Skip to content

Commit

Permalink
Add Parallel docs
Browse files Browse the repository at this point in the history
  • Loading branch information
Luka Jacobowitz committed Nov 17, 2017
1 parent 2ca66c9 commit 4f57f66
Show file tree
Hide file tree
Showing 2 changed files with 122 additions and 0 deletions.
4 changes: 4 additions & 0 deletions docs/src/main/resources/microsite/data/menu.yml
Original file line number Diff line number Diff line change
Expand Up @@ -84,6 +84,10 @@ options:
url: typeclasses/foldable.html
menu_type: typeclasses

- title: Parallel
url: typeclasses/parallel.html
menu_type: typeclasses

- title: MonoidK
url: typeclasses/monoidk.html
menu_type: typeclasses
Expand Down
118 changes: 118 additions & 0 deletions docs/src/main/tut/typeclasses/parallel.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,118 @@
---
layout: docs
title: "Parallel"
section: "typeclasses"
source: "core/src/main/scala/cats/Parallel.scala"
scaladoc: "#cats.Parallel"
---
# Parallel

When browsing the various `Monads` included in cats,
you may have noticed that some of them have data types that are actually of the same structure,
but instead have instances of `Applicative`. E.g. `Either` and `Validated`.

This is because defining a `Monad` instance for data types like `Validated` would be inconsistent with its error-accumulating behaviour.
In short, `Monads` describe dependent computations and `Applicatives` describe independent computations.

Sometimes however, we want to use both in conjuction with each other.
In the example of `Either` and `Validated` it is trivial albeit cumbersome to convert between the two types.
Below is a short example of a situation where we might run into this.
For simplicity, we'll use `String` as our type to represent errors.

```tut:book
import cats.implicits._
import cats.data._
case class Name(value: String)
case class Age(value: Int)
case class Person(name: Name, age: Age)
def parse(s: String): Either[NonEmptyList[String], Int] = {
if (s.matches("-?[0-9]+")) Right(s.toInt)
else Left(NonEmptyList.one(s"$s is not a valid integer."))
}
def validateAge(a: Int): Either[NonEmptyList[String], Age] = {
if (a > 18) Right(Age(a))
else Left(NonEmptyList.one(s"$a is not old enough"))
}
def validateName(n: String): Either[NonEmptyList[String], Name] = {
if (n.length >= 8) Right(Name(n))
else Left(NonEmptyList.one(s"$n Does not have enough characters"))
}
```

Now we want to parse two Strings into a value of `Person`:

```tut:book
def parsePerson(ageString: String, nameString: String) =
for {
age <- parse(ageString)
person <- (validateName(nameString).toValidated, validateAge(age).toValidated)
.mapN(Person)
.toEither
} yield person
```

We had to convert to and from `Validated` manually.
While this is still manageble, it get's worse the more `Eithers` we want to combine in parallel.

To mitigate this pain, cats introduces a type class `Parallel` that abstracts over `Monads` which also support parallel composition.
It is simply defined in terms of conversion functions between the two data types:

```scala
trait Parallel[M[_], F[_]] {
def sequential: F ~> M

def parallel: M ~> F
}
```
Where `M[_]` has to have an instance of `Monad` and `F[_]` an instance of `Applicative`.

Recall that `~>` is just an alias for [`FunctionK`](datatypes/functionk.html).
This allows us to get rid of most of our boilerplate from earlier:

```tut:book
def parsePerson(ageString: String, nameString: String) =
for {
age <- parse(ageString)
person <- (validateName(nameString), validateAge(age)).parMapN(Person)
} yield person
```

We can also traverse over a `Traverse` using `Parallel`:

```tut
List(Left(42), Right(NonEmptyList.one("Error 1")), Right(NonEmptyList.one("Error 2"))).parSequence
```



Parallel is also really useful for `zipping` collections. The standard `Applicative` instance for `List`, `Vector`, etc.
behaves like the cartesian product of the individual collections:

```tut
(List(1, 2, 3), List(4, 5, 6)).mapN(_ + _)
```

However often we will want to `zip` two or more collections together.
We can define a different `ap` for most of them and use the `parMapN` syntax for that:

```tut
(List(1, 2, 3), List(4, 5, 6)).parMapN(_ + _)
```

## NonEmptyParallel - a weakened Parallel

If you recall that some types cannot form a `Monad` or an `Applicative` because it's not possible to implement the `pure` function for them.
However, these types usually can have instances for `FlatMap` or `Apply`.
For types like these we can use the `NonEmptyParallel` type class.
An example for one of these is `ZipList`.


With instances of `NonEmptyParallel` it's not possible to use the `parTraverse` and `parSequence` functions,
but we can still use `parMapN` and also `parNonEmptyTraverse` and `parNonEmptySequence`,
which are analogous to the functions defined on [`NonEmptyTraverse`](nonemptytraverse.html).

0 comments on commit 4f57f66

Please sign in to comment.