How to make a class JSON serializable

Question

How to make a Python class serializable?

class FileItem:
    def __init__(self, fname):
        self.fname = fname

Attempt to serialize to JSON:

>>> import json
>>> x = FileItem('/foo/bar')
>>> json.dumps(x)
TypeError: Object of type 'FileItem' is not JSON serializable

Answer 1

Here is a simple solution for a simple feature:

.toJSON() Method

Instead of a JSON serializable class, implement a serializer method:

import json

class Object:
    def toJSON(self):
        return json.dumps(
            self,
            default=lambda o: o.__dict__, 
            sort_keys=True,
            indent=4)

So you just call it to serialize:

me = Object()
me.name = "Onur"
me.age = 35
me.dog = Object()
me.dog.name = "Apollo"

print(me.toJSON())

will output:

{
    "age": 35,
    "dog": {
        "name": "Apollo"
    },
    "name": "Onur"
}

---

For a fully-featured library, you can use orjson.

Answer 2

Do you have an idea about the expected output? For example, will this do?

>>> f  = FileItem("/foo/bar")
>>> magic(f)
'{"fname": "/foo/bar"}'

In that case you can merely call json.dumps(f.__dict__).

If you want more customized output then you will have to subclass JSONEncoder and implement your own custom serialization.

For a trivial example, see below.

>>> from json import JSONEncoder
>>> class MyEncoder(JSONEncoder):
        def default(self, o):
            return o.__dict__    

>>> MyEncoder().encode(f)
'{"fname": "/foo/bar"}'

Then you pass this class into the json.dumps() method as cls kwarg:

json.dumps(cls=MyEncoder)

If you also want to decode then you'll have to supply a custom object_hook to the JSONDecoder class. For example:

>>> 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>
>>> 

Answer 3

For more complex classes you could consider the tool jsonpickle:

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.

Transform an object into a JSON string:

import jsonpickle
json_string = jsonpickle.encode(obj)

Recreate a Python object from a JSON string:

recreated_obj = jsonpickle.decode(json_string)

(link to jsonpickle on PyPi)

Answer 4

Most of the answers involve changing the call to json.dumps(), which is not always possible or desirable (it may happen inside a framework component for example).

If you want to be able to call json.dumps(obj) as is, then a simple solution is inheriting from dict:

class FileItem(dict):
    def __init__(self, fname):
        dict.__init__(self, fname=fname)

f = FileItem('tasks.txt')
json.dumps(f)  #No need to change anything here

This works if your class is just basic data representation, for trickier things you can always set keys explicitly in the call to dict.__init__().

This works because json.dumps() checks if the object is one of several known types via a rather unpythonic isinstance(value, dict) - so it would be possible to fudge this with __class__ and some other methods if you really don't want to inherit from dict.

Answer 5

As mentioned in many other answers you can pass a function to json.dumps to convert objects that are not one of the types supported by default to a supported type. Surprisingly none of them mentions the simplest case, which is to use the built-in function vars to convert objects into a dict containing all their attributes:

json.dumps(obj, default=vars)

Note that this covers only basic cases, if you need more specific serialization for certain types (e.g. exluding certain attributes or for objects that don't have a __dict__ attribute) you need to use a custom function or a JSONEncoder as desribed in the other answers.

Answer 6

Just add to_json method to your class like this:

def to_json(self):
  return self.message # or how you want it to be serialized

And add this code (from this answer), to somewhere at the top of everything:

from json import JSONEncoder

def _default(self, obj):
    return getattr(obj.__class__, "to_json", _default.default)(obj)

_default.default = JSONEncoder().default
JSONEncoder.default = _default

This will monkey-patch json module when it's imported, so JSONEncoder.default() automatically checks for a special to_json() method and uses it to encode the object if found.

Just like Onur said, but this time you don't have to update every json.dumps() in your project.

Answer 7

TLDR: copy-paste Option 1 or Option 2 below

So You Want Python's json module work with Your Class?

• The good news: Yeah, a reliable solution exists
• The bad news: No, there is no python "official" solution
  • By official solution, I mean there is no way (as of 2024) 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:
  • Add def __json__(self) method to your class
  • Mutate json.dumps to check for __json__ method (affects everywhere, even pip modules that import json)
  • Note: Modifing builtin stuff usually isn't great, however this change should have no side effects, even if its applied multiple times by different codebases. It is entirely reversable durning runtime (if a module wants to undo the modification). And for better or worse, is the best that can done at the moment.

Option 1: Let a Module do the Patching

pip install json-fix
(extended + packaged version of Fancy John's answer, thank you @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"

Thats it.

Example usage:

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]'

To make json.dumps work for Numpy arrays, Pandas DataFrames, and other 3rd party objects, see the Module (only ~2 lines of code but needs explanation).

How does it work? Well...

Option 2: Patch json.dumps yourself

Note: this approach is simplified, it fails on known edgecases (ex: if your custom class inherits from dict or another builtin), and it misses out on controlling the json behavior for external classes (numpy arrays, datetime, dataframes, tensors, etc).

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"

_

All other answers seem to be "Best practices/approaches to serializing a custom object"

Which, is alreadly covered here in the docs (search "complex" for an example of encoding complex numbers)

Answer 8

I like Onur's answer but would expand to include an optional toJSON() method for objects to serialize themselves:

def dumper(obj):
    try:
        return obj.toJSON()
    except:
        return obj.__dict__
print json.dumps(some_big_object, default=dumper, indent=2)

Answer 9

If you're using Python3.5+, you could use jsons. (PyPi: https://pypi.org/project/jsons/) It will convert your object (and all its attributes recursively) to a dict.

import jsons

a_dict = jsons.dump(your_object)

Or if you wanted a string:

a_str = jsons.dumps(your_object)

Or if your class implemented jsons.JsonSerializable:

a_dict = your_object.json

Answer 10

Another option is to wrap JSON dumping in its own class:

import json

class FileItem:
    def __init__(self, fname: str) -> None:
        self.fname = fname

    def __repr__(self) -> str:
        return json.dumps(self.__dict__)

Or, even better, subclassing FileItem class from a JsonSerializable protocol class:

import json
from typing import Protocol

class JsonSerializable(Protocol):
    def to_json(self) -> str:
        return json.dumps(self.__dict__)

    def __repr__(self) -> str:
        return self.to_json()


class FileItem(JsonSerializable):
    def __init__(self, fname: str) -> None:
        self.fname = fname

Testing:

>>> f = FileItem('/foo/bar')
>>> f.to_json()
'{"fname": "/foo/bar"}'
>>> f
'{"fname": "/foo/bar"}'
>>> str(f) # string coercion
'{"fname": "/foo/bar"}'

Answer 11

I came across this problem the other day and implemented a more general version of an Encoder for Python objects that can handle nested objects and inherited fields:

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

Example:

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)

Result:

{
  "a": "A", 
  "b": [
    {
      "ab": {
        "b": "B", 
        "i": "I", 
        "y": "y"
      }
    }
  ], 
  "c": {
    "c": "YES"
  }, 
  "i": "I"
}

Answer 12

A really simplistic one-liner solution

import json

json.dumps(your_object, default=vars)

The end!

What comes below is a test.

import json
from dataclasses import dataclass


@dataclass
class Company:
    id: int
    name: str

@dataclass
class User:
    id: int
    name: str
    email: str
    company: Company


company = Company(id=1, name="Example Ltd")
user = User(id=1, name="John Doe", email="[email protected]", company=company)


json.dumps(user, default=vars)

Output:

{
  "id": 1, 
  "name": "John Doe", 
  "email": "[email protected]", 
  "company": {
    "id": 1, 
    "name": "Example Ltd"
  }
}

Answer 13

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', '[email protected]')))

if using standard json, you need to define a default function

import json
def default(o):
    return o._asdict()

print(json.dumps(User('alice', '[email protected]'), default=default))

Answer 14

The most simple answer

class Object(dict):
    def __init__(self):
        pass

    def __getattr__(self, key):
        return self[key]

    def __setattr__(self, key, value):
        self[key] = value

# test
obj = Object()
obj.name = "John"
obj.age = 25
obj.brothers = [ Object() ]
text = json.dumps(obj)

Now it gives you the output, don't change anything to json.dumps(...)

'{"name": "John", "age": 25, "brothers": [{}]}'

Answer 15

json is limited in terms of objects it can print, and jsonpickle (you may need a pip install jsonpickle) is limited in terms it can't indent text. If you would like to inspect the contents of an object whose class you can't change, I still couldn't find a straighter way than:

 import json
 import jsonpickle
 ...
 print  json.dumps(json.loads(jsonpickle.encode(object)), indent=2)

Note: that still they can't print the object methods.

Answer 16

jaraco gave a pretty neat answer. I needed to fix some minor things, but this works:

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__

Note that we need two steps for loading. For now, the __python__ property is not used.

How common is this?

Using the method of AlJohri, I check popularity of approaches:

Serialization (Python -> JSON):

• to_json: 266,595 on 2018-06-27
• toJSON: 96,307 on 2018-06-27
• __json__: 8,504 on 2018-06-27
• for_json: 6,937 on 2018-06-27

Deserialization (JSON -> Python):

• from_json: 226,101 on 2018-06-27

Answer 17

To throw another log on this 11 year old fire, I want a solution that meets the following criteria:

• Allows an instance of class FileItem to be serialized using only json.dumps(obj)
• Allows FileItem instances to have properties: fileItem.fname
• Allows FileItem instances to be given to any library which will serialise it using json.dumps(obj)
• Doesn't require any other fields to be passed to json.dumps (like a custom serializer)

IE:

fileItem = FileItem('filename.ext')
assert json.dumps(fileItem) == '{"fname": "filename.ext"}'
assert fileItem.fname == 'filename.ext'

My solution is:

• Have obj's class inherit from dict
• Map each object property to the underlying dict

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

Yes, this is somewhat long winded if you have lots of properties, but it is JSONSerializable and it behaves like an object and you can give it to any library that's going to json.dumps(obj) it.

Answer 18

Here is my 3 cents ...
This demonstrates explicit json serialization for a tree-like python object.
Note: If you actually wanted some code like this you could use the twisted FilePath class.

import json, sys, os

class File:
    def __init__(self, path):
        self.path = path

    def isdir(self):
        return os.path.isdir(self.path)

    def isfile(self):
        return os.path.isfile(self.path)

    def children(self):        
        return [File(os.path.join(self.path, f)) 
                for f in os.listdir(self.path)]

    def getsize(self):        
        return os.path.getsize(self.path)

    def getModificationTime(self):
        return os.path.getmtime(self.path)

def _default(o):
    d = {}
    d['path'] = o.path
    d['isFile'] = o.isfile()
    d['isDir'] = o.isdir()
    d['mtime'] = int(o.getModificationTime())
    d['size'] = o.getsize() if o.isfile() else 0
    if o.isdir(): d['children'] = o.children()
    return d

folder = os.path.abspath('.')
json.dump(File(folder), sys.stdout, default=_default)

Answer 19

This class can do the trick, it converts object to standard json .

import json


class Serializer(object):
    @staticmethod
    def serialize(object):
        return json.dumps(object, default=lambda o: o.__dict__.values()[0])

usage:

Serializer.serialize(my_object)

working in python2.7 and python3.

Answer 20

Why are you guys making it so complicated? Here is a simple example:

#!/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__))

This way you could also serialize nested classes, as __json__ returns a python object and not a string. No need to use a JSONEncoder, as the default parameter with a simple lambda also works fine.

I've used @property instead of a simple function, as this feels more natural and modern. The @dataclass is also just an example, it works for a "normal" class as well.

Answer 21

This has worked well for me:

class JsonSerializable(object):

    def serialize(self):
        return json.dumps(self.__dict__)

    def __repr__(self):
        return self.serialize()

    @staticmethod
    def dumper(obj):
        if "serialize" in dir(obj):
            return obj.serialize()

        return obj.__dict__

and then

class FileItem(JsonSerializable):
    ...

and

log.debug(json.dumps(<my object>, default=JsonSerializable.dumper, indent=2))

Answer 22

import json

class Foo(object):
    def __init__(self):
        self.bar = 'baz'
        self._qux = 'flub'

    def somemethod(self):
        pass

'''
The parameter default(obj) is a function that should return a 
serializable version of obj or raise TypeError. The default 
default simply raises TypeError. 

https://docs.python.org/3.4/library/json.html#json.dumps
'''
def default(instance):
    return {k: v
            for k, v in vars(instance).items()
            if not str(k).startswith('_')}

json_foo = json.dumps(Foo(), default=default)
assert '{"bar": "baz"}' == json_foo

print(json_foo)

Answer 23

If you don't mind installing a package for it, you can use json-tricks:

pip install json-tricks

After that you just need to import dump(s) from json_tricks instead of json, and it'll usually work:

from json_tricks import dumps
json_str = dumps(cls_instance, indent=4)

which'll give

{
        "__instance_type__": [
                "module_name.test_class",
                "MyTestCls"
        ],
        "attributes": {
                "attr": "val",
                "dct_attr": {
                        "hello": 42
                }
        }
}

And that's basically it!

---

This will work great in general. There are some exceptions, e.g. if special things happen in __new__, or more metaclass magic is going on.

Obviously loading also works (otherwise what's the point):

from json_tricks import loads
json_str = loads(json_str)

This does assume that module_name.test_class.MyTestCls can be imported and hasn't changed in non-compatible ways. You'll get back an instance, not some dictionary or something, and it should be an identical copy to the one you dumped.

If you want to customize how something gets (de)serialized, you can add special methods to your class, like so:

class CustomEncodeCls:
        def __init__(self):
                self.relevant = 42
                self.irrelevant = 37

        def __json_encode__(self):
                # should return primitive, serializable types like dict, list, int, string, float...
                return {'relevant': self.relevant}

        def __json_decode__(self, **attrs):
                # should initialize all properties; note that __init__ is not called implicitly
                self.relevant = attrs['relevant']
                self.irrelevant = 12

which serializes only part of the attributes parameters, as an example.

And as a free bonus, you get (de)serialization of numpy arrays, date & times, ordered maps, as well as the ability to include comments in json.

Disclaimer: I created json_tricks, because I had the same problem as you.

Answer 24

Kyle Delaney's comment is correct so i tried to use the answer https://stackoverflow.com/a/15538391/1497139 as well as an improved version of https://stackoverflow.com/a/10254820/1497139

to create a "JSONAble" mixin.

So to make a class JSON serializeable use "JSONAble" as a super class and either call:

 instance.toJSON()

or

 instance.asJSON()

for the two offered methods. You could also extend the JSONAble class with other approaches offered here.

The test example for the Unit Test with Family and Person sample results in:

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'}}}

Unit Test with Family and Person sample

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 defining 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__)   

You'll find these approaches now integrated in the https://github.com/WolfgangFahl/pyLoDStorage project which is available at https://pypi.org/project/pylodstorage/

Answer 25

jsonweb seems to be the best solution for me. See 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"}'

Answer 26

I came up with my own solution. Use this method, pass any document (dict,list, ObjectId etc) to serialize.

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

Answer 27

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))

Answer 28

Building on Quinten Cabo's answer:

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)

The differences are

1. Works for any iterable instead of just list and tuple (it works for NumPy arrays, etc.)
2. Works for dynamic types (ones that contain a __dict__).
3. Includes native types float and None so they don't get converted to string.
4. Classes that have __dict__ and members will mostly work (if the __dict__ and member names collide, you will only get one - likely the member)
5. Classes that are lists and have members will look like a tuple of the list and a dictionary
6. Python3 (that isinstance() call may be the only thing that needs changing)

Answer 29

I liked Lost Koder's method the most. I ran into issues when trying to serialize more complex objects whos members/methods aren't serializable. Here's my implementation that works on more objects:

class Serializer(object):
    @staticmethod
    def serialize(obj):
        def check(o):
            for k, v in o.__dict__.items():
                try:
                    _ = json.dumps(v)
                    o.__dict__[k] = v
                except TypeError:
                    o.__dict__[k] = str(v)
            return o
        return json.dumps(check(obj).__dict__, indent=2)

Answer 30

I ran into this problem when I tried to store Peewee's model into PostgreSQL JSONField.

After struggling for a while, here's the general solution.

The key to my solution is going through Python's source code and realizing that the code documentation (described here) already explains how to extend the existing json.dumps to support other data types.

Suppose you current have a model that contains some fields that are not serializable to JSON and the model that contains the JSON field originally looks like this:

class SomeClass(Model):
    json_field = JSONField()

Just define a custom JSONEncoder like this:

class CustomJsonEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, SomeTypeUnsupportedByJsonDumps):
            return < whatever value you want >
        return json.JSONEncoder.default(self, obj)

    @staticmethod
    def json_dumper(obj):
        return json.dumps(obj, cls=CustomJsonEncoder)

And then just use it in your JSONField like below:

class SomeClass(Model):
    json_field = JSONField(dumps=CustomJsonEncoder.json_dumper)

The key is the default(self, obj) method above. For every single ... is not JSON serializable complaint you receive from Python, just add code to handle the unserializable-to-JSON type (such as Enum or datetime)

For example, here's how I support a class inheriting from Enum:

class TransactionType(Enum):
   CURRENT = 1
   STACKED = 2

   def default(self, obj):
       if isinstance(obj, TransactionType):
           return obj.value
       return json.JSONEncoder.default(self, obj)

Finally, with the code implemented like above, you can just convert any Peewee models to be a JSON-seriazable object like below:

peewee_model = WhateverPeeweeModel()
new_model = SomeClass()
new_model.json_field = model_to_dict(peewee_model)

Though the code above was (somewhat) specific to Peewee, but I think:

1. It's applicable to other ORMs (Django, etc) in general
2. Also, if you understood how json.dumps works, this solution also works with Python (sans ORM) in general too

Any questions, please post in the comments section. Thanks!