Safe / Unsafe pattern in scala - scala

Question

Hi I have class which does some json extraction and want to do a safe/unsafe version.
Currently I have a class definition like this
class Safe {
def getA: Option[String] = ...
def getB: Option[Int] = ...
... etc ...
}
And then a Unsafe version of that which just delegates to the Safe class:
class Unsafe(delegate: Safe) {
def getA: String = delegate.getA.get
def getB: Int = delegate.getB.get
... etc ...
}
this works but obviously the main problem is that the delegation is maintained by hand, and that if we ever change anything about the Safe interface, someone has to manually also make sure that is reflected in the Unsafe class as well.
Is there a more idomatic and less manual pattern in scala to do this?

Answer 1

Here is an implementation of my proposal.
Define Extractor interface parameterized by a type constructor:
trait Extractor[F[_]] { outer =>
def getA: F[String]
def getB: F[Int]
/* insert `transform` here */
}
Implement a transform method once and for all, which takes an arbitrary F ~> G:
def transform[G[_]](natTrafo: F ~> G): Extractor[G] =
new Extractor[G] {
def getA: G[String] = natTrafo[String](outer.getA)
def getB: G[Int] = natTrafo[Int](outer.getB)
}
Here, the F ~> G is a type of polymorphic functions that can transform any F[A] into G[A] for arbitrary type A (String, Int, or thousand other types you want to get in your extractor):
trait ~>[F[_], G[_]] {
def apply[A](fa: F[A]): G[A]
}
This interface is quite ubiquitous, it's available in Scalaz and Cats (it's called FunctionK there), sometimes called "natural transformation".
Implement SafeExtractor:
class SafeExtractor extends Extractor[Option] {
def getA: Option[String] = None /* do sth. more clever here? */
def getB: Option[Int] = None
}
Get UnsafeExtractor for free by providing a simple Option ~> Id implementation to transform:
type Id[X] = X
val safe: Extractor[Option] = new SafeExtractor()
val unsafe: Extractor[Id] = safe.transform(
new ~>[Option, Id] {
def apply[A](x: Option[A]): Id[A] = x.get
}
)
You can now also easily reuse the same transform function to convert Extractor[Future] to Extractor[Id] by Awaiting results, or Extractor[Id] to Extractor[Try] by catching all errors etc.
Full code
import scala.language.higherKinds
trait Extractor[F[_]] { outer =>
def getA: F[String]
def getB: F[Int]
def transform[G[_]](natTrafo: F ~> G): Extractor[G] =
new Extractor[G] {
def getA: G[String] = natTrafo[String](outer.getA)
def getB: G[Int] = natTrafo[Int](outer.getB)
}
}
/** A polymorphic function that can transform any
* `F[A]` into a `G[A]` for all possible `A`.
*/
trait ~>[F[_], G[_]] {
def apply[A](fa: F[A]): G[A]
}
class SafeExtractor extends Extractor[Option] {
def getA: Option[String] = None
def getB: Option[Int] = None
}
type Id[X] = X
val safe: Extractor[Option] = new SafeExtractor()
val unsafe: Extractor[Id] = safe.transform(
new ~>[Option, Id] {
def apply[A](x: Option[A]): Id[A] = x.get
}
)

Answer 2

The answer by Andrey Tyukin is a good way to address this specific problem, but there is perhaps a bigger design issue.
Your code assumes that the structure of the JSON (as defined in Safe) matches the structure of the data in your code (as defined by Unsafe). This causes problems when you want to change the structure of the data in your code, or when the JSON format changes, or when you want to import data from a different source (e.g. XML), or when you want to do more complex validation of the data.
So the correct way to handle this is to design the application data structures (your Unsafe class) in the way that fits your application. You then provide a JSON-reading library that converts incoming data to that format. This library uses your Safe class internally. This can perform any validation/data conditioning that may be required, and can adjust to changes in the JSON format without affecting the rest of the system. Your unit testing framework will make sure that your two classes stay in sync.
This design pattern is an example of separation of concerns
Here is some sample code:
In the main application:
// Data structure for use by application
case class Unsafe(a: String, b: Int)
// Abstract interface for loading data
trait Loader {
def load(): Unsafe
}
In the data loading library:
// JSON implementation of loading interface
object JsonLoader extends Loader {
protected case class Safe(
a: Option[String],
b: Option[Int]
)
def load(): Unsafe = {
val json = rawLibrary.readData() // Load data in JSON format
val safe: Safe = jsonLibrary.extract[Safe](json)
// Validate/condition the raw data here
val a = safe.a.getOrElse("")
val b = safe.b.getOrElse(0)
// Return the application data
Unsafe(a, b)
}
}
The mapping from JSON to application data is hidden inside the JsonLoader object. This makes it easier to make sure that they are in sync allows the JSON format to change without affecting the wider code.