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
为了给这场11年的大火再添一根柴,我想要一个满足以下条件的解决方案:
只允许使用json.dumps(obj)序列化类FileItem的实例 允许FileItem实例具有属性:FileItem .fname 允许FileItem实例提供给任何库,使用json.dumps(obj)序列化它 不需要将任何其他字段传递给json。转储(如自定义序列化器)
IE:
fileItem = FileItem('filename.ext')
assert json.dumps(fileItem) == '{"fname": "filename.ext"}'
assert fileItem.fname == 'filename.ext'
我的解决方案是:
obj的类是否继承自dict 将每个对象属性映射到底层字典
class FileItem(dict):
def __init__(self, fname):
self['fname'] = fname
#fname property
fname: str = property()
@fname.getter
def fname(self):
return self['fname']
@fname.setter
def fname(self, value: str):
self['fname'] = value
#Repeat for other properties
是的,如果你有很多属性,这有点冗长,但它是JSONSerializable,它的行为像一个对象,你可以把它给任何库,去json.dumps(obj)它。
其他回答
解决这个问题有很多方法。'ObjDict' (pip install object)是另一个。重点是提供像javascript一样的对象,它也可以像字典一样最好地处理从JSON加载的数据,但还有其他功能也很有用。这为原始问题提供了另一种解决方案。
加拉科给出了一个非常简洁的答案。我需要修复一些小的东西,但这是有效的:
Code
# Your custom class
class MyCustom(object):
def __json__(self):
return {
'a': self.a,
'b': self.b,
'__python__': 'mymodule.submodule:MyCustom.from_json',
}
to_json = __json__ # supported by simplejson
@classmethod
def from_json(cls, json):
obj = cls()
obj.a = json['a']
obj.b = json['b']
return obj
# Dumping and loading
import simplejson
obj = MyCustom()
obj.a = 3
obj.b = 4
json = simplejson.dumps(obj, for_json=True)
# Two-step loading
obj2_dict = simplejson.loads(json)
obj2 = MyCustom.from_json(obj2_dict)
# Make sure we have the correct thing
assert isinstance(obj2, MyCustom)
assert obj2.__dict__ == obj.__dict__
注意,加载需要两个步骤。现在是__python__属性 未使用。
这种情况有多普遍?
使用AlJohri的方法,我检查了流行的方法:
序列化(Python -> JSON):
To_json: 266,595 on 2018-06-27 toJSON: 96,307 on 2018-06-27 __json__: 8504 on 2018-06-27 For_json: 6937 on 2018-06-27
反序列化(JSON -> Python):
From_json: 226,101 on 2018-06-27
Kyle Delaney的评论是正确的,所以我尝试使用https://stackoverflow.com/a/15538391/1497139以及https://stackoverflow.com/a/10254820/1497139的改进版本
创建一个“JSONAble”mixin。
因此,要使一个类JSON可序列化使用“JSONAble”作为超类,并调用:
instance.toJSON()
or
instance.asJSON()
对于这两种方法。您还可以使用本文提供的其他方法扩展JSONAble类。
家庭和个人单元测试样本的测试示例结果如下:
toJSOn ():
{
"members": {
"Flintstone,Fred": {
"firstName": "Fred",
"lastName": "Flintstone"
},
"Flintstone,Wilma": {
"firstName": "Wilma",
"lastName": "Flintstone"
}
},
"name": "The Flintstones"
}
asJSOn ():
{'name': 'The Flintstones', 'members': {'Flintstone,Fred': {'firstName': 'Fred', 'lastName': 'Flintstone'}, 'Flintstone,Wilma': {'firstName': 'Wilma', 'lastName': 'Flintstone'}}}
使用家庭和个人样本进行单元测试
def testJsonAble(self):
family=Family("The Flintstones")
family.add(Person("Fred","Flintstone"))
family.add(Person("Wilma","Flintstone"))
json1=family.toJSON()
json2=family.asJSON()
print(json1)
print(json2)
class Family(JSONAble):
def __init__(self,name):
self.name=name
self.members={}
def add(self,person):
self.members[person.lastName+","+person.firstName]=person
class Person(JSONAble):
def __init__(self,firstName,lastName):
self.firstName=firstName;
self.lastName=lastName;
JSONAble .py定义JSONAble mixin
'''
Created on 2020-09-03
@author: wf
'''
import json
class JSONAble(object):
'''
mixin to allow classes to be JSON serializable see
https://stackoverflow.com/questions/3768895/how-to-make-a-class-json-serializable
'''
def __init__(self):
'''
Constructor
'''
def toJSON(self):
return json.dumps(self, default=lambda o: o.__dict__,
sort_keys=True, indent=4)
def getValue(self,v):
if (hasattr(v, "asJSON")):
return v.asJSON()
elif type(v) is dict:
return self.reprDict(v)
elif type(v) is list:
vlist=[]
for vitem in v:
vlist.append(self.getValue(vitem))
return vlist
else:
return v
def reprDict(self,srcDict):
'''
get my dict elements
'''
d = dict()
for a, v in srcDict.items():
d[a]=self.getValue(v)
return d
def asJSON(self):
'''
recursively return my dict elements
'''
return self.reprDict(self.__dict__)
您将发现这些方法现在集成在https://github.com/WolfgangFahl/pyLoDStorage项目中,该项目可在https://pypi.org/project/pylodstorage/上获得
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。
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)