Python defaultdict

The `defaultdict` is a dictionary subclass in Python’s `collections` module that provides a default value for non-existing keys. Unlike a standard dictionary, where attempting to access a missing key results in a `KeyError`, `defaultdict` initializes a new entry for the missing key using a specified default factory function. This is particularly useful for cases like counting occurrences, grouping items, or initializing complex data structures.

1. Importing and Creating a `defaultdict`

from collections import defaultdict

# Create a defaultdict with int as the default factory
int_dict = defaultdict(int)

# Accessing a non-existent key initializes it with default int (0)
print("Value for missing key 'apple':", int_dict["apple"])

Output:
Value for missing key 'apple': 0

2. Specifying Different Default Factories

# Default factory as list
list_dict = defaultdict(list)
print("Accessing a missing key with list factory:", list_dict["fruits"])

# Default factory as string
str_dict = defaultdict(str)
print("Accessing a missing key with str factory:", str_dict["greeting"])

Output:
Accessing a missing key with list factory: []
Accessing a missing key with str factory:

3. Using `defaultdict` for Counting Items

# Counting occurrences of items in a list
items = ["apple", "banana", "apple", "orange", "banana", "apple"]
count_dict = defaultdict(int)

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

print("Item counts:", count_dict)

Output:
Item counts: defaultdict(, {'apple': 3, 'banana': 2, 'orange': 1})

4. Using `defaultdict` for Grouping Items

# Grouping items by length
words = ["dog", "cat", "elephant", "rat", "mouse"]
grouped_by_length = defaultdict(list)

for word in words:
    grouped_by_length[len(word)].append(word)

print("Grouped by length:", grouped_by_length)

Output:
Grouped by length: defaultdict(<class 'list'>, {3: ['dog', 'cat', 'rat'], 8: ['elephant'], 5: ['mouse']})

5. Using `defaultdict` for Nested Dictionaries

# Creating a nested defaultdict
nested_dict = defaultdict(lambda: defaultdict(int))

# Assign values at multiple levels
nested_dict["fruits"]["apple"] += 5
nested_dict["fruits"]["banana"] += 2
nested_dict["vegetables"]["carrot"] += 3

print("Nested defaultdict:", nested_dict)

Output:
Nested defaultdict: defaultdict(<function <lambda> at 0x...>, {'fruits': defaultdict(<class 'int'>, {'apple': 5, 'banana': 2}), 'vegetables': defaultdict(<class 'int'>, {'carrot': 3})})

6. Converting `defaultdict` to Regular Dictionary

# Convert defaultdict to regular dict
regular_dict = dict(count_dict)
print("Converted to regular dict:", regular_dict)

Output:
Converted to regular dict: {'apple': 3, 'banana': 2, 'orange': 1}

7. Setting a Default Function for Complex Objects

# Setting a default factory with a custom object
def default_person():
    return {"name": "Unknown", "age": 0}

person_dict = defaultdict(default_person)
print("Accessing a missing key:", person_dict["person1"])

Output:
Accessing a missing key: {'name': 'Unknown', 'age': 0}

8. Combining `defaultdict` with Lambda Expressions

# Conditional default using a lambda
conditional_dict = defaultdict(lambda: "N/A")

# Access missing and existing keys
conditional_dict["name"] = "Alice"
print("Name:", conditional_dict["name"])
print("Missing key 'age':", conditional_dict["age"])

Output:
Name: Alice
Missing key 'age': N/A

9. Practical Example: Character Frequency Counter

# Character frequency counter
text = "hello world"
char_count = defaultdict(int)

for char in text:
    char_count[char] += 1

print("Character frequency:", char_count)

Output:
Character frequency: defaultdict(<class 'int'>, {'h': 1, 'e': 1, 'l': 3, 'o': 2, ' ': 1, 'w': 1, 'r': 1, 'd': 1})

10. Comparison with Standard Dictionary

# Using standard dictionary (not defaultdict)
item_counts = {}
items = ["apple", "banana", "apple"]

for item in items:
    if item not in item_counts:
        item_counts[item] = 0
    item_counts[item] += 1

print("Item counts:", item_counts)

Output:
Item counts: {'apple': 2, 'banana': 1}

Summary