In fact, every mutator method can be replaced by a function that returns a new array with the desired changes. The same thing goes when using a Map or a Set.
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We can avoid mutator methods by returning a new Map or Set with the desired changes. If you call Object. Because of how Maps and Sets are represented internally, calling Object. But it's easy enough to tell the compiler that you would like them to be read-only.
Okay, so we can create new objects instead of mutating existing ones, but won't that adversely affect performance? Yes, it can. Be sure to do performance testing in your own app. If you need a performance boost, then consider using Immutable. This is the same technique used internally by functional programming languages such as Clojure and Scala. Remember thinking, "When am I ever going to use this? There are libraries such as Ramda and lodash that provide a more elegant way of composing functions.
There will be no loops for , for None period. But that's impossible, you say! Not so. That leads us to the next two topics: recursion and higher-order functions. Let's say that you would like to implement a function that computes the factorial of a number. Let's recall the definition of factorial from mathematics:. That is, n! We can write a loop that computes that for us easily enough. Notice that both product and i are repeatedly being reassigned inside the loop. This is a standard procedural approach to solving the problem.
How would we solve it using a functional approach? We would need to eliminate the loop and make sure we have no variables being reassigned.
Recursion is one of the most powerful tools in the functional programmer's toolbelt. Recursion asks us to break down the overall problem into sub-problems that resemble the overall problem. Computing the factorial is a perfect example. To compute n!
Functional Programming Fundamentals
That's the same thing as saying:. We found a sub-problem to solve n-1! There's one more thing to take care of: the base case. The base case tells us when to stop the recursion. If we didn't have a base case, then recursion would go on forever. In practice, you'll get a stack overflow error if there are too many recursive calls.
What is the base case for the factorial function? With this information in mind, let's write a recursive factorial function. Okay, so let's compute recursiveFactorial , because When we do, we get this:. So what's going on here? We got a stack overflow error! It's not because of infinite recursion. We know that we handled the base case i.
It's because the browser has a finite stack and we have exceeded it. Each call to recursiveFactorial causes a new frame to be put on the stack. We can visualize the stack as a set of boxes stacked on top of each other. Each time recursiveFactorial gets called, a new box is added to the top.
The following diagram shows a stylized version of what the stack might look like when computing recursiveFactorial 3. Note that in a real stack, the frame on top would store the memory address of where it should return after executing, but I have chosen to depict the return value using the variable r.
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In a conveyor belt or assembly line, a raw input is passed down the different steps on the belt, with each step adding to or modifying the item in some way and passing it onto the next function on the belt. Functions can be thought of as steps taken to convert the raw input the parts into the processed good the output. The assembly line in functional programming builds new outputs while leaving the inputs intact , whereas the assembly line in traditional object-oriented programming transforms the input.
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A good way to conceptualise and understand the benefit of functional programming is to think in terms of values. Rich Hickey , the author of Clojure a functional programming language , sums up this concept in this excellent video. He calls this paradigm place-oriented programming PLOP , and explains how it was born of limitations of early computers where RAM and durable storage was expensive and in short supply, rendering place-centric implementation necessary.
In modern computing, these limitations no longer exist. Place is therefore no longer a concern and has NO relevance in an information model. In the value-oriented programming model, values are immutable, easily shared and semantically transparent you can see all of what it is. This is the key of functional programming and higher order functions. Some of the other awesome benefits of value-programming that Rich describes are:. Operations on values are stable performing the same operation on the same value will always produce the same answer. This means easily r eproducible results.
Testing and debugging can therefore reproduce failures without needing to replicate state first. Values are language independent , enabling polyglot programming. Places are defined by language constructs. Values are generic. They consist of very few value types lists, maps, sets, strings, numbers.