我喜欢Onur的答案，但会扩展到包括一个可选的toJSON()方法，用于对象序列化自己:

def dumper(obj):
    try:
        return obj.toJSON()
    except:
        return obj.__dict__
print json.dumps(some_big_object, default=dumper, indent=2)

对于更复杂的类，您可以考虑使用jsonpickle工具:

jsonpickle is a Python library for serialization and deserialization of complex Python objects to and from JSON. The standard Python libraries for encoding Python into JSON, such as the stdlib’s json, simplejson, and demjson, can only handle Python primitives that have a direct JSON equivalent (e.g. dicts, lists, strings, ints, etc.). jsonpickle builds on top of these libraries and allows more complex data structures to be serialized to JSON. jsonpickle is highly configurable and extendable–allowing the user to choose the JSON backend and add additional backends.

(链接到PyPi上的jsonpickle)

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。

任何人都想在没有外部库的情况下使用基本转换，这只是如何使用以下方式覆盖自定义类的__iter__ & __str__函数。

class JSONCustomEncoder(json.JSONEncoder):
    def default(self, obj):
        return obj.__dict__


class Student:
    def __init__(self, name: str, slug: str):
        self.name = name
        self.age = age

    def __iter__(self):
        yield from {
            "name": self.name,
            "age": self.age,
        }.items()

    def __str__(self):
        return json.dumps(
            self.__dict__, cls=JSONCustomEncoder, ensure_ascii=False
        )

通过在dict()中进行包装来使用该对象，从而保留数据。

s = Student("aman", 24)
dict(s)

要添加另一个选项:您可以使用attrs包和asdict方法。

class ObjectEncoder(JSONEncoder):
    def default(self, o):
        return attr.asdict(o)

json.dumps(objects, cls=ObjectEncoder)

然后再转换回去

def from_json(o):
    if '_obj_name' in o:
        type_ = o['_obj_name']
        del o['_obj_name']
        return globals()[type_](**o)
    else:
        return o

data = JSONDecoder(object_hook=from_json).decode(data)

类看起来像这样

@attr.s
class Foo(object):
    x = attr.ib()
    _obj_name = attr.ib(init=False, default='Foo')

我喜欢Onur的答案，但会扩展到包括一个可选的toJSON()方法，用于对象序列化自己:

def dumper(obj):
    try:
        return obj.toJSON()
    except:
        return obj.__dict__
print json.dumps(some_big_object, default=dumper, indent=2)