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?
在寻找解决方案时,我偶然发现了这个博客:https://blog.mosthege.net/2016/11/12/json-deserialization-of-nested-objects/
它使用与前面回答中相同的技术,但使用了装饰器。
我发现另一件有用的事情是,它在反序列化结束时返回一个类型化对象
class JsonConvert(object):
class_mappings = {}
@classmethod
def class_mapper(cls, d):
for keys, cls in clsself.mappings.items():
if keys.issuperset(d.keys()): # are all required arguments present?
return cls(**d)
else:
# Raise exception instead of silently returning None
raise ValueError('Unable to find a matching class for object: {!s}'.format(d))
@classmethod
def complex_handler(cls, Obj):
if hasattr(Obj, '__dict__'):
return Obj.__dict__
else:
raise TypeError('Object of type %s with value of %s is not JSON serializable' % (type(Obj), repr(Obj)))
@classmethod
def register(cls, claz):
clsself.mappings[frozenset(tuple([attr for attr,val in cls().__dict__.items()]))] = cls
return cls
@classmethod
def to_json(cls, obj):
return json.dumps(obj.__dict__, default=cls.complex_handler, indent=4)
@classmethod
def from_json(cls, json_str):
return json.loads(json_str, object_hook=cls.class_mapper)
用法:
@JsonConvert.register
class Employee(object):
def __init__(self, Name:int=None, Age:int=None):
self.Name = Name
self.Age = Age
return
@JsonConvert.register
class Company(object):
def __init__(self, Name:str="", Employees:[Employee]=None):
self.Name = Name
self.Employees = [] if Employees is None else Employees
return
company = Company("Contonso")
company.Employees.append(Employee("Werner", 38))
company.Employees.append(Employee("Mary"))
as_json = JsonConvert.to_json(company)
from_json = JsonConvert.from_json(as_json)
as_json_from_json = JsonConvert.to_json(from_json)
assert(as_json_from_json == as_json)
print(as_json_from_json)
更新
在Python3中,你可以使用SimpleNamespace和object_hook在一行中完成:
import json
from types import SimpleNamespace
data = '{"name": "John Smith", "hometown": {"name": "New York", "id": 123}}'
# Parse JSON into an object with attributes corresponding to dict keys.
x = json.loads(data, object_hook=lambda d: SimpleNamespace(**d))
print(x.name, x.hometown.name, x.hometown.id)
旧答案(Python2)
在Python2中,你可以使用namedtuple和object_hook在一行中完成(但对于嵌套对象非常慢):
import json
from collections import namedtuple
data = '{"name": "John Smith", "hometown": {"name": "New York", "id": 123}}'
# Parse JSON into an object with attributes corresponding to dict keys.
x = json.loads(data, object_hook=lambda d: namedtuple('X', d.keys())(*d.values()))
print x.name, x.hometown.name, x.hometown.id
或者,为了便于重用:
def _json_object_hook(d): return namedtuple('X', d.keys())(*d.values())
def json2obj(data): return json.loads(data, object_hook=_json_object_hook)
x = json2obj(data)
如果希望它处理不是很好的属性名称的键,请检查namedtuple的rename参数。
我认为最简单的解决方法是
import orjson # faster then json =)
from typing import NamedTuple
_j = '{"name":"Иван","age":37,"mother":{"name":"Ольга","age":58},"children":["Маша","Игорь","Таня"],"married": true,' \
'"dog":null} '
class PersonNameAge(NamedTuple):
name: str
age: int
class UserInfo(NamedTuple):
name: str
age: int
mother: PersonNameAge
children: list
married: bool
dog: str
j = orjson.loads(_j)
u = UserInfo(**j)
print(u.name, u.age, u.mother, u.children, u.married, u.dog)
>>> Ivan 37 {'name': 'Olga', 'age': 58} ['Mary', 'Igor', 'Jane'] True None
这不是一个很难的事情,我看到上面的答案,他们中的大多数在“列表”中有一个性能问题
这段代码比上面的代码快得多
import json
class jsonify:
def __init__(self, data):
self.jsonify = data
def __getattr__(self, attr):
value = self.jsonify.get(attr)
if isinstance(value, (list, dict)):
return jsonify(value)
return value
def __getitem__(self, index):
value = self.jsonify[index]
if isinstance(value, (list, dict)):
return jsonify(value)
return value
def __setitem__(self, index, value):
self.jsonify[index] = value
def __delattr__(self, index):
self.jsonify.pop(index)
def __delitem__(self, index):
self.jsonify.pop(index)
def __repr__(self):
return json.dumps(self.jsonify, indent=2, default=lambda x: str(x))
exmaple
response = jsonify(
{
'test': {
'test1': [{'ok': 1}]
}
}
)
response.test -> jsonify({'test1': [{'ok': 1}]})
response.test.test1 -> jsonify([{'ok': 1}])
response.test.test1[0] -> jsonify({'ok': 1})
response.test.test1[0].ok -> int(1)
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)