How to Solve Python TypeError: Object of type function is not JSON serializable

by | Programming, Python, Tips

This error occurs when you pass the name of a function to the json.dumps() method instead of the function call. You can pass a function to json.dumps() that returns a JSON serializable object. You can solve this error by putting parentheses after the function name to call the function. For example,

json_str = json.dumps(function_name())

This tutorial will go through how to solve the error with code examples.

TypeError: Object of type function is not JSON serializable

Let’s break up the error message to understand what the error means. TypeError occurs whenever you attempt to use an illegal operation for a specific data type.

The part “Object of type function” tells us the error is due to an illegal operation with a function.

Serialization in Python refers to converting a Python object into a transmittable format that we can recreate when needed using deserialization. JSON serialization returns a human-readable string form called a JSON string.

The JSON encoder json.dump() and json.dumps() can only serialize certain object types like dictionaries, lists, or strings.

is not JSON serializable” informs us that the JSON serialization is an illegal operation for the function type.


Let’s look at an example of serializing a list of prime numbers returned by a function. First, we will define the function as follows:

import json

def get_prime_numbers():

    num_lists = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29]

    return num_lists

Next, we will attempt to pass the function to the json.dumps() method to serialize the list.

json_str = json.dumps(get_prime_numbers)


Let’s run the code to see the result:

TypeError: Object of type function is not JSON serializable

The error occurs because we passed the function when calling json.dumps() instead of the function call.

If we do not put parentheses () after the variable name get_prime_numbers, the object is a function.

If we put parentheses after get_prime_numbers, we call the function, which returns a list.

We can verify the difference between a function and a function call using the type() function as follows:

<class 'function'>
<class 'list'>


We can solve the error by passing the function call to json.dumps().

The function call returns the list of integers, which is serializable.

Let’s look at the updated code:

json_str = json.dumps(get_prime_numbers())


Let’s run the code to get the result:

[2, 3, 5, 7, 11, 13, 17, 19, 23, 29]

We successfully serialized the list to a JSON string.


Congratulations on reading to the end of this tutorial.

For further reading on errors involving JSON serialization, go to the articles:

Go to the online courses page on Python to learn more about Python for data science and machine learning.

Have fun and happy researching!

Research Scientist at Moogsoft | + posts

Suf is a research scientist at Moogsoft, specializing in Natural Language Processing and Complex Networks. Previously he was a Postdoctoral Research Fellow in Data Science working on adaptations of cutting-edge physics analysis techniques to data-intensive problems in industry. In another life, he was an experimental particle physicist working on the ATLAS Experiment of the Large Hadron Collider. His passion is to share his experience as an academic moving into industry while continuing to pursue research. Find out more about the creator of the Research Scientist Pod here and sign up to the mailing list here!

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