What approaches do you use when working with data collections in your projects?

When working with data collections in Python, I usually use built-in data types such as lists, sets, dictionaries, and tuples, choosing them depending on the task. For example, lists for ordered mutable sequences, sets for unique elements, and dictionaries for key-value pairs.

I also actively use list comprehensions and generator expressions for efficient creation and processing of collections.

For more complex tasks, I use the collections module, for example, defaultdict for convenient work with dictionaries with default values, Counter for counting elements, and deque for efficient queue operations.

An example of using defaultdict:

from collections import defaultdict

word_count = defaultdict(int)
words = ['apple', 'banana', 'apple', 'orange', 'banana', 'apple']
for word in words:
    word_count[word] += 1

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

When working with large data, I also try to use iterators and generators to avoid loading the entire collection into memory at once.