Accumulating More Than One Failure In A ValidationNEL

This is an adaptation of an internal blog post I made for Gravity engineers. To preface, Gravity likes to use 2 very predictable patterns throughout its Scala codebase, which is very important for a TIMTOWTDI language like Scala.

  1. The for-comprehension: it expresses so much of Gravity’s business logic, so it is valuable to see its familiar syntax over and over.
  2. ValidationNEL: it captures success and failure states better than traditional imperative means.

But what does it mean for the for-compehensions to interact with ValidationNEL?

(Note at the time this was written, the post targeted ValidationNEL in Scalaz 6. Since then, Scalaz 7 has been released. There may be differences in the examples.)

Beyond ValidationNEL distinguishing success and failure cases, its other sell is accumulation of failures. I think it’s superior to throwing a single exception. From one Validation tutorial:

Methods using exceptions automatically combine, but unfortunately not in the way you would like: any failure will immediately be reported, and it will be the only failure reported. It is of course possible to combine exceptions in other ways, but that means riddling your program with try-catch blocks around every sub step, which clutters the code beyond recognition.

However in Gravity’s typical usage of ValidationNELs, they don’t accumulate failures; they tend to produce exactly one failure, if any. This post will explain why, what use-case it fulfills, and the magic to actually accumulate failures, if that’s what you want.

Of its 2 use-cases for ValidationNELs,

  1. Fail-fast: pass the success of each step of a computation into the next, until a step fails
  2. Fail-slow: several things can go wrong, and all can be reported up front (e.g. missing fields in a shopping checkout form)

Gravity tends toward #1. This is the easiest way to use ValidationNEL, since you can use familiar syntax: the for-comprehension. However this tends to only ever produce one failure.

Let’s get one thing out of the way: if this is the case, why use a ValidationNEL over a Validation at all? ValidationNEL is preferable throughout the codebase regardless of how many potential failures can occur because it plays nicer with type inference. If you accidentally mix e.g. Validation[String, Int] with ValidationNEL[String, Int] you’ll get a Validation[Object, Int]. D’oh. It’s also future-proof if you later decide to yield additional failures. On the flip side, you must accept the wart of running NonEmptyList.list.contains to handle specific errors; perhaps write a custom extractor.

So why are we practically restricted to one failure? A for-comprehenion is often sugar for calls to flatMap1. This could also be called fail-fast. Let’s review flatMap behavior.

def evenNumber(n: Int) = if (n % 2 == 0) Some(n) else None

// an example for-comprehension …
for {
  num <- List(1, 2, 3)
  evenNum <- evenNumber(num)
} yield evenNum

// … which desugars to …
List(1, 2, 3) flatMap (evenNumber)

For empty collections, flatMap is a no-op.

// evenNumber won't get called at all (what args could it possibly be called with?)
for {
  num <- List.empty[Int] // comprehension doesn't get past this
  evenNum <- evenNumber(num)
  doubleEven <- evenNumber(evenNum * 2)
} yield doubleEven

So when flatMapping over a series of Validations, as soon as one of them is a Failure, you won’t reach the others.

val sumV: ValidationNEL[String, Int] = for {
  a <- 42.successNel[String]
  b <- "Boo".failNel[Int]
  c <- "Wah wah".failNel[Int] // by defn of flatMap, can't get here
} yield a + b + c
// sumV == Failure(NonEmptyList(Boo))

So how do you accumulate failures, fail-slow?

Fail-Slow: The Short Answer

The short answer is in the general Applicative Builder operator |@|.

The Applicative Builder operator |@| takes Validations (and other Applicative Functors) and a handler that accepts the combined result as a tuple. In the case of Validations, the hander is called if all inputs are Successes. If any of the inputs is a Failure, the handler is not called, while |@| accumulates the Failures for you.

For example, if you build 3 ValidationNELs together with Success types Int, String, and Double respectively and Failure type String, you must then provide a handler (Int, String, Double) => T. The handler will be invoked iff all 3 Validations are Successes. The return type of this whole operation will be ValidationNEL[String, T].

(I suppose T could even be a nested ValidationNEL[E, A], so you’d get back ValidationNEL[String, ValidationNEL[E, A]].)

Let’s see |@| in action. Note the NonEmptyList of length 2 at the end.

val yes = 3.14.successNel[String]
val doh = "Error".failNel[Double]

def addTwo(x: Double, y: Double) = x + y

(yes |@| yes)(addTwo) // Success(6.28)
(doh |@| doh)(addTwo) // Failure(NonEmptyList(Error, Error))

// or shorthand
(yes |@| yes){_ + _} // Success(6.28)
(yes |@| doh){_ + _} // Failure(NonEmptyList(Error))
(doh |@| yes){_ + _} // Failure(NonEmptyList(Error))
(doh |@| doh){_ + _} // Failure(NonEmptyList(Error, Error))

|@| is the most general way to deal with ValidationNELs. There are also more specific operators for shorthand accumulation, if you can make certain restrictions on the Success and Failure types.

If you wanted to sum their Success values, like in the above example, you could use this fun method, >>*<<. It appends Successes to each other or Failures to each other, favoring Success rather than failing fast. Note, for appending to be possible, the Success type and Failure type must both be Semigroups, such as numbers, strings, and NonEmptyLists, among others.

yes >>*<< yes // Success(6.28)
yes >>*<< doh // Success(3.14)
doh >>*<< yes // Success(3.14)
doh >>*<< doh // Failure(NonEmptyList(Error, Error))

Scalaz 7 introduces findSuccess, which short-circuits, returning first success, otherwise appending failures. Unlike >>*<<, only the Failure type must be a Semigroup.

yes findSuccess yes // Success(3.14)
yes findSuccess doh // Success(3.14)
doh findSuccess yes // Success(3.14)
doh findSuccess doh // Failure(NonEmptyList(Error, Error))

Finally, for favoring Failure, Scalaz 7 introduces +++. Both Success and Failure must be Semigroups again.

yes +++ yes // Success(6.28)
yes +++ doh // Failure(NonEmptyList(Error))
doh +++ yes // Failure(NonEmptyList(Error))
doh +++ doh // Failure(NonEmptyList(Error, Error))

The alternative to learning these typeclasses and their operators is constructing a mutable buffer and side-effectfully accumulating failures yourself.

var sum = 0.0
val fails = collection.mutable.ArrayBuffer[String]()
yes fold (fails ++= _.list, sum += _)
doh fold (fails ++= _.list, sum += _)
if (fails.isEmpty) {
} else {
  NonEmptyList(fails.head, fails.tail: _*).fail
// Failure(NonEmptyList(Error))

Awkward, no? You’d have to copy & paste that block for every different accumulation strategy. And tweak each slightly.2

So, I’ve shown you how to accumulate a handful of Validations. If you’re interested in accumulating errors for N Validations, still fail-slow, check out more examples in A Tale of 3 Nightclubs. Take a look for calls to sequence which essentially inverts a sequence of Validations into a Validation of a sequence: Seq[ValidationNEL[E, A] => ValidationNEL[E, Seq[A]]. It’s beyond my current ability to explain the type lambda on sequence though, so good luck.

You can stop here with your newfound Validation knowledge if you like. Otherwise, onto the more theoretical digression.

Validation As Monad? Validation As Applicative Functor?

Back to |@|. Why another operator? Why this promise of Validations playing nicely with for-comprehensions—syntax we already know—and yet we can’t get failure accumulation? Because of Scalaz’s definition of Validation as a monad. Though very convenient for much of Gravity’s business logic, Validation defining flatMap is an accident. Validation is primarily an applicative functor.

It’s beyond this post’s scope to fully explain the utility of monad and applicative functor typeclasses, so I’ll just say that monads and Scala for-comprehensions go hand in hand. When I said Gravity expresses so much of its business logic in for-comprehensions, that means our business logic is monadic. If you’ve written a for-comprehension, or directly called flatMap, you’ve used a monad.

But Validation, being an applicative functor, has more power than map and flatMap, that a for-comprehension can’t harness. Borrowing from this intro to monadic design, “… unlike a monad, an applicative functor can carry forward results of previous computations.” Sounds like the accumulation we need.

Unfortunately there’s no native Scala syntax for applicatives. You have to use the funny Scalaz |@| operator and its kin.

I didn’t realize that Validation isn’t supposed to be a monad until Validation.flatMap was removed in a Scalaz 7 milestone. The community has since brought it back for backwards-compatibility, so Validation will continue to be targetable by for-comprehensions. But now you know: it can viewed as a monad and an applicative functor, and they behave differently (if you like to think in terms of these typeclasses, you know Validation is similar to Either. Think of Scalaz’s flatMap-carrying Validation as a right-biased Either monad, as its flatMap would only deal with its right-side/success). For more Validation potential though, use it as an applicative functor with |@| and company.



  1. For-comprehensions compile to flatMap, map, filter, and/or foreach calls. That’s it.

  2. Reminds me of clinging to old, verbose, C-style for (int i = 0; i < length; i++) { ... } blocks. Nowadays, you use map, filter, and friends. Declarative over imperative. Separate what you want from how you get it.