avatarDurgesh Samariya


Python’s defaultdict for Efficient Data Storage

Python Series — Part 38

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When working with data in Python, you often need to store and manipulate collections of items. Python provides a rich set of data structures for this purpose, and one particularly useful tool is the defaultdict from the collections module. In this article, we'll explore what a defaultdict is, how it differs from a regular dictionary, and how to use it efficiently for data storage. We'll also provide code examples to make it beginner-friendly.

What is a defaultdict?

A defaultdict is a specialized dictionary available in Python's collections module. It is a subclass of the built-in dict type and provides an elegant solution to a common problem when working with dictionaries: handling missing keys.

In a regular dictionary, if you try to access a key that doesn’t exist, you’ll encounter a KeyError. For example:

my_dict = {}
value = my_dict['nonexistent_key']  # Raises a KeyError

To avoid this issue, you’d typically need to check if a key exists before trying to access it, like this:

my_dict = {}
if 'nonexistent_key' in my_dict:
    value = my_dict['nonexistent_key']
    value = 'default_value'

This can be quite cumbersome and can lead to less readable code, especially when dealing with nested dictionaries. This is where defaultdict comes to the rescue.

How does defaultdict work?

A defaultdict allows you to specify a default value for any nonexistent keys. You provide a factory function when creating a defaultdict, which will be used to generate default values for missing keys. This factory function can be a built-in function or a custom function you define.

Here’s how to create a defaultdict:

from collections import defaultdict

my_defaultdict = defaultdict(int)  # Uses int() as the factory function

In this example, we use int() as the factory function, so any missing key will default to 0. Let's see how this works in practice:

my_defaultdict = defaultdict(int)
value = my_defaultdict['nonexistent_key']  # No KeyError, value is 0

With defaultdict, you don't need to explicitly check if a key exists, and you can avoid raising KeyError exceptions.

Common use cases

Counting elements

One common use case for defaultdict is counting elements. You can use it to create a histogram of values without worrying about key existence:

from collections import defaultdict

data = [1, 2, 2, 3, 1, 2, 4, 4, 4]
count_dict = defaultdict(int)

for item in data:
    count_dict[item] += 1


The count_dict will automatically create keys with default values (0) when you encounter a new item in the data list. The output will be a dictionary that shows the count of each unique item.

Grouping elements

defaultdict is also handy when you want to group elements. For example, you can group a list of names by the starting letter:

from collections import defaultdict

names = ["Alice", "Bob", "Charlie", "Dave", "Eve", "Frank"]
grouped_names = defaultdict(list)

for name in names:


In this example, grouped_names will create a list for each starting letter, allowing you to group names efficiently.

Customizing the default value

You’re not limited to using built-in types as the factory function for defaultdict. You can also define your custom functions. This enables you to specify more complex default values. Here's an example:

from collections import defaultdict

def default_color():
    return "unknown"

color_dict = defaultdict(default_color)

color_dict['apple'] = 'red'
color_dict['banana'] = 'yellow'

print(color_dict['apple'])     # Output: 'red'
print(color_dict['grape'])     # Output: 'unknown'

In this case, we define a default_color function that returns "unknown." This function is used as the factory for missing keys in the color_dict.


Python’s defaultdict is a powerful tool for efficient data storage. It simplifies code, reduces the chance of errors, and enhances readability by handling default values for missing keys automatically. It is particularly useful for counting, grouping, and other data storage tasks, making your code more elegant and less error-prone.

In summary, defaultdict can be a game-changer when dealing with dictionaries, especially when you want to avoid KeyError exceptions and make your code more beginner-friendly. So, next time you work with dictionaries in Python, consider using defaultdict to simplify your code and improve your data storage efficiency.

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