我想将JSON数据转换为Python对象。
我从Facebook API收到JSON数据对象，我想将其存储在数据库中。
我的当前视图在Django (Python)(请求。POST包含JSON):
response = request.POST
user = FbApiUser(user_id = response['id'])
user.name = response['name']
user.username = response['username']
user.save()
这很好，但是如何处理复杂的JSON数据对象呢? 如果我能以某种方式将这个JSON对象转换为易于使用的Python对象，是不是会更好?
当前回答
这是我的办法。
特性
支持类型提示 如果缺少键则引发错误。 跳过数据中的额外值
import typing
class User:
name: str
age: int
def __init__(self, data: dict):
for k, _ in typing.get_type_hints(self).items():
setattr(self, k, data[k])
data = {
"name": "Susan",
"age": 18
}
user = User(data)
print(user.name, user.age)
# Output: Susan 18
其他回答
使用json模块(Python 2.6新增)或几乎总是安装的simplejson模块。
我正在寻找一个与recordclass一起工作的解决方案。RecordClass，支持嵌套对象，可用于json序列化和json反序列化。
扩展DS的答案，扩展BeneStr的解决方案，我想出了以下似乎有效的方法:
代码:
import json
import recordclass
class NestedRec(recordclass.RecordClass):
a : int = 0
b : int = 0
class ExampleRec(recordclass.RecordClass):
x : int = None
y : int = None
nested : NestedRec = NestedRec()
class JsonSerializer:
@staticmethod
def dumps(obj, ensure_ascii=True, indent=None, sort_keys=False):
return json.dumps(obj, default=JsonSerializer.__obj_to_dict, ensure_ascii=ensure_ascii, indent=indent, sort_keys=sort_keys)
@staticmethod
def loads(s, klass):
return JsonSerializer.__dict_to_obj(klass, json.loads(s))
@staticmethod
def __obj_to_dict(obj):
if hasattr(obj, "_asdict"):
return obj._asdict()
else:
return json.JSONEncoder().default(obj)
@staticmethod
def __dict_to_obj(klass, s_dict):
kwargs = {
key : JsonSerializer.__dict_to_obj(cls, s_dict[key]) if hasattr(cls,'_asdict') else s_dict[key] \
for key,cls in klass.__annotations__.items() \
if s_dict is not None and key in s_dict
}
return klass(**kwargs)
用法:
example_0 = ExampleRec(x = 10, y = 20, nested = NestedRec( a = 30, b = 40 ) )
#Serialize to JSON
json_str = JsonSerializer.dumps(example_0)
print(json_str)
#{
# "x": 10,
# "y": 20,
# "nested": {
# "a": 30,
# "b": 40
# }
#}
# Deserialize from JSON
example_1 = JsonSerializer.loads(json_str, ExampleRec)
example_1.x += 1
example_1.y += 1
example_1.nested.a += 1
example_1.nested.b += 1
json_str = JsonSerializer.dumps(example_1)
print(json_str)
#{
# "x": 11,
# "y": 21,
# "nested": {
# "a": 31,
# "b": 41
# }
#}
JSON到python对象
下面的代码递归地使用对象键创建动态属性。
JSON对象- fb_data.json:
{
"name": "John Smith",
"hometown": {
"name": "New York",
"id": 123
},
"list": [
"a",
"b",
"c",
1,
{
"key": 1
}
],
"object": {
"key": {
"key": 1
}
}
}
在转换中我们有三种情况:
列表 Dicts(新对象) Bool, int, float和STR
import json
class AppConfiguration(object):
def __init__(self, data=None):
if data is None:
with open("fb_data.json") as fh:
data = json.loads(fh.read())
else:
data = dict(data)
for key, val in data.items():
setattr(self, key, self.compute_attr_value(val))
def compute_attr_value(self, value):
if isinstance(value, list):
return [self.compute_attr_value(x) for x in value]
elif isinstance(value, dict):
return AppConfiguration(value)
else:
return value
if __name__ == "__main__":
instance = AppConfiguration()
print(instance.name)
print(instance.hometown.name)
print(instance.hometown.id)
print(instance.list[4].key)
print(instance.object.key.key)
键值对是属性-对象。
输出:
John Smith
New York
123
1
1
将JSON作为代码粘贴
支持TypeScript、Python、Go、Ruby、c#、Java、Swift、Rust、Kotlin、c++、Flow、Objective-C、JavaScript、Elm、JSON Schema。
从JSON、JSON Schema和TypeScript中交互式地生成类型和(反)序列化代码 将JSON/JSON Schema/TypeScript作为代码粘贴
quicktype从示例JSON数据中推断类型，然后输出强类型模型和序列化器，以便用所需的编程语言处理这些数据。
输出:
# Generated by https://quicktype.io
#
# To change quicktype's target language, run command:
#
# "Set quicktype target language"
from typing import List, Union
class Hometown:
name: str
id: int
def __init__(self, name: str, id: int) -> None:
self.name = name
self.id = id
class Key:
key: int
def __init__(self, key: int) -> None:
self.key = key
class Object:
key: Key
def __init__(self, key: Key) -> None:
self.key = key
class FbData:
name: str
hometown: Hometown
list: List[Union[Key, int, str]]
object: Object
def __init__(self, name: str, hometown: Hometown, list: List[Union[Key, int, str]], object: Object) -> None:
self.name = name
self.hometown = hometown
self.list = list
self.object = object
这个扩展可以在Visual Studio代码市场中免费获得。
class SimpleClass:
def __init__(self, **kwargs):
for k, v in kwargs.items():
if type(v) is dict:
setattr(self, k, SimpleClass(**v))
else:
setattr(self, k, v)
json_dict = {'name': 'jane doe', 'username': 'jane', 'test': {'foo': 1}}
class_instance = SimpleClass(**json_dict)
print(class_instance.name, class_instance.test.foo)
print(vars(class_instance))
数据类向导是一种现代的选项，可以类似地为您工作。它支持自动键大小写转换，如camelCase或TitleCase，这两者在API响应中都很常见。
当将实例转储到dict/JSON时，默认的键转换是camelCase，但这可以很容易地使用主数据类上提供的Meta配置来覆盖。
https://pypi.org/project/dataclass-wizard/
from dataclasses import dataclass
from dataclass_wizard import fromdict, asdict
@dataclass
class User:
name: str
age: int
is_active: bool
data = {
'name': 'John',
'age': 30,
'isActive': True,
}
user = fromdict(User, data)
assert user == User(name='John', age=30, is_active=True)
json_dict = asdict(user)
assert json_dict == {'name': 'John', 'age': 30, 'isActive': True}
设置元配置的例子，当序列化为dict/JSON时，将字段转换为lisp-case:
DumpMeta(key_transform='LISP').bind_to(User)
