如何使一个Python类序列化?
class FileItem:
def __init__(self, fname):
self.fname = fname
尝试序列化为JSON:
>>> import json
>>> x = FileItem('/foo/bar')
>>> json.dumps(x)
TypeError: Object of type 'FileItem' is not JSON serializable
如何使一个Python类序列化?
class FileItem:
def __init__(self, fname):
self.fname = fname
尝试序列化为JSON:
>>> import json
>>> x = FileItem('/foo/bar')
>>> json.dumps(x)
TypeError: Object of type 'FileItem' is not JSON serializable
当前回答
这个类可以做到这一点,它将object转换为标准json。
import json
class Serializer(object):
@staticmethod
def serialize(object):
return json.dumps(object, default=lambda o: o.__dict__.values()[0])
用法:
Serializer.serialize(my_object)
在python2.7和python3中工作。
其他回答
你知道预期产量是多少吗?例如,这个可以吗?
>>> f = FileItem("/foo/bar")
>>> magic(f)
'{"fname": "/foo/bar"}'
在这种情况下,你只需调用json.dumps(f.__dict__)。
如果您想要更多自定义输出,那么您必须继承JSONEncoder并实现您自己的自定义序列化。
对于一个简单的例子,请参见下面。
>>> from json import JSONEncoder
>>> class MyEncoder(JSONEncoder):
def default(self, o):
return o.__dict__
>>> MyEncoder().encode(f)
'{"fname": "/foo/bar"}'
然后你把这个类作为cls kwarg传递给json.dumps()方法:
json.dumps(cls=MyEncoder)
如果还想解码,则必须向JSONDecoder类提供一个自定义object_hook。例如:
>>> def from_json(json_object):
if 'fname' in json_object:
return FileItem(json_object['fname'])
>>> f = JSONDecoder(object_hook = from_json).decode('{"fname": "/foo/bar"}')
>>> f
<__main__.FileItem object at 0x9337fac>
>>>
如果你不介意为它安装一个包,你可以使用json-tricks:
pip install json-tricks
之后,你只需要从json_tricks导入dump(s)而不是json,它通常会工作:
from json_tricks import dumps
json_str = dumps(cls_instance, indent=4)
这将给
{
"__instance_type__": [
"module_name.test_class",
"MyTestCls"
],
"attributes": {
"attr": "val",
"dct_attr": {
"hello": 42
}
}
}
基本上就是这样!
这在一般情况下会很有效。有一些例外,例如,如果特殊的事情发生在__new__中,或者更多的元类魔法正在发生。
显然加载也可以(否则有什么意义):
from json_tricks import loads
json_str = loads(json_str)
这确实假设module_name.test_class。MyTestCls可以导入,并且没有以不兼容的方式进行更改。您将返回一个实例,而不是某个字典或其他东西,它应该是您转储的实例的相同副本。
如果你想自定义一些东西是如何(反)序列化的,你可以添加特殊的方法到你的类,像这样:
class CustomEncodeCls:
def __init__(self):
self.relevant = 42
self.irrelevant = 37
def __json_encode__(self):
# should return primitive, serializable types like dict, list, int, string, float...
return {'relevant': self.relevant}
def __json_decode__(self, **attrs):
# should initialize all properties; note that __init__ is not called implicitly
self.relevant = attrs['relevant']
self.irrelevant = 12
其中仅序列化部分属性参数,作为示例。
作为免费的奖励,你可以获得numpy数组、日期和时间、有序地图的(反)序列化,以及在json中包含注释的能力。
免责声明:我创建了json_tricks,因为我遇到了与您相同的问题。
我选择使用装饰器来解决datetime对象序列化问题。 这是我的代码:
#myjson.py
#Author: jmooremcc 7/16/2017
import json
from datetime import datetime, date, time, timedelta
"""
This module uses decorators to serialize date objects using json
The filename is myjson.py
In another module you simply add the following import statement:
from myjson import json
json.dumps and json.dump will then correctly serialize datetime and date
objects
"""
def json_serial(obj):
"""JSON serializer for objects not serializable by default json code"""
if isinstance(obj, (datetime, date)):
serial = str(obj)
return serial
raise TypeError ("Type %s not serializable" % type(obj))
def FixDumps(fn):
def hook(obj):
return fn(obj, default=json_serial)
return hook
def FixDump(fn):
def hook(obj, fp):
return fn(obj,fp, default=json_serial)
return hook
json.dumps=FixDumps(json.dumps)
json.dump=FixDump(json.dump)
if __name__=="__main__":
today=datetime.now()
data={'atime':today, 'greet':'Hello'}
str=json.dumps(data)
print str
通过导入上述模块,我的其他模块以正常的方式(没有指定默认关键字)使用json来序列化包含日期时间对象的数据。datetime序列化器代码会自动为json调用。Dumps和json.dump。
一个非常简单的一行程序解决方案
import json
json.dumps(your_object, default=lambda __o: __o.__dict__)
结束!
下面是一个测试。
import json
from dataclasses import dataclass
@dataclass
class Company:
id: int
name: str
@dataclass
class User:
id: int
name: str
email: str
company: Company
company = Company(id=1, name="Example Ltd")
user = User(id=1, name="John Doe", email="john@doe.net", company=company)
json.dumps(user, default=lambda __o: __o.__dict__)
输出:
{
"id": 1,
"name": "John Doe",
"email": "john@doe.net",
"company": {
"id": 1,
"name": "Example Ltd"
}
}
基于Quinten Cabo的回答:
def sterilize(obj):
"""Make an object more ameniable to dumping as json
"""
if type(obj) in (str, float, int, bool, type(None)):
return obj
elif isinstance(obj, dict):
return {k: sterilize(v) for k, v in obj.items()}
list_ret = []
dict_ret = {}
for a in dir(obj):
if a == '__iter__' and callable(obj.__iter__):
list_ret.extend([sterilize(v) for v in obj])
elif a == '__dict__':
dict_ret.update({k: sterilize(v) for k, v in obj.__dict__.items() if k not in ['__module__', '__dict__', '__weakref__', '__doc__']})
elif a not in ['__doc__', '__module__']:
aval = getattr(obj, a)
if type(aval) in (str, float, int, bool, type(None)):
dict_ret[a] = aval
elif a != '__class__' and a != '__objclass__' and isinstance(aval, type):
dict_ret[a] = sterilize(aval)
if len(list_ret) == 0:
if len(dict_ret) == 0:
return repr(obj)
return dict_ret
else:
if len(dict_ret) == 0:
return list_ret
return (list_ret, dict_ret)
区别在于
Works for any iterable instead of just list and tuple (it works for NumPy arrays, etc.) Works for dynamic types (ones that contain a __dict__). Includes native types float and None so they don't get converted to string. Classes that have __dict__ and members will mostly work (if the __dict__ and member names collide, you will only get one - likely the member) Classes that are lists and have members will look like a tuple of the list and a dictionary Python3 (that isinstance() call may be the only thing that needs changing)