Methods for Working with Collections in Python

Python offers a series of built-in functions and methods that facilitate the manipulation and processing of lists, tuples, and other iterables.

Functions on Iterables

map() Function

The map() function in Python is used to apply a function to each element of a sequence and return an iterable with the results.

# Basic usage of map():
def square(x):
    return x ** 2

numbers = [1, 2, 3, 4, 5]
squares = map(square, numbers)

print(list(squares)) # [1, 4, 9, 16, 25]

Often, we will use the map() function with a lambda function to make the code more concise:

# Using map() with a lambda function:
numbers = [1, 2, 3, 4, 5]
squares = map(lambda x: x ** 2, numbers)

print(list(squares)) # [1, 4, 9, 16, 25]

filter() Function

The filter() function in Python is used to filter elements from a sequence based on a condition defined by a function.

# Basic usage of filter():
def is_even(x):
    return x % 2 == 0

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = filter(is_even, numbers)

Just like with map(), a lambda function can also be used with filter():

# Basic usage of filter():
def is_even(x):
    return x % 2 == 0

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = filter(is_even, numbers)

print(list(evens))  # Output: [2, 4, 6, 8, 10]

any() and all() Functions

The any() and all() functions in Python are boolean functions that return True based on the values of an iterable:

• any() if at least one element is True
• all() if all elements are True

(any()) or all elements (all()) of an iterable are true, respectively.

# Using any() and all():
values = [True, False, True, False, True]
is_any_true = any(values)  # True
are_all_true = all(values)  # False

These functions are useful for checking conditions in iterables (like lists or generators).

They are often used together with map to apply a function to the values of an iterable. For example, like this:

values = [1, 2, 3, 4, 5]
is_any_greater_than_ten = any(map(lambda x: x > 10, values))  # False

sorted() Function

The sorted() function in Python returns a new sorted list from the elements of the specified iterable.

# Basic usage of sorted():
numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3]
sorted_numbers = sorted(numbers)

print(sorted_numbers) # Output: [1, 1, 2, 3, 3, 4, 5, 5, 6, 9]

Optionally, we can specify:

• A key function to customize the sorting
• A reverse argument to invert the order

# Using sorted() with key and reverse:
words = ["python", "java", "c++", "ruby", "javascript"]
sorted_words = sorted(words, key=len, reverse=True)

print(sorted_words) # ['javascript', 'python', 'java', 'c++', 'ruby']

Here, sorted(words, key=len, reverse=True) sorts the words list by the length of the strings in descending order.

sum() Function

The sum() function in Python returns the sum of the elements of the specified iterable, optionally starting from a specified initial value (by default, 0).

# Basic usage of sum():
numbers = [1, 2, 3, 4, 5]

total_sum = sum(numbers)  # 15

enumerate() Function

The enumerate() function in Python returns an enumerated object that produces tuples with a counter and an element from the specified iterable, optionally starting from a specified index (by default, 0).

# Basic usage of enumerate():
teams = ["Real Madrid", "Barcelona", "Atlético de Madrid"]
enumerated_teams = list(enumerate(teams, start=1))

print(enumerated_teams) # [(1, 'Real Madrid'), (2, 'Barcelona'), (3, 'Atlético de Madrid')]

reduce() Function

The reduce() function in Python is used to reduce a sequence of elements to a single value by repeatedly applying a function of two arguments to the elements of the sequence.

# Basic usage of reduce():
from functools import reduce

def add(x, y):
    return x + y

numbers = [1, 2, 3, 4, 5]
total_sum = reduce(add, numbers)

print(total_sum) # Output: 15

zip() Function

The zip() function in Python combines elements from multiple iterables into tuples until the elements of the shortest iterable are exhausted.

# Basic usage of zip():
names = ["Luis", "María", "Pedro"]
ages = [30, 25, 35, 40]

print(persons) # [("Luis", 30), ("María", 25), ("Pedro", 35)]