python - type - How to make a class JSON serializable

typeerror: object of type is not json serializable (15)

How to make a Python class serializable?

A simple class:

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

What should I do to be able to get output of:


Without an error (FileItem instance at ... is not JSON serializable)

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


# 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

    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):

Deserialization (JSON -> Python):

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 objecth 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.

Do you have an idea about the expected output? For e.g. 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:


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

>>> 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>

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.

(jsonpickle on PyPi)

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)

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


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)


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

I chose to use decorators to solve the datetime object serialization problem. Here is my code:
#Author: jmooremcc 7/16/2017

import json
from datetime import datetime, date, time, timedelta
This module uses decorators to serialize date objects using json
The filename is
In another module you simply add the following import statement:
    from myjson import json

json.dumps and json.dump will then correctly serialize datetime and date 

def json_serial(obj):
    """JSON serializer for objects not serializable by default json code"""

    if isinstance(obj, (datetime, date)):
        serial = str(obj)
        return serial
    raise TypeError ("Type %s not serializable" % type(obj))

def FixDumps(fn):
    def hook(obj):
        return fn(obj, default=json_serial)

    return hook

def FixDump(fn):
    def hook(obj, fp):
        return fn(obj,fp, default=json_serial)

    return hook


if __name__=="__main__":
    data={'atime':today, 'greet':'Hello'}
    print str

By importing the above module, my other modules use json in a normal way (without specifying the default keyword) to serialize data that contains date time objects. The datetime serializer code is automatically called for json.dumps and json.dump.

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

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

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)

    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!

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__": [
        "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.

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.

There are many approaches to this problem. 'ObjDict' (pip install objdict) is another. There is an emphasis on providing javascript like objects which can also act like dictionaries to best handle data loaded from JSON, but there are other features which can be useful as well. This provides another alternative solution to the original problem.

jsonweb seems to be the best solution for me. See

from jsonweb.encode import to_object, dumper

class DataModel(object):
  def __init__(self, id, value): = id
   self.value = value

>>> data = DataModel(5, "foo")
>>> dumper(data)
'{"__type__": "DataModel", "id": 5, "value": "foo"}'

import simplejson

class User(object):
    def __init__(self, name, mail): = name
        self.mail = mail

    def _asdict(self):
        return self.__dict__

print(simplejson.dumps(User('alice', '[email protected]')))

if use standard json, u need to define a default function

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

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