In this tutorial we implement in Scala some basic ideas from category theory. The goal is to produce a library that can be used in production for bridging an "unsafe" public api and a "safe" private api. In particular, we look at how to validate input and safely compose it with functions that don't know (or care) about validation.

When we're done, we'll be able to write code like this:

```
> val fortyTwo = add2 <%> atoi("20") <*> atoi("22")
scala: scala.util.Either[List[String],Int] = Right(42) fortyTwo
```

From category theory, we implement representations of the following:

We also make use of some interesting Scala features:

- Algebraic data types
- Type lambdas
- Higher-kinded types
- Implicit conversions
- Type classes

For further reading, see:

- Validation (learning Scalaz)

Imagine building a Web service that takes input from a client, performs some computation on the server, and returns output to the client.

```
Client || Server Service
------ || ------ -------
| || | |
.-. || | |
| |-----||----->.-. |
| | || | |---------->.-.
| | || | | | |
| | || | |<----------|_|
| |<----||------|_| |
|_| || | |
| || | |
============||===========================
Dragons || Rainbows
```

When processing raw input from a client, we don't have the luxury of validated, well-typed data -- the input might be malformed, incomplete, malicious, or missing entirely.

To bridge the gap between the unsafe Web and our warm and fuzzy functional code, we can build and use a small library out a few principles from category theory.

In the examples below, we focus specifically on Scala's
`Either`

data type, which takes one of two values:

```
sealed abstract class Either[+A, +B]
case class Left[+A, +B](a: A) extends Either[A, B]
case class Right[+A, +B](b: B) extends Either[A, B]
```

There's nothing inherently special about `Left`

or
`Right`

-- they're just boxes for holding values.

By convention, `Left`

captures "erroneous" or "invalid"
values, and `Right`

contains "error-free" or "valid" values,
where "erroneousness" and "validity" are defined by context.

For example, consider the function `atoi`

, which attempts
to parse a string representation of an integer:

```
def atoi(x: String): Either[String,Int] =
try {
Right(x.toInt)
} catch {
case _ : Throwable => Left("'" + x + "' is not an integer")
}
```

If `x.toInt`

succeeds, `atoi`

returns a
`Right`

containing the parsed integer value. If not, it
returns a `Left`

containing an error message:

```
> val one = atoi("1")
scala: Either[String,Int] = Right(1)
one
> val two = atoi("two")
scala: Either[String,Int] = Left('two' is not an integer) two
```

Consider a simple absolute value function:

`val abs: Int => Int = math.abs`

The type of this function is `Int => Int`

. When we
supply it an integer, we get back an integer.

```
> val twenty = abs(-20)
scala: Int = 20 twenty
```

Now imagine that we want to turn this function into a Web service. We
can't be sure that the input provided by the client will indeed be an
integer, so this is a good time to use `Either`

. We'll pass
our client's input through `atoi`

to get an
`Either[String,Int]`

.

Now we want a nice way to apply our `abs`

function if and
only if `atoi`

returns valid data, and return an error
message if not. We need a functor.

Given some `F[A]`

, a functor lifts a function of type
`A => B`

to a function of type
`F[A] => F[B]`

.

```
trait Functor[A,F[_]] {
def map[B](f: A => B): F[B]
}
```

Picture the category of "regular" types next to the category of
"lifted" types. The `map`

function lets us apply a morphism
from the "regular category" to an object in the "lifted" category.

```
.--------------. .-----------------------.
| Category _ | | Category F[_] |
|--------------| |-----------------------|
| a: A | | aF: F[A] |
| b: B | | bF: F[B] |
| f: A => B ~~~~~ map ~~~~> fF: F[A] => F[B] |
'--------------' '-----------------------'
```

We need to lift `Int => Int`

to
`F[Int] => F[Int]`

, where `F[_]`

is defined as
`Either[String,_]`

using a type lambda. This produces a
function of type
`Either[String,Int] => Either[String,Int]`

.

While we're at it, let's put it in an implicit function to implement a type class:

```
implicit def eitherFunctor[A,Z](x: Either[Z,A]) =
new Functor[A,({type EitherZ[B] = Either[Z,B]})#EitherZ] {
override def map[B](f: A => B): Either[Z,B] =
match {
x case Left(l) => Left(l)
case Right(r) => Right(f(r))
}
}
```

Now we can pimp `map`

onto any `Either`

instance:

```
> val negativeTwenty: Either[String,Int] = Right(-20)
scala: Either[String,Int] = Right(-20)
negativeTwenty
> val twenty = negativeTwenty map abs
scala: scala.util.Either[String,Int] = Right(20) twenty
```

Finally, we can plug it into our `atoi`

function:

```
> val twenty = atoi("-20") map abs
scala: scala.util.Either[String,Int] = Right(20)
twenty
> val notTwenty = atoi("negative twenty") map abs
scala: scala.util.Either[String,Int] = Left('negative twenty' is not an integer) notTwenty
```

Sometimes it's handy to do all this in reverse by first lifting a function and then applying it to a lifted value:

```
implicit class FnCofunctor[A,B](g: A => B) {
def <%>[Z](x: Either[Z,A]) = x map g
}
```

Now we can use `<%>`

as an infix operator to
implicity lift `abs`

and apply it to a value returned by
`atoi`

:

```
> val twenty = abs <%> atoi("-20")
scala: scala.util.Either[String,Int] = Right(20) twenty
```

We will come back to the `<%>`

operator in the next
section.

So far we've built enough code to cleanly parse some input and, if it is valid, apply it to a function.

Now consider a higher arity function:

`val add2: Int => Int => Int = { x => y => x + y }`

This function has two inputs. To turn it into a Web service as before, we'll need to parse two separate values and apply them both. We need an applicative functor.

An applicative functor builds upon a functor with a way to apply an
already-lifted function of type `F[A => B]`

as a function
of type `F[A] => F[B]`

.

```
trait Applicative[A,F[_]] extends Functor[A,F] {
def ap[B](f: F[A => B]): F[B]
}
```

Picture the categories from before with an additional transformation,
`ap`

, that converts a morphism within the "lifted"
category:

```
.--------------. .-----------------------.
| Category _ | | Category F[_] |
|--------------| |-----------------------|
| a: A | | aF: F[A] |
| b: B | | bF: F[B] |
| f: A => B ~~~~~ map ~~~~> fF: F[A] => F[B] <~~~ ap ~.
| | | | |
| | | gF: F[A => B] ~~~~~~~~~~~~'
'--------------' '-----------------------'
```

This gives us a way to apply an `Either[Z,A]`

to an
`Either[Z,A => B]`

to get an `Either[Z,B]`

,
where `F[_]`

is `Either[Z,_]`

.

Note that `B`

might itself be a function
`C => D`

, giving us another `ap`

-able
`Either[Z,C => D]`

. In our case, `A => B`

is
`Int => Int => Int`

.

Note also that, since we have multiple inputs to parse, we will potentially be capturing multiple error messages (one per input). We need to change our parser slightly:

```
def atoi(x: String): Either[List[String], Int] =
try {
Right(x.toInt)
} catch {
case _ : Throwable => Left(List("'" + x + "' is not an integer"))
}
```

Our parser now gives us either the parsed integer, or a list of error messages.

To build up lists of errors without coupling ourselves to the
`List`

API, we introduce `Semigroup`

to generalize
the characteristic of "appendability":

```
trait Semigroup[A] {
def append(x: A): A
}
```

```
implicit def listSemigroup[A](x: List[A]): Semigroup[List[A]] =
new Semigroup[List[A]] {
override def append(y: List[A]) = x ++ y
}
```

Now we can bang out an applicative functor for `Either`

.
As before, we'll put it in an implicit function:

```
implicit def eitherApplicative[A,Z](x: Either[Z,A])(implicit zs: Z => Semigroup[Z]) =
new Applicative[A,({type EitherZ[B] = Either[Z,B]})#EitherZ] {
override def map[B](f: A => B) =
match {
x case Left(l) => Left(l)
case Right(r) => Right(f(r))
}
override def ap[B](f: Either[Z,A => B]) =
match {
x case Left(l) =>
match {
f case Left(l2) => Left(l append l2)
case Right(_) => Left(l)
}
case Right(r) =>
match {
f case Left(l2) => Left(l2)
case Right(r2) => Right(r2(r))
}
}
}
```

Now we can use `ap`

on our parsed values:

```
> val fortyTwo = atoi("20") ap (atoi("22") map add2)
scala: scala.util.Either[List[String],Int] = Right(42) fortyTwo
```

```
> val notFortyTwo = atoi("twenty") ap (atoi("twenty two") map add2)
scala: scala.util.Either[List[String],Int] = Left(List('twenty' is not an integer, 'twenty two' is not an integer)) notFortyTwo
```

Again, it can be handy to do all this in reverse by first lifting a function and then applying it to a lifted value:

```
implicit class FnCofunctor[A,B](g: A => B) {
def <%>[Z](x: Either[Z,A])(implicit zs: Z => Semigroup[Z]) = x map g
}
implicit class EitherCofunctor[A,B,Z](f: Either[Z,A => B])(implicit zs: Z => Semigroup[Z]) {
def <*>(a: Either[Z,A]) = a ap f
}
```

Now we can implicity lift `add2`

and apply it to two
values returned by `atoi`

:

```
> val fortyTwo = add2 <%> atoi("20") <*> atoi("22")
scala: scala.util.Either[List[String],Int] = Right(42) fortyTwo
```

```
> val notFortyTwo = add2 <%> atoi("twenty") <*> atoi("twenty two")
scala: scala.util.Either[List[String],Int] = Left(List('twenty two' is not an integer, 'twenty' is not an integer)) notFortyTwo
```

Note the difference in evaluation order -- the error messages are
returned in the reverse order when using `<*>`

instead
of `ap`

.

We can combine `<%>`

and `<*>`

as
needed:

```
> val fortyTwo = add2 <%> (abs <%> atoi("-20")) <*> atoi("22")
scala: scala.util.Either[List[String],Int] = Right(42) fortyTwo
```