PYTHON
Filtering and Mapping Lists with Comprehensions
Use Python list comprehensions for concise filtering and transformation of list elements, streamlining data processing and preparation for web applications.
# Example 1: Filtering a list
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = [num for num in numbers if num % 2 == 0]
# even_numbers will be [2, 4, 6, 8, 10]
# Example 2: Mapping values (transforming each item)
words = ["hello", "world", "python", "web"]
uppercase_words = [word.upper() for word in words]
# uppercase_words will be ['HELLO', 'WORLD', 'PYTHON', 'WEB']
# Example 3: Combining filtering and mapping
products = [
{"name": "Laptop", "price": 1200, "in_stock": True},
{"name": "Mouse", "price": 25, "in_stock": False},
{"name": "Keyboard", "price": 75, "in_stock": True},
]
available_product_names = [p["name"] for p in products if p["in_stock"]]
# available_product_names will be ['Laptop', 'Keyboard']
How it works: List comprehensions offer a succinct syntax to create new lists based on existing iterables. They can be used to filter elements (by including an `if` clause) or to transform elements (by applying an expression to each item), or both. This method significantly improves code readability and performance compared to traditional `for` loops with `append()`, making it a go-to for data manipulation, cleaning, and preparation tasks in web applications.