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2509165008
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# 此目录用于存放学生提交的文件，请勿删除
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102
q2_1_crawler/move.html
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102
q2_1_crawler/move.html
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[
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{
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"id": "1",
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"title": "泰坦尼克号",
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"director": "Frank Darabont",
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"year": "2015",
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"rating": "6.8",
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"duration": "91",
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"genre": "科幻",
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"actors_count": "3"
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},
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{
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"id": "2",
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"title": "星际穿越",
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"director": "陈凯歌",
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"year": "2021",
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"rating": "6.2",
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"duration": "113",
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"genre": "科幻",
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"actors_count": "2"
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},
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{
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"id": "3",
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"title": "三傻大闹宝莱坞",
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"director": "Robert Zemeckis",
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"year": "2004",
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"rating": "7.4",
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"duration": "95",
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"genre": "悬疑",
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"actors_count": "4"
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},
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{
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"id": "4",
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"title": "阿甘正传",
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"director": "James Cameron",
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"year": "2013",
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"rating": "6.9",
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"duration": "93",
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"genre": "爱情",
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"actors_count": "4"
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},
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{
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"id": "5",
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"title": "放牛班的春天",
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"director": "宫崎骏",
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"year": "2005",
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"rating": "7.1",
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"duration": "127",
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"genre": "悬疑",
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"actors_count": "3"
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},
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{
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"id": "6",
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"title": "千与千寻",
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"director": "Christopher Nolan",
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"year": "2024",
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"rating": "6.4",
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"duration": "147",
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"genre": "动画",
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"actors_count": "3"
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},
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{
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"id": "7",
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"title": "忠犬八公的故事",
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"director": "Lasse Hallström",
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"year": "2002",
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"rating": "6.2",
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"duration": "166",
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"genre": "剧情",
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"actors_count": "4"
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},
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{
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"id": "8",
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"title": "霸王别姬",
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"director": "Rajkumar Hirani",
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"year": "2005",
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"rating": "7.9",
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"duration": "149",
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"genre": "冒险",
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"actors_count": "2"
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},
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{
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"id": "9",
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"title": "肖申克的救赎",
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"director": "Christophe Barratier",
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"year": "2008",
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"rating": "9.3",
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"duration": "91",
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"genre": "冒险",
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"actors_count": "2"
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},
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{
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"id": "10",
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"title": "盗梦空间",
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"director": "Christopher Nolan",
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"year": "2019",
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"rating": "7.1",
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"duration": "132",
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"genre": "剧情",
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"actors_count": "5"
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}
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]
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102
q2_1_crawler/movie.json
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102
q2_1_crawler/movie.json
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[
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{
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"id": "1",
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"title": "泰坦尼克号",
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"director": "Frank Darabont",
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"year": "2015",
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"rating": "6.8",
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"duration": "91",
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"genre": "科幻",
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"actors_count": "3"
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},
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{
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"id": "2",
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"title": "星际穿越",
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"director": "陈凯歌",
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"year": "2021",
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"rating": "6.2",
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"duration": "113",
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"genre": "科幻",
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"actors_count": "2"
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},
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{
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"id": "3",
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"title": "三傻大闹宝莱坞",
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"director": "Robert Zemeckis",
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"year": "2004",
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"rating": "7.4",
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"duration": "95",
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"genre": "悬疑",
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"actors_count": "4"
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},
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{
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"id": "4",
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"title": "阿甘正传",
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"director": "James Cameron",
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"year": "2013",
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"rating": "6.9",
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"duration": "93",
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"genre": "爱情",
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"actors_count": "4"
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},
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{
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"id": "5",
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"title": "放牛班的春天",
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"director": "宫崎骏",
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"year": "2005",
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"rating": "7.1",
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"duration": "127",
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"genre": "悬疑",
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"actors_count": "3"
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},
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{
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"id": "6",
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"title": "千与千寻",
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"director": "Christopher Nolan",
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"year": "2024",
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"rating": "6.4",
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"duration": "147",
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"genre": "动画",
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"actors_count": "3"
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},
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{
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"id": "7",
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"title": "忠犬八公的故事",
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"director": "Lasse Hallström",
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"year": "2002",
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"rating": "6.2",
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"duration": "166",
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"genre": "剧情",
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"actors_count": "4"
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},
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{
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"id": "8",
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"title": "霸王别姬",
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"director": "Rajkumar Hirani",
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"year": "2005",
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"rating": "7.9",
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"duration": "149",
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"genre": "冒险",
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"actors_count": "2"
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},
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{
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"id": "9",
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"title": "肖申克的救赎",
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"director": "Christophe Barratier",
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"year": "2008",
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"rating": "9.3",
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"duration": "91",
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"genre": "冒险",
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"actors_count": "2"
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},
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{
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"id": "10",
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"title": "盗梦空间",
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"director": "Christopher Nolan",
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"year": "2019",
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"rating": "7.1",
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"duration": "132",
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"genre": "剧情",
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"actors_count": "5"
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}
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]
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65
q2_1_crawler/q2_1.py
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65
q2_1_crawler/q2_1.py
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import requests
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from bs4 import BeautifulSoup as bs
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import json
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url = 'https://exam.detr.top/exam-b/movies'
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headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/149.0.0.0 Safari/537.36 Edg/149.0.0.0',
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'Referer':'https://exam.detr.top/exam-b/movies'}
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req = requests.get(url, headers=headers)
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req.encoding="utf-8"
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data=[]
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soup=bs(req.text,"html.parser")
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# print(soup)
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#id, title, director, year, rating, duration, genre, actors_count
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item=soup.select("table tbody tr" )
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movie_list=[]
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for tr in item:
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tds=tr.find_all("td")
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tds=list(tds)
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# print(tds)
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if len(tds)<8:
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continue
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movie={
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"id":tds[0].get_text(strip=True),
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"title":tds[1].get_text(strip=True),
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"director":tds[2].get_text(strip=True),
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"year":tds[3].get_text(strip=True),
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"rating":tds[4].get_text(strip=True),
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"duration":tds[5].get_text(strip=True),
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"genre":tds[6].get_text(strip=True),
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"actors_count":tds[7].get_text(strip=True)
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}
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movie_list.append(movie)
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print(movie_list)
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with open('movie.json', 'w', encoding='utf-8') as f:
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json.dump(movie_list, f, ensure_ascii=False, indent=2)
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with open("move.html","w",encoding='utf-8') as f:
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json.dump(movie_list, f, ensure_ascii=False, indent=2)
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# for i in range(len(items)):
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# rank=i+1
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# title=items[i].find("span",class_="title").get_text()
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# actors=items[i].find("div",class_="bd").get_text().strip()
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# try:
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# actors=actors.split("主演：")[1].split("\n")[0]
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# except:
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# actors="无"
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# quote=items[i].find("p",class_="quote").get_text().strip()
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# data.append({
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# "rank":rank,
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# "title":title,
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# "actors":actors,
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# "quote":quote
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# })
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43
q2_1_crawler/q2_2.py
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43
q2_1_crawler/q2_2.py
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# ① 找出评分最高和最低的电影，打印电影名 + 评分。
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# ② 统计各类型的电影数量，用字典格式输出。
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# ③ 统计各导演的电影数量，用字典格式输出。
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# ④ 统计 2020 年（含）以后上映的电影数量。
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import json
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with open('movie.json', 'r', encoding='utf-8') as f:
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data=json.load(f)
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# print(data)
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sort_movie=sorted(data,key=lambda x:x["rating"])
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min=sort_movie[0]
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max=sort_movie[-1]
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print("评分最低的电影",min["title"],min["rating"])
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print("评分最高的电影",max["title"],max["rating"])
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genre_shu={}
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for g in data:
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ge=g["genre"]
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if ge in genre_shu:
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genre_shu[ge]+=1
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else:
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genre_shu[ge]=1
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print("各类型的电影数量",genre_shu)
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director_shu={}
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for d in data:
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di=d["director"]
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if di in director_shu:
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director_shu[di]+=1
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else:
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director_shu[di]=1
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print("各导演的电影数量",director_shu)
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a=0
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for y in data:
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if int(y["year"]) >= 2020:
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a+=1
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print("2020 年（含）以后上映的电影数量",a)
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Reference in New Issue
Block a user