python collections defaultdict example

The main advantage of defaultdict is that it will not report an error when accessing non-existent keys, but will automatically generate default values. 1. Use defaultdict(int) to automatically initialize the value of the new key to 0, which is suitable for counting the number of elements; 2. Use defaultdict(list) to create an empty list for the new key, which is convenient for grouping data; 3. Use defaultdict(set) to automatically deduplicate, which is suitable for building graph structures; 4. You can pass in a custom callable object as the default factory, such as lambda or function, to achieve flexible initialization. Compared with ordinary dictionaries, it is necessary to manually determine whether the key exists or use the get method. The defaultdict is written more concise and efficient, especially in data grouping, counting and graph construction scenarios. However, it should be noted that it is not suitable for scenarios where precise control of key initialization or involves serialization. The final conclusion is that defaultdict is extremely practical in data processing and can significantly improve code readability.

defaultdict is a very practical class in the Python collections module. It inherits from dict . The main advantage is that when accessing non-existent keys, there will be no errors, but a default type value will be automatically created . This is particularly convenient in handling grouping, counting and other scenarios.

The following is a few common examples to illustrate the usage of defaultdict .

1. Use defaultdict to count the number of elements to appear (replace dict.get() )

 from collections import defaultdict

words = ['apple', 'banana', 'apple', 'orange', 'banana', 'apple']

# Use defaultdict to initialize the default value of each key to 0
word_count = defaultdict(int)

for word in words:
    word_count[word] = 1

print(word_count)
# Output: defaultdict(<class &#39;int&#39;>, {&#39;apple&#39;: 3, &#39;banana&#39;: 2, &#39;orange&#39;: 1})

✅ In defaultdict(int) int() returns 0 by default, so the initial value of the key that does not appear is 0.

2. Use defaultdict(list) to group data

 from collections import defaultdict

pairs = [('a', 1), ('b', 2), ('a', 3), ('b', 4), ('c', 5)]

# Group according to the first element and collect the corresponding second element grouped = defaultdict(list)

for key, value in pairs:
    grouped[key].append(value)

print(grouped)
# Output: defaultdict(<class &#39;list&#39;>, {&#39;a&#39;: [1, 3], &#39;b&#39;: [2, 4], &#39;c&#39;: [5]})

✅ defaultdict(list) will automatically create an empty list [] for each new key, avoiding manual judgment on whether the key exists.

3. Use defaultdict(set) to decompose and group

 from collections import defaultdict

edges = [('a', 1), ('b', 2), ('a', 1), ('a', 3), ('b', 2)]

# Use set to avoid duplicate values graph = defaultdict(set)

for node, neighbor in edges:
    graph[node].add(neighbor)

print(graph)
# Output: defaultdict(<class &#39;set&#39;>, {&#39;a&#39;: {1, 3}, &#39;b&#39;: {2}})

✅ set can automatically deduplicate, which is suitable for constructing structures such as undirected graphs and adjacency tables.

4. Customize the default value (such as returning a default list or string)

 from collections import defaultdict

# Custom factory function def default_value():
    return "not set"

user_info = defaultdict(default_value)
user_info['name'] = 'Alice'

print(user_info['name']) # Output: Alice
print(user_info['age']) # Output: Not set (no error report)

✅ You can pass in any "no parameter callable object" as the default factory, such as lambda: 'unknown' .

Summary: Commonly used defaultdict types

Comparing the writing method of ordinary dictionaries (highlighting advantages)

 # Ordinary dict writing (cumbersome)
d = {}
for word in words:
    if word not in d:
        d[word] = 0
    d[word] = 1

# or use get
d[word] = d.get(word, 0) 1

# defaultdict writing (concise)
dd = defaultdict(int)
for word in words:
    dd[word] = 1

✅ defaultdict makes the code more concise and easy to read, reducing judgment logic.

Basically these common uses. defaultdict is not omnipotent (for example, be careful when serializing), but it is very practical in data processing. If you use it too much, you will find that it is much refreshing than dict.setdefault() or frequent judgment in .

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