How to Solve Python TypeError: ‘method’ object is not iterable

by | Programming, Python, Tips

This error occurs when you try to iterate over a method object, for example, using a for loop.

If your method returns an iterable object, you can solve the error by adding parentheses () after the method name to call it and return the object. For example,

class Particle:

    def __init__(self, name, charge, mass):

        self.name = name

        self.charge = charge

        self.mass = mass
    
    def get_info(self):

        return([self.name, self.charge, self.mass])

muon = Particle("Muon", -1, 105.7)

for attribute in muon.get_info():

    print(attribute)

This tutorial will detail the error and how to solve it with code examples.


TypeError: ‘method’ object is not iterable

TypeError occurs in Python when you perform an illegal operation for a specific data type. A method is a function that belongs to an object of a class, and we cannot iterate over it.

What is an Iterable Object in Python?

An iterable is an object that can be “iterated over“, for example in a for loop. In terms of dunder methods under the hood, an object can be iterated over with “for” if it implements __iter__() or __getitem__().

An iterator returns the next value in the iterable object. An iterable generates an iterator when it is passed to the iter() method.

In terms of dunder methods under the hood, an iterator is an object that implements the __next__() method.

A for loop automatically calls the iter() method to get an iterator and then calls next over and over until it reaches the end of the iterable object.

Example

Let’s look at an example of trying to iterate over a method.

First, we will create a class which stores and returns attributes of fundamental physics particles.

class Particle:

    def __init__(self, name, charge, mass):

        self.name = name

        self.charge = charge

        self.mass = mass
    
    def get_info(self):

        return([self.name, self.charge, self.mass])

The __init__ method is the class constructor and sets the name, charge and mass attributes for the particle.

The get_info method returns a list containing the particle attributes.

Next, we will create an instance of the Particle class containing attributes of the muon particle.

muon = Particle("Muon", -1, 105.7)

Next, we will try to iterate over the attributes returned by the get_info method.

for attribute in muon.get_info:

    print(attribute)

Let’s run the code to see what happens:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [16], in <cell line: 13>()
      9         return([self.name, self.charge, self.mass])
     11 muon = Particle("Muon", -1, 105.7)
---> 13 for attribute in muon.get_info:
     14     print(attribute)

TypeError: 'method' object is not iterable

The error occurs because we did not call the get_info method. Therefore Python interprets the for loop as trying to iterate over the method object, which is not iterable.

Solution

We can solve this error by calling the method get_info. We can call a method by specifying the method name and putting parentheses after the name. Let’s look at the revised code.

class Particle:

    def __init__(self, name, charge, mass):
        self.name = name
        self.charge = charge
        self.mass = mass
    
    def get_info(self):
        return([self.name, self.charge, self.mass])

muon = Particle("Muon", -1, 105.7)

for attribute in muon.get_info():
    print(attribute)

Let’s run the code to get the attributes of the muon particle:

Muon
-1
105.7

Summary

Congratulations on reading to the end of this tutorial!

For more reading on not iterable TypeErrors, 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!