파이썬 dict defaultdict 사용 및 고치는 방법

Python defaultdict

Handling Missing Keys in Dictionaries

Python dictionaries are a fundamental data structure in Python that allow you to store and retrieve key-value pairs. However, when working with dictionaries, you may encounter situations where you need to access or modify keys that don’t exist in the dictionary. This can raise a KeyError and disrupt the execution of your code. To handle this issue, the Python standard library provides the defaultdict type from the collections module.

The defaultdict type behaves similarly to a regular dictionary, but it automatically generates a default value when trying to access or modify a missing key. This makes defaultdict a useful tool for handling missing keys in dictionaries.

In this tutorial, we will cover the following topics:

1. Understanding the Python defaultdict Type
2. Using the Python defaultdict Type
3. Diving Deeper Into defaultdict
4. Emulating the Python defaultdict Type
5. Passing Arguments to .default_factory
6. Conclusion

So let’s dive into each topic and explore how to effectively use the Python defaultdict type to handle missing keys in dictionaries.

Understanding the Python defaultdict Type

The defaultdict type is part of the collections module in the Python standard library. It is a subclass of the dict class and works almost the same way. However, the defaultdict type takes a default factory as an argument, which generates a default value for missing keys.

The default factory can be any callable object, such as a function, lambda expression, or class. When a missing key is accessed, the default factory is called to generate a default value for that key.

Using the Python defaultdict Type

To use the Python defaultdict type, you need to import it from the collections module. Here’s an example:

from collections import defaultdict

d = defaultdict(int)

In this example, we create a defaultdict object called d with a default factory of int. The int function generates a default value of 0 for missing keys.

Grouping Items

One common use case for defaultdict is grouping items based on a specific key. Here’s an example:

from collections import defaultdict

# List of names
names = ['Alice', 'Bob', 'Charlie', 'Alice', 'Bob', 'Alice']

# Grouping names by first letter
grouped_names = defaultdict(list)
for name in names:
    grouped_names[name[0]].append(name)

print(grouped_names)

In this example, we have a list of names. We create a defaultdict object called grouped_names with a default factory of list. We iterate over the names and append each name to the list corresponding to its first letter. The resulting grouped_names dictionary will contain lists of names grouped by their first letter.

Grouping Unique Items

You can also use defaultdict to group unique items. Here’s an example:

from collections import defaultdict

# List of numbers
numbers = [1, 2, 3, 4, 5, 1, 2, 3]

# Grouping unique numbers
grouped_numbers = defaultdict(set)
for number in numbers:
    grouped_numbers[number].add(number)

print(grouped_numbers)

In this example, we have a list of numbers. We create a defaultdict object called grouped_numbers with a default factory of set. We iterate over the numbers and add each number to the set corresponding to its value. The resulting grouped_numbers dictionary will contain sets of unique numbers grouped by their value.

Counting Items

Another useful application of defaultdict is counting items. Here’s an example:

from collections import defaultdict

# List of fruits
fruits = ['apple', 'banana', 'apple', 'orange', 'apple', 'banana']

# Counting fruits
fruit_count = defaultdict(int)
for fruit in fruits:
    fruit_count[fruit] += 1

print(fruit_count)

In this example, we have a list of fruits. We create a defaultdict object called fruit_count with a default factory of int. We iterate over the fruits and increment the count for each fruit in the dictionary. The resulting fruit_count dictionary will contain the number of occurrences of each fruit.

Accumulating Values

You can also use defaultdict to accumulate values. Here’s an example:

from collections import defaultdict

# List of numbers
numbers = [1, 2, 3, 4, 5]

# Accumulating values
sum_dict = defaultdict(int)
for number in numbers:
    sum_dict['sum'] += number

print(sum_dict['sum'])

In this example, we have a list of numbers. We create a defaultdict object called sum_dict with a default factory of int. We iterate over the numbers and accumulate their values in the dictionary under the key ‘sum’. The resulting sum_dict dictionary will contain the sum of all the numbers.

Diving Deeper Into defaultdict

Now that we have covered the basics of using defaultdict, let’s dive deeper into its features and compare it with the regular dict class.

defaultdict vs dict

The main difference between defaultdict and the regular dict class is how they handle missing keys. When you try to access a missing key in a regular dict, it will raise a KeyError. However, when you access a missing key in a defaultdict, it will automatically generate a default value using the default factory.

defaultdict.default_factory

The default_factory attribute of a defaultdict specifies the default factory used to generate default values. You can access and modify this attribute as needed. Here’s an example:

from collections import defaultdict

d = defaultdict(list)
print(d.default_factory)  # Output: <class 'list'>

d.default_factory = set
print(d.default_factory)  # Output: <class 'set'>

In this example, we create a defaultdict object d with a default factory of list. We print the default_factory attribute, which gives us the default factory’s type. Then, we modify the default_factory attribute to set, changing the default factory’s type to a set.

defaultdict vs dict.setdefault()

The setdefault() method of the dict class allows you to specify a default value for a missing key. However, it requires you to call the method explicitly. On the other hand, a defaultdict automatically generates a default value when accessing a missing key without the need for explicit method calls.

Here’s an example comparing defaultdict and setdefault():

from collections import defaultdict

d1 = defaultdict(list)
d1['key']  # Output: []

d2 = {}
d2.setdefault('key', [])  # Output: []

In this example, we create a defaultdict object d1 and a regular dict object d2. We access a missing key in both dictionaries. The defaultdict returns an empty list as a default value, while the regular dict returns an empty list after calling setdefault().

defaultdict.missing()

The __missing__() method is a special method that is called when trying to access a missing key in a defaultdict or a regular dict. If __missing__() is defined, it will be called instead of raising a KeyError. You can override this method to implement custom behavior when accessing missing keys.

Emulating the Python defaultdict Type

If you don’t have access to the defaultdict type or prefer not to use it, you can emulate its behavior using a regular dict with a custom default_factory. Here’s an example:

d = {}

# Emulating defaultdict with dict
def default_factory():
    return []

key = 'key'
value = d.get(key, default_factory())
value.append('item')
d[key] = value

print(d)  # Output: {'key': ['item']}

In this example, we create a regular dict d with an empty initial dictionary. We define a custom default_factory function that returns an empty list. We access a missing key key in the dictionary using the get() method and the default_factory() function. We append an item to the resulting list and assign it to the key key. Finally, we print the updated dictionary.

Passing Arguments to .default_factory

The default factory of a defaultdict can accept additional arguments when called. This allows you to customize the default value generation process based on different criteria. Here are two common ways to pass arguments to the default factory:

Using lambda

The lambda expression is an anonymous function that allows you to define small, one-line functions. You can use lambda to pass arguments to the default factory. Here’s an example:

from collections import defaultdict

d = defaultdict(lambda: [1, 2, 3])
print(d[1])  # Output: [1, 2, 3, 4]
print(d[2])  # Output: [1, 2, 3]
print(d[3])  # Output: [1, 2, 3]

In this example, we create a defaultdict object d with a default factory defined as a lambda expression that returns a list [1, 2, 3]. When accessing keys 1, 2, and 3, the defaultdict generates the default value using the lambda expression.

Using functools.partial()

The functools.partial() function allows you to create a new function with some arguments pre-set. You can use this function to pass arguments to the default factory. Here’s an example:

from collections import defaultdict
from functools import partial

def default_factory(arg1, arg2):
    return arg1 + arg2

d = defaultdict(partial(default_factory, 5, 10))
print(d[1])  # Output: 15
print(d[2])  # Output: 15
print(d[3])  # Output: 15

In this example, we create a defaultdict object d with a default factory defined as a partial function with the default_factory function and preset arguments 5 and 10. When accessing any key, the defaultdict generates the default value by calling the default_factory with the preset arguments.

Conclusion

In this tutorial, we have explored the Python defaultdict type and learned how to use it to handle missing keys in dictionaries. We have seen how defaultdict allows us to group items, count items, and accumulate values easily. We have also learned about the differences between defaultdict and the regular dict class, as well as how to emulate defaultdict behavior using a regular dict. Additionally, we have discussed how to pass arguments to the default factory function of a defaultdict. With this knowledge, you can confidently use the Python defaultdict type to handle missing keys and enhance your coding efficiency.

Remember to reference the official Python documentation and experiment with different use cases to further deepen your understanding of defaultdict. Happy coding!

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