How are lambda functions used in functional programming?

Lambda functions in functional programming are used to create anonymous functions for quick, inline processing.

Lambda functions, also known as anonymous functions, are a fundamental concept in functional programming. They are functions that are defined without a name. While normal functions are defined using the 'def' keyword, in Python anonymous functions are defined using the 'lambda' keyword. Hence, anonymous functions are also called lambda functions.

The use of lambda functions can make your code more concise and easier to read, as they allow you to perform simple, one-off computations without the need for a full function definition. They are typically used in places where you need a small, short-lived function that’s only going to be used once. For example, they are often used as arguments to higher-order functions, which are functions that take other functions as inputs.

Lambda functions are also used extensively in functional programming languages like Lisp and Haskell, where they form the basis for many complex programming constructs. In these languages, lambda functions can be used to create and manipulate other functions, leading to highly flexible and powerful programming techniques.

In Python, a lambda function's syntax is: lambda arguments: expression. The expression is executed and the result is returned. A lambda function can have any number of arguments but can only have one expression. It cannot contain any statements and it returns a function object which can be assigned to any variable.

For example, a lambda function that adds 10 to the number passed in as an argument, and print the result could be: add10 = lambda x: x + 10; print(add10(5)). The output will be 15.

In conclusion, lambda functions in functional programming are a powerful tool that allow for more concise, readable code. They are particularly useful for simple, one-off computations and as arguments to higher-order functions.