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
我有了自己的解决办法。使用此方法,将任何文档(字典、列表、ObjectId等)传递给序列化。
def getSerializable(doc):
# check if it's a list
if isinstance(doc, list):
for i, val in enumerate(doc):
doc[i] = getSerializable(doc[i])
return doc
# check if it's a dict
if isinstance(doc, dict):
for key in doc.keys():
doc[key] = getSerializable(doc[key])
return doc
# Process ObjectId
if isinstance(doc, ObjectId):
doc = str(doc)
return doc
# Use any other custom serializting stuff here...
# For the rest of stuff
return doc
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>
>>>
你们为什么要把事情搞得这么复杂?这里有一个简单的例子:
#!/usr/bin/env python3
import json
from dataclasses import dataclass
@dataclass
class Person:
first: str
last: str
age: int
@property
def __json__(self):
return {
"name": f"{self.first} {self.last}",
"age": self.age
}
john = Person("John", "Doe", 42)
print(json.dumps(john, indent=4, default=lambda x: x.__json__))
这样你也可以序列化嵌套类,因为__json__返回一个python对象而不是字符串。不需要使用JSONEncoder,因为使用简单lambda的默认参数也可以很好地工作。
我使用@property代替了一个简单的函数,因为这样感觉更自然和现代。@dataclass也只是一个例子,它也适用于“普通”类。
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"
}
Json在它可以打印的对象方面受到限制,而jsonpickle(你可能需要一个PIP安装jsonpickle)在它不能缩进文本方面受到限制。如果你想检查一个你不能改变类的对象的内容,我仍然找不到比:
import json
import jsonpickle
...
print json.dumps(json.loads(jsonpickle.encode(object)), indent=2)
注意:他们仍然不能打印对象方法。
TLDR:复制-粘贴下面的选项1或选项2
真正的/完整的答案:让Pythons json模块与你的类一起工作
AKA,求解:json。dump ({"thing": YOUR_CLASS()})
解释:
Yes, a good reliable solution exists No, there is no python "official" solution By official solution, I mean there is no way (as of 2023) to add a method to your class (like toJSON in JavaScript) and/or no way to register your class with the built-in json module. When something like json.dumps([1,2, your_obj]) is executed, python doesn't check a lookup table or object method. I'm not sure why other answers don't explain this The closest official approach is probably andyhasit's answer which is to inherit from a dictionary. However, inheriting from a dictionary doesn't work very well for many custom classes like AdvancedDateTime, or pytorch tensors. The ideal workaround is this: Mutate json.dumps (affects everywhere, even pip modules that import json) Add def __json__(self) method to your class
选项1:让一个模块来做补丁
PIP安装json-fix (扩展+包装版FancyJohn的回答,谢谢@FancyJohn)
your_class_definition.py
import json_fix
class YOUR_CLASS:
def __json__(self):
# YOUR CUSTOM CODE HERE
# you probably just want to do:
# return self.__dict__
return "a built-in object that is naturally json-able"
这是它。
使用示例:
from your_class_definition import YOUR_CLASS
import json
json.dumps([1,2, YOUR_CLASS()], indent=0)
# '[\n1,\n2,\n"a built-in object that is naturally json-able"\n]'
生成json。dump适用于Numpy数组,Pandas DataFrames和其他第三方对象,请参阅模块(只有大约2行代码,但需要解释)。
它是如何工作的?嗯…
选项2:补丁json。把你自己
注意:这种方法是简化的,它在已知的edgcase上失败(例如:如果你的自定义类继承了dict或其他内置类),并且它错过了控制外部类的json行为(numpy数组,datetime, dataframes,张量等)。
some_file_thats_imported_before_your_class_definitions.py
# Step: 1
# create the patch
from json import JSONEncoder
def wrapped_default(self, obj):
return getattr(obj.__class__, "__json__", wrapped_default.default)(obj)
wrapped_default.default = JSONEncoder().default
# apply the patch
JSONEncoder.original_default = JSONEncoder.default
JSONEncoder.default = wrapped_default
your_class_definition.py
# Step 2
class YOUR_CLASS:
def __json__(self, **options):
# YOUR CUSTOM CODE HERE
# you probably just want to do:
# return self.__dict__
return "a built-in object that is natually json-able"
_
其他答案似乎都是“序列化自定义对象的最佳实践/方法”
在这里的文档中已经介绍过了(搜索“complex”可以找到编码复数的例子)