This error occurs when you try to use indexing syntax to access values in a module.
A Python module is a file containing Python code. A module can define functions, classes, and variables. You can import modules into your program.
You can solve this error by using dot notation to access the subscriptable variable from the module or import the variable directly.
This tutorial will go through how to solve the error with code examples.
TypeError: ‘module’ object is not subscriptable
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 “module
object” tells us the error concerns an illegal operation for Python modules.
The part “is not subscriptable” tells us we cannot access an element of the module
object using the subscript operator, which is square brackets []
.
A subscriptable object is a container for other objects and implements the __getitem__()
method. Examples of subscriptable objects include strings, lists, tuples, and dictionaries.
We can check if an object implements the __getitem__()
method by listing its attributes with the dir
function.
If we want to check if a specific attribute belongs to an object, we can check for membership using the in
operator. This approach is more straightforward than looking through the list of attributes by eye.
Let’s check if __getitem__
is an attribute of the re
module and a string.
import re attributes = dir(re) print(type(re)) print('__getitem__' in attributes)
<class 'module'> False
We can see that __getitem__
is not present in the list of attributes for the module re
.
string = "Python" print(type(string)) print('__getitem__' in dir(string))
<class 'str'> True
We can see that __getitem__
is an attribute of the str
class.
Example
Let’s look at an example of attempting to index a module. First, we will define a file called pizzas.py
which contains a nested dictionary containing the names and information about four pizzas served in a restaurant.
pizzas_dict = { "margherita" : { "price" : 9.99, "is_vegetarian" : True }, "pepperoni" : { "price" : 10.99, "is_vegetarian" : False }, "tartufo" : { "price" : 13.99, "is_vegetarian" : False }, "marinara" : { "price" : 7.99, "is_vegetarian" : True } }
Next, we will try to import the pizzas
module and try to retrieve the dictionary for the margherita
pizza, using the key 'margherita'
.
import pizzas print(pizzas['margherita'])
Let’s run the code to see what happens:
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) Input In [3], in <cell line: 1>() ----> 1 print(pizzas['margherita']) TypeError: 'module' object is not subscriptable
The error occurred because we did not access the pizzas_dict
attribute from the pizzas
module and Python interprets the indexing operation as indexing the pizzas
module.
Solution
We can solve the error by using the dot notation to access the pizzas_dict
object. Dot notation requires a full stop followed by the name of the attribute we want to access. Let’s look at the revised code:
import pizzas print(pizzas.pizzas_dict['margherita'])
Let’s run the code to see the result:
{'price': 9.99, 'is_vegetarian': True}
We successfully retrieved the dictionary for the margherita
pizza.
We can also use the from
keyword to import pizzas_dict
. This approach improves the readability of the code. Let’s look at the revised code:
from pizzas import pizzas_dict print(pizzas_dict['margherita'])
Let’s run the code to see the result:
{'price': 9.99, 'is_vegetarian': True}
We successfully retrieved the dictionary for the margherita
pizza.
Summary
Congratulations on reading to the end of this tutorial!
For further reading on AttributeErrors, go to the articles:
- How to Solve Python TypeError: ‘dict_items’ object is not subscriptable
- How to Solve Python TypeError: ‘dict_keys’ object is not subscriptable
To learn more about Python for data science and machine learning, you can go to the online courses page on Python for the most comprehensive courses.
Have fun and happy researching!
Suf is a senior advisor in data science with deep expertise in Natural Language Processing, Complex Networks, and Anomaly Detection. Formerly a postdoctoral research fellow, he applied advanced physics techniques to tackle real-world, data-heavy industry challenges. Before that, he was a particle physicist at the ATLAS Experiment of the Large Hadron Collider. Now, he’s focused on bringing more fun and curiosity to the world of science and research online.