3. What is SCALA ?
1. Martin Odersky
2. General purpose programming language.
1. It blends in “Object Oriented” and “functional Programming”
paradigms.
2. SCALA’s innovations come primarily from how its constructs are
put together.
4. What is SCALA ?
Functional Programming:
Is a programming paradigm where we try to divide programs into
functions, which have no side effects i.e. don’t change program state
and void mutable data. Eliminating side effects can make it much
easier to understand and predict the behavior of a program.
5. What is SCALA ?
Object-oriented-programming:
Is a programming paradigm where programs are divided into
containers called Objects which have data fields and
behavior(methods). SCALA is a pure OOP language.
6. SCALA and JAVA
SCALA
JAVA
C++
C
1. SCALA was written keeping in mind that “its impractical” to
come-up with a new programming language and make it widely
acceptable without interoperating with applications from Java.
2. “Java code can call SCALA code” and “SCALA code can can java
code”. Scala gets compiled into Java Byte codes, which gets executed
on Java virtual machine.
7. SCALA AND JAVA
1. So, SCALA was written for Java programmers ?.
2. Most of the courses, books and tutorials assume that you already
know java or at least OOP.
But
8. SCALA for a C language
PROGRAMMER.
There is no shortcut here.
First go and learn Java , or at least go here :
http://docs.oracle.com/javase/tutorial/java/index.html , and ramp up on
Basic OOP concepts.
New and important features of SCALA such as pattern matching, Traits
and compositions need OOP concepts.
Even basic language constructs like If-else, for loops, function
declarations and definitions, etc. are quite different , and not only with
respect to syntax.
9. BUT why SCALA ?
1. A lot of interesting companies like Twitter, Foursquare and
LinkedIn are using/adopting SCALA.
1. There are even some VIM plugins around.
2. Good build tool support like SBT, Maven, Ant etc..
3. SCALA is now in its v2.10. Lot of new features every release.
5. And it is not like IPv4 to IPv6 transformation. It must be fairly
easy for java based applications to port to SCALA.
10. 1.
SOME attractive features OF scala
Variables in SCALA.
1. Variable Immutability.
2. Type inference.
2. Functions in SCALA.
1. Anonymous Functions.
3. SCALA control constructs.
1. If expression.
2. For expression.
4. Pattern Matching.
1. With Constants.
2. With Regular expressions.
11. Variables in SCALA: VAL AND VAR
When programming in C, If we want a variable, most of us will be
thinking in these steps
1. I need an Integer
int
12. VAL AND VAR
1.Let me give it a name “x”, that declares x. This is enough we can go
ahead ,but…
int x;
13. VAL AND VAR
1. Let me initialize it to 0, to be safe. This defines x(allocates
memory)
int x = 0;
14. VAL AND VAR
In SCALA we will have to think in this way:
1. I need a mutable or a immutable field? i.e. val or var ? Lets go
with a val.
val
17. VAL AND VAR
3. Let me initialize it to 0. This ends the value definition.
val x: Int = 0
4. But scala has “Type inference” right!? Why do I need to type it as “Int”. Yes we can omit it. Its enough just to
have this:
val x = 0
20. Function Definitions
• In SCALA
• def factorial(x: Int): Int = {
if(x == 1) x
else x * factorial(x - 1)
}
• So this function is of type (Important!)
• (Int) => Int
21. Function Definitions
• If there is no parameter to function!
• def function1(): Int = {
255
• }
• We can even forget about () and Int!!
• def function2 = {
• 1+2
• } // These functions are of type () => Int
22. Function Definitions
• If the function is not returning anything then we can forget about
“=”
def function3 {
//Body
}
If the function body is of only one line then we can even forget about
“{ }”
def function4 = 1
23. FUNCTION LITERALS
1. Also called as Anonymous Functions, these functions are not
bound to an identifier. Can be written in below format in SCALA.
(x: Int, y:Int) => (x+y)
2. These functions can be passed as arguments to “Higher-order
functions”.
def higherOrderFunc(f: (Int, Int) => Int) : Int;
24. SCALA IF EXPRESSION
It looks similar to if in C, but SCALAS “if” is an expression. So it
returns a value.
if(!args.isEmpty) args(0)
else “default.txt”
And it can be used inside function calls, and as function bodies.
println(if(!args.isEmpty) args(0) else “default.txt”)
OR
def function(args: Array[String]): String =
if(!args.isEmpty) args(0) else “default.txt”
25. SCALA FOR EXPRESSION
For expression in SCALA is the Swiss army knife of iteration.
for ( generator definition filter)
1. Iteration through an Array.
for (x <- 0 to 100)
OR
for (x <- 0 until 100)
OR just
for(x <- args)
26. SCALA FOR EXPRESSION
2. Using Filters
for ( x <- 1 to 100 if x%2 == 0) println(x)
You can use multiple filters :
for { x <-1 to 100
if x%2 == 0
if x%3 == 0 } println(x)
for (x <- args if x.matches(“^d*$”)) println(x)
27. SCALA FOR EXPRESSION
3. Using definitions
for (x <- args y = x.length if y <= max) println(x)
4 . Multiple Generators:
for (x <- args y <- x) println(y)
5. Returning from a for expression using Yield
val y = for(x <- 1 to 100 if x%3 == 0) yield x
28. Pattern Matchinga construct called
Pattern matching in scala is done with the help of
match which looks similar to c language switch.
Simple example: pattern matching with constants
x match {
case “-help” | “-h” => displayHelp
case “-version” | “-v” => displayVersion
case _ => process
}
29. Pattern Matching with Regular
expressions
A simple example, with regular expressions
val regex = "(^d*$)".r
def patternMatch(x: String) = x match {
case regex(a) => println("matched")
case _ => println("Did Not matched")
}
patternMatch("1234")
patternMatch("abcd")
30. KEY DIFFRENCES BETWEEN C AND SCALA
Comparable features C SCALA
Programming paradigm Imperative programming Functional and object oriented programming
Compiler Compiled to machine code Compiled to Byte codes
High-level Data-structures No Language support, but libraries are added on Lists[T], Maps[T,M], Set[T], SortedSet[T,M]
top using primary data types
Concurrency With Help of locks and shared-memory With help of actors, share nothing strategy. But
still supports locks and shared-memory.
Scripting No scripting support Scripting support
Memory management Logic has to be built into the application code to Garbage collector frees memory as soon as it
free allocated memory. goes out of scope
Pattern Matching No support Pattern matching with help of case classes,
regular expressions.
Performance Benchmarking Highly optimized C ++ , short run time code is -----------
about 3 times faster.
Debuggability / Maintenance Difficult to debug as everything is mutable Much easier to debug as mostly everything can
be immutable.
Development Longer development time. Most concise language constructs reduce
development time and number of lines of code
by half compared to Java.
Source: Google benchmarks C++, Go, Java and SCALA Performance
31. 1.
Other Features of SCALA
Singleton Objects.
2. Pattern Matching with case classes.
3. Stackable features with Traits.
4. Companion objects and Factory Methods.
5. Synchronized collections.
6. Concurrent programming with Actors.
These and more can be covered in Part II.
32. 1.
References
Official Scala API database:
http://www.scala-lang.org/api/current/index.html#package
2. Programming in SCALA second edition by Martin Odersky
3. Scala Tutorial at
http://www.tutorialspoint.com/scala/index.htm
