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Introduction to Scala
Scala, a programming language, was developed by Martin Odersky and his research group in 2003. The development of Scala was a revolution in the world of big data. It is an extremely sturdy and merited language that was going to change the world for generations to come. It is compiler-based, which makes it extremely quick and proficient.
The significant bit of leeway of Scala is the Java Virtual Machine (JVM). Scala code was first accumulated by a Scala compiler and the byte code for the equivalent is created, which will be then moved to the Java Virtual Machine to produce the yield. Along these lines, Scala turned into the way to progress for dealing with the gigantic measure of big-data.
Why is Scala fancied so much in the programming community?
Scala has more than just a few reasons to be preferred by various programmers. Let’s discuss a few of them here.
It is a multi-paradigm language
Scala is competent enough to underpin two programming paradigms, i.e., Functional Programming (FP) and Object-Oriented Programming (OOP).
The compiler in Scala, also known as Scala is extremely capable and can perform more than you’d expect. To name a few things, it can engender hasCode(), equals(), toString(), and more.
Easy to learn
Since Scala supports object-oriented programming, it is relatively easy to learn for programmers when compared to Java. With a rapidly growing online community, Scala forums are becoming more and more recurrent. A major part of this is because it has fine libraries along with a neat syntax. While programmers manoeuvre their way through functional programming and learn, they can still use their pre-existing object-oriented programming skills and build things in Scala.
New career opportunities
Due to its massive scalability, Scala is now more and more in demand in the industry. With top-notch brands like Twitter, Quora, LinkedIn, etc. migrating to Scala, it is obvious that they’d be looking for coders skilled in Scala. It’s only a matter of time until Scala becomes the need of the hour for other major firms in other industries.
The Scala compiler uses its type-inference to the utmost of its capability and hence, though it feels dynamic, Scala is methodically statically typed. This enables type inference for variables and functions in Scala.
Now that we’ve understood what Scala is, let’s move forward and understand currying in Scala.
Currying in Scala
Currying is named after an American mathematician Haskell Curry, known for his work in combinatory logic.
Currying in Scala can be defined as the strategy behind interpreting the assessment of a function that takes various arguments in order to assess a group of functions, each with a solitary function.
Mathematically, we can write it as follows –
f1 = f(a)
f2 = f1(b)
result = f2(c)
And, the pseudo code for this will be as –
result = f(a)(b)(c)
Syntax of Currying
The syntax used for performing currying in Scala is mentioned as follows:
def multiply(a:Int)(b:Int) = a*b
It can also be written as the following:
def multiply(a:Int) = (b:Int) => a*b
How to call a Currying Function
In order to call the currying functions in Scala, we have to assign values to the variables ‘a’ and ‘b’ mentioned in the above equations.
What are Partially Applied Functions?
When a function is invoked, it is done in order to apply the function to a set of arguments. In the event that you pass all the anticipated arguments, you end up applying the function fully. When you send just a couple of arguments, you get back a partially applied function. This gives you the accommodation of restricting a few arguments and filling out the rest later.
Example of a partially applied function –
Step 1: Define a function with multiple parameters
scala> def plus(a: int)(b: int) = a + b
plus: (a: int)(b: int)int
Step 2: Only give the value for the variable ‘a’ while a placeholder in the form of an underscore for variable ‘b’
scala> def X = X(2)(_)
X: int => int
The output here creates a new function ‘X’ of the type int => int.
Here, X can be written as follows
def X(b:int) = 2 + b
What the above equation portrays is that when X is seeded with the initial int value of 2, it sits there waiting for another int value it can add to.
As a rundown, partially applied functions give the following capacities
- You compose a general function.
- You make a particular function from the general function.
- You will have access to both the functions despite everything.
- You keep your code dry as you didn’t have to copy-paste code to create a new function.
Comparing Currying and Partially Applied Functions (PAFs)
Currying and PAFs are closely related. Currying and partially applied functions may appear equivalent – both transform your functions into ones with fewer arguments. However, there’s a distinction between them.
- Currying in Scala consistently creates nested unary or 1-ary functions. The function hence changed is still, to a great extent, similar to the first one.
- The partial application creates functions of a subjective number of arguments. The changed function is not quite the same as the first – it needs lesser arguments when compared to the first one.
- Currying in Scala isn’t a partial application, but it can very well be executed in utilizing the partial application. You can’t apply curry to a function if it doesn’t take the fixed quantity of parameters. It won’t work successfully otherwise.
Here are a few preeminent Scala frameworks you can check out to get a good understanding of Scala –
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