由于随机值，在Python中解析JSON数据时出现问题

我正在浏览一个产品评论网站。我可以成功地获取JSON数据，但是我在解析方面遇到了问题。数据的级别如下所示： 有效负载->评论->22Y6N61W6TO2->客户评论

我想要的数据处于“customerReviews”级别。但是，查看其他项目时，“6IYETQATGRMP”值将不同

我不想对每个项目都使用不同的python脚本来解释这个值。如何使用通配符之类的东西来获取我要查找的数据

我在脚本中使用了Python 3、请求和JSON

我的脚本如下所示：

import json
import pandas as pd
with open('data.json', 'r') as f:
    data = json.load(f)

df = pd.json_normalize(data['payload']['reviews']['22Y6N61W6TO2']['customerReviews'])
    print(df)

下面是我正在使用的JSON的一部分：

"payload": {
      "products": {},
      "offers": {},
      "idmlMap": {},
      "reviews": {
         "22Y6N61W6TO2": {
            "averageOverallRating": 4.4783,
            "roundedAverageOverallRating": 4.5,
            "overallRatingRange": 5.0,
            "totalReviewCount": 759,
            "recommendedPercentage": 89,
            "ratingValueOneCount": 35,
            "ratingValueTwoCount": 27,
            "ratingValueThreeCount": 30,
            "ratingValueFourCount": 115,
            "ratingValueFiveCount": 552,
            "percentageOneCount": 4,
            "percentageTwoCount": 3,
            "percentageThreeCount": 3,
            "percentageFourCount": 15,
            "percentageFiveCount": 72,
            "activeSort": "relevancy",
            "pagination": {
               "total": 759,
               "pages": [
                  {
                     "num": 1,
                     "gap": false,
                     "active": true,
                     "url": "sort=relevancy&page=1"
                  },
                  {
                     "num": 2,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=2"
                  },
                  {
                     "num": 3,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=3"
                  },
                  {
                     "num": 4,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=4"
                  },
                  {
                     "num": 5,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=5"
                  },
                  {
                     "num": 6,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=6"
                  },
                  {
                     "num": 0,
                     "gap": true,
                     "active": false
                  },
                  {
                     "num": 38,
                     "gap": false,
                     "active": false,
                     "url": "sort=relevancy&page=38"
                  }
               ],
               "next": {
                  "num": 0,
                  "gap": false,
                  "active": false,
                  "url": "sort=relevancy&page=2"
               },
               "currentSpan": "1-20"
            },
            "customerReviews": [
               {
                  "reviewId": "248695872",
                  "authorId": "13b0b650b7694a54267279bf80e0fdfa99cc7c3c5150d32aff7db274e74c07f5f6e7f7b6c4fe8cb64a007c9e3c0f0c04",
                  "negativeFeedback": 0,
                  "positiveFeedback": 0,
                  "rating": 5.0,
                  "reviewTitle": "Amazing",
                  "reviewText": "This thing is amazing. I cooked bbq ribs in 30 mins. Then caramelized for 6 mins in my oven. They was awesome. Best kitchen appliance of 2020. Wish i had bought it before dec 31st. Buy one folks. You'll love it.",
                  "reviewSubmissionTime": "1/1/2021",
                  "userNickname": "Keith",
                  "badges": [
                     {
                        "badgeType": "Custom",
                        "id": "VerifiedPurchaser",
                        "contentType": "REVIEW"
                     }
                  ],
                  "userAttributes": {},
                  "photos": [
                     {
                        "Id": "e917ed53-cf49-48af-b454-42f3fd87536a",
                        "Sizes": {
                           "normal": {
                              "Id": "normal",
                              "Url": "https://i5.walmartimages.com/dfw/6e29e393-988c/k2-_d716ba9d-2c5b-4f82-b9a6-588575975fe6.v1.bin"
                           },
                           "thumbnail": {
                              "Id": "thumbnail",
                              "Url": "https://i5.walmartimages.com/dfw/6e29e393-988c/k2-_d716ba9d-2c5b-4f82-b9a6-588575975fe6.v1.bin?odnWidth=150&odnHeight=150&odnBg=ffffff"
                           }
                        },
                        "SizesOrder": [
                           "normal",
                           "thumbnail"
                        ]
                     }
                  ],
                  "videos": [],
                  "externalSource": "bazaarvoice"
               }

---

您必须设置一个简单的变量才能使用标准的导出函数

导入json
随机输入
id_1='6IYETQATGRMP'
id_2='7GAADHOOLWCT'
id_3='8WWBHOLWQNNZ'

json\u数据=“”{
“1级”：{
“2级”：{
“6IYETQATGRMP”：{
“级别4”：“您的第一个级别4数据”
},
“7GAADHOOLWCT”：{
“第四级”：“您的第二级第四级数据”
},
“8WWBHOLWQNNZ”：{
“4级”：“您的3级4级数据”
}
}
}
}'''

your\u var=random.choice（[id\u 1，id\u 2，id\u 3]）
data=json.load（_json_数据）
打印（数据['level_1']['level_2'][your_var]['level_4']））

---

通过这种方式，您可以使用“your_var”设置所需的ID，如果ID存在，该函数将按预期工作。

我相信您可以像这样首先获得密钥

key=list（数据[“有效负载”][reviews'].keys（））[0]
df=pd.json_规范化（数据['payload']['reviews'][key]['customerReviews']）

请将此作为一个示例，并包含JSON响应示例，您可以完美地完成此操作。谢谢。