How to use list comprehensions in Python?

List comprehensions in Python provide 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 a condition to filter items. They are often used as a more compact and expressive alternative to traditional for-loops that build lists. The basic syntax of a list comprehension is: ```python [expression for item in iterable if condition] ``` - **expression**: The value or operation applied to each `item`. - **item**: The variable representing each element in the iterable. - **iterable**: Any Python iterable (e.g., list, tuple, range). - **if condition** (optional): A filter that includes only items where the condition evaluates to `True`. ### Example 1: Creating a list of squares Using a traditional loop: ```python squares = [] for x in range(10): squares.append(x**2) print(squares) ``` Using a list comprehension: ```python squares = [x**2 for x in range(10)] print(squares) ``` Both produce: `[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]` ### Example 2: Filtering with a condition Suppose you want only the even squares: ```python even_squares = [x**2 for x in range(10) if x % 2 == 0] print(even_squares) ``` Output: `[0, 4, 16, 36, 64]` ### Additional notes - List comprehensions can be nested to handle multi-dimensional data, but be careful to keep them readable. - They can also be used with functions and more complex expressions. - For very complex logic, traditional loops may be clearer. Overall, list comprehensions help you write compact, readable, and often faster code when creating lists from iterables. They are a fundamental Python idiom worth practicing!