- By Javier Martínez
- ·
- Posted 10 Aug 2021
Functional patterns
Welcome pythonistas! In our last video session on design patterns we focused exclusively on patterns for the object oriented paradigm (OOP). To some..
In the first part of this series, we went through a basic introduction to Functor and Applicative Functor. In this second part, we will go through an exercise to show how to use them to perform input data validation.
Create the types:
Address
Body
Email
Create the functions:
makeAddress
that takes a String and validates that it contains a '@'. It returns an Address
value wrapped in a Just
if it is valid or Nothing
otherwise.makeBody
that takes a String and validates that it is not empty. It returns a Body
value wrapped in a Just
if it is valid or Nothing
otherwise.makeEmail
that takes as arguments three strings, fromAddress
, toAddress
, and body
. It returns an email instance wrapped in Just
if fromAddress
, toAddress
and body
are valid, Nothing
otherwise.Types:
type FromAddress = Address
type ToAddress = Address
data Address = Address String
data Body = Body String
data Email = Email FromAddress ToAddress Body
FromAddress
and ToAddress
are type aliases to the Address
type so that it’s easier to identify which one is which in the Email data constructor.
It is worth noting that the data constructors for our types Address
, Body
and Email
are just functions with one, one and three arguments respectively.
For instance the Email
constructor has the following type signature:
Email :: Address -> Address -> Body -> Email
Functions:
makeAddress :: String -> Maybe Address
makeAddress address = fmap Address (validateContains '@' address)
makeBody :: String -> Maybe Body
makeBody body = fmap Body (validateNonEmpty body)
makeEmail :: String -> String -> String -> Maybe Email
makeEmail from to body =
case makeAddress from of
Nothing -> Nothing
Just fromAddress ->
case makeAddress to of
Nothing -> Nothing
Just toAddress ->
case makeBody body of
Nothing -> Nothing
Just body ->
Just (Email fromAddress toAddress body)
Auxiliary functions to validate input.
validateNonEmpty :: String -> Maybe String
validateNonEmpty [] = Nothing
validateNonEmpty xs = Just xs
validateContains :: Char -> String -> Maybe String
validateContains x xs
| elem x xs = Just xs
| otherwise = Nothing
makeAddress
and makeBody
successfully leveraged the functoriality of Maybe. We were able to apply the validation function to obtain a Maybe String
to then fmap it to Maybe Address
and Maybe Body
respectively.
On the other hand, the makeEmail
implementation is much more involved and cumbersome. Let's see why we had to do the break down of Maybe values manually.
If we try to fmap the Email
constructor as we did with Address
and Body ,
for makeAddress
and makeBody
, the expression has the following type:
fmap Email (makeAddress "carlos@codurance.com") :: Maybe (Address -> Body -> Person)
Examining the type of the expression, we can see that we have partially applied the Email
constructor, successfully applying it to the Address
value inside the Maybe structure. However, it is still waiting for two more arguments in order to produce the desired result type for makeEmail
, Maybe Email
.
If we now try to apply the second argument by applying fmap again we get a type error, as fmap
does not take a function embedded in a structure, but a function on its own.
fromAddress :: Maybe Address
fromAddress = makeAddress "carlos@codurance.com"
toAddress :: Maybe Address
toAddress = makeAddress "user@email.com"
emailWithFromApplied :: Maybe (Address -> Body -> Email)
emailWithFromApplied = fmap Email fromAddress
-- does not compile
emailWithFromAndToApplied :: Maybe (Body -> Email)
emailWithFromAndToApplied = fmap emailWithFromApplied toAddress
The problem here is that the function that we are passing to fmap
in the case of emailWithFromAndToApplied
is wrapped in a Maybe structure and fmap
does not accept a function wrapped in a structure.
Applicatives to the rescue! They let us do exactly what we need, apply a function inside a structure to a value inside a structure of the same type.
Let's implement emailWithFromAndToApplied
using <*>
:
emailWithFromAndToApplied :: Maybe (Body -> Email)
emailWithFromAndToApplied = emailWithFromApplied <*> toAddress
Now we have successfully applied the second argument to the Email
constructor, but there is still one more to go, the Body
argument, so let's apply it using <*>
once again:
body :: Maybe Body
body = makeBody "Haskell rocks."
emailFullyApplied :: Maybe Email
emailFullyApplied = emailWithFromAndToApplied <*> body
We just implemented the function emailFullyApplied
by leveraging the power of Functor and Applicative. Let's break down what we just did:
Email
constructor under the Maybe structure that makeAddress
provides. This resulted in the Email
constructor been partially applied to its first argument, fromAddress
. The rest of the function, Address -> Body -> Email
, is now embedded or wrapped inside a Maybe structure.toAddress
, obtaining the Email
constructor now applied to its two first arguments.Email
constructor, body
, obtaining the desired result.The implementation did not look as bad as the first attempt, but just because we broke it down into several intermediate results. If we were to inline the implementation of the function emailFullyApplied
we would get:
emailFullyApplied :: Maybe Email
emailFullyApplied = ((fmap Email (makeAddress "carlos@codurance.com")) <*> makeAddress "user@email.com") <*> makeBody "Haskell rocks"
The Applicative package in Haskell also provides an infix operator <$>
for fmap
that makes the implementation a bit nicer, by getting rid of the parenthesis. It behaves as fmap
, but it is placed between its two arguments:
emailFullyApplied :: Maybe Email
emailFullyApplied =
Email <$> makeAddress "carlos@codurance.com"
<*> makeAddress "user@email.com"
<*> makeBody "Haskell rocks"
We can go back to the original makeEmail
function by extracting the hardcoded values as parameters:
makeEmail :: String -> String -> String -> Maybe Email
makeEmail from to body =
Email <$> makeAddress from
<*> makeAddress to
<*> makeBody body
It is worth noting that this implementation of makeEmail
, apart from being far nicer than the original one, is much easier to extend if we were to add more arguments or fields to the Email
constructor.
Map a function using
<$>
to partially apply it and to embed it inside a structure, then apply it to the rest of it arguments using<*>
This pattern is so common in Haskell that the Applicative package provides several utility functions, liftA2
, liftA3
... The liftAn functions will take a function of n arguments and will apply it to all its arguments wrapped in a structure f.
For instance, liftA3, takes a function of three arguments and three values wrapped in a structure f and it applies the function to the values as we did in the makeEmail
implementation:
liftA3 :: Applicative f => (a -> b -> c -> d) -> f a -> f b -> f c -> f d`
Substituting our types:
liftA3 :: Applicative f =>
(a -> b -> c -> d)
-> f a
-> f b
-> f c
-> f d
liftA3 ::
(Address -> Address -> Body -> Email)
-> Maybe Address
-> Maybe Address
-> Maybe Body
-> Maybe Email
Rewriting makeEmail
to make use of liftA3:
makeEmail :: String -> String -> String -> Maybe Email
makeEmail from to body =
liftA3 Email (makeAddress from)
(makeAddress to)
(makeBody body)
We just saw how to use the Maybe Functor and Applicative Functor to validate input data, however, Maybe cannot offer any information about the error.
We will see how we can signal errors and also accumulate all the errors occurred during the validation process using the Validation
data type. This is a more practical scenario for real-life applications, as it is often required to return some information about the errors.
The data type Validation
is very similar to Either
. You may be familiar with Either
as it is quite a common type in most functional languages.
data Either a b = Left a | Right b
data Validation err a = Failure err | Success a
The definition of both types shows that Either
and Validation
are indeed identical, they just have different names for their type and data constructors.
Either is a general purpose data type. Validation is a variation of Either exclusively for validation purposes that accumulates all the errors. This difference is not visible in the definitions of the data types, but it is in their Applicative instances.
We will be using the Validation package Haskell, which defines the AccValidation
data type that accumulates errors in a given type.
Either
just short-circuits as soon as there is an error, as Maybe does, but it can carry with it information about the actual error.AccValidation
accumulates all the errors in a given type, usually List.AccValidation
accumulates all the errors using the Semigroup typeclass. A semigroup is an abstraction that combines two arguments of the same type into a single one, as Monoid does, but it does not have an identity element. We are going to show how to combine all the errors using AccValidation
and List. List has both a Monoid instance and a Semigroup instance.
The AccValidation
data type and its Applicative instance are defined as follows:
data AccValidation err a = AccFailure err | AccSuccess a
Semigroup err => Applicative (AccValidation err)
Let's see how we can use it in code.
First, we need to define an Error
data type for our implementation:
data Error = EmptyBody | AddressMustContain String deriving (Eq, Show)
And three new functions validateAddress
, validateBody
and validateEmail
that return information about the error in case there is one:
validateAddress :: String -> AccValidation [Error] Address
validateAddress address = maybeToValidation error (makeAddress address)
where error = AddressMustContain "@"
validateBody :: String -> AccValidation [Error] Body
validateBody body = maybeToValidation EmptyBody (makeBody body)
validateEmail :: String -> String -> String -> AccValidation [Error] Email
validateEmail from to body =
Email <$> validateAddress from
<*> validateAddress to
<*> validateBody body
Auxiliary function to convert Maybe to AccValidation:
maybeToValidation :: Error -> Maybe a -> AccValidation [Error] a
maybeToValidation error Nothing = AccFailure [error]
maybeToValidation _ (Just x) = AccSuccess x
Using liftA3
:
validateEmail :: String -> String -> String -> AccValidation [Error] Email
validateEmail from to body =
liftA3 Email (validateAddress from)
(validateAddress to)
(validateBody body)
Note how the implementation of validateEmail
is identical to the one we defined earlier for makeEmail
. The type signature has changed, as it now returns an AccValidation
instead of a Maybe
, but given that both types are Applicatives Functors we don’t need to change the implementation to change the behaviour.
To see how errors accumulate, let's write the following two functions that feed sample data to validateEmail
:
allWrong :: AccValidation [Error] Email
allWrong = validateEmail "wrong" "alsoWrong" ""
allGood :: AccValidation [Error] Email
allGood = validateEmail "carlos@codurance.com" "info@codurance.com" "Haskell rocks"
Evaluating both expresions in the REPL:
Prelude> print allWrong
AccFailure [AddressMustContain "@",AddressMustContain "@",EmptyBody]
Prelude> print allGood
AccSuccess (Email (Address "carlos@codurance.com") (Address "info@codurance.com") (Body "Haskell rocks"))
To recap:
As a further observation, note how the type signatures for $
, the function application operator, <$>
, for fmap, and <*>
, for apply, are very similar. They all play around adding an extra layer of structure to the arguments, a function and a value, and the return type. They all are function application.
$ :: (a -> b) -> a -> b
<$> :: (a -> b) -> f a -> f b
<*> :: f (a -> b) -> f a -> f b
Welcome pythonistas! In our last video session on design patterns we focused exclusively on patterns for the object oriented paradigm (OOP). To some..
Solving a simple problem in Elixir In this article, I am going to solve the Word Count problem from Exercism in Elixir. I'll start with a form that..
Crafting web apps using finite state machines - Part 1 Code on Gitlab
Join our newsletter for expert tips and inspirational case studies
Join our newsletter for expert tips and inspirational case studies