Arrow

abstract def compose[A, B, C](f: F[B, C], g: F[A, B]): F[A, C]

Here's how you can use >>> and <<< Example:

scala> import cats.implicits._
scala> val f : Int => Int = (_ + 1)
scala> val g : Int => Int = (_ * 100)
scala> (f >>> g)(3)
res0: Int = 400
scala> (f <<< g)(3)
res1: Int = 301

abstract def first[A, B, C](fa: F[A, B]): F[(A, C), (B, C)]

Create a new F that takes two inputs, but only modifies the first input

scala> import cats.implicits._
scala> import cats.arrow.Strong
scala> val f: Int => Int = _ * 2
scala> val fab = Strong[Function1].first[Int,Int,Int](f)
scala> fab((2,3))
res0: (Int, Int) = (4,3)

abstract def id[A]: F[A, A]

abstract def lift[A, B](f: (A) ⇒ B): F[A, B]

Lift a function into the context of an Arrow.

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def algebra[A]: Monoid[F[A, A]]

def algebraK: MonoidK[[α]F[α, α]]

def andThen[A, B, C](f: F[A, B], g: F[B, C]): F[A, C]

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def dimap[A, B, C, D](fab: F[A, B])(f: (C) ⇒ A)(g: (B) ⇒ D): F[C, D]

Contramap on the first type parameter and map on the second type parameter

scala> import cats.implicits._
scala> import cats.arrow.Profunctor
scala> val fab: Double => Double = x => x + 0.3
scala> val f: Int => Double = x => x.toDouble / 2
scala> val g: Double => Double = x => x * 3
scala> val h = Profunctor[Function1].dimap(fab)(f)(g)
scala> h(3)
res0: Double = 5.4

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def lmap[A, B, C](fab: F[A, B])(f: (C) ⇒ A): F[C, B]

contramap on the first type parameter

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def rmap[A, B, C](fab: F[A, B])(f: (B) ⇒ C): F[A, C]

map on the second type parameter

def second[A, B, C](fa: F[A, B]): F[(C, A), (C, B)]

Create a new F that takes two inputs, but only modifies the second input

scala> import cats.implicits._
scala> import cats.arrow.Strong
scala> val f: Int => Int = _ * 2
scala> val fab = Strong[Function1].second[Int,Int,Int](f)
scala> fab((2,3))
res0: (Int, Int) = (2,6)

def split[A, B, C, D](f: F[A, B], g: F[C, D]): F[(A, C), (B, D)]

Create a new computation F that splits its input between f and g and combines the output of each.

scala> import cats.implicits._
scala> import cats.arrow.Arrow
scala> val toLong: Int => Long = _.toLong
scala> val toDouble: Float => Double = _.toDouble
scala> val f: ((Int, Float)) => (Long, Double) = Arrow[Function1].split(toLong, toDouble)
scala> f((3, 4.0f))
res0: (Long, Double) = (3,4.0)

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit