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

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))

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。

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)

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"
}

任何人都想在没有外部库的情况下使用基本转换,这只是如何使用以下方式覆盖自定义类的__iter__ & __str__函数。

class JSONCustomEncoder(json.JSONEncoder):
    def default(self, obj):
        return obj.__dict__


class Student:
    def __init__(self, name: str, slug: str):
        self.name = name
        self.age = age

    def __iter__(self):
        yield from {
            "name": self.name,
            "age": self.age,
        }.items()

    def __str__(self):
        return json.dumps(
            self.__dict__, cls=JSONCustomEncoder, ensure_ascii=False
        )

通过在dict()中进行包装来使用该对象,从而保留数据。

s = Student("aman", 24)
dict(s)
class DObject(json.JSONEncoder):
    def delete_not_related_keys(self, _dict):
        for key in ["skipkeys", "ensure_ascii", "check_circular", "allow_nan", "sort_keys", "indent"]:
            try:
                del _dict[key]
            except:
                continue

    def default(self, o):
        if hasattr(o, '__dict__'):
            my_dict = o.__dict__.copy()
            self.delete_not_related_keys(my_dict)
            return my_dict
        else:
            return o

a = DObject()
a.name = 'abdul wahid'
b = DObject()
b.name = a

print(json.dumps(b, cls=DObject))