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
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)
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>
>>>
import simplejson
class User(object):
def __init__(self, name, mail):
self.name = name
self.mail = mail
def _asdict(self):
return self.__dict__
print(simplejson.dumps(User('alice', 'alice@mail.com')))
如果使用标准json,则需要定义一个默认函数
import json
def default(o):
return o._asdict()
print(json.dumps(User('alice', 'alice@mail.com'), default=default))
为了在10年前的火灾中再添加一个日志,我还将为这个任务提供数据类向导,假设您使用的是Python 3.6+。这可以很好地用于数据类,这实际上是3.7+版本的python内置模块。
dataclass-wizard库将把对象(及其所有属性递归地)转换为dict,并使用fromdict使反向(反序列化)非常简单。另外,这里是PyPi链接:https://pypi.org/project/dataclass-wizard/。
import dataclass_wizard
import dataclasses
@dataclasses.dataclass
class A:
hello: str
a_field: int
obj = A('world', 123)
a_dict = dataclass_wizard.asdict(obj)
# {'hello': 'world', 'aField': 123}
或者如果你想要一个字符串:
a_str = jsons.dumps(dataclass_wizard.asdict(obj))
或者您的类是否从dataclass_wizard扩展。JSONWizard:
a_str = your_object.to_json()
最后,标准库还支持Union类型的数据类,这基本上意味着可以将dict反序列化为类C1或C2的对象。例如:
from dataclasses import dataclass
from dataclass_wizard import JSONWizard
@dataclass
class Outer(JSONWizard):
class _(JSONWizard.Meta):
tag_key = 'tag'
auto_assign_tags = True
my_string: str
inner: 'A | B' # alternate syntax: `inner: typing.Union['A', 'B']`
@dataclass
class A:
my_field: int
@dataclass
class B:
my_field: str
my_dict = {'myString': 'test', 'inner': {'tag': 'B', 'myField': 'test'}}
obj = Outer.from_dict(my_dict)
# True
assert repr(obj) == "Outer(my_string='test', inner=B(my_field='test'))"
obj.to_json()
# {"myString": "test", "inner": {"myField": "test", "tag": "B"}}
我们经常在日志文件中转储JSON格式的复杂字典。虽然大多数字段携带重要信息,但我们不太关心内置的类对象(例如子进程)。Popen对象)。由于存在这些不可序列化的对象,对json.dumps()的调用会失败。
为了解决这个问题,我构建了一个小函数来转储对象的字符串表示形式,而不是转储对象本身。如果您正在处理的数据结构嵌套太多,您可以指定嵌套的最大级别/深度。
from time import time
def safe_serialize(obj , max_depth = 2):
max_level = max_depth
def _safe_serialize(obj , current_level = 0):
nonlocal max_level
# If it is a list
if isinstance(obj , list):
if current_level >= max_level:
return "[...]"
result = list()
for element in obj:
result.append(_safe_serialize(element , current_level + 1))
return result
# If it is a dict
elif isinstance(obj , dict):
if current_level >= max_level:
return "{...}"
result = dict()
for key , value in obj.items():
result[f"{_safe_serialize(key , current_level + 1)}"] = _safe_serialize(value , current_level + 1)
return result
# If it is an object of builtin class
elif hasattr(obj , "__dict__"):
if hasattr(obj , "__repr__"):
result = f"{obj.__repr__()}_{int(time())}"
else:
try:
result = f"{obj.__class__.__name__}_object_{int(time())}"
except:
result = f"object_{int(time())}"
return result
# If it is anything else
else:
return obj
return _safe_serialize(obj)
由于字典也可以有不可序列化的键,转储它们的类名或对象表示将导致所有键都具有相同的名称,这将抛出错误,因为所有键都需要有唯一的名称,这就是为什么当前时间Since epoch被int(time())附加到对象名称。
可以使用以下具有不同级别/深度的嵌套字典来测试该函数
d = {
"a" : {
"a1" : {
"a11" : {
"a111" : "some_value" ,
"a112" : "some_value" ,
} ,
"a12" : {
"a121" : "some_value" ,
"a122" : "some_value" ,
} ,
} ,
"a2" : {
"a21" : {
"a211" : "some_value" ,
"a212" : "some_value" ,
} ,
"a22" : {
"a221" : "some_value" ,
"a222" : "some_value" ,
} ,
} ,
} ,
"b" : {
"b1" : {
"b11" : {
"b111" : "some_value" ,
"b112" : "some_value" ,
} ,
"b12" : {
"b121" : "some_value" ,
"b122" : "some_value" ,
} ,
} ,
"b2" : {
"b21" : {
"b211" : "some_value" ,
"b212" : "some_value" ,
} ,
"b22" : {
"b221" : "some_value" ,
"b222" : "some_value" ,
} ,
} ,
} ,
"c" : subprocess.Popen("ls -l".split() , stdout = subprocess.PIPE , stderr = subprocess.PIPE) ,
}
执行以下命令将会得到-
print("LEVEL 3")
print(json.dumps(safe_serialize(d , 3) , indent = 4))
print("\n\n\nLEVEL 2")
print(json.dumps(safe_serialize(d , 2) , indent = 4))
print("\n\n\nLEVEL 1")
print(json.dumps(safe_serialize(d , 1) , indent = 4))
结果:
LEVEL 3
{
"a": {
"a1": {
"a11": "{...}",
"a12": "{...}"
},
"a2": {
"a21": "{...}",
"a22": "{...}"
}
},
"b": {
"b1": {
"b11": "{...}",
"b12": "{...}"
},
"b2": {
"b21": "{...}",
"b22": "{...}"
}
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 2
{
"a": {
"a1": "{...}",
"a2": "{...}"
},
"b": {
"b1": "{...}",
"b2": "{...}"
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 1
{
"a": "{...}",
"b": "{...}",
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
[注意]:仅在不关心内置类对象的序列化时使用此选项。
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)