每天推荐一个 GitHub 优质开源项目和一篇精选英文科技或编程文章原文，欢迎关注开源日报。交流QQ群：202790710；微博：https://weibo.com/openingsource；电报群 https://t.me/OpeningSourceOrg

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今日推荐开源项目：《简单粗暴的 CMS rwtxt》传送门：GitHub链接

推荐理由：如果打开这个项目会发现个网站，当然也能往网站里瞎写一点东西，不要忘记开地址栏 ctrl + c 再 + v， 只要收好这个链接就没任何问题；之后如果还想看看写的什么玩意，找出链接丢地址栏回车就能运行，这就是它简单粗暴的根本的原因，作为内容管理系统它还相当可行。

顺带一提你们可以看看我的链接：https://rwtxt.com/public/f38cqgo0tm

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今日推荐英文原文：《A 10-Minute Introduction to Scala》作者：Teiva Harsanyi

原文链接：https://hackernoon.com/a-10-minute-introduction-to-scala-d1fed19eb74c

推荐理由：Scala 的入门级简介，这门语言基于 Java 之上，设计初衷是集成面向对象编程和函数式编程的各种特性。

A 10-Minute Introduction to Scala

Scala is a programming language released in 2004 by Martin Odersky. It provides support for functional programming and is designed to be concise and compiled to Java bytecode so that a Scala application can be executed on a Java Virtual Machine (JVM).

Let’s check at the core features of the language.

Hello World

First, let’s see how to implement a hello world in Scala:

package io.teivah.helloworld

object HelloWorld {
  def main(args: Array[String]) {
    println("Hello, World!")
  }
}

We defined a HelloWorld object containing a main method. This method takes an array of String as an input.

In the main, we called the method println which takes an object as an input to print something in the console.

Meanwhile, HelloWorld is also part of the io.teivah.helloworld package.

Values

We can name the result of an expression using the val keyword. In the following example, both expressions are a valid way to define a value:

val v1: String = "foo"
val v2 = "bar"

The type is optional. In the example, v1 and v2 are both typed as a String.

The Scala compiler can infer the type of a value without having to explicitly declare it. This is known as type inference.

A value in Scala is immutable. This means, the following code is not going to compile:

val i = 0
i = 1 // Compilation error

Last but not least, a value can be evaluated lazily using the lazy keyword:

lazy val context = initContext()

In this case, context will not be evaluated during its declaration but during its first invocation.

Variables

A variable is a mutable value. It is declared with the var keyword.

var counter = 0
counter = counter + 5

Just like with values, the type is optional. Yet, a variable cannot be evaluated lazily.

Furthermore, Scala is a statically typed language. The following code, for example, is invalid as we try to map an Int into a variable already defined as a String:

var color = "red"
color = 5 // Invalid

Blocks

In Scala, we can combine expressions by surrounding them with {}. Let’s consider the println() function which takes an object as an input. The two following expressions are similar:

println(7) // Prints 7

println {
  val i = 5
  i + 2
} // Prints 7

Note that for the second println the last expression (i + 2) is the result of the overall block.

When we call a function with a single argument just like println, we can also omit the parenthesis:

println 7

Basic Types

Scala is considered a pure object-oriented language because every value is an object. Hence, there is no primitive in Scala (like Java int for example).

There are 8 basic types in Scala:

• Byte
• Short
• Int
• Long
• Float
• Double
• Char
• Boolean

Every basic Scala type inherits from AnyVal. On the other side, AnyRef is an alias for java.lang.Object. Lastly, both AnyVal and AnyRef inherits from Any.

String Interpolation

Scala provides an elegant way to embed variable/value references directly in processed string literals. As a concrete example:

val name = "Bob"
println(s"Hello $name!") // Hello Bob!

This is made possible by the s interpolator before the quotation mark. Otherwise, it would print Hello $name!.

There are few interpolators provided by Scala but it is a customizable mechanism. We can create for example our own interpolator to handle JSON conversions like this: println(json"{name: $name}").

Array and List

An array is also handled in Scala as an object:

val a = new Array[Int](2)
a(0) = 5
a(1) = 2

Two things to highlight here.

Firstly, the way to set elements. Instead of using a[0] like in many languages, we use the syntax a(0). This is a syntactic sugar to let us call an object just as if it was a function. Under the hood, the compiler is calling a default method called apply() taking a single input (an Int in our case) to make it possible.

Secondly, despite being declared as a val in this example, the Array object is mutable so we can change the value of indexes 0 and 1. val just enforces to not mutate the reference, not the corresponding object.

An array can also be initialized this way:

val a = Array(5, 2)

This expression is similar than above. Moreover, because it is initialized with 5 and 2, the compiler infers a as an Array[Int].

To manage multi-dimensional arrays:

val m = Array.ofDim[Int](3, 3)
m(0)(0) = 5

This code creates a two-dimensional array and initializes the very first element to 5.

There are many different data structures composing the Scala standard library. One of them is the immutable List:

val list = List(5, 2)
list(0) = 5 // Compilation error

Compared to Array, modifying an index after having initialized a List will lead to a compilation error.

Map

A map can be initialized like this:

val colors = Map("red" -> "#FF0000", "azure" -> "#F0FFFF", "peru" -> "#CD853F")

Note the -> operator to associate a color key to its corresponding hexadecimal value.

Map is an immutable data structure. Adding an element means creating another Map:

val colors1 = Map("red" -> "#FF0000", "azure" -> "#F0FFFF", "peru" -> "#CD853F")
val colors2 = colors1 + ("blue" -> "#0033FF")

Meanwhile, the elements cannot be modified. In the case we need a mutable structure, we can use scala.collection.mutable.Map:

val states = scala.collection.mutable.Map("AL" -> "Alabama", "AK" -> "tobedefined")
states("AK") = "Alaska"

In this example, we mutated the AK key.

Methods/Functions: Basics

We have to make the distinction between methods and functions. A method is a function that is a member of a class, trait or object (we are going those notions).

Let’s see a basic method example:

def add(x: Int, y: Int): Int = {
  x + y
}

Here we defined an add method with the def keyword. It took two Int as an input and returned an Int. Both inputs are immutable (in the sense that they are managed just like if they were declared as val).

The return keyword is optional. The method will automatically return the last expression. Moreover, it’s worth mentioning that in Scala (compared to Java), return exits the current method, not the current block.

One last thing to add, the return type is optional. The Scala compiler is also able to infer it. Yet, for the sake of code maintainability, it might be a good option to set it explicitly.

Furthermore, a method without output can be written is both ways:

def printSomething(s: String) = {
  println(s)
}

def printSomething(s: String): Unit = {
  println(s)
}

We can also return multiple outputs like this:

def increment(x: Int, y: Int): (Int, Int) = {
  (x + 1, y + 1)
}

This prevents us from having to wrap a set of outputs in a specific object.

Another syntactic sugar to mention. Let’s consider a bar method without arguments. We can call this method in both ways:

def foo(): Unit = {
  bar()
  bar
}

The best practice is to keep the parenthesis only if bar introduces a side-effect. Otherwise, we call bar like in the second expression.

Also, Scala allows us to indicate that a method argument can be repeated. Just like in Java, this repeatable argument must be the last parameter:

def variablesArguments(args: Int*): Int = {
  var n = 0
  for (arg <- args) {
    n += arg
  }
  n
}

Here, we iterate over each args element and we return an aggregated sum.

Last but not least, we can also define default parameters value:

def default(x: Int = 1, y: Int): Int = {
  x * y
}

Invoking default without providing a value for x can be done in two ways.

First, using the _ operator:

default(_, 3)

Or, using named arguments like this:

default(y = 3)

Methods/Functions: Advanced

Nested Methods

In Scala, we can nest method definitions. Let’s consider the following example:

def mergesort1(array: Array[Int]): Unit = {
  val helper = new Array[Int](array.length)
  mergesort2(array, helper, 0, array.length - 1)
}

private def mergesort2(array: Array[Int], helper: Array[Int], low: Int, high: Int): Unit = {
  if (low < high) {
    val middle = (low + high) / 2
    mergesort2(array, helper, low, middle)
    mergesort2(array, helper, middle + 1, high)
    merge(array, helper, low, middle, high)
  }
}

In this case, mergesort2 method is used solely by mergesort1. To restrict its access, we may decide to set it private (we’ll see later on the different visibility levels).

Yet, in Scala we can also decide to nest the second method into the first one like that:

def mergesort1(array: Array[Int]): Unit = {
  val helper = new Array[Int](array.length)
  mergesort2(array, helper, 0, array.length - 1)

  def mergesort2(array: Array[Int], helper: Array[Int], low: Int, high: Int): Unit = {
    if (low < high) {
      val middle = (low + high) / 2
      mergesort2(array, helper, low, middle)
      mergesort2(array, helper, middle + 1, high)
      merge(array, helper, low, middle, high)
    }
  }
}

mergesort2 becomes available only in the scope of mergesort1.

Higher-Order Functions

Higher-order functions take as parameters a function or return a function as a result. As an example of a method taking a function as a parameter:

def foo(i: Int, f: Int => Int): Int = {
  f(i)
}

f is a function taking an Int as an input and returning an Int. In our example, foo delegates the execution to f by passing i to it.

Function Literals

Scala is considered as a functional language in the sense that every function is a value. It means we can express a function in a function literal syntax like that:

val increment: Int => Int = (x: Int) => x + 1

println(increment(5)) // Prints 6

increment is a function with an Int => Int type (which could have been inferred by the Scala compiler). For each integer x it returns x + 1.

If we take again the previous example, we could pass increment to foo:

def foo(i: Int, f: Int => Int): Int = {
  f(i)
}

def bar() = {
  val increment: Int => Int = (x: Int) => x + 1

  val n = foo(5, increment)
}

We can also manage so-called anonymous functions:

val n = foo(5, (x: Int) => x + 1)

The second parameter is a function without any name.

Closure

A closure in a function literal which depends on the value of one or more variable/value declared outside this function.

A simple example:

val Pi = 3.14

val foo = (n: Int) => {
  n * Pi
}

Here, foo depends on Pi which is declared outside of foo.

Partial Functions

Let’s consider the following method to compute the speed from a distance and a time:

def speed(distance: Float, time: Float): Float = {
  distance / time
}

Scala allows us to partially apply speed by calling it only with a subset of the mandatory inputs:

val partialSpeed: Float => Float = speed(5, _)

Note that in this example, none of the parameters of speed have a default value. So in order to call it, we need to fill all the parameters.

In this example, partialSpeed is a function of type Float => Float.

Then, in the same way as we were calling increment, we can call partialSpeed like this:

println(partialSpeed(2.5f)) // Prints 2.0

Currying

A method can define multiple parameter lists:

def multiply(n1: Int)(n2: Int): Int = {
  n1 * n2
}

This method is doing exactly the same job than:

def multiply2(n1: Int, n2: Int): Int = {
  n1 * n2
}

Yet, the way to call multiply is different:

val n = multiply(2)(3)

Like requested by the method signature, we call it with two lists of parameters. Then, what if we call multiply with only one list of parameters?

val partial: Int => Int = multiply(2)

In this case, we partially applied multiply which gives us in return an Int => Int function.

What are the benefits? Let’s consider a function to send a message given a particular context:

def send(context: Context, message: Array[Byte]): Unit = {
  // Send message
}

As you can see, there’s an effort made to make this function pure. Instead of depending on an external context, we make it available as a parameter of the send function.

Yet, it might be somewhat tedious to have to pass this context during every single call of send. Or maybe a function does not need to know about the context.

One solution may be to partially apply send with a predefined context and to manage an Array[Byte] => Unit function.

Another solution is to curry send and make the context parameter implicit like this:

def send(message: Array[Byte])(implicit context: Context): Unit = {
  // Send message
}

How can we call send in this case? We can define an implicit context before to call send:

implicit val context = new Context(...)
send(bytes)

The implicit keyword means that for every function managing an implicit Context parameter, we don’t even need to pass it. It will automatically be mapped by the Scala compiler.

In our case, send manages the Context object as a potential implicit (we can also decide to pass it explicitly). So, we can simply call send with the first argument list.

Classes

A class in Scala is a similar concept than in Java:

class Point(var x: Int, var y: Int) {
  def move(dx: Int, dy: Int): Unit = {
    x += dx
    y += dy

    println(s"$x $y")
  }
}

Point exposed a default (Int, Int) constructor because of the syntax line 1. Meanwhile, x and y are two members of the class.

A class can also contain a collection of methods just like move in the previous example.

We can instantiate Point with the new keyword:

val point = new Point(5, 2)

A class can be abstract meaning it cannot be instantiated.

Case Classes

Case classes are a particular kind of classes. If you are familiar with DDD (Domain Driven Design), a case class is a value object.

By default, a case class is immutable:

case class Point(x: Int, y: Int)

The value of x and y cannot be changed.

A case class must be instantiated without new:

val point = Point(5, 2)

Case classes (compared to regular classes) are compared by value (and not by reference):

if (point1 == point2) {
  // ...
} else {
  // ...
}

Objects

An object in Scala is a singleton:

object EngineFactory {
  def create(context: Context): Engine = {
    // ...
  }
}

Objects are defined with the object keyword (?).

Traits

Traits are in a way similar to Java interfaces. They are used to share interfaces between classes but also fields. As an example:

trait Car {
  val color: String
  def drive(): Point
}

A trait method can also have a default implementation.

Traits cannot be instantiated but they can be extended by classes and objects.

Visibility

In Scala, every member of a class/object/trait is public by default. There are two other access modifiers:

• protected: members are only accessible from sub-classes
• private: members are only accessible from the current class/object

Furthermore, we can also have a more granular way to restrict access by specifying a package in which the restriction is applied.

Let’s consider a class Foo in a bar package. If we want to make a method private only outside of bar we can do it this way:

class Foo {
  private[bar] def foo() = {}
}

Generics

Generics is also a feature provided by Scala:

class Stack[A] {
  def push(x: A): Unit = { 
    // ...
  }
}

To instantiate a generic class:

val stack = new Stack[Int]
stack.push(1)

If-else

If-else syntax is similar in Scala than in several other languages:

if (condition1) {

} else if (condition2) {

} else {

}

Yet, in Scala an if-else statement is also an expression. It means we can, for example, define methods like this:

def max(x: Int, y: Int) = if (x > y) x else y

Loops

A basic loop can be implemented like this:

// Include
for (a <- 0 to 10) {
  println(a)
}

// Exclude
for (a <- 0 until 10) {
  println(a)
}

to means from 0 to 10 included whereas until means from 0 to 10 excluded.

We can also loop over two elements:

for (a <- 0 until 2; b <- 0 to 2) {
  
}

In this example we iterated over all the possible tuple combinations:

a=0, b=0
a=0, b=1
a=0, b=2
a=1, b=0
a=1, b=1
a=1, b=2

We can also include conditions in the for. Let’s consider the following list of elements:

val list = List(5, 7, 3, 0, 10, 6, 1)

If we need to iterate over each element of list and consider only the even integers, we can do it this way:

for (elem <- list if elem % 2 == 0) {
  
}

Moreover, Scala provides so-called for comprehensions to create sequence of elements with the form for() yield element. As an example:

val sub = for (elem <- list if elem % 2 == 0) yield elem

In this example, we created a collection of even integers by iterating over each element and yielding it in case it is even. As a result, sub will be inferred as a sequence of integers (a Seq object, the parent of List).

In the same way than with if-else statement, for is also an expression. So we can also define methods like this:

def even(list: List[Integer]) = for (elem <- list if elem % 2 == 0) yield elem

Pattern Matching

Pattern matching is a mechanism to check a value against a given pattern. It is an enhanced version of the Java switch statement.

Let’s consider a simple function to translate an integer into a string:

def matchA(i: Int): String = {
  i match {
    case 1 => return "one"
    case 2 => return "two"
    case _ => return "something else"
  }
}

Scala adds a bit of syntactic sugar to implement an equivalent this way:

def matchB(i: Int): String = i match {
  case 1 => "one"
  case 2 => "two"
  case _ => "something else"
}

First, we removed the return statements. Then, matchB function becomes a pattern matcher as we removed the block statement after the function definition.

Anything else apart from some sugar? Pattern matching is a great addition to case classes. Let’s consider an example taken from Scala documentation.

We want to return a String depending on a notification type. We define an abstract class Notification and two case classes Email and SMS:

abstract class Notification
case class Email(sender: String, title: String, body: String) extends Notification
case class SMS(caller: String, message: String) extends Notification

The most elegant way to do it in Scala is to use pattern matching on the notification:

def showNotification(notification: Notification): String = {
  notification match {
    case Email(email, title, _) =>
      s"You got an email from $email with title: $title"
    case SMS(number, message) =>
      s"You got an SMS from $number! Message: $message"
  }
}

This mechanism allows us to cast the given notification and to automatically parse the parameters we are interested in. For example, in the case of an email, maybe we are not interested in displaying the body so we simply omit it with _ keyword.

Exceptions

Let’s consider the concrete use case where we need to print the number of bytes from a given file. To perform the I/O operation, we are going to use java.io.FileReader which may throw exceptions.

The most common way to do it if you are a Java developer would be something like this using a try/catch statement:

try {
  val n = new FileReader("input.txt").read()
  println(s"Success: $n")
} catch {
  case e: Exception =>
    e.printStackTrace
}

The second way to implement it is somewhat similar to Java Optional. As a reminder, Optional is a container brought in Java 8 for optional values.

In Scala, Try is a container for success or failures. It is an abstract class, extended by two case classes Success and Failure.

val tried: Try[Int] = Try(new FileReader("notes.md")).map(f => f.read())
    
tried match {
  case Success(n) => println(s"Success: $n")
  case Failure(e) => e.printStackTrace
}

We first wrap the creation of a new FileReader in a Try call. We use a map to convert an eventual FileReader to an Int by calling the read method. As a result, we get a Try[Int].

Then, we can use pattern matching to determine the type of tried.

Implicit Conversions

Let’s analyze the following example:

case class Foo(x: Int)
case class Bar(y: Int, z: Int)

object Consumer {
  def consume(foo: Foo): Unit = {
    println(foo.x)
  }
}

object Test {
  def test() = {
    val bar = new Bar(5, 2)
    Consumer.consume(bar)
  }
}

We defined two case classes Foo and Bar.

Meanwhile, an object Consumer exposes a consume method taking a Foo in parameter.

In Test, we call Consumer.consume() but not with a Foo as required by the signature of the method but with a Bar. How is this possible?

In Scala, we can define implicit conversions between two classes. In the last example, we simply need to describe how to convert a Bar to a Foo:

implicit def barToFoo(bar: Bar): Foo = new Foo(bar.y + bar.z)

If this method barToFoo is imported, the Scala compiler will make sure that we can call consumer with either a Foo or a Bar.

Concurrency

To handle concurrency, Scala was initially based on the actor model. Scala was providing the scala.actors library. Yet, since Scala 2.10 this library became deprecated in favor of Akka actors.

Akka is a set of libraries for implementing concurrent and distributed applications. Nonetheless, we can also use Akka only at the scale of a single process.

The main idea is to manage actors as a primitive for concurrent computation. An actor can send messages to other actors, receive and react to messages and spawn new actors

Just like other concurrent computation models like CSP (Communicating Sequential Processes), the key is to communicate through messages instead of sharing memory between different threads.

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Scala is a very elegant language. Yet, the learning curve is not that small compared to other languages like Go for example. Reading an existing Scala code as a beginner might be somewhat difficult. But once you start to master it, developing an application can be done in a very efficient way.

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Further Reading

Documentation | Scala Documentation
Install Scala on your computer and start writing some Scala code!docs.scala-lang.org

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每天推荐一个 GitHub 优质开源项目和一篇精选英文科技或编程文章原文，欢迎关注开源日报。交流QQ群：202790710；微博：https://weibo.com/openingsource；电报群 https://t.me/OpeningSourceOrg