针对河南大学数据结构傻逼学堂在线的自动化脚本

news2025/1/19 20:30:14

首先展示一下我们的答案

{'1': ['对象'], '2': ['关系']}
{'1': ['非数值计算'], '2': ['操作']}
{'1': ['线性表']}
['D']
['B']
['B']
['C']
['C']
{'1': ['操作']}
{'1': ['数据关系', '数据对象上关系的集合']}
{'1': ['性质相同']}
{'1': ['物理结构']}
{'1': ['存储结构', '操作表示']}
['C']
['B']
['D']
['B']
['D']
['true']
['false']
['false']
['false']
['true']
['C']
['B']
['A']
['C']
['D']
['false']
['false']
['false']
['false']
['false']
['C']
['B']
['D']
['A']
['D']
['C']
['B']
['D']
['A']
['A']
{'1': ['栈']}
{'1': ['链栈', '链式栈']}
{'1': ['先进先出']}
{'1': ['队头'], '2': ['队尾']}
['B']
['C']
['C']
['C']
['D']
{'1': ['后进先出']}
{'1': ['具有递归特性的数据结构', '递归的数据结构'], '2': ['可递归求解的问题', '可以递归求解的问题']}
{'1': ['分治法']}
{'1': ['递归部分', '递归步骤']}
['B']
['B']
['C']
['B']
['C']
{'1': ['s, ‘WORKER’, t', 's， ‘WORKER’， t', 's, ‘WORKER’， t', 's， ‘WORKER’, t'], '2': [' ‘GOOD BOY’', 'GOOD BOY']}
{'1': ['模式匹配']}
{'1': ['空串']}
{'1': ['堆式顺序存储结构']}
{'1': ['链式存储']}
['D']
['B']
['A']
['B']
['C']
{'1': ['01122']}
{'1': ['01123']}
{'1': ['数据元素是一个字符', '数据元素是单个字符']}
{'1': ['当前位置']}
{'1': ['7 ']}
['D']
['A']
['B']
['D']
['C']
['B']
['B']
['B']
['D']
['C']
{'1': ['非线性']}
{'1': ['1', '一']}
{'1': ['度']}
{'1': ['最大']}
{'1': ['0', '零']}
{'1': ['1']}
{'1': ['383']}
{'1': ['32']}
{'1': ['9']}
{'1': ['11']}
{'1': ['A'], '2': ['J']}
{'1': ['E'], '2': ['H']}
{'1': ['C']}
['true']
['true']
['false']
['true']
['false']
['A']
['B']
['B']
['C']
['D']
['C']
['C']
['A']
['D']
['B']
{'1': ['空']}
{'1': ['n1-1'], '2': ['n2+n3']}
{'1': ['双亲'], '2': ['孩子兄弟']}
['true']
['false']
['true']
['false']
['true']
{'1': ['叶子']}
{'1': ['6'], '2': ['261']}
{'1': ['2n-1']}
{'1': ['前缀', '最优前缀']}
['A']
['B']
['A']
['B']
['D']
{'1': ['最小']}
{'1': ['贪心算法思想', '贪心算法的思想'], '2': ['动态规划思想', '动态规划的思想']}
{'1': ['Dijkstra'], '2': ['Floyd']}
['D']
['C']
['D']
['C']
['A']
['A']
['C']
['A']
['A']
['B']
{'1': ['静态查找表', '动态查找表'], '2': ['动态查找表', '静态查找表']}
{'1': ['平均查找长度']}
{'1': ['主关键字']}
['C']
['D']
['A']
['A']
['D']
['B']
['C']
['true']
['false']
['C']
['A']
['C']
['true']
['true']
['true']
['true']
['false']
['C']
['D']
['A']
{'1': ['查找']}
{'1': ['内部排序']}
{'1': ['空间效率'], '2': ['稳定性']}
{'1': ['插入排序']}
['false']
['true']
['true']
['false']
['true']
['false']
['true']
['true']
['true']
['false']
['true']
['true']
['false']
['true']
['false']
['true']
['false']
['true']
['false']
['true']
['false']

经过抓包分析

其答案在data.problems[0].user.answer下

而且对于填空题它是answers{}

为此写了一个小的处理

让其可以提取到两类答案

对的这是源码

import requests
j=0
for i in range(3845905,3846006):

    url = f"https://www.xuetangx.com/api/v1/lms/exercise/get_exercise_list/{i}/9357137/"
    headers = {
        "Accept": "application/json, text/plain, */*",
        "Accept-Encoding": "gzip, deflate, br, zstd",
        "Accept-Language": "zh",
        "App-Name": "xtzx",
        "Cache-Control": "no-cache",
        "Content-Type": "application/json",
        "Cookie": "_abfpc=73f3154febe39bed2d1a540a8a94f67551d2d361_2.0; cna=0e5d0ea34bdd926182ad8f3ecbef9aec; mode_type=normal; provider=xuetang; django_language=zh; point={%22point_active%22:true%2C%22platform_task_active%22:true%2C%22learn_task_active%22:true}; 59584271video_seconds=146; 77831809video_seconds=3; login_type=WX; csrftoken=BSJSNDMqRjXmygIMUjRE9kVD1dGetAh5; sessionid=n0ghs2l1c5dct15z0nlzxwztq6qzob92; k=59584271; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%2259584271%22%2C%22first_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E8%87%AA%E7%84%B6%E6%90%9C%E7%B4%A2%E6%B5%81%E9%87%8F%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC%22%2C%22%24latest_referrer%22%3A%22https%3A%2F%2Fwww.bing.com%2F%22%7D%2C%22%24device_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%7D; JG_016f5b1907c3bc045f8f48de1_PV=1718967129887|1718968519390",
        "Django-Language": "zh",
        "Pragma": "no-cache",
        "Priority": "u=1, i",
        # "Referer": "https://www.xuetangx.com/learn/henu08091007584/henu08091007584/19322491/exercise/43306490",

        "Sec-Ch-Ua": "\"Not/A)Brand\";v=\"8\", \"Chromium\";v=\"126\", \"Microsoft Edge\";v=\"126\"",
        "Sec-Ch-Ua-Mobile": "?0",
        "Sec-Ch-Ua-Platform": "\"Windows\"",
        "Sec-Fetch-Dest": "empty",
        "Sec-Fetch-Mode": "cors",
        "Sec-Fetch-Site": "same-origin",
        "Terminal-Type": "web",
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36 Edg/126.0.0.0",
        "X-Client": "web",
        "X-Csrftoken": "BSJSNDMqRjXmygIMUjRE9kVD1dGetAh5",
        "Xtbz": "xt"
    }



    response = requests.get(url, headers=headers)
    data = response.json()

    try:
        anwser_list = data["data"]["problems"]
        j=j+1
        print(j)
    except:
        continue
    for list in anwser_list:
        try:
            print(list["user"]["answer"])
        except:
            print(list["user"]["answers"])

不过需要注意的是，你要F12自己抓包一下

将Cookie和X-Csrftoken搞到，然后沾到对应的请求头上

不过这还没啥

重点是：

自动填答案脚本

from time import sleep
import requests

def promble_get(exce_idd):
    url = f"https://www.xuetangx.com/api/v1/lms/exercise/get_exercise_list/{exce_idd}/9357137/"

    headers = {
        "Accept": "application/json, text/plain, */*",
        "Accept-Encoding": "gzip, deflate, br, zstd",
        "Accept-Language": "zh",
        "App-Name": "xtzx",
        "Cache-Control": "no-cache",
        "Content-Type": "application/json",
        #替换成自己的
        "Cookie": "_abfpc=73f3154febe39bed2d1a540a8a94f67551d2d361_2.0; cna=0e5d0ea34bdd926182ad8f3ecbef9aec; mode_type=normal; provider=xuetang; django_language=zh; point={%22point_active%22:true%2C%22platform_task_active%22:true%2C%22learn_task_active%22:true}; 77831809video_seconds=3; 59584271video_seconds=151; undefinedvideo_seconds=151; login_type=P; csrftoken=dadHEX0qMOTyNfvQbDNd2zm3Fu1VoVtG; sessionid=9ml5t7q958j7rnd03owedypb5ek7oqb5; k=77831809; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%2277831809%22%2C%22first_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E8%87%AA%E7%84%B6%E6%90%9C%E7%B4%A2%E6%B5%81%E9%87%8F%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC%22%2C%22%24latest_referrer%22%3A%22https%3A%2F%2Fwww.bing.com%2F%22%7D%2C%22%24device_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%7D; JG_016f5b1907c3bc045f8f48de1_PV=1718967129887|1718970073104",
        "Django-Language": "zh",
        "Pragma": "no-cache",
        "Priority": "u=1, i",
        "Referer": "https://www.xuetangx.com/learn/henu08091007584/henu08091007584/19322491/exercise/43306308",
        "Sec-Ch-Ua": "\"Not/A)Brand\";v=\"8\", \"Chromium\";v=\"126\", \"Microsoft Edge\";v=\"126\"",
        "Sec-Ch-Ua-Mobile": "?0",
        "Sec-Ch-Ua-Platform": "\"Windows\"",
        "Sec-Fetch-Dest": "empty",
        "Sec-Fetch-Mode": "cors",
        "Sec-Fetch-Site": "same-origin",
        "Terminal-Type": "web",
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36 Edg/126.0.0.0",
        "X-Client": "web",
        #替换成自己的
        "X-Csrftoken": "dadHEX0qMOTyNfvQbDNd2zm3Fu1VoVtG",
        "Xtbz": "xt"
    }

    response = requests.get(url, headers=headers)
    datad = response.json()
    anwerlist = datad["data"]["problems"]
    list = []
    for ll in anwerlist:
        list.append(ll["problem_id"])
    return list

exce_id = [3845905, 3845907, 3845910, 3845913, 3845915, 3845917, 3845920, 3845923, 3845925,
 3845929, 3845931, 3845933, 3845936, 3845939, 3845942, 3845945, 3845948, 3845954,
 3845957, 3845960, 3845962, 3845964, 3845967, 3845970, 3845971, 3845973, 3845976,
 3845979, 3845982, 3845984, 3845987, 3845988, 3845990, 3845991,
    3845992, 3845993,3845995, 3845997,
    3845998, 3845999, 3846000, 3846002, 3846004, 3846005]

leaf_id = [
    43306297,
    43306301,
    43306308,
    43306312,
    43306316,
    43306323,
    43306328,
    43306335,
    43306340,
    43306346,
    43306350,
    43306358,
    43306363,
    43306368,
    43306374,
    43306380,
    43306386,
    43306398,
    43306404,
    43306410,
    43306415,
    43306421,
    43306428,
    43306433,
    43306438,
    43306444,
    43306449,
    43306456,
    43306463,
    43306468,
    43306472,
    43306475,
    43306478,
    43306480,
    43306482,
    43306486,
    43306490,
    43306493,
    43306496,
    43306499,
    43306503,
    43306505,
    43306509,
    43306512
]
data = [
    [1,
     {1: "对象", 2: "关系"},
     {1: "非数值计算", 2: "操作"},
     {1: "线性表"}
    ],
    [2,
     ["D"],
     ["B"],
     ["B"],
     ["C"],
     ["C"]
    ],
    [3,
     {1: "操作"},
     {1: "数据关系,数据对象上关系的集合"},
     {1: "性质相同"},
     {1: "物理结构"},
     {1: "存储结构, 操作表示"}
    ],
    [4,
     ['C'],
     ['B'],
     ['D'],
     ['B'],
     ['D']
    ],
    [5,
     ['true'],
     ['false'],
     ['false'],
     ['false'],
     ['true']
    ],
    [6,
     ['C'],
     ['B'],
     ['A'],
     ['C'],
     ['D']
    ],
    [7,
     ['false'],
     ['false'],
     ['false'],
     ['false'],
     ['false']
    ],
    [8,
     ['C'],
     ['B'],
     ['D'],
     ['A'],
     ['D']
    ],
    [9,
     ['C'],
     ['B'],
     ['D'],
     ['A'],
     ['A']
    ],
    [10,
     {1: "栈"},
     {1: "链栈, 链式栈"},
     {1: "先进先出"},
     {1: "队头", '2': "队尾"}
    ],
    [11,
     ['B'],
     ['C'],
     ['C'],
     ['C'],
     ['D']
    ],
    [12,
     {1: "后进先出"},
     {1: "具有递归特性的数据结构, 递归的数据结构", 2: "可递归求解的问题, 可以递归求解的问题"},
     {1: "分治法"},
     {1: "递归部分, 递归步骤"}
    ],
    [13,
     ['B'],
     ['B'],
     ['C'],
     ['B'],
     ['C']
    ],
    [14,
     {1: "s, ‘WORKER’, t, s， ‘WORKER’， t, s, ‘WORKER’， t, s， ‘WORKER’, t", '2': " ‘GOOD BOY’, GOOD BOY"},
     {1: "模式匹配"},
     {1: "空串"},
     {1: "堆式顺序存储结构"},
     {1: "链式存储"}
    ],
    [15,
     ['D'],
     ['B'],
     ['A'],
     ['B'],
     ['C']
    ],
    [16,
     {1: "01122"},
     {1: "01123"},
     {1: "数据元素是一个字符, 数据元素是单个字符"},
     {1: "当前位置"},
     {1: 7 }
    ],
    [17,
     ['D'],
     ['A'],
     ['B'],
     ['D'],
     ['C']
    ],
    [18,
     ['B'],
     ['B'],
     ['B'],
     ['D'],
     ['C']
    ],
    [19,
     {1: "非线性"},
     {1: "1, 一"},
     {1: "度"},
     {1: "最大"},
     {1: "0, 零"}
    ],
    [20,
     {1: "1"},
     {1: "383"},
     {1: "32"},
     {1: "9"},
     {1: "11"}
    ],
    [21,
     {1: "A", 2: "J"},
     {1: "E", 2: "H"},
     {1: "C"}
    ],
    [22,
     ['true'],
     ['true'],
     ['false'],
     ['true'],
     ['false']
    ],
    [23,
     ['A'],
     ['B'],
     ['B'],
     ['C'],
     ['D']
    ],
    [24,
     ['C'],
     ['C'],
     ['A'],
     ['D'],
     ['B']
    ],
    [25,
     {1: "空"},
     {1: "n1-1", 2: "n2+n3"},
     {1: "双亲", 2: "孩子兄弟"}
    ],
    [26,
     ['true'],
     ['false'],
     ['true'],
     ['false'],
     ['true']
    ],
    [27,
     {1: "叶子"},
     {1: "6", 2: "261"},
     {1: "2n-1"},
     {1: "前缀, 最优前缀"}
    ],
    [28,
     ['A'],
     ['B'],
     ['A'],
     ['B'],
     ['D']
    ],
    [29,
     {1: "最小"},
     {1: "贪心算法思想, 贪心算法的思想", 2: "动态规划思想, 动态规划的思想"},
     {1: "Dijkstra", 2: "Floyd"}
    ],
    [30,
     ['D'],
     ['C'],
     ['D'],
     ['C'],
     ['A']
    ],
    [31,
     ['A'],
     ['C'],
     ['A'],
     ['A'],
     ['B']
    ],
    [32,
     {1: "静态查找表, 动态查找表", 2: "动态查找表, 静态查找表"},
     {1: "平均查找长度"},
     {1: "主关键字"}
    ],
    [33,
     ['C'],
     ['D'],
     ['A']
    ],
    [34,
     ['A'],
     ['D'],
     ['B']
    ],
    [35,
     ['C'],
     ['true'],
     ['false']
    ],
    [36,
     ['C'],
     ['A'],
     ['C'],
     ['true'],
     ['true']
    ],
    [37,
     ['true'],
     ['true'],
     ['false']
    ],
    [38,
     ['C'],
     ['D'],
     ['A']
    ],
    [39,
     {1: "查找"},
     {1: "内部排序"},
     {1: "空间效率", 2: "稳定性"},
     {1: "插入排序"}
    ],
    [40,
     ['false'],
     ['true'],
     ['true'],
     ['false'],
     ['true']
    ],
    [41,
     ['false'],
     ['true'],
     ['true'],
     ['true']
    ],
    [42,
     ['false'],
     ['true'],
     ['true'],
     ['false']
    ],
    [43,
     ['true'],
     ['false'],
     ['true']
    ],
    [44,
     ['false'],
     ['true'],
     ['false'],
     ['true'],
     ['false']
    ]
]
i = -1

for item in data:
    # print(item)
    url = "https://www.xuetangx.com/api/v1/lms/exercise/problem_apply/"
    # 设置HTTP头信息
    headers = {
        "Accept": "application/json, text/plain, */*",
        "Accept-Encoding": "gzip, deflate, br, zstd",
        "Accept-Language": "zh",
        "App-Name": "xtzx",
        "Cache-Control": "no-cache",
        "Content-Type": "application/json",
        # 必要的
        "Cookie": "_abfpc=73f3154febe39bed2d1a540a8a94f67551d2d361_2.0; cna=0e5d0ea34bdd926182ad8f3ecbef9aec; mode_type=normal; provider=xuetang; django_language=zh; point={%22point_active%22:true%2C%22platform_task_active%22:true%2C%22learn_task_active%22:true}; 77831809video_seconds=3; 59584271video_seconds=151; undefinedvideo_seconds=151; login_type=P; csrftoken=dadHEX0qMOTyNfvQbDNd2zm3Fu1VoVtG; sessionid=9ml5t7q958j7rnd03owedypb5ek7oqb5; k=77831809; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%2277831809%22%2C%22first_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E8%87%AA%E7%84%B6%E6%90%9C%E7%B4%A2%E6%B5%81%E9%87%8F%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC%22%2C%22%24latest_referrer%22%3A%22https%3A%2F%2Fwww.bing.com%2F%22%7D%2C%22%24device_id%22%3A%2219025a34692932-03fb6f51d259324-4c657b58-1638720-19025a346931fb3%22%7D; JG_016f5b1907c3bc045f8f48de1_PV=1718967129887|1718970073104",
        "Django-Language": "zh",
        "Origin": "https://www.xuetangx.com",
        "Pragma": "no-cache",
        "Referer": "https://www.xuetangx.com/learn/henu08091007584/henu08091007584/19322491/exercise/43306496",
        "Sec-Ch-Ua": "\"Not/A)Brand\";v=\"8\", \"Chromium\";v=\"126\", \"Microsoft Edge\";v=\"126\"",
        "Sec-Ch-Ua-Mobile": "?0",
        "Sec-Ch-Ua-Platform": "\"Windows\"",
        "Sec-Fetch-Dest": "empty",
        "Sec-Fetch-Mode": "cors",
        "Sec-Fetch-Site": "same-origin",
        "Terminal-Type": "web",
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36 Edg/126.0.0.0",
        "X-Client": "web",
        # 必要的
        "X-Csrftoken": "dadHEX0qMOTyNfvQbDNd2zm3Fu1VoVtG",
        "Xtbz": "xt"
    }
    i += 1
    j = 0
    problem_id_list = promble_get(exce_id[i])
    for item_true in item[1:]:
        print(item_true)
        print(problem_id_list[j])
        data = {
            "leaf_id": leaf_id[i],
            "classroom_id": 19322491,
            "exercise_id": exce_id[i],
            "problem_id": problem_id_list[j],
            "sign": "henu08091007584",
            "answers": str(item_true),
            "answer": str(item_true),
        }
        j+=1
        sleep(5)
        response = requests.post(url, headers=headers, json=data)
        print(response.json())

同理也是那两个换成自己的

 

然后这个可能有点不一样

很简单自己交个题打开网络抓包，对应的改改进行了

已经经过博主测试，代码可行，可以自动填答案哈哈
解放你的双手吧老弟

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