How to Resolve "TypeError: Object of type X is not JSON serializable" in Python

JSON serialization is the process of converting Python objects into a JSON string using the json module. However, the standard library only supports a limited set of native types (dicts, lists, strings, numbers, booleans, and None). Attempting to serialize other common types, such as datetime objects, Sets, NumPy arrays, or custom classes, will raise a TypeError.

This guide explains why this error occurs and provides standard solutions for serializing complex data types.

Understanding the Error

The json.dumps() function expects data that maps directly to JSON standards. If you pass an object it doesn't recognize, it throws an error.

Supported Types: dict, list, tuple, str, int, float, bool, None. Unsupported Types: datetime, set, complex, custom classes, NumPy arrays.

import json

data = {"unique_ids": {1, 2, 3}} # Sets are not supported

try:
    print(json.dumps(data))
except TypeError as e:
    print(f"Error: {e}")

Output:

Error: Object of type set is not JSON serializable

Solution 1: Serializing DateTime Objects

Dates are one of the most common causes of serialization errors. JSON has no native date type, so they are typically stored as strings (ISO 8601 format).

Using default=str

The quickest fix is to tell json.dumps to convert unknown types to their string representation.

import json
from datetime import datetime

data = {
    "event": "Login",
    "timestamp": datetime.now()
}

try:
    print(json.dumps(data))
except TypeError as e:
    print(f"Error: {e}")

json_output = json.dumps(data, default=str)
print(json_output)

Output:

Error: Object of type datetime is not JSON serializable
{"event": "Login", "timestamp": "2025-12-26 18:06:48.555990"}

Solution 2: Serializing Sets

Sets ({1, 2}) are not ordered, whereas JSON arrays [] are. To serialize a set, you simply need to convert it to a list first.

import json

users = {"id": 1, "roles": {"admin", "editor"}}


users["roles"] = list(users["roles"])
print(json.dumps(users))

Output:

{"id": 1, "roles": ["admin", "editor"]}

Solution 3: Serializing Custom Classes

Python classes are not serializable by default because json doesn't know which attributes to save or how to represent them.

Returning __dict__

Most classes store their attributes in a __dict__ attribute. You can return this dictionary to serialize the object's data.

import json

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

user = User("Alice", 30)

try:
    print(json.dumps(user))
except TypeError as e:
    print(f"Error: {e}")

json_output = json.dumps(user, default=lambda o: o.__dict__)
print(json_output)

Output:

Error: Object of type User is not JSON serializable
{"name": "Alice", "age": 30}

Solution 4: The Universal default Parameter

Instead of handling every case individually or using lambda, you can define a robust serialization function that handles multiple types (Dates, Sets, Custom Classes) in one place.

import json
from datetime import datetime

class Product:
    def __init__(self, name, price):
        self.name = name
        self.price = price

def custom_serializer(obj):
    """JSON serializer for objects not serializable by default json code"""
    if isinstance(obj, (datetime,)):
        return obj.isoformat()
    if isinstance(obj, set):
        return list(obj)
    if hasattr(obj, '__dict__'):
        return obj.__dict__
    
    raise TypeError(f"Type {type(obj)} not serializable")

complex_data = {
    "time": datetime.now(),
    "tags": {"new", "sale"},
    "item": Product("Laptop", 999.99)
}

print(json.dumps(complex_data, default=custom_serializer, indent=2))

Output:

{
  "time": "2025-12-26T18:08:04.624217",
  "tags": [
    "sale",
    "new"
  ],
  "item": {
    "name": "Laptop",
    "price": 999.99
  }
}

Conclusion

To fix JSON serialization errors in Python:

1. Identify the Type: Check the error message to see which object (datetime, set, etc.) is causing the issue.
2. Convert Primitives: Convert set to list manually if feasible.
3. Use default=str: For quick logging of dates or simple objects.
4. Use Custom Serializers: For complex applications, define a function that checks isinstance() and converts objects to dictionaries or strings, then pass it to json.dumps(data, default=serializer).