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
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
# }
#}
其他回答
你可以试试这个:
class User(object):
def __init__(self, name, username):
self.name = name
self.username = username
import json
j = json.loads(your_json)
u = User(**j)
只需创建一个新对象，并将参数作为映射传递。
你也可以有一个带有对象的JSON:
import json
class Address(object):
def __init__(self, street, number):
self.street = street
self.number = number
def __str__(self):
return "{0} {1}".format(self.street, self.number)
class User(object):
def __init__(self, name, address):
self.name = name
self.address = Address(**address)
def __str__(self):
return "{0} ,{1}".format(self.name, self.address)
if __name__ == '__main__':
js = '''{"name":"Cristian", "address":{"street":"Sesame","number":122}}'''
j = json.loads(js)
print(j)
u = User(**j)
print(u)
使用json模块(Python 2.6新增)或几乎总是安装的simplejson模块。
改进lovasoa非常好的答案。
如果你正在使用python 3.6+，你可以使用: PIP安装棉花糖-enum和 PIP安装棉花糖数据类
它简单且类型安全。
你可以在string-json中转换你的类，反之亦然:
从对象到字符串Json:
from marshmallow_dataclass import dataclass
user = User("Danilo","50","RedBull",15,OrderStatus.CREATED)
user_json = User.Schema().dumps(user)
user_json_str = user_json.data
从String Json到Object:
json_str = '{"name":"Danilo", "orderId":"50", "productName":"RedBull", "quantity":15, "status":"Created"}'
user, err = User.Schema().loads(json_str)
print(user,flush=True)
类定义:
class OrderStatus(Enum):
CREATED = 'Created'
PENDING = 'Pending'
CONFIRMED = 'Confirmed'
FAILED = 'Failed'
@dataclass
class User:
def __init__(self, name, orderId, productName, quantity, status):
self.name = name
self.orderId = orderId
self.productName = productName
self.quantity = quantity
self.status = status
name: str
orderId: str
productName: str
quantity: int
status: OrderStatus
Python3.x
以我的知识，我能找到的最好的方法是。 注意，这段代码也处理set()。 这种方法是通用的，只需要类的扩展(在第二个例子中)。 请注意，我只是对文件执行此操作，但是很容易根据自己的喜好修改行为。
然而，这是一个编解码器。
再做一点工作，就可以用其他方式构造类。 我假设有一个默认构造函数来实例它，然后更新类dict。
import json
import collections
class JsonClassSerializable(json.JSONEncoder):
REGISTERED_CLASS = {}
def register(ctype):
JsonClassSerializable.REGISTERED_CLASS[ctype.__name__] = ctype
def default(self, obj):
if isinstance(obj, collections.Set):
return dict(_set_object=list(obj))
if isinstance(obj, JsonClassSerializable):
jclass = {}
jclass["name"] = type(obj).__name__
jclass["dict"] = obj.__dict__
return dict(_class_object=jclass)
else:
return json.JSONEncoder.default(self, obj)
def json_to_class(self, dct):
if '_set_object' in dct:
return set(dct['_set_object'])
elif '_class_object' in dct:
cclass = dct['_class_object']
cclass_name = cclass["name"]
if cclass_name not in self.REGISTERED_CLASS:
raise RuntimeError(
"Class {} not registered in JSON Parser"
.format(cclass["name"])
)
instance = self.REGISTERED_CLASS[cclass_name]()
instance.__dict__ = cclass["dict"]
return instance
return dct
def encode_(self, file):
with open(file, 'w') as outfile:
json.dump(
self.__dict__, outfile,
cls=JsonClassSerializable,
indent=4,
sort_keys=True
)
def decode_(self, file):
try:
with open(file, 'r') as infile:
self.__dict__ = json.load(
infile,
object_hook=self.json_to_class
)
except FileNotFoundError:
print("Persistence load failed "
"'{}' do not exists".format(file)
)
class C(JsonClassSerializable):
def __init__(self):
self.mill = "s"
JsonClassSerializable.register(C)
class B(JsonClassSerializable):
def __init__(self):
self.a = 1230
self.c = C()
JsonClassSerializable.register(B)
class A(JsonClassSerializable):
def __init__(self):
self.a = 1
self.b = {1, 2}
self.c = B()
JsonClassSerializable.register(A)
A().encode_("test")
b = A()
b.decode_("test")
print(b.a)
print(b.b)
print(b.c.a)
Edit
通过更多的研究，我发现了一种不需要SUPERCLASS寄存器方法调用的泛化方法，使用元类
import json
import collections
REGISTERED_CLASS = {}
class MetaSerializable(type):
def __call__(cls, *args, **kwargs):
if cls.__name__ not in REGISTERED_CLASS:
REGISTERED_CLASS[cls.__name__] = cls
return super(MetaSerializable, cls).__call__(*args, **kwargs)
class JsonClassSerializable(json.JSONEncoder, metaclass=MetaSerializable):
def default(self, obj):
if isinstance(obj, collections.Set):
return dict(_set_object=list(obj))
if isinstance(obj, JsonClassSerializable):
jclass = {}
jclass["name"] = type(obj).__name__
jclass["dict"] = obj.__dict__
return dict(_class_object=jclass)
else:
return json.JSONEncoder.default(self, obj)
def json_to_class(self, dct):
if '_set_object' in dct:
return set(dct['_set_object'])
elif '_class_object' in dct:
cclass = dct['_class_object']
cclass_name = cclass["name"]
if cclass_name not in REGISTERED_CLASS:
raise RuntimeError(
"Class {} not registered in JSON Parser"
.format(cclass["name"])
)
instance = REGISTERED_CLASS[cclass_name]()
instance.__dict__ = cclass["dict"]
return instance
return dct
def encode_(self, file):
with open(file, 'w') as outfile:
json.dump(
self.__dict__, outfile,
cls=JsonClassSerializable,
indent=4,
sort_keys=True
)
def decode_(self, file):
try:
with open(file, 'r') as infile:
self.__dict__ = json.load(
infile,
object_hook=self.json_to_class
)
except FileNotFoundError:
print("Persistence load failed "
"'{}' do not exists".format(file)
)
class C(JsonClassSerializable):
def __init__(self):
self.mill = "s"
class B(JsonClassSerializable):
def __init__(self):
self.a = 1230
self.c = C()
class A(JsonClassSerializable):
def __init__(self):
self.a = 1
self.b = {1, 2}
self.c = B()
A().encode_("test")
b = A()
b.decode_("test")
print(b.a)
# 1
print(b.b)
# {1, 2}
print(b.c.a)
# 1230
print(b.c.c.mill)
# s
这里有一个快速而肮脏的json pickle替代方案
import json
class User:
def __init__(self, name, username):
self.name = name
self.username = username
def to_json(self):
return json.dumps(self.__dict__)
@classmethod
def from_json(cls, json_str):
json_dict = json.loads(json_str)
return cls(**json_dict)
# example usage
User("tbrown", "Tom Brown").to_json()
User.from_json(User("tbrown", "Tom Brown").to_json()).to_json()
