Python 将包含许多嵌套对象的JSON文件保存到列表中
我目前有一个JSON文件，其格式如下。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[]等之间依次排列。我正在尝试将这些单独的列表（例如，下面的列表）存储在一个结构中，以便我可以迭代该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（）导入此列表，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，如果有任何想法/见解，我将不胜感激Python 将包含许多嵌套对象的JSON文件保存到列表中,python,json,python-3.x,parsing,Python,Json,Python 3.x,Parsing,我目前有一个JSON文件，其格式如下。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[]等之间依次排列。我正在尝试将这些单独的列表（例如，下面的列表）存储在一个结构中，以便我可以迭代该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（）导入此列表，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，如果有任何想法/见解，我将不胜感激 [ { "File_Name": "1.jpg
[
{
"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"
}
}
]
my_processed_dict = {}
for file in big_json_file:
my_processed_dict[file['File_Name']] = file['Analysis']['Labels']
for key, value in my_processed_dict.items():
# value is the list of confidence values!
pass
你能更好地了解这个结构吗？我需要知道你需要哪把钥匙，以及最后的列表应该是什么样子。还有很多文件结果吗？这是您想要的标签列表吗？@cal97g是的，我必须收集文件名、所有标签和置信值。解析单个JSON对象应该不会有任何问题，我只是从来没有在Python中处理/导入过这么大的嵌套JSON文件。问题还不是很清楚。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，以便更好地了解您正在做的事情，这将非常有用after@damores基本上，问题是我想将一个JSON文件导入到我的python脚本中。假设我使用cal97g（顶级大json文件片段）提供的最佳答案，我将收到一个ValueError：由于json文件的格式，无法解码任何json对象
for key, value in my_processed_dict.items():
# value is the list of confidence values!
pass