Don't's

  • Using null in Scala code is not idiomatic at all.

    • private var author:Author = null
  • If you can't give a default value, you really should use

    • var author: Option[Author] = None
  • Don't rebind names for different uses:

    • Use vals

  • Avoid using 's to overload reserved names:

    • typ instead of 'type'

  • Don't prefix getters with get

    • money.count not money.getCount

  • Do not use relative imports from other packages :

     Avoid

          import com.twitter

          import concurrent

    In favor of the unambiguous

          import com.twitter.concurrent
  • The return keyword exits from the enclosing method, not the enclosing function. It behaves like a restricted throw, so don't use return unless it's in an exceptional situation where an API mandates error codes.  In all other situations, prefer Option, Either, case classes, or, if necessary, exceptions.

  • Do not use structural types in normal use.
private type FooParam = {
 val baz: List[String => String]
 def bar(a: Int, b: Int): String
}
def foo(a: FooParam) = ...

Do's

  • Use short names for small scopes:
    • is,js and ks are all but expected in loops
  • Use longer names for larger scopes:
    • External API's should have longer and explanatory names that confer meaning,  Future.collect not Future.all.
  • Use common abbreviations:
    • Ex: ok, err
  • Use active names for operations with side effects:
    • user.activate() not user.setActive()
  • Use descriptive names for methods that return values:
    • file.isDir not file.dir
  • Use private[this] = visibility to the particular instance. Sometimes it aids performance optimizations.
  • In singleton class types , visibility can be constrained by declaring the returned type:  

def foo(): Foo with Bar = new Foo with Bar with Baz {
            ...
      }


Traits

  • Traits that contain implementation are not directly usable from Java: extend an abstract class with the trait instead.

// Not directly usable from Java
        trait Animal {
           def eat(other: Animal)
           def eatMany(animals: Seq[Animal) = animals foreach(eat(_))
         }
// But this is:
abstract class JavaAnimal extends Animal
  • Keep traits short and orthogonal: don’t lump separable functionality into a trait, think of the smallest related ideas that fit together.   

    For example, imagine you have an something that can do IO:

  trait IOer {
          def write(bytes: Array[Byte])
          def read(n: Int): Array[Byte]
   }

separate the two behaviors:

  trait Reader {
        def read(n: Int): Array[Byte]
    }
   trait Writer {
       def write(bytes: Array[Byte])
   }

and mix them together to form what was an IOer:

new Reader with Writer…

Names

Don't repeat names that are already encapsulated in package or object name.
Prefer:

object User{
	def user(id: Int): Option[User]
}

Instead of:

object User{
	def getUser(id: Int): Option[User]
}

Pattern Matching

  • Use pattern matching directly in function definitions whenever applicable

          Use this :    

     list map {
                   case Some(x) => x
                   case None => default
              }

    Instead of :

    list map { item =>
                    item match {
                        case Some(x) => x
                        case None => default
                   } }


  • Pattern matching works best when also combined with destructuring

    Use this:

    animal match {
    	case Dog(breed) => "dog (%s)".format(breed)
    	case other => other.species
    }

    Instead of:

     animal match {
            case dog: Dog => "dog (%s)".format(dog.breed)
            case _ => animal.species
         }

Don't use pattern matching for conditional execution when defaults make more sense.

Use:

val x = list.headOption getOrElse default

NOT:

 val x = list match {
             case head :: _ => head
             case Nil => default
         }
  • Scala provides an exception facility, but do not use it for commonplace errors, Instead, encode such errors explicitly: using Option

Use: 

trait Repository[Key, Value] {
          def get(key: Key): Option[Value]
     }

Instead of:

trait Repository[Key, Value] {
          def get(key: Key): Value
      }
  • Use the following style:    
/**
     * ServiceBuilder builds services
     * ...
*/

Instead of the standard ScalaDoc style:

/** ServiceBuilder builds services
     * ...
*/

Imports

  • Sort import lines alphabetically. This makes it easy to examine visually, and is simple to automate.
  • Use braces when importing several names from a package:
    • import com.twitter.concurrent.{Broker, Offer}
  • Use wildcards when more than six names are imported:
    • import com.twitter.concurrent._
  • When using collections, qualify names by importing scala.collection.immutable and/or scala.collection.mutable

    • e.g. "immutable.Map"

  • Put imports at the top of the file. The reader can refer to all imports in one place


Return Types

  • Scala allows return type annotations to be omitted.

  • Return type is especially important for public methods.
  • Return type is especially important when instantiating objects with mixins
    Use:

def make(): Service = new Service{}

instead of 

trait Service
def make() = new Service {
  def getId = 123
}

Use the mutable namespace explicitly. Use:

import scala.collection.mutable
val set = mutable.Set()
  • instead of importing scala.collection.mutable._ and referring to Set.

Require and Assert

  • Require and assert both serve as executable documentation. Both are useful for situations in which the type system cannot express the required invariants. assert is used for invariants that the code assumes (either internal or external), for example: 

  val stream = getClass.getResourceAsStream("someclassdata")
               assert(stream != null)

Whereas require is used to express API contracts:

def fib(n: Int) = {
require(n > 0)
  ...
  }

Exception Handling

Some exceptions are fatal and should never be caught; the block of code below is unsafe for this reason:

  try {
        operation()
      } catch {
          case _ => ...
      }    // almost always wrong, as it would catch fatal errors that need to be propagated.

This can be improved by using scala.util.control.NonFatal extractor to handle only non-fatal exceptions:

import scala.util.control.NonFatal
...
  try {
      operation()
     } catch {
          case NonFatal(exc) => ...
    }

However, try/catch blocks are low-level control constructs which are not always as expressive or idiomatic as other aspects of Scala. Therefore, better still would be to use scala.util.Try in order to automatically only catch non-fatal errors and to have monadic access patterns for error handling (see https://www.scala-lang.org/api/current/scala/util/Try.html for more details):

import scala.util.{Try, Success, Failure}
...
  val result: Try[ResultType] = Try( operation() )
  result match {
    case Success(v) => ... //do something with the return value
    case Failure(ex) => ... //non-fatal error handling here
  }

Braces

Use braces for if, while for, etc. even when there's just a single line:

if (cond) {
  result
} else {
  otherResult
}

for (x <- y if cond) yield {
  operation(x)
}

while (notDone()) {
  doTheThing()
}

Collections and Arrays


  • Use the default constructor for the collection type
 val seq = Seq(1, 2, 3)
 val set = Set(1, 2, 3)
 val map = Map(1 -> "one", 2 -> "two", 3 -> "three")

It is often appropriate to use lower level collections in situations that require better performance or space efficiency.


  • Use arrays  instead of lists for large sequences (the immutable Vector collections provides a referentially transparent interface to arrays); and use buffers instead of direct sequence construction when performance matters.

for (item <- container) {
    if (item != 2) return
   }

   It is often preferable to call foreach, flatMap, map, and filter directly — but do use fors when they clarify.

Querying and Transforming Data

  • Use map, flatMap, filter and fold
  •      List(1, 2, 3).map(_ * 2)

         .filter(_ > 2)

         .foldLeft(0)(_ + _)   //> res1: Int = 10

Implicits:

Use implicits in the following situations:

  1. Extending or adding a Scala-style collection
  2. Adapting or extending an object (“pimp my library” pattern)
  3. Use to enhance type safety by providing constraint evidence
  4. To provide type evidence (typeclassing)
  5. For Manifests

Do not use implicits to do automatic conversions between similar datatypes (for example, converting a list to a stream); these are better done explicitly because the types have different semantics, and the reader should beware of these implications.  Phrasing your problem in recursive terms often simplifies it, and if the tail call optimization applies (which can be checked by the @tailrec annotation), the compiler will even translate your code into a regular loop.

Aliases

  • Don’t use subclassing when an alias will do.
trait SocketFactory extends (SocketAddress => Socket

A SocketFactory is a function that produces a Socket.

Using a type alias

type SocketFactory = SocketAddress => Socket

is better. We may now provide function literals for values of type SocketFactory and also use function composition:

val addrToInet: SocketAddress => Long
val inetToSocket: Long => Socket
val factory: SocketFactory = addrToInet andThen inetToSocket

Type Aliases

Use type aliases when they provide convenient naming or clarify purpose, but do not alias types that are self-explanatory.

() => Int

   is clearer than

type IntMaker = () => Int

IntMaker

   since it is both short and uses a common type. However,

class ConcurrentPool[K, V] {
   type Queue = ConcurrentLinkedQueue[V]
   type Map   = ConcurrentHashMap[K, Queue]
 ...
}

 is helpful since it communicates purpose and enhances brevity.


Dont know if this is good or bad - need input here.
  • Fluent” method chaining :  You will often see Scala code that looks like this:

people.sortBy(_.name)

.zipWithIndex

.map { case (person, i) => "%d: %s".format(i + 1, person.name) }

.foreach { println(_) }