python - 如何更改可序列化 python 对象的 json 编码行为？

Question

更改非 JSON 可序列化对象的格式很容易，例如 datetime.datetime。

出于调试目的，我的要求是改变一些自定义对象从基础对象扩展的方式，例如dictand list，以 json 格式序列化。代码 ：

import datetime
import json

def json_debug_handler(obj):
    print("object received:")
    print type(obj)
    print("\n\n")
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,mDict):
        return {'orig':obj , 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        return {'orig':obj, 'attrs': vars(obj)}
    else:
        return None


class mDict(dict):
    pass


class mList(list):
    pass


def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games , 'scores' : scores , 'date': datetime.datetime.now() }
    print(json.dumps(test_json,default=json_debug_handler))

if __name__ == '__main__':
    test_debug_json()

演示：http: //ideone.com/hQJnLy

输出：

{"date": "2013-05-07T01:03:13.098727", "games": ["mario", "contra", "tetris"], "scores": {"pk": 45, "dp": 10}}

期望的输出：

{"date": "2013-05-07T01:03:13.098727", "games": { "orig": ["mario", "contra", "tetris"] ,"attrs" : { "src":"console"}} , "scores": { "orig": {"pk": 45, "dp": 10},"attrs": "processed":"unprocessed }}

default处理程序不适用于可序列化对象吗？如果没有，我怎样才能覆盖它，而不向扩展类添加 toJSON 方法？

此外，还有这个版本的 JSON 编码器不起作用：

class JsonDebugEncoder(json.JSONEncoder):
    def default(self,obj):
        if  isinstance(obj, datetime.datetime):
            return obj.isoformat()
        elif isinstance(obj,mDict):
            return {'orig':obj , 'attrs': vars(obj)}
        elif isinstance(obj,mList):
            return {'orig':obj, 'attrs': vars(obj)}
        else:
            return json.JSONEncoder.default(self, obj)

如果pickle,__getstate__,__setstate__,在 pickle.loads 对象上使用 json.dumps 进行破解，我也对此持开放态度，我尝试过，但没有奏效。

Answer 1

似乎要在给定的限制下实现您想要的行为，您必须深入研究一下JSONEncoder课程。下面我写了一个自定义JSONEncoder，它覆盖了iterencode将自定义isinstance方法传递给_make_iterencode. 它不是世界上最干净的东西，但考虑到选项，它似乎是最好的，并且它将定制化程度降至最低。

# customencoder.py
from json.encoder import (_make_iterencode, JSONEncoder,
                          encode_basestring_ascii, FLOAT_REPR, INFINITY,
                          c_make_encoder, encode_basestring)


class CustomObjectEncoder(JSONEncoder):

    def iterencode(self, o, _one_shot=False):
        """
        Most of the original method has been left untouched.

        _one_shot is forced to False to prevent c_make_encoder from
        being used. c_make_encoder is a funcion defined in C, so it's easier
        to avoid using it than overriding/redefining it.

        The keyword argument isinstance for _make_iterencode has been set
        to self.isinstance. This allows for a custom isinstance function
        to be defined, which can be used to defer the serialization of custom
        objects to the default method.
        """
        # Force the use of _make_iterencode instead of c_make_encoder
        _one_shot = False

        if self.check_circular:
            markers = {}
        else:
            markers = None
        if self.ensure_ascii:
            _encoder = encode_basestring_ascii
        else:
            _encoder = encode_basestring
        if self.encoding != 'utf-8':
            def _encoder(o, _orig_encoder=_encoder, _encoding=self.encoding):
                if isinstance(o, str):
                    o = o.decode(_encoding)
                return _orig_encoder(o)

        def floatstr(o, allow_nan=self.allow_nan,
                     _repr=FLOAT_REPR, _inf=INFINITY, _neginf=-INFINITY):
            if o != o:
                text = 'NaN'
            elif o == _inf:
                text = 'Infinity'
            elif o == _neginf:
                text = '-Infinity'
            else:
                return _repr(o)

            if not allow_nan:
                raise ValueError(
                    "Out of range float values are not JSON compliant: " +
                    repr(o))

            return text

        # Instead of forcing _one_shot to False, you can also just
        # remove the first part of this conditional statement and only
        # call _make_iterencode
        if (_one_shot and c_make_encoder is not None
                and self.indent is None and not self.sort_keys):
            _iterencode = c_make_encoder(
                markers, self.default, _encoder, self.indent,
                self.key_separator, self.item_separator, self.sort_keys,
                self.skipkeys, self.allow_nan)
        else:
            _iterencode = _make_iterencode(
                markers, self.default, _encoder, self.indent, floatstr,
                self.key_separator, self.item_separator, self.sort_keys,
                self.skipkeys, _one_shot, isinstance=self.isinstance)
        return _iterencode(o, 0)

您现在可以将其子类化，CustomObjectEncoder以便正确序列化您的自定义对象。它还可以做一些很酷的CustomObjectEncoder事情，比如处理嵌套对象。

# test.py
import json
import datetime
from customencoder import CustomObjectEncoder


class MyEncoder(CustomObjectEncoder):

    def isinstance(self, obj, cls):
        if isinstance(obj, (mList, mDict)):
            return False
        return isinstance(obj, cls)

    def default(self, obj):
        """
        Defines custom serialization.

        To avoid circular references, any object that will always fail
        self.isinstance must be converted to something that is
        deserializable here.
        """
        if isinstance(obj, datetime.datetime):
            return obj.isoformat()
        elif isinstance(obj, mDict):
            return {"orig": dict(obj), "attrs": vars(obj)}
        elif isinstance(obj, mList):
            return {"orig": list(obj), "attrs": vars(obj)}
        else:
            return None


class mList(list):
    pass


class mDict(dict):
    pass


def main():
    zelda = mList(['zelda'])
    zelda.src = "oldschool"
    games = mList(['mario', 'contra', 'tetris', zelda])
    games.src = 'console'
    scores = mDict({'dp': 10, 'pk': 45})
    scores.processed = "unprocessed"
    test_json = {'games': games, 'scores': scores,
                 'date': datetime.datetime.now()}
    print(json.dumps(test_json, cls=MyEncoder))

if __name__ == '__main__':
    main()

Answer 2

FastTurtle 的答案可能是一个更清洁的解决方案。

根据我的问题/答案中解释的技术，这与您想要的很接近：覆盖继承的默认支持对象的嵌套 JSON 编码，如字典、列表

import json
import datetime


class mDict(dict):
    pass


class mList(list):
    pass


class JsonDebugEncoder(json.JSONEncoder):
    def _iterencode(self, o, markers=None):
        if isinstance(o, mDict):
            yield '{"__mDict__": '
            # Encode dictionary
            yield '{"orig": '
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers):
                yield chunk
            yield ', '
            # / End of Encode dictionary
            # Encode attributes
            yield '"attr": '
            for key, value in o.__dict__.iteritems():
                yield '{"' + key + '": '
                for chunk in super(JsonDebugEncoder, self)._iterencode(value, markers):
                    yield chunk
                yield '}'
            yield '}'
            # / End of Encode attributes
            yield '}'
        elif isinstance(o, mList):
            yield '{"__mList__": '
            # Encode list
            yield '{"orig": '
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers):
                yield chunk
            yield ', '
            # / End of Encode list
            # Encode attributes
            yield '"attr": '
            for key, value in o.__dict__.iteritems():
                yield '{"' + key + '": '
                for chunk in super(JsonDebugEncoder, self)._iterencode(value, markers):
                    yield chunk
                yield '}'
            yield '}'
            # / End of Encode attributes
            yield '}'
        else:
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers=markers):
                yield chunk

    def default(self, obj):
        if isinstance(obj, datetime.datetime):
            return obj.isoformat()


class JsonDebugDecoder(json.JSONDecoder):
    def decode(self, s):
        obj = super(JsonDebugDecoder, self).decode(s)
        obj = self.recursiveObjectDecode(obj)
        return obj

    def recursiveObjectDecode(self, obj):
        if isinstance(obj, dict):
            decoders = [("__mList__", self.mListDecode),
                        ("__mDict__", self.mDictDecode)]
            for placeholder, decoder in decoders:
                if placeholder in obj:                  # We assume it's supposed to be converted
                    return decoder(obj[placeholder])
                else:
                    for k in obj:
                        obj[k] = self.recursiveObjectDecode(obj[k])
        elif isinstance(obj, list):
            for x in range(len(obj)):
                obj[x] = self.recursiveObjectDecode(obj[x])
        return obj

    def mDictDecode(self, o):
        res = mDict()
        for key, value in o['orig'].iteritems():
            res[key] = self.recursiveObjectDecode(value)
        for key, value in o['attr'].iteritems():
            res.__dict__[key] = self.recursiveObjectDecode(value)
        return res

    def mListDecode(self, o):
        res = mList()
        for value in o['orig']:
            res.append(self.recursiveObjectDecode(value))
        for key, value in o['attr'].iteritems():
            res.__dict__[key] = self.recursiveObjectDecode(value)
        return res


def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games, 'scores' : scores ,'date': datetime.datetime.now() }
    jsonDump = json.dumps(test_json, cls=JsonDebugEncoder)
    print jsonDump
    test_pyObject = json.loads(jsonDump, cls=JsonDebugDecoder)
    print test_pyObject

if __name__ == '__main__':
    test_debug_json()

这导致：

{"date": "2013-05-06T22:28:08.967000", "games": {"__mList__": {"orig": ["mario", "contra", "tetris"], "attr": {"src": "console"}}}, "scores": {"__mDict__": {"orig": {"pk": 45, "dp": 10}, "attr": {"processed": "unprocessed"}}}}

通过这种方式，您可以对其进行编码并将其解码回它来自的 python 对象。

编辑：

这是一个实际上将其编码为您想要的输出并且也可以对其进行解码的版本。每当字典包含“orig”和“attr”时，它将检查“orig”是否包含字典或列表，如果是，它将分别将对象转换回mDict或mList。

import json
import datetime


class mDict(dict):
    pass


class mList(list):
    pass


class JsonDebugEncoder(json.JSONEncoder):
    def _iterencode(self, o, markers=None):
        if isinstance(o, mDict):    # Encode mDict
            yield '{"orig": '
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers):
                yield chunk
            yield ', '
            yield '"attr": '
            for key, value in o.__dict__.iteritems():
                yield '{"' + key + '": '
                for chunk in super(JsonDebugEncoder, self)._iterencode(value, markers):
                    yield chunk
                yield '}'
            yield '}'
            # / End of Encode attributes
        elif isinstance(o, mList):    # Encode mList
            yield '{"orig": '
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers):
                yield chunk
            yield ', '
            yield '"attr": '
            for key, value in o.__dict__.iteritems():
                yield '{"' + key + '": '
                for chunk in super(JsonDebugEncoder, self)._iterencode(value, markers):
                    yield chunk
                yield '}'
            yield '}'
        else:
            for chunk in super(JsonDebugEncoder, self)._iterencode(o, markers=markers):
                yield chunk

    def default(self, obj):
        if isinstance(obj, datetime.datetime):    # Encode datetime
            return obj.isoformat()


class JsonDebugDecoder(json.JSONDecoder):
    def decode(self, s):
        obj = super(JsonDebugDecoder, self).decode(s)
        obj = self.recursiveObjectDecode(obj)
        return obj

    def recursiveObjectDecode(self, obj):
        if isinstance(obj, dict):
            if "orig" in obj and "attr" in obj and isinstance(obj["orig"], list):
                return self.mListDecode(obj)
            elif "orig" in obj and "attr" in obj and isinstance(obj['orig'], dict):
                return self.mDictDecode(obj)
            else:
                for k in obj:
                    obj[k] = self.recursiveObjectDecode(obj[k])
        elif isinstance(obj, list):
            for x in range(len(obj)):
                obj[x] = self.recursiveObjectDecode(obj[x])
        return obj

    def mDictDecode(self, o):
        res = mDict()
        for key, value in o['orig'].iteritems():
            res[key] = self.recursiveObjectDecode(value)
        for key, value in o['attr'].iteritems():
            res.__dict__[key] = self.recursiveObjectDecode(value)
        return res

    def mListDecode(self, o):
        res = mList()
        for value in o['orig']:
            res.append(self.recursiveObjectDecode(value))
        for key, value in o['attr'].iteritems():
            res.__dict__[key] = self.recursiveObjectDecode(value)
        return res


def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games, 'scores' : scores ,'date': datetime.datetime.now() }
    jsonDump = json.dumps(test_json, cls=JsonDebugEncoder)
    print jsonDump
    test_pyObject = json.loads(jsonDump, cls=JsonDebugDecoder)
    print test_pyObject
    print test_pyObject['games'].src

if __name__ == '__main__':
    test_debug_json()

以下是有关输出的更多信息：

# Encoded
{"date": "2013-05-06T22:41:35.498000", "games": {"orig": ["mario", "contra", "tetris"], "attr": {"src": "console"}}, "scores": {"orig": {"pk": 45, "dp": 10}, "attr": {"processed": "unprocessed"}}}

# Decoded ('games' contains the mList with the src attribute and 'scores' contains the mDict processed attribute)
# Note that printing the python objects doesn't directly show the processed and src attributes, as seen below.
{u'date': u'2013-05-06T22:41:35.498000', u'games': [u'mario', u'contra', u'tetris'], u'scores': {u'pk': 45, u'dp': 10}}

对不起，任何不好的命名约定，这是一个快速的设置。;)

注意：日期时间不会被解码回 python 表示。可以通过检查任何称为“日期”并包含日期时间的有效字符串表示的字典键来实现这一点。

Answer 3

正如其他人已经指出的那样，默认处理程序仅被调用为不是可识别类型之一的值。对于这个问题，我建议的解决方案是预处理要序列化的对象，递归列表、元组和字典，但将所有其他值包装在自定义类中。

像这样的东西：

def debug(obj):
    class Debug:
        def __init__(self,obj):
            self.originalObject = obj
    if obj.__class__ == list:
        return [debug(item) for item in obj]
    elif obj.__class__ == tuple:
        return (debug(item) for item in obj)
    elif obj.__class__ == dict:
        return dict((key,debug(obj[key])) for key in obj)
    else:
        return Debug(obj)

在将对象传递给json.dumps之前，您将调用此函数，如下所示：

test_json = debug(test_json)
print(json.dumps(test_json,default=json_debug_handler))

请注意，此代码正在检查其类与列表、元组或字典完全匹配的对象，因此从这些类型扩展的任何自定义对象都将被包装而不是解析。因此，常规列表、元组和字典将照常进行序列化，但所有其他值将传递给默认处理程序。

所有这一切的最终结果是，保证到达默认处理程序的每个值都被包装在这些 Debug 类之一中。所以你要做的第一件事就是提取原始对象，如下所示：

obj = obj.originalObject

然后，您可以检查原始对象的类型并处理需要特殊处理的类型。对于其他所有内容，您应该只返回原始对象（因此处理程序的最后返回不应是return objnot return None）。

def json_debug_handler(obj):
    obj = obj.originalObject      # Add this line
    print("object received:")
    print type(obj)
    print("\n\n")
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,mDict):
        return {'orig':obj, 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        return {'orig':obj, 'attrs': vars(obj)}
    else:
        return obj                # Change this line

请注意，此代码不检查不可序列化的值。这些将通过 final return obj，然后将被序列化程序拒绝并再次传递回默认处理程序 - 只是这次没有 Debug 包装器。

如果您需要处理这种情况，您可以在处理程序的顶部添加一个检查，如下所示：

if not hasattr(obj, 'originalObject'):
    return None

Ideone 演示：http: //ideone.com/tOloNq

Answer 4

只有当被转储的节点本身不是可序列化的并且您的 mDict 类按原样序列化时，才会调用默认函数。这是一个小演示，显示何时调用默认值以及何时不调用：

import json

def serializer(obj):
    print 'serializer called'
    return str(obj)

class mDict(dict):
    pass

class mSet(set):
    pass

d = mDict(dict(a=1))
print json.dumps(d, default=serializer)

s = mSet({1, 2, 3,})
print json.dumps(s, default=serializer)

和输出：

{"a": 1}
serializer called
"mSet([1, 2, 3])"

请注意，集合本身不是可序列化的，但 dicts 是。

由于您的 m___ 类是可序列化的，因此您的处理程序永远不会被调用。

更新#1 -----

您可以更改 JSON 编码器代码。如何执行此操作的详细信息取决于您使用的 JSON 实现。例如在 simplejson 中，相关代码是这样的，在 encode.py 中：

def _iterencode(o, _current_indent_level):
    ...
        for_json = _for_json and getattr(o, 'for_json', None)
        if for_json and callable(for_json):
            ...
        elif isinstance(o, list):
            ...
        else:
            _asdict = _namedtuple_as_object and getattr(o, '_asdict', None)
            if _asdict and callable(_asdict):
                for chunk in _iterencode_dict(_asdict(),
                        _current_indent_level):
                    yield chunk
            elif (_tuple_as_array and isinstance(o, tuple)):
                ...
            elif isinstance(o, dict):
                ...
            elif _use_decimal and isinstance(o, Decimal):
                ...
            else:
                ...
                o = _default(o)
                for chunk in _iterencode(o, _current_indent_level):
                    yield chunk
                ...

换句话说，只有当被编码的节点不是可识别的基本类型之一时，才会调用默认行为。您可以通过以下几种方式之一覆盖它：

1 -- 子类 JSONEncoder 就像您在上面所做的那样，但在其初始化程序中添加一个参数，该参数指定要使用的函数来代替标准 _make_iterencode，您可以在其中添加一个测试，该测试将为满足您的标准的类调用默认值。这是一种干净的方法，因为您没有更改 JSON 模块，但您将重复原始 _make_iterencode 中的大量代码。（此方法的其他变体包括猴子补丁 _make_iterencode 或其子函数 _iterencode_dict）。

2 -- 更改 JSON 模块源，并使用__debug__常量更改行为：

def _iterencode(o, _current_indent_level):
    ...
        for_json = _for_json and getattr(o, 'for_json', None)
        if for_json and callable(for_json):
            ...
        elif isinstance(o, list):
            ...
        ## added code below
        elif __debug__:
            o = _default(o)
            for chunk in _iterencode(o, _current_indent_level):
                yield chunk
        ## added code above
        else:
            ...

理想情况下，JSONEncoder 类会提供一个参数来指定“对所有类型使用默认值”，但事实并非如此。以上是一个简单的一次性更改，可以满足您的需求。

Answer 5

试试下面的。它产生你想要的输出并且看起来相对简单。与您的编码器类的唯一真正区别是我们应该覆盖解码和编码方法（因为编码器知道如何处理的类型仍然调用后者）。

import json
import datetime

class JSONDebugEncoder(json.JSONEncoder):
    # transform objects known to JSONEncoder here
    def encode(self, o, *args, **kw):
        for_json = o
        if isinstance(o, mDict):
            for_json = { 'orig' : o, 'attrs' : vars(o) }
        elif isinstance(o, mList):
            for_json = { 'orig' : o, 'attrs' : vars(o) }
        return super(JSONDebugEncoder, self).encode(for_json, *args, **kw)

    # handle objects not known to JSONEncoder here
    def default(self, o, *args, **kw):
        if isinstance(o, datetime.datetime):
            return o.isoformat()
        else:
            return super(JSONDebugEncoder, self).default(o, *args, **kw)


class mDict(dict):
    pass

class mList(list):
    pass

def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games , 'scores' : scores , 'date': datetime.datetime.now() }
    print(json.dumps(test_json,cls=JSONDebugEncoder))

if __name__ == '__main__':
    test_debug_json()

Answer 6

如果您将这些定义为覆盖__instancecheck__：

def strict_check(builtin):
    '''creates a new class from the builtin whose instance check
    method can be overridden to renounce particular types'''
    class BuiltIn(type):
        def __instancecheck__(self, other):
            print 'instance', self, type(other), other
            if type(other) in strict_check.blacklist:
                return False
            return builtin.__instancecheck__(other)
    # construct a class, whose instance check method is known.
    return BuiltIn('strict_%s' % builtin.__name__, (builtin,), dict())

# for safety, define it here.
strict_check.blacklist = ()

json.encoder然后像这样修补覆盖_make_iterencode.func_defaults：

# modify json encoder to use some new list/dict attr.
import json.encoder
# save old stuff, never know when you need it.
old_defaults = json.encoder._make_iterencode.func_defaults
old_encoder = json.encoder.c_make_encoder
encoder_defaults = list(json.encoder._make_iterencode.func_defaults)
for index, default in enumerate(encoder_defaults):
    if default in (list, dict):
        encoder_defaults[index] = strict_check(default)

# change the defaults for _make_iterencode.
json.encoder._make_iterencode.func_defaults = tuple(encoder_defaults)
# disable C extension.
json.encoder.c_make_encoder = None

...您的示例几乎可以逐字进行：

import datetime
import json

def json_debug_handler(obj):
    print("object received:")
    print type(obj)
    print("\n\n")
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,mDict):
        # degrade obj to more primitive dict()
        # to avoid cycles in the encoding.
        return {'orig': dict(obj) , 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        # degrade obj to more primitive list()
        # to avoid cycles in the encoding.
        return {'orig': list(obj), 'attrs': vars(obj)}
    else:
        return None


class mDict(dict):
    pass


class mList(list):
    pass

# set the stuff we want to process differently.
strict_check.blacklist = (mDict, mList)

def test_debug_json():
    global test_json
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games , 'scores' : scores , 'date': datetime.datetime.now() }
    print(json.dumps(test_json,default=json_debug_handler))

if __name__ == '__main__':
    test_debug_json()

我需要改变的是确保没有周期：

    elif isinstance(obj,mDict):
        # degrade obj to more primitive dict()
        # to avoid cycles in the encoding.
        return {'orig': dict(obj) , 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        # degrade obj to more primitive list()
        # to avoid cycles in the encoding.
        return {'orig': list(obj), 'attrs': vars(obj)}

并将其添加到之前的某处test_debug_json：

# set the stuff we want to process differently.
strict_check.blacklist = (mDict, mList)

这是我的控制台输出：

>>> test_debug_json()
instance <class '__main__.strict_list'> <type 'dict'> {'date': datetime.datetime(2013, 7, 17, 12, 4, 40, 950637), 'games': ['mario', 'contra', 'tetris'], 'scores': {'pk': 45, 'dp': 10}}
instance <class '__main__.strict_dict'> <type 'dict'> {'date': datetime.datetime(2013, 7, 17, 12, 4, 40, 950637), 'games': ['mario', 'contra', 'tetris'], 'scores': {'pk': 45, 'dp': 10}}
instance <class '__main__.strict_list'> <type 'datetime.datetime'> 2013-07-17 12:04:40.950637
instance <class '__main__.strict_dict'> <type 'datetime.datetime'> 2013-07-17 12:04:40.950637
instance <class '__main__.strict_list'> <type 'datetime.datetime'> 2013-07-17 12:04:40.950637
instance <class '__main__.strict_dict'> <type 'datetime.datetime'> 2013-07-17 12:04:40.950637
object received:
<type 'datetime.datetime'>



instance <class '__main__.strict_list'> <class '__main__.mList'> ['mario', 'contra', 'tetris']
instance <class '__main__.strict_dict'> <class '__main__.mList'> ['mario', 'contra', 'tetris']
instance <class '__main__.strict_list'> <class '__main__.mList'> ['mario', 'contra', 'tetris']
instance <class '__main__.strict_dict'> <class '__main__.mList'> ['mario', 'contra', 'tetris']
object received:
<class '__main__.mList'>



instance <class '__main__.strict_list'> <type 'dict'> {'attrs': {'src': 'console'}, 'orig': ['mario', 'contra', 'tetris']}
instance <class '__main__.strict_dict'> <type 'dict'> {'attrs': {'src': 'console'}, 'orig': ['mario', 'contra', 'tetris']}
instance <class '__main__.strict_list'> <type 'dict'> {'src': 'console'}
instance <class '__main__.strict_dict'> <type 'dict'> {'src': 'console'}
instance <class '__main__.strict_list'> <type 'list'> ['mario', 'contra', 'tetris']
instance <class '__main__.strict_list'> <class '__main__.mDict'> {'pk': 45, 'dp': 10}
instance <class '__main__.strict_dict'> <class '__main__.mDict'> {'pk': 45, 'dp': 10}
instance <class '__main__.strict_list'> <class '__main__.mDict'> {'pk': 45, 'dp': 10}
instance <class '__main__.strict_dict'> <class '__main__.mDict'> {'pk': 45, 'dp': 10}
object received:
<class '__main__.mDict'>



instance <class '__main__.strict_list'> <type 'dict'> {'attrs': {'processed': 'unprocessed'}, 'orig': {'pk': 45, 'dp': 10}}
instance <class '__main__.strict_dict'> <type 'dict'> {'attrs': {'processed': 'unprocessed'}, 'orig': {'pk': 45, 'dp': 10}}
instance <class '__main__.strict_list'> <type 'dict'> {'processed': 'unprocessed'}
instance <class '__main__.strict_dict'> <type 'dict'> {'processed': 'unprocessed'}
instance <class '__main__.strict_list'> <type 'dict'> {'pk': 45, 'dp': 10}
instance <class '__main__.strict_dict'> <type 'dict'> {'pk': 45, 'dp': 10}
{"date": "2013-07-17T12:04:40.950637", "games": {"attrs": {"src": "console"}, "orig": ["mario", "contra", "tetris"]}, "scores": {"attrs": {"processed": "unprocessed"}, "orig": {"pk": 45, "dp": 10}}}

Answer 7

为什么你不能创建一个新的对象类型来传递给编码器？尝试：

class MStuff(object):
    def __init__(self, content):
        self.content = content

class mDict(MStuff):
    pass

class mList(MStuff):
    pass

def json_debug_handler(obj):
    print("object received:")
    print(type(obj))
    print("\n\n")
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,MStuff):
        attrs = {}
        for key in obj.__dict__:
            if not ( key.startswith("_") or key == "content"):
                attrs[key] = obj.__dict__[key]

        return {'orig':obj.content , 'attrs': attrs}
    else:
        return None

如果需要，您可以在 mDict 和 mList 上添加验证。

Answer 8

如果你能够改变json.dumps调用方式。您可以在 JSON 编码器使用它之前完成所有所需的处理。此版本不使用任何类型的复制，并将就地编辑结构。copy()如果需要，您可以添加。

import datetime
import json
import collections


def json_debug_handler(obj):
    print("object received:")
    print type(obj)
    print("\n\n")
    if isinstance(obj, collections.Mapping):
        for key, value in obj.iteritems():
            if isinstance(value, (collections.Mapping, collections.MutableSequence)):
                value = json_debug_handler(value)

            obj[key] = convert(value)
    elif isinstance(obj, collections.MutableSequence):
        for index, value in enumerate(obj):
            if isinstance(value, (collections.Mapping, collections.MutableSequence)):
                value = json_debug_handler(value)

            obj[index] = convert(value)
    return obj

def convert(obj):
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,mDict):
        return {'orig':obj , 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        return {'orig':obj, 'attrs': vars(obj)}
    else:
        return obj


class mDict(dict):
    pass


class mList(list):
    pass


def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "qunprocessed"
    test_json = { 'games' : games , 'scores' : scores , 'date': datetime.datetime.now() }
    print(json.dumps(json_debug_handler(test_json)))

if __name__ == '__main__':
    test_debug_json()

在将json_debug_handler要序列化的对象传递给json.dumps. 使用此模式，您还可以轻松地反转更改和/或添加额外的转换规则。

编辑：

如果您无法更改json.dumps调用方式，则可以随时对其进行monkeypatch 以执行您想要的操作。比如这样做：

json.dumps = lambda obj, *args, **kwargs: json.dumps(json_debug_handler(obj), *args, **kwargs)

Answer 9

我们可以只预处理test_json，使其适合您的要求吗？操作 python dict 比编写无用的 Encode 更容易。

import datetime
import json
class mDict(dict):
    pass

class mList(list):
    pass

def prepare(obj):
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj, mDict):
        return {'orig':obj , 'attrs': vars(obj)}
    elif isinstance(obj, mList):
        return {'orig':obj, 'attrs': vars(obj)}
    else:
        return obj
def preprocessor(toJson):
    ret ={}
    for key, value in toJson.items():
        ret[key] = prepare(value)
    return ret
if __name__ == '__main__':
    def test_debug_json():
        games = mList(['mario','contra','tetris'])
        games.src = 'console'
        scores = mDict({'dp':10,'pk':45})
        scores.processed = "unprocessed"
        test_json = { 'games' : games, 'scores' : scores , 'date': datetime.datetime.now() }
        print(json.dumps(preprocessor(test_json)))
    test_debug_json()

Answer 10

您应该能够覆盖JSONEncoder.encode()：

class MyEncoder(JSONEncoder):
  def encode(self, o):
    if isinstance(o, dict):
      # directly call JSONEncoder rather than infinite-looping through self.encode()
      return JSONEncoder.encode(self, {'orig': o, 'attrs': vars(o)})
    elif isinstance(o, list):
      return JSONEncoder.encode(self, {'orig': o, 'attrs': vars(o)})
    else:
      return JSONEncoder.encode(self, o)

然后如果你想将它修补到json.dumps它看起来从http://docs.buildbot.net/latest/reference/json-pysrc.html就像你需要json._default_encoder用一个MyEncoder.

Answer 11

Python 3 的简化（仅在 3.9 上测试）：

from json.encoder import (_make_iterencode, JSONEncoder,
                          encode_basestring_ascii, INFINITY,
                          encode_basestring)

class CustomObjectEncoder(JSONEncoder):

    def iterencode(self, o, _one_shot=False):
        """Encode the given object and yield each string
        representation as available.

        For example::

            for chunk in JSONEncoder().iterencode(bigobject):
                mysocket.write(chunk)
                
        Change from json.encoder.JSONEncoder.iterencode is setting
        _one_shot=False and isinstance=self.isinstance
        in call to `_make_iterencode`.
        And not using `c_make_encoder`.

        """
        if self.check_circular:
            markers = {}
        else:
            markers = None
        if self.ensure_ascii:
            _encoder = encode_basestring_ascii
        else:
            _encoder = encode_basestring

        def floatstr(o, allow_nan=self.allow_nan,
                _repr=float.__repr__, _inf=INFINITY, _neginf=-INFINITY):
            # Check for specials.  Note that this type of test is processor
            # and/or platform-specific, so do tests which don't depend on the
            # internals.

            if o != o:
                text = 'NaN'
            elif o == _inf:
                text = 'Infinity'
            elif o == _neginf:
                text = '-Infinity'
            else:
                return _repr(o)

            if not allow_nan:
                raise ValueError(
                    "Out of range float values are not JSON compliant: " +
                    repr(o))

            return text

        _iterencode = _make_iterencode(
                markers, self.default, _encoder, self.indent, floatstr,
                self.key_separator, self.item_separator, self.sort_keys,
                self.skipkeys, _one_shot=False, isinstance=self.isinstance)
        return _iterencode(o, 0)

示例子类：

import datetime

from rdflib.term import Literal, BNode

class RDFTermEncoder(CustomObjectEncoder):
    def isinstance(self, o, cls):
        if isinstance(o, (Literal, BNode)):
            return False
        return isinstance(o, cls)
    def default(self, o):
        if isinstance(o, Literal):
            rv = {"value": o.value}
            if o.datatype is not None:
                rv["datatype"] = o.datatype
            if o.language is not None:
                rv["lang"] = o.language
            return rv
        if isinstance(o, BNode):
            return "http://localhost/bnode/" + str(o)
        if isinstance(o, datetime.datetime):
            return o.isoformat()
        if isinstance(o, datetime.date):
            return str(o)
        # Let the base class default method raise the TypeError
        return super().default(o)

我刚刚成功地将它用于我的工作

db_json = json.loads(json.dumps(db_custom, cls=RDFTermEncoder))

谢谢大家在这个线程！

Answer 12

如果您只是在寻找序列化而不是反序列化，那么您可以在将对象发送到json.dumps. 见下面的例子

import datetime
import json


def is_inherited_from(obj, objtype):
    return isinstance(obj, objtype) and not type(obj).__mro__[0] == objtype


def process_object(data):
    if isinstance(data, list):
        if is_inherited_from(data, list):
            return process_object({"orig": list(data), "attrs": vars(data)})
        new_data = []
        for d in data:
            new_data.append(process_object(d))
    elif isinstance(data, tuple):
        if is_inherited_from(data, tuple):
            return process_object({"orig": tuple(data), "attrs": vars(data)})
        new_data = []
        for d in data:
            new_data.append(process_object(d))
        return tuple(new_data)
    elif isinstance(data, dict):
        if is_inherited_from(data, dict):
            return process_object({"orig": list(data), "attrs": vars(data)})
        new_data = {}
        for k, v in data.items():
            new_data[k] = process_object(v)
    else:
        return data
    return new_data


def json_debug_handler(obj):
    print("object received:")
    print("\n\n")
    if isinstance(obj, datetime.datetime):
        return obj.isoformat()


class mDict(dict):
    pass


class mList(list):
    pass


def test_debug_json():
    games = mList(['mario', 'contra', 'tetris'])
    games.src = 'console'
    scores = mDict({'dp': 10, 'pk': 45})
    scores.processed = "unprocessed"
    test_json = {'games': games, 'scores': scores, 'date': datetime.datetime.now()}
    new_object = process_object(test_json)
    print(json.dumps(new_object, default=json_debug_handler))


if __name__ == '__main__':
    test_debug_json()

同样的输出是

{"games": {"orig": ["mario", "contra", "tetris"], "attrs": {"src": "console"}}, "scores": {"orig": [" dp”，“pk”]，“attrs”：{“已处理”：“未处理”}}，“日期”：“2018-01-24T12:59:36.581689”}

也可以覆盖 JSONEncoder，但由于它使用嵌套方法，它会很复杂并且需要下面讨论的技术

你可以修补 *just* 一个带有闭包的嵌套函数，还是必须重复整个外部函数？

既然你想保持简单，我不建议走那条路

Answer 13

我尝试更改默认解析器优先级并更改默认迭代器输出以实现您的目的。

1. 更改默认解析器优先级，在所有标准类型验证之前执行：

   继承 json.JSONEncoder 并覆盖该iterencode()方法。

   所有值都应该由ValueWrapper类型包装，避免这些值被默认的标准解析器解析。

2. 更改默认迭代器输出；

   实现三个自定义包装类ValueWrapper、ListWrapper和DictWrapper。ListWrapper 实现__iter__()和 DictWrapper 实现__iter__(),items()和iteritems().

import datetime
import json

class DebugJsonEncoder(json.JSONEncoder):
    def iterencode(self, o, _one_shot=False):
        default_resolver = self.default
        # Rewrites the default resolve, self.default(), with the custom resolver.
        # It will process the Wrapper classes
        def _resolve(o):
            if isinstance(o, ValueWrapper):
                # Calls custom resolver precede others. Due to the _make_iterencode()
                # call the custom resolver following by all standard type verifying 
                # failed. But we want custom resolver can be executed by all standard 
                # verifying.
                # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L442
                result = default_resolver(o.data)
                if (o.data is not None) and (result is not None):
                    return result
                elif isinstance(o.data, (list, tuple)):
                    return ListWrapper(o.data)
                elif isinstance(o.data, dict):
                    return DictWrapper(o.data)
                else:
                    return o.data
            else:
                return default_resolver(o)

        # re-assign the default resolver self.default with custom resolver.
        # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L161
        self.default = _resolve
        # The input value must be wrapped by ValueWrapper, avoid the values are 
        # resolved by the standard resolvers.
        # The last one arguemnt _one_shot must be False, we want to encode with
        # _make_iterencode().
        # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L259
        return json.JSONEncoder.iterencode(self, _resolve(ValueWrapper(o)), False)


class ValueWrapper():
    """
    a wrapper wrapped the given object
    """

    def __init__(self, o):
        self.data = o

class ListWrapper(ValueWrapper, list):
    """
    a wrapper wrapped the given list
    """

    def __init__(self, o):
        ValueWrapper.__init__(self, o)

    # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L307
    def __iter__(self):
        for chunk in self.data:
            yield ValueWrapper(chunk)

class DictWrapper(ValueWrapper, dict):
    """
    a wrapper wrapped the given dict
    """

    def __init__(self, d):
        dict.__init__(self, d)

    def __iter__(self):
        for key, value in dict.items(self):
            yield key, ValueWrapper(value)

    # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L361
    def items(self):
        for key, value in dict.items(self):
            yield key, ValueWrapper(value)

    # see https://github.com/python/cpython/blob/2.7/Lib/json/encoder.py#L363
    def iteritems(self):
        for key, value in dict.iteritems(self):
            yield key, ValueWrapper(value)


def json_debug_handler(obj):
    print("object received:")
    print type(obj)
    print("\n\n")
    if  isinstance(obj, datetime.datetime):
        return obj.isoformat()
    elif isinstance(obj,mDict):
        return {'orig':obj , 'attrs': vars(obj)}
    elif isinstance(obj,mList):
        return {'orig':obj, 'attrs': vars(obj)}
    else:
        return None


class mDict(dict):
    pass

class mList(list):
    pass


def test_debug_json():
    games = mList(['mario','contra','tetris'])
    games.src = 'console'
    scores = mDict({'dp':10,'pk':45})
    scores.processed = "unprocessed"
    test_json = { 'games' : games , 'scores' : scores , 'date': datetime.datetime.now(), 'default': None}
    print(json.dumps(test_json,cls=DebugJsonEncoder,default=json_debug_handler))

if __name__ == '__main__':
    test_debug_json()