新类型
类型安全的包装器
新类型 是 CoddyKit 上的免费 Scala for Backend Engineering & Functional Programming 课时。 这是第 3 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Scala for Backend Engineering & Functional Programming 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Scala for Backend Engineering & Functional Programming 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Type-Safe Wrappers
A newtype is a distinct type that wraps a single underlying value. It prevents mixing up values that share a primitive representation, like a UserId and a ProductId that are both Ints.
case class UserId(value: Int)
case class ProductId(value: Int)
object Main:
def main(args: Array[String]): Unit =
val u = UserId(1)
val p = ProductId(1)
println(u.value == p.value) // values equal, types differThe Primitive Obsession Problem
Primitive obsession is overusing String and Int for domain concepts. It allows nonsense like passing an email where a name belongs. Newtypes fix this by giving each concept its own type.
case class Email(value: String)
case class City(value: String)
object Main:
def greet(c: City): String = s"Welcome to ${c.value}"
def main(args: Array[String]): Unit =
println(greet(City("Berlin")))Case Class Newtypes
The simplest newtype is a single-field case class. It gives equality, a readable toString, and pattern matching out of the box. The cost is one object allocation per value.
case class OrderId(value: String)
object Main:
def main(args: Array[String]): Unit =
val id = OrderId("ORD-42")
println(id)
println(id.value)Opaque Type Newtypes
For zero allocation, implement a newtype with an opaque type. It behaves like the underlying type at runtime but is distinct at compile time.
object Ids:
opaque type UserId = Int
def apply(i: Int): UserId = i
extension (u: UserId) def value: Int = u
object Main:
def main(args: Array[String]): Unit =
val u = Ids(7)
println(u.value)Adding Behavior with Extensions
Give a newtype operations through extension methods, exposing only what makes sense for the domain concept.
object Money:
opaque type Cents = Long
def apply(n: Long): Cents = n
extension (c: Cents)
def +(o: Cents): Cents = c + o
def toDollars: Double = c / 100.0
object Main:
def main(args: Array[String]): Unit =
val total = Money(250) + Money(750)
println(total.toDollars)Newtypes in Function Signatures
Newtypes make signatures self-documenting and catch argument-order bugs at compile time. You cannot accidentally swap two parameters of different newtypes.
case class Width(value: Int)
case class Height(value: Int)
object Main:
def area(w: Width, h: Height): Int = w.value * h.value
def main(args: Array[String]): Unit =
println(area(Width(4), Height(5)))Newtypes and Collections
A Map keyed by a newtype is clearer and safer than one keyed by a raw Int. The type prevents using the wrong kind of key.
case class UserId(value: Int)
object Main:
def main(args: Array[String]): Unit =
val names = Map(UserId(1) -> "Ada", UserId(2) -> "Bob")
println(names(UserId(2)))Validated Newtypes
Combine a newtype with a smart constructor so the wrapper also enforces invariants. Here a NonEmptyString can never be empty.
case class NonEmptyString private (value: String)
object NonEmptyString:
def of(s: String): Option[NonEmptyString] =
if s.nonEmpty then Some(NonEmptyString(s)) else None
object Main:
def main(args: Array[String]): Unit =
println(NonEmptyString.of("hi"))
println(NonEmptyString.of(""))Choosing a Representation
Pick based on your needs.
- case class: easiest, pattern-matchable, allocates an object.
- opaque type: zero-cost, no boxing, ideal for hot paths and big collections.
object Temp:
opaque type Kelvin = Double
def apply(d: Double): Kelvin = d
extension (k: Kelvin) def value: Double = k
object Main:
def main(args: Array[String]): Unit =
val readings = List(Temp(300.0), Temp(310.5))
println(readings.map(_.value).sum)Preventing Accidental Conversions
Two newtypes over the same base do not implicitly convert. To go between them you write an explicit function, documenting the intent.
case class Meters(value: Double)
case class Feet(value: Double)
object Main:
def toFeet(m: Meters): Feet = Feet(m.value * 3.281)
def main(args: Array[String]): Unit =
println(toFeet(Meters(2.0)))When to Use Newtypes
Reach for newtypes whenever a primitive carries domain meaning.
- Identifiers, units, formatted strings.
- Use case class for simplicity, opaque type for performance.
- Add a smart constructor when there are invariants.
object Domain:
opaque type Sku = String
def of(s: String): Option[Sku] =
if s.startsWith("SKU-") then Some(s) else None
extension (k: Sku) def raw: String = k
object Main:
def main(args: Array[String]): Unit =
println(Domain.of("SKU-9").map(_.raw))Quick Check
Test your understanding of newtypes.
Recap
You learned newtypes.
- Newtypes wrap one underlying value in a distinct type.
- They cure primitive obsession and prevent argument mixups.
- Use
case classfor simplicity,opaque typefor zero cost. - Add a smart constructor for validated wrappers.
- Conversions between newtypes are always explicit.
object Ids:
opaque type AccountId = Long
def apply(n: Long): AccountId = n
extension (a: AccountId) def value: Long = a
object Main:
def main(args: Array[String]): Unit =
val acc = Ids(1001L)
println(acc.value)常见问题解答
「新类型」课时是免费的吗？
是的 — 「新类型」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Scala for Backend Engineering & Functional Programming 课程的其余内容，请升级到 CoddyKit PRO。 Scala for Backend Engineering & Functional Programming 课程共包含 4 节课。
「新类型」这节课中我会学到什么？
类型安全的包装器 你通过在浏览器中直接运行的动手代码来练习 Scala for Backend Engineering & Functional Programming，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 Scala for Backend Engineering & Functional Programming 需要有经验吗？
无需任何先前经验。CoddyKit 上的 Scala for Backend Engineering & Functional Programming 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 3 节课，共 4 节。
「新类型」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 Scala for Backend Engineering & Functional Programming 课中编写并运行代码吗？
能。每节 Scala for Backend Engineering & Functional Programming 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。