将包含许多嵌套对象的 JSON 文件保存到列表中答案

【问题标题】：Saving JSON File with Many Nested Objects to a List将包含许多嵌套对象的 JSON 文件保存到列表中
【发布时间】：2018-03-02 01:25:43
【问题描述】：

我目前有一个格式如下的 JSON 文件。请记住，这不是整个文件。整个 JSON 文件由数百个键值对列表组成，这些键值对在方括号 [][][]...等之间一个接一个地跟随。我正在尝试存储每个单独的列表，例如结构中的下面的列表，以便我可以迭代结构并解析每个列表的文件名、标签等。我最初尝试使用 json.loads() 导入它，但由于对象的嵌套性质，我遇到了问题。对于如何将此文件导入列表或其他适当的 python 结构的任何想法/见解，我将不胜感激。

[
   {
      "File_Name": "1.jpg",
      "Analysis": {
         "Labels": [
            {
               "Confidence": 94.77251434326172,
               "Name": "Flora"
            },
            {
               "Confidence": 94.77251434326172,
               "Name": "Grass"
            },
            {
               "Confidence": 94.77251434326172,
               "Name": "Plant"
            },
            {
               "Confidence": 78.49254608154297,
               "Name": "Animal"
            },
            {
               "Confidence": 78.49254608154297,
               "Name": "Cheetah"
            },
            {
               "Confidence": 78.49254608154297,
               "Name": "Mammal"
            },
            {
               "Confidence": 78.49254608154297,
               "Name": "Wildlife"
            },
            {
               "Confidence": 69.79740142822266,
               "Name": "Field"
            },
            {
               "Confidence": 69.79740142822266,
               "Name": "Grassland"
            },
            {
               "Confidence": 69.79740142822266,
               "Name": "Outdoors"
            },
            {
               "Confidence": 67.31356048583984,
               "Name": "Leisure Activities"
            },
            {
               "Confidence": 67.31356048583984,
               "Name": "Walking"
            },
            {
               "Confidence": 57.44683837890625,
               "Name": "Jaguar"
            },
            {
               "Confidence": 57.44683837890625,
               "Name": "Leopard"
            },
            {
               "Confidence": 57.44683837890625,
               "Name": "Panther"
            },
            {
               "Confidence": 55.88261032104492,
               "Name": "Bush"
            },
            {
               "Confidence": 55.88261032104492,
               "Name": "Vegetation"
            },
            {
               "Confidence": 53.4413948059082,
               "Name": "Lawn"
            }
         ],
         "ResponseMetadata": {
            "RetryAttempts": 0,
            "HTTPStatusCode": 200,
            "RequestId": "978e32e4-1da8-11e8-a380-cd680f89684e",
            "HTTPHeaders": {
               "date": "Thu, 01 Mar 2018 23:30:59 GMT",
               "x-amzn-requestid": "978e32e4-1da8-11e8-a380-cd680f89684e",
               "content-length": "947",
               "content-type": "application/x-amz-json-1.1",
               "connection": "keep-alive"
            }
         },
         "OrientationCorrection": "ROTATE_0"
      }
   }
][
   {
      "File_Name": "2.jpg",
      "Analysis": {
         "Labels": [
            {
               "Confidence": 98.57389068603516,
               "Name": "Astronomy"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Galaxy"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Nebula"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Night"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Outdoors"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Outer Space"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Space"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Universe"
            }
         ],
         "ResponseMetadata": {
            "RetryAttempts": 0,
            "HTTPStatusCode": 200,
            "RequestId": "98d2c109-1da8-11e8-a2d9-b91cf22c7f33",
            "HTTPHeaders": {
               "date": "Thu, 01 Mar 2018 23:30:59 GMT",
               "x-amzn-requestid": "98d2c109-1da8-11e8-a2d9-b91cf22c7f33",
               "content-length": "449",
               "content-type": "application/x-amz-json-1.1",
               "connection": "keep-alive"
            }
         },
         "OrientationCorrection": "ROTATE_0"
      }
   },
   {
      "File_Name": "2.jpg",
      "Analysis": {
         "Labels": [
            {
               "Confidence": 98.57389068603516,
               "Name": "Astronomy"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Galaxy"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Nebula"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Night"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Outdoors"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Outer Space"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Space"
            },
            {
               "Confidence": 98.57389068603516,
               "Name": "Universe"
            }
         ],
         "ResponseMetadata": {
            "RetryAttempts": 0,
            "HTTPStatusCode": 200,
            "RequestId": "98d2c109-1da8-11e8-a2d9-b91cf22c7f33",
            "HTTPHeaders": {
               "date": "Thu, 01 Mar 2018 23:30:59 GMT",
               "x-amzn-requestid": "98d2c109-1da8-11e8-a2d9-b91cf22c7f33",
               "content-length": "449",
               "content-type": "application/x-amz-json-1.1",
               "connection": "keep-alive"
            }
         },
         "OrientationCorrection": "ROTATE_0"
      }
   }
]

【问题讨论】：

你能更好地了解结构吗？我需要知道您需要哪个键以及列表最后应该是什么样子。还有很多文件结果吗？是你想要的标签列表吗？
@cal97g 是的，我必须收集文件名、所有标签和置信度值。解析单个 JSON 对象应该没有任何问题，我之前从未在 Python 中处理/导入过这么大的嵌套 JSON 文件。
问题不是很清楚。你能提供预期的结果吗？此外，如果您提供您所做尝试的代码以便更好地了解您所追求的目标，这将很有用
@damores 基本上问题是我想将 JSON 文件导入到我的 python 脚本中。假设我使用 cal97g (top big_json_file sn-p) 提供的最佳答案，我将收到 ValueError: No JSON object could be decoded because of the format of the JSON file

标签： python json python-3.x parsing

【解决方案1】：

big_json_file = json.loads(file_string)
big_list_of_labels = []

for file in big_json_file:
    big_list_of_labels.append(file['Analysis']['Labels'])

或者，如果您想存储文件名和列表，我推荐如下：

my_processed_dict = {}
for file in big_json_file:
    my_processed_dict[file['File_Name']] = file['Analysis']['Labels']

您可以在哪里迭代 my_processed_dict：

for key, value in my_processed_dict.items():
    # value is the list of confidence values!
    pass

【讨论】：