12/19/2023 0 Comments Recursive sequence ruby![]() ![]() We can say that this is a function generator in some sense. Currying - Transforming a function that takes multiple arguments into a function that takes one argument and return function.Higher-order functions - Functions which can get function as argument or return function as a result.This is also a side effect of referential transparency. Idempotence - You will get the same results no matter how many times you will call a function.It can seed up computations by saving the results of previous calls. Memoization - It is a side effect of referential transparency.Referential transparency - this is combining pure function and immutability.Instead of changing state or value, you create a new one. Immutability - After the state/value is created, you cannot change it.This is how the function works in the mathematical world. Pure functions (no side-effects) - Function always returns the same result for the same arguments and function can never cause any observable side effects.OK, so what are the features of functional programming language? That means it is a way to classify programming languages based on their features. ![]() What is functional programming? You can find out, that functional programming is a programming paradigm. Let’s focus on functional programming its self. Because of this different inspirations we can find in Ruby not only object oriented concepts, but also a little bit of functional programming.īefore we start going deep in functional programming in Ruby. When you take a look closer to the history of the Ruby language, you can find out, that Ruby was influenced by other languages like Perl, Smalltalk, Eiffel, Ada, Basic or Lisp. That doesn’t mean we cannot do some functional programming in Ruby. (1) yields a " is an object oriented language. * Different ways to calculate the sum of a list using ![]() ![]() The third approach shows how to use an if/else construct instead of a match expression. This solution uses the “accumulator” I mentioned above. The second approach shows how to fix the first approach by using a tail-recursive algorithm. I don’t think the first approach is practical it is simple, but results in a StackOverflowError when the list is large. The following code shows three ways to calculate the sum of a List recursively. I show this in the examples that follow, and I’ll describe it more at some point in the future. In the Fibonacci example the function prints its result as it goes along, so it doesn’t return anything.Īs another note, in some cases it helps to have an “accumulator” function inside your main function. For instance, in the sum, product, and max functions that follow, the function returns an Int.
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