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The names "lambda abstraction", "lambda function", and "lambda expression" refer to the notation of function abstraction in lambda calculus, where the usual function f (x) = M would be written (λx. M), and where M is an expression that uses x. Compare to the Python syntax of lambda x: M.
In Python, functions are first-class objects that can be created and passed around dynamically. Python's limited support for anonymous functions is the lambda construct. An example is the anonymous function which squares its input, called with the argument of 5:
In this example, the lambda expression (lambda (book) (>= (book-sales book) threshold)) appears within the function best-selling-books. When the lambda expression is evaluated, Scheme creates a closure consisting of the code for the lambda expression and a reference to the threshold variable, which is a free variable inside the lambda expression.
The function that accepts a callback may be designed to store the callback so that it can be called back after returning which is known as asynchronous, non-blocking or deferred. Programming languages support callbacks in different ways such as function pointers, lambda expressions and blocks.
In the untyped lambda calculus, where the basic types are functions, lifting may change the result of beta reduction of a lambda expression. The resulting functions will have the same meaning, in a mathematical sense, but are not regarded as the same function in the untyped lambda calculus. See also intensional versus extensional equality.
In calculus, an example of a higher-order function is the differential operator /, which returns the derivative of a function . Higher-order functions are closely related to first-class functions in that higher-order functions and first-class functions both allow functions as arguments and results of other functions.
For example ((call/cc f) e2) is equivalent to applying f to the current continuation of the expression. The current continuation is given by replacing (call/cc f) by a variable c bound by a lambda abstraction, so the current continuation is (lambda (c) (c e2)). Applying the function f to it gives the final result (f (lambda (c) (c e2))).
Currying provides a way for working with functions that take multiple arguments, and using them in frameworks where functions might take only one argument. For example, some analytical techniques can only be applied to functions with a single argument. Practical functions frequently take more arguments than this.