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
Jsonweb似乎是我的最佳解决方案。参见http://www.jsonweb.info/en/latest/
from jsonweb.encode import to_object, dumper
@to_object()
class DataModel(object):
def __init__(self, id, value):
self.id = id
self.value = value
>>> data = DataModel(5, "foo")
>>> dumper(data)
'{"__type__": "DataModel", "id": 5, "value": "foo"}'
其他回答
下面是一个简单功能的简单解决方案:
.toJSON()方法
实现一个序列化器方法,而不是一个JSON可序列化类:
import json
class Object:
def toJSON(self):
return json.dumps(self, default=lambda o: o.__dict__,
sort_keys=True, indent=4)
所以你只需调用它来序列化:
me = Object()
me.name = "Onur"
me.age = 35
me.dog = Object()
me.dog.name = "Apollo"
print(me.toJSON())
将输出:
{
"age": 35,
"dog": {
"name": "Apollo"
},
"name": "Onur"
}
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)
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"}}
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)
前几天我遇到了这个问题,并为Python对象实现了一个更通用的Encoder版本,可以处理嵌套对象和继承字段:
import json
import inspect
class ObjectEncoder(json.JSONEncoder):
def default(self, obj):
if hasattr(obj, "to_json"):
return self.default(obj.to_json())
elif hasattr(obj, "__dict__"):
d = dict(
(key, value)
for key, value in inspect.getmembers(obj)
if not key.startswith("__")
and not inspect.isabstract(value)
and not inspect.isbuiltin(value)
and not inspect.isfunction(value)
and not inspect.isgenerator(value)
and not inspect.isgeneratorfunction(value)
and not inspect.ismethod(value)
and not inspect.ismethoddescriptor(value)
and not inspect.isroutine(value)
)
return self.default(d)
return obj
例子:
class C(object):
c = "NO"
def to_json(self):
return {"c": "YES"}
class B(object):
b = "B"
i = "I"
def __init__(self, y):
self.y = y
def f(self):
print "f"
class A(B):
a = "A"
def __init__(self):
self.b = [{"ab": B("y")}]
self.c = C()
print json.dumps(A(), cls=ObjectEncoder, indent=2, sort_keys=True)
结果:
{
"a": "A",
"b": [
{
"ab": {
"b": "B",
"i": "I",
"y": "y"
}
}
],
"c": {
"c": "YES"
},
"i": "I"
}