丽和马克思'], [111733, 9.1999999999999993, '大闹天宫'], [295606, 8.8000000000000007, '心灵捕手'], [189568, 8.9000000000000004, '末代皇帝'], [292721, 8.8000000000000007, '阳光灿烂的日子'], [254400, 8.8000000000000007, '幽灵公主'], [252833, 8.8000000000000007, '第六感'], [359281, 8.6999999999999993, '重庆森林'], [389844, 8.6999999999999993, '禁闭岛'], [345885, 8.8000000000000007, '布达佩斯大饭店'], [271656, 8.6999999999999993, '大鱼'], [142601, 9.0, '狩猎'], [284871, 8.6999999999999993, '哈利·波特与魔法石'], [296911, 8.6999999999999993, '射雕英雄传之东成西就'], [344355, 8.5999999999999996, '致命ID'], [248165, 8.8000000000000007, '甜蜜蜜'], [344588, 8.5999999999999996, '断背山'], [251749, 8.6999999999999993, '猫鼠游戏'], [166973, 8.9000000000000004, '一一'], [367791, 8.6999999999999993, '告白'], [289385, 8.8000000000000007, '阳光姐妹淘'], [373118, 8.5999999999999996, '加勒比海盗'], [166903, 8.9000000000000004, '上帝之城'], [97659, 9.1999999999999993, '摩登时代'], [162190, 8.9000000000000004, '穿条纹睡衣的男孩'], [565530, 8.5999999999999996, '阿凡达'], [237864, 8.6999999999999993, '爱在黎明破晓前'], [385266, 8.6999999999999993, '消失的爱人'], [188690, 8.8000000000000007, '风之谷'], [212467, 8.6999999999999993, '爱在日落黄昏时'], [181917, 8.8000000000000007, '侧耳倾听'], [275127, 8.5999999999999996, '倩女幽魂'], [146507, 8.9000000000000004, '红辣椒'], [241887, 8.6999999999999993, '恐怖直播'], [185888, 8.8000000000000007, '超脱'], [217398, 8.6999999999999993, '萤火虫之墓'], [304866, 8.6999999999999993, '驯龙高手'], [239308, 8.5999999999999996, '幸福终点站'], [195650, 8.6999999999999993, '菊次郎的夏天'], [144405, 8.9000000000000004, '小森林 夏秋篇'], [341432, 8.5, '喜剧之王'], [323425, 8.5999999999999996, '岁月神偷'], [232077, 8.6999999999999993, '借东西的小人阿莉埃蒂'], [82623, 9.1999999999999993, '七武士'], [405200, 8.5, '神偷奶爸'], [222549, 8.6999999999999993, '杀人回忆'], [102681, 9.0, '海洋'], [332455, 8.5, '真爱至上'], [210611, 8.6999999999999993, '电锯惊魂'], [415291, 8.5, '贫民窟的百万富翁'], [191225, 8.6999999999999993, '谍影重重3'], [149579, 8.8000000000000007, '喜宴'], [266681, 8.5999999999999996, '东邪西毒'], [295660, 8.5, '记忆碎片'], [220414, 8.5999999999999996, '雨人'], [257769, 8.5999999999999996, '怪兽电力公司'], [440539, 8.5, '黑天鹅'], [391224, 8.6999999999999993, '疯狂原始人'], [179698, 8.6999999999999993, '英雄本色'], [154659, 8.6999999999999993, '燃情岁月'], [127219, 8.8000000000000007, '卢旺达饭店'], [112345, 8.9000000000000004, '虎口脱险'], [189074, 8.6999999999999993, '7号房的礼物'], [300454, 8.5, '恋恋笔记本'], [125724, 8.9000000000000004, '小森林 冬春篇'], [320997, 8.5, '傲慢与偏见'], [208380, 8.5999999999999996, '海边的曼彻斯特'], [290089, 8.6999999999999993, '哈利·波特与死亡圣器(下)'], [168987, 8.6999999999999993, '萤火之森'], [138798, 8.8000000000000007, '教父3'], [86319, 9.0, '完美的世界'], [156471, 8.6999999999999993, '纵横四海'], [151799, 8.8000000000000007, '荒蛮故事'], [105774, 8.8000000000000007, '二十二'], [135526, 8.8000000000000007, '魂断蓝桥'], [259388, 8.5, '猜火车'], [194663, 8.5999999999999996, '穿越时空的少女'], [201714, 8.8000000000000007, '玩具总动员3'], [260957, 8.5, '花样年华'], [97486, 9.0, '雨中曲'], [183786, 8.5999999999999996, '心迷宫'], [214531, 8.5999999999999996, '时空恋旅人'], [351836, 8.4000000000000004, '唐伯虎点秋香'], [392857, 8.5999999999999996, '超能陆战队'], [110358, 8.8000000000000007, '我是山姆'], [309924, 8.5999999999999996, '蝙蝠侠：黑暗骑士崛起'], [199924, 8.5999999999999996, '人工智能'], [139242, 8.6999999999999993, '浪潮'], [285601, 8.4000000000000004, '冰川时代'], [289504, 8.4000000000000004, '香水'], [288650, 8.5, '朗读者'], [132226, 8.6999999999999993, '罗生门'], [174301, 8.8000000000000007, '请以你的名字呼唤我'], [251364, 8.5999999999999996, '爆裂鼓手'], [85770, 8.9000000000000004, '追随'], [138571, 8.6999999999999993, '一次别离'], [104317, 8.8000000000000007, '未麻的部屋'], [181166, 8.5999999999999996, '撞车'], [334741, 8.6999999999999993, '血战钢锯岭'], [135259, 8.6999999999999993, '可可西里'], [182221, 8.5, '战争之王'], [343703, 8.3000000000000007, '恐怖游轮'], [89868, 8.8000000000000007, '地球上的星星'], [116667, 8.6999999999999993, '梦之安魂曲'], [176988, 8.6999999999999993, '达拉斯买家俱乐部'], [270993, 8.5999999999999996, '被解救的姜戈'], [192717, 8.5, '阿飞正传'], [112326, 8.6999999999999993, '牯岭街少年杀人事件'], [200329, 8.5, '谍影重重'], [166328, 8.5, '谍影重重2'], [204653, 8.5, '魔女宅急便'], [240090, 8.6999999999999993, '头脑特工队'], [164479, 8.8000000000000007, '房间'], [63374, 9.0, '忠犬八公物语'], [87474, 8.9000000000000004, '惊魂记'], [110499, 8.6999999999999993, '碧海蓝天'], [179269, 8.5, '再次出发之纽约遇见你'], [231647, 8.4000000000000004, '青蛇'], [157071, 8.5999999999999996, '小萝莉的猴神大叔'], [53476, 9.1999999999999993, '东京物语'], [312322, 8.3000000000000007, '秒速5厘米'], [84575, 8.9000000000000004, '哪吒闹海'], [109454, 8.6999999999999993, '末路狂花'], [169778, 8.5999999999999996, '海盗电台'], [111040, 8.6999999999999993, '绿里奇迹'], [147035, 8.5999999999999996, '终结者2：审判日'], [424177, 8.3000000000000007, '源代码'], [267159, 8.5999999999999996, '模仿游戏'], [192005, 8.5, '新龙门客栈'], [162903, 8.5, '黑客帝国3：矩阵革命'], [147043, 8.5, '勇闯夺命岛'], [189831, 8.5, '这个男人来自地球'], [125973, 8.6999999999999993, '一个叫欧维的男人决定去死'], [129304, 8.5999999999999996, '卡萨布兰卡'], [494602, 8.4000000000000004, '你的名字。'], [46323, 9.1999999999999993, '城市之光'], [221714, 8.4000000000000004, '变脸'], [132083, 8.5999999999999996, '荒野生存'], [53099, 9.0999999999999996, '迁徙的鸟'], [159426, 8.5, 'E.T. 外星人'], [192409, 8.4000000000000004, '发条橙'], [231469, 8.4000000000000004, '无耻混蛋'], [479894, 8.3000000000000007, '初恋这件小事'], [53709, 9.0999999999999996, '黄金三镖客'], [191992, 8.4000000000000004, '美国丽人'], [121427, 8.8000000000000007, '爱在午夜降临前'], [178607, 8.4000000000000004, '英国病人'], [60049, 9.0, '无人知晓'], [110300, 8.5999999999999996, '燕尾蝶'], [120585, 8.5999999999999996, '非常嫌疑犯'], [328162, 8.3000000000000007, '疯狂的石头'], [112286, 8.5999999999999996, '叫我第一名'], [90201, 8.9000000000000004, '勇士'], [242926, 8.3000000000000007, '穆赫兰道'], [190730, 8.5999999999999996, '无敌破坏王'], [352129, 8.3000000000000007, '国王的演讲'], [77399, 8.8000000000000007, '步履不停'], [137843, 8.5, '血钻'], [99101, 8.5999999999999996, '上帝也疯狂'], [186988, 8.4000000000000004, '彗星来的那一夜'], [103282, 8.5999999999999996, '枪火'], [278772, 8.3000000000000007, '蓝色大门'], [97025, 8.5999999999999996, '大卫·戈尔的一生'], [134046, 8.5, '遗愿清单'], [59825, 9.0, '我爱你'], [89377, 8.6999999999999993, '千钧一发'], [139223, 8.5, '荒岛余生'], [48744, 9.0, '爱·回家'], [119390, 8.5, '黑鹰坠落'], [131277, 8.8000000000000007, '聚焦'], [131618, 8.5, '麦兜故事'], [148685, 8.4000000000000004, '暖暖内含光']] # from IPython.display import display_html, HTML # HTML('') 作业：#抓取复旦新媒体微信公众号最新一期的内容 requests.post模拟登录豆瓣（包括获取验证码）#https://blog.csdn.net/zhuzuwei/article/details/80875538 |
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