如何从谷歌的自然语言API对对象进行JSON序列化？(无__dict__属性)

Question

我正在使用Google自然语言API进行项目，通过情感分析标记文本。我想将我的 NL 结果存储为 JSON。如果向Google发出直接HTTP请求，则会返回JSON响应。

但是，当使用提供的 Python 库时，会返回一个对象，并且该对象不能直接 JSON 序列化。

这是我的代码示例：

import os
import sys
import oauth2client.client
from google.cloud.gapic.language.v1beta2 import enums, language_service_client
from google.cloud.proto.language.v1beta2 import language_service_pb2
class LanguageReader:
# class that parses, stores and reports language data from text
def __init__(self, content=None):
try:
# attempts to autheticate credentials from env variable
oauth2client.client.GoogleCredentials.get_application_default()
except oauth2client.client.ApplicationDefaultCredentialsError:
print("=== ERROR: Google credentials could not be authenticated! ===")
print("Current enviroment variable for this process is: {}".format(os.environ['GOOGLE_APPLICATION_CREDENTIALS']))
print("Run:")
print("   $ export GOOGLE_APPLICATION_CREDENTIALS=/YOUR_PATH_HERE/YOUR_JSON_KEY_HERE.json")
print("to set the authentication credentials manually")
sys.exit()
self.language_client = language_service_client.LanguageServiceClient()
self.document = language_service_pb2.Document()
self.document.type = enums.Document.Type.PLAIN_TEXT
self.encoding = enums.EncodingType.UTF32
self.results = None
if content is not None:
self.read_content(content)
def read_content(self, content):
self.document.content = content
self.language_client.analyze_sentiment(self.document, self.encoding)
self.results = self.language_client.analyze_sentiment(self.document, self.encoding)

现在，如果您要运行：

sample_text="I love R&B music. Marvin Gaye is the best. 'What's Going On' is one of my favorite songs. It was so sad when Marvin Gaye died."
resp = LanguageReader(sample_text).results
print resp

你会得到：

document_sentiment {
magnitude: 2.40000009537
score: 0.40000000596
}
language: "en"
sentences {
text {
content: "I love R&B music."
}
sentiment {
magnitude: 0.800000011921
score: 0.800000011921
}
}
sentences {
text {
content: "Marvin Gaye is the best."
begin_offset: 18
}
sentiment {
magnitude: 0.800000011921
score: 0.800000011921
}
}
sentences {
text {
content: "'What's Going On' is one of my favorite songs."
begin_offset: 43
}
sentiment {
magnitude: 0.40000000596
score: 0.40000000596
}
}
sentences {
text {
content: "It was so sad when Marvin Gaye died."
begin_offset: 90
}
sentiment {
magnitude: 0.20000000298
score: -0.20000000298
}
}

这不是 JSON。这是google.cloud.proto.language.v1beta2.language_service_pb2的一个实例。分析情绪响应对象。它没有__dict__属性属性，因此无法使用 json.dumps(( 进行序列化。

如何指定响应应采用 JSON 格式或将对象序列化为 JSON？

Answer 1

编辑：@Zach注意到谷歌的protobuf数据交换格式。似乎首选选项是使用以下protobuf.json_format方法：

from google.protobuf.json_format import MessageToDict, MessageToJson 
self.dict = MessageToDict(self.results)
self.json = MessageToJson(self.results)

从文档字符串：

MessageToJson(message, including_default_value_fields=False, preserving_proto_field_name=False)
Converts protobuf message to JSON format.
Args:
message: The protocol buffers message instance to serialize.
including_default_value_fields: If True, singular primitive fields,
repeated fields, and map fields will always be serialized.  If
False, only serialize non-empty fields.  Singular message fields
and oneof fields are not affected by this option.
preserving_proto_field_name: If True, use the original proto field
names as defined in the .proto file. If False, convert the field
names to lowerCamelCase.
Returns:
A string containing the JSON formatted protocol buffer message.