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This creates a higher-order function, and passing this higher function itself allows anonymous recursion within the actual recursive function. This can be done purely anonymously by applying a fixed-point combinator to this higher order function. This is mainly of academic interest, particularly to show that the lambda calculus has recursion ...
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.
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.
The term closure is often used as a synonym for anonymous function, though strictly, an anonymous function is a function literal without a name, while a closure is an instance of a function, a value, whose non-local variables have been bound either to values or to storage locations (depending on the language; see the lexical environment section below).
Chains of three or more functions are possible; for example, function 1 calls function 2, function 2 calls function 3, and function 3 calls function 1 again. Indirect recursion is also called mutual recursion , which is a more symmetric term, though this is simply a difference of emphasis, not a different notion.
An example is the anonymous function which squares its input, called with the argument of 5: f = lambda x : x ** 2 f ( 5 ) Lambdas are limited to containing an expression rather than statements , although control flow can still be implemented less elegantly within lambda by using short-circuiting, [ 20 ] and more idiomatically with conditional ...
In computer programming, apply applies a function to a list of arguments. Eval and apply are the two interdependent components of the eval-apply cycle, which is the essence of evaluating Lisp, described in SICP. [1] Function application corresponds to beta reduction in lambda calculus.
The practical motivation for partial application is that very often the functions obtained by supplying some but not all of the arguments to a function are useful; for example, many languages have a function or operator similar to plus_one. Partial application makes it easy to define these functions, for example by creating a function that ...