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ThrushCond is not a Monad

Clojure has a useful macro called cond-> — let's explore a Scala equivalent

BY TREVOR HARTMAN

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Clojure has a useful macro called cond-> that conditionally threads an initial value through a series of predicate/function pairs only applying each function if its predicate returns true. In this post we're going to look at a Scala representation, and whether it fits the shape and laws of any common algebraic structures. We'll look at Functor, Monad, Semigroup, and Monoid.

TL;DR — view the full code listing.

Let's start with an example in Clojure. We want to build up a request based on some arbitrary conditions:

;; sample values from user input

(def user-id 1)
(def user-name "devth")
(def user-address nil)
(def accept :json)

;; validation and helper functions

(def accept-map )
(defn valid-accept? [a] (accept-map a))
(defn set-header [req k v] (update-in req [:headers] assoc k v))
(defn set-param [req k v] (update-in req [:params] assoc k v))

;; build up a request map using cond-> to decide which items to add to params
;; and headers maps

(def request
  (cond->
    user-name (set-param :user-name user-name)
    user-address (set-param :user-address user-address)
    (valid-accept? accept) (set-header :accept accept)))

;; request value:

{:target "/users"
 :query-params
 :headers

Since Clojure's -> operator is sometimes referred to as the "thrush" operator, I'm going to call cond-> in Scala ThrushCond.

First let's model the Request and helpers equivalent to those we used in the Clojure example:

case class Request(
  target: String,
  params: Map[String, String] = Map.empty,
  headers: Map[String, String] = Map.empty) {

  // validation and helper functions
  val acceptMap = Map("html" -> "text/html", "json" -> "application/json")
  val isValidAccept: (String => Boolean) = acceptMap.isDefinedAt _

  def addParam(k: String, v: String) = this.copy(params=params.updated(k, v))
  def addHeader(k: String, v: String) = this.copy(headers=headers.updated(k, v))
}

// sample values from user input
val userId: Int = 1
val userName: Option[String] = Some("devth")
val address: Option[String] = None
val accept = "json"

Now we'll create the ThrushCond class that takes any number of predicate/function pairs, provides a guard function to only run a function if the predicate passes, a method to flatten the chain of functions via composition, and finally a run method that takes a value and runs it through the chain.

type Step[A] = (A => Boolean, A => A)

case class ThrushCond[A](steps: Step[A]*) {
  /** Perform a pipeline step only if the value meets a predicate */
  def guard[A](pred: (A => Boolean), fn: (A => A)): (A => A) =
    (a: A) => if (pred(a)) fn(a) else a
  /** Compose the steps into a single function */
  def comp = Function.chain(steps.map { step => guard(step._1, step._2) })
  /** Run a value through the pipeline */
  def run(a: A) = comp(a)
}

Try it out:

val requestPipeline = ThrushCond[Request](
  ({_ => userName.isDefined}, {_.addParam("userName", userName.get)}),
  ({_ => address.isDefined}, {_.addParam("address", address.get)}),
  ({_.isValidAccept(accept)}, {r => r.addHeader("accept", r.acceptMap(accept))}))

val request = requestPipeline run Request("/users")

//=>
Request(/users,Map(userName -> devth),Map(accept -> application/json))

As you can see, it correctly skipped the 2nd step based on the address.isDefined condition and runs the other steps because their predicates evaluate to true.

Will this work as one of the algebraic structures mentioned at the start?

Functor

Consider Functor's fmap:

def fmap[A, B](f: A => B): F[A] => F[B]

In our case, both A are the same type, Request produces a function that fits, but we could easily use that with an existing Functor, e.g.:

val step: Request => Request =
  guard({_ => userName.isDefined}, {setParam(_, "userName", userName.get)})
Some(Request("/users")).map(step)

The essense of ThrushCond itself so it makes no sense to design a new Functor around it.

Monad

Likewise, Monad's flatMap:

def flatMap[A, B](f: A => F[B]): F[A] => F[B]

We could make guard's signature, but there's no point in doing so for the same reason it didn't make sense for Functor: the essense is not how a transformation is applied, it's whether the transformation is applied, and because of the signature, the decision whether to perform a transformation must be embedded in the transformation itself, hence guard.

Semigroup

Let's see if it meets Semigroup's associativity laws:

case class F(x: Int)
val f = F(10)
val always = Function.const(true) _

val mult2: F => F = guard(always, {f => f.copy(x = f.x * 2)})
val sub4: F => F = guard(always, {f => f.copy(x = f.x - 4)})
val sub6: F => F = guard(always, {f => f.copy(x = f.x - 6)})

val g: (F => F) = (mult2 andThen sub6) andThen sub4
val h: (F => F) = mult2 andThen (sub6 andThen sub4)

g(f)
//=> F(10)
h(f)
//=> F(10)

guard is associative when composed with itself because function composition is associative. Because of this associative binary operation we can provide evidence that ThrushCond's Semigroup representation:

import scalaz._, Scalaz._

case object ThrushCond {
  /** Evidence of a Semigroup */
  implicit def thrushCondSemigroup[A]: Semigroup[ThrushCond[A]] =
    new Semigroup[ThrushCond[A]] {
      def append(t1: ThrushCond[A], t2: => ThrushCond[A]): ThrushCond[A] =
        ThrushCond[A]((Function.const(true), t2.comp compose t1.comp))
    }
}

We've defined a Semigroup over the set of all ThrushCond[A]s. What does this give us? We can now combine any number of ThrushConds using Semigroup's |+| operator. A simple example using ThrushCond[Int]:

import ThrushCond.thrushCondSemigroup

val addPipeline = ThrushCond[Int](
  ((_ > 10), (_ + 2)),
  ((_ < 20), (_ + 20)))

val multPipeline = ThrushCond[Int](
  ((_ == 70), (_ * 10)),
  ((_ > 0), (_ * 7)))

val pipeline = addPipeline |+| multPipeline

// Examples
multPipeline run 70 //=> 70 * 10 * 7 == 4900
pipeline run 2 //=> (2 + 20) * 7 == 154
pipeline run 12 //=> (12 + 2 + 20) * 7 == 238

Monoid via PlusEmpty

Monoids are Semigroups with an identity element. ThrushCond's identity is simply a ThrushCond arguments. However, as @lmm mentioned in the comments:

it's not ThrushCond itself that forms a Monoid but rather ThrushCond[A] for any given A

This is where PlusEmpty comes in. PlusEmpty is a "universally quantified Monoid" which means it's like a Monoid but for first-order * -> * types instead of proper * types. PlusEmpty itself is a higher-order (* -> *) -> * type. A helpful quote from #scalaz:

tpolecat: so String is a monoid, but List (which means that List[A])

To provide evidence of a PlusEmpty, we must be able to implement these two methods (where F):

def plus[A](a: F[A], b: => F[A]): F[A] // from Plus
def empty[A]: F[A] // from PlusEmpty which extends Plus

We already implemented plus for Semigroup's append, and empty is simply a ThrushCond without args.

case object ThrushCond {
  /** Evidence of a PlusEmpty */
  implicit def thrushCondPlusEmpty: PlusEmpty[ThrushCond] =
    new PlusEmpty[ThrushCond] {
      def plus[A](a: ThrushCond[A], b: => ThrushCond[A]): ThrushCond[A] =
        ThrushCond[A((Function.const(true), b.comp compose a.comp)))

      def empty[A]: ThrushCond[A] = ThrushCond[A]()
    }
  /** Use PlusEmpty to provide evidence of a Monoid[Request] */
  implicit def requestMonoid: Monoid[ThrushCond[Request]] =
    thrushCondPlusEmpty.monoid[Request]
  /** Evidence of a Semigroup */
  implicit def thrushCondSemigroup[A]: Semigroup[ThrushCond[A]] =
    new Semigroup[ThrushCond[A]] {
      def append(t1: ThrushCond[A], t2: => ThrushCond[A]): ThrushCond[A] =
        ThrushCond[A]((Function.const(true), t2.comp compose t1.comp))
    }
}

Let's go back to our Request example in Clojure and use PlusEmpty's <+> to combine separate transformation pipelines:

import ThrushCond._ // evidence

val userPipeline = ThrushCond[Request](
  ({_ => userName.isDefined}, {_.addParam("userName", userName.get)}),
  ({_ => address.isDefined}, {_.addParam("address", address.get)}))

val headerPipeline = ThrushCond[Request](
  ({_.isValidAccept(accept)}, {req =>
    req.addHeader("accept", req.acceptMap(accept))}))

// <+> is an alias for plus
val requestPipeline = userPipeline <+> headerPipeline
// A PlusEmpty[ThrushCond] is implicitly obtained and used to plus the two
// ThrushCond[Request]s

requestPipeline run Request("/users")
//=>
Request(/users,Map(userName -> devth),Map(accept -> application/json))

Because PlusEmpty can derive a Monoid for a given type, we can combine any number of ThrushConds from a List. Let's construct one more ThrushCond pipeline that conditionally adds a cache-control header and try out our Monoid using Foldable's suml:

import scala.language.postfixOps

val shouldCache = false

val cachePipeline = ThrushCond[Request](
  ({_ => !shouldCache}, {_.addHeader("cache-control", "no-cache")}))

val requestPipeline = List(userPipeline, headerPipeline, cachePipeline) suml
requestPipeline run Request("/users")
//=>
Request(/users,
  Map(userName -> devth),
  Map(accept -> application/json, cache-control -> no-cache))

ThrushCond is not a Monad, nor a Functor, but it is a PlusEmpty from which can be derived a Monoid.

View the full code listing.

Updated July 1, 2015: incorporated lmm's PlusEmpty suggestion.

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