您好我正在尝试从此JSON文件导入数据以在我的python脚本中使用它。但是，我收到以下错误，我相信由于JSON对象的嵌套特性。我的最终目标是收集每个JSON对象的文件名和标签。我不关心重复项，类似于.JSON文件的当前格式。
File "test.py", line 4, in <module>
big_json_file = json.loads(file_string)
File "/usr/lib/python2.7/json/__init__.py", line 339, in loads
return _default_decoder.decode(s)
File "/usr/lib/python2.7/json/decoder.py", line 364, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/lib/python2.7/json/decoder.py", line 382, in raw_decode
raise ValueError("No JSON object could be decoded")
ValueError: No JSON object could be decoded
下面是python脚本“test.py”：
import json
file_string = 'output.json'
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'])
以下是我尝试导入的.JSON文件：
[
{
"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"
}
}
][
{
"File_Name": "3.jpg",
"Analysis": {
"Labels": [
{
"Confidence": 98.6434555053711,
"Name": "Human"
},
{
"Confidence": 98.6434097290039,
"Name": "People"
},
{
"Confidence": 98.6434555053711,
"Name": "Person"
},
{
"Confidence": 96.43375396728516,
"Name": "Audience"
},
{
"Confidence": 96.43375396728516,
"Name": "Crowd"
},
{
"Confidence": 96.43375396728516,
"Name": "Speech"
},
{
"Confidence": 80.42803192138672,
"Name": "Badge"
},
{
"Confidence": 80.42803192138672,
"Name": "Emblem"
},
{
"Confidence": 80.42803192138672,
"Name": "Logo"
},
{
"Confidence": 80.42803192138672,
"Name": "Trademark"
},
{
"Confidence": 59.94097137451172,
"Name": "Worker"
}
],
"ResponseMetadata": {
"RetryAttempts": 0,
"HTTPStatusCode": 200,
"RequestId": "99394a95-1da8-11e8-876f-6db2ab84a252",
"HTTPHeaders": {
"date": "Thu, 01 Mar 2018 23:30:59 GMT",
"x-amzn-requestid": "99394a95-1da8-11e8-876f-6db2ab84a252",
"content-length": "583",
"content-type": "application/x-amz-json-1.1",
"connection": "keep-alive"
}
},
"OrientationCorrection": "ROTATE_0"
}
},
{
"File_Name": "3.jpg",
"Analysis": {
"Labels": [
{
"Confidence": 98.6434555053711,
"Name": "Human"
},
{
"Confidence": 98.6434097290039,
"Name": "People"
},
{
"Confidence": 98.6434555053711,
"Name": "Person"
},
{
"Confidence": 96.43375396728516,
"Name": "Audience"
},
{
"Confidence": 96.43375396728516,
"Name": "Crowd"
},
{
"Confidence": 96.43375396728516,
"Name": "Speech"
},
{
"Confidence": 80.42803192138672,
"Name": "Badge"
},
{
"Confidence": 80.42803192138672,
"Name": "Emblem"
},
{
"Confidence": 80.42803192138672,
"Name": "Logo"
},
{
"Confidence": 80.42803192138672,
"Name": "Trademark"
},
{
"Confidence": 59.94097137451172,
"Name": "Worker"
}
],
"ResponseMetadata": {
"RetryAttempts": 0,
"HTTPStatusCode": 200,
"RequestId": "99394a95-1da8-11e8-876f-6db2ab84a252",
"HTTPHeaders": {
"date": "Thu, 01 Mar 2018 23:30:59 GMT",
"x-amzn-requestid": "99394a95-1da8-11e8-876f-6db2ab84a252",
"content-length": "583",
"content-type": "application/x-amz-json-1.1",
"connection": "keep-alive"
}
},
"OrientationCorrection": "ROTATE_0"
}
},
{
"File_Name": "3.jpg",
"Analysis": {
"Labels": [
{
"Confidence": 98.6434555053711,
"Name": "Human"
},
{
"Confidence": 98.6434097290039,
"Name": "People"
},
{
"Confidence": 98.6434555053711,
"Name": "Person"
},
{
"Confidence": 96.43375396728516,
"Name": "Audience"
},
{
"Confidence": 96.43375396728516,
"Name": "Crowd"
},
{
"Confidence": 96.43375396728516,
"Name": "Speech"
},
{
"Confidence": 80.42803192138672,
"Name": "Badge"
},
{
"Confidence": 80.42803192138672,
"Name": "Emblem"
},
{
"Confidence": 80.42803192138672,
"Name": "Logo"
},
{
"Confidence": 80.42803192138672,
"Name": "Trademark"
},
{
"Confidence": 59.94097137451172,
"Name": "Worker"
}
],
"ResponseMetadata": {
"RetryAttempts": 0,
"HTTPStatusCode": 200,
"RequestId": "99394a95-1da8-11e8-876f-6db2ab84a252",
"HTTPHeaders": {
"date": "Thu, 01 Mar 2018 23:30:59 GMT",
"x-amzn-requestid": "99394a95-1da8-11e8-876f-6db2ab84a252",
"content-length": "583",
"content-type": "application/x-amz-json-1.1",
"connection": "keep-alive"
}
},
"OrientationCorrection": "ROTATE_0"
}
}
]
答案 0 :(得分：3)
所以问题是json.loads期望传递实际的json（字符串），而不是文件名。您可以使用with打开一个文件，并使用json.load中的filepointer。
import json
with open('output.json') as thefile:
big_json_file = json.load(thefile)
big_list_of_labels = []
for file in big_json_file:
big_list_of_labels.append(file['Analysis']['Labels'])
此外，您的json无效..在两个地方需要,而不是][。
答案 1 :(得分：1)
也许阅读文档会有所帮助吗？
json.loads(s, *, encoding=None, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)将s（包含JSON文档的str，bytes或bytearray实例）反序列化为Python对象
以上是几行的例子：
>>> import json
>>> json.loads('["foo", {"bar":["baz", null, 1.0, 2]}]')
['foo', {'bar': ['baz', None, 1.0, 2]}]
在您的代码段中：
file_string = 'output.json'
big_json_file = json.loads(file_string)
文字字符串"output.json"显然不是JSON文档。它可能是包含json文档的文件的名称，但不是json.loads()所期望的（参见示例）。
您希望它阅读文件的内容并将其传递给json.loads()：
with open ("output.json") as f:
data = json.loads(f.read())
print(data)
可以使用json.load()（没有＆＃39; s＆＃39;）进一步简化，而不是将打开的文件作为参数：
with open ("output.json") as f:
data = json.load(f)
print(data)