Lambda Functions

Lambda functions, also known as anonymous functions, are small, one-line functions defined using the lambda keyword. They are used for creating small, throwaway functions that are not necessarily required to be named.

Syntax

lambda arguments: expression

Arguments: The inputs to the lambda function, similar to parameters in regular functions.
Expression: A single expression that is evaluated and returned by the lambda function.

Example

Define a lambda function that adds two numbers:

add = lambda x, y: x + y
print(add(5, 3))  # Output: 8

Common Uses

Short-lived Functions: Lambda functions are often used for short operations where defining a full function is unnecessary.
Higher-order Functions: Useful in functions like map(), filter(), and sorted() where a simple function is required.

Example with `map()`:

numbers = [1, 2, 3, 4]
squared = map(lambda x: x**2, numbers)
print(list(squared))  # Output: [1, 4, 9, 16]

Example with `filter()`:

numbers = [1, 2, 3, 4, 5, 6]
even_numbers = filter(lambda x: x % 2 == 0, numbers)
print(list(even_numbers))  # Output: [2, 4, 6]

Example with `sorted()`:

points = [(2, 3), (1, 2), (4, 1)]
sorted_points = sorted(points, key=lambda point: point[1])
print(sorted_points)  # Output: [(4, 1), (1, 2), (2, 3)]

Limitations

Single Expression: Lambda functions can only contain a single expression, not multiple statements or complex logic.
Readability: Overusing lambda functions for complex operations can reduce code readability. For complex functions, prefer regular function definitions.

Best Practices

Use for Simple Operations: Lambda functions are ideal for simple, short operations.
Prefer Named Functions for Complex Logic: For more complex logic, define a named function using def to improve readability and maintainability.
Keep it Readable: Ensure lambda functions are used in contexts where their brevity enhances code clarity, not detracts from it.

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