3.1. Collections

collections is a built-in Python library to deal with Python dictionary efficiently. This section will show you some useful methods of this module.

3.1.1. collections.Counter: Count The Occurrences of Items in a List

Counting the occurrences of each item in a list using a for-loop is slow and inefficient.

char_list = ["a", "b", "c", "a", "d", "b", "b"]
def custom_counter(list_: list):
    char_counter = {}
    for char in list_:
        if char not in char_counter:
            char_counter[char] = 1
        else:
            char_counter[char] += 1

    return char_counter


custom_counter(char_list)
{'a': 2, 'b': 3, 'c': 1, 'd': 1}

Using collections.Counter is more efficient, and all it takes is one line of code!

from collections import Counter

Counter(char_list)
Counter({'a': 2, 'b': 3, 'c': 1, 'd': 1})

In my experiment, using Counter is more than 2 times faster than using a custom counter.

from timeit import timeit
import random

random.seed(0)
num_list = [random.randint(0, 22) for _ in range(1000)]

numExp = 100
custom_time = timeit("custom_counter(num_list)", globals=globals())
counter_time = timeit("Counter(num_list)", globals=globals())
print(custom_time / counter_time)
2.6199148843686806

3.1.2. namedtuple: A Lightweight Python Structure to Mange your Data

If you need a small class to manage data in your project, consider using namedtuple.

namedtuple object is like a tuple but can be used as a normal Python class.

In the code below, I use namedtuple to create a Person object with attributes name and gender.

from collections import namedtuple

Person = namedtuple("Person", "name gender")

oliver = Person("Oliver", "male")
khuyen = Person("Khuyen", "female")
oliver
Person(name='Oliver', gender='male')
khuyen
Person(name='Khuyen', gender='female')

Just like Python class, you can access attributes of namedtuple using obj.attr.

oliver.name
'Oliver'

3.1.3. Defaultdict: Return a Default Value When a Key is Not Available

If you want to create a Python dictionary with default value, use defaultdict. When calling a key that is not in the dictionary, the default value is returned.

from collections import defaultdict

classes = defaultdict(lambda: "Outside")
classes["Math"] = "B23"
classes["Physics"] = "D24"
classes["Math"]
'B23'
classes["English"]
'Outside'

3.1.4. Defaultdict: Create a Dictionary with Values that are List

If you want to create a dictionary with the values that are list, the cleanest way is to pass a list class to a defaultdict.

from collections import defaultdict

# Instead of this
food_price = {"apple": [], "orange": []}

# Use this
food_price = defaultdict(list)

for i in range(1, 4):
    food_price["apple"].append(i)
    food_price["orange"].append(i)

print(food_price.items())
dict_items([('apple', [1, 2, 3]), ('orange', [1, 2, 3])])