How do list comprehensions work?

List comprehensions are a concise and readable way to create new lists by applying an expression to each item in an existing iterable (like a list or range), optionally including conditions to filter elements. They are often used to simplify code that would otherwise require writing loops and appending items to a list. ### Basic Syntax ```python [new_item for item in iterable if condition] ``` - `new_item` is an expression that transforms each `item`. - `iterable` is any sequence or collection you loop over. - The `if condition` is optional and filters which items are included. ### Simple Example Suppose you want to create a list of squares for numbers 0 through 4: ```python squares = [x**2 for x in range(5)] print(squares) # Output: [0, 1, 4, 9, 16] ``` This replaces the more verbose: ```python squares = [] for x in range(5): squares.append(x**2) ``` ### Example with Condition If you want only the squares of even numbers: ```python even_squares = [x**2 for x in range(10) if x % 2 == 0] print(even_squares) # Output: [0, 4, 16, 36, 64] ``` This filters out odd numbers by including only those `x` where `x % 2 == 0`. ### When Are List Comprehensions Useful? - They make code shorter and often easier to read. - Great for simple transformations and filtering. - Useful for creating lists in a single, clear expression. - Preferred in many Python codebases for readability and conciseness. However, for very complex logic, nested loops, or multiple conditions, traditional loops might be clearer. But for most everyday tasks, list comprehensions are a powerful and Pythonic tool to keep your code clean and efficient.