lens-tutorial-1.0.3: Tutorial for the lens library
Safe HaskellNone
LanguageHaskell2010

Control.Lens.Tutorial

Contents

Description

This lens tutorial targets Haskell beginners and assumes only basic familiarity with Haskell. By the end of this tutorial you should:

  • understand what problems the lens library solves,
  • know when it is appropriate to use the lens library,
  • be proficient in the most common lens idioms,
  • understand the drawbacks of using lenses, and:
  • know where to look if you wish to learn more advanced tricks.

If you would like to follow along with these examples, just import this module:

$ ghci
>>> import Control.Lens.Tutorial

Synopsis

Motivation

The simplest problem that the lens library solves is updating deeply nested records. Suppose you had the following nested Haskell data types:

data Atom = Atom { _element :: String, _point :: Point }

data Point = Point { _x :: Double, _y :: Double }

If you wanted to increase the x coordinate of an Atom by one unit, you would have to write something like this in Haskell:

shiftAtomX :: Atom -> Atom
shiftAtomX (Atom e (Point x y)) = Atom e (Point (x + 1) y)

This unpacking and repacking of data types grows increasingly difficult the more fields you add to each data type or the more deeply nested your data structures become.

The lens library solves this problem by letting you instead write:

-- atom.hs

{-# LANGUAGE TemplateHaskell #-}

import Control.Lens hiding (element)

data Atom = Atom { _element :: String, _point :: Point } deriving (Show)

data Point = Point { _x :: Double, _y :: Double } deriving (Show)

makeLenses ''Atom
makeLenses ''Point

shiftAtomX :: Atom -> Atom
shiftAtomX = over (point . x) (+ 1)

Let's convince ourselves that this works:

>>> let atom = Atom { _element = "C", _point = Point { _x = 1.0, _y = 2.0 } }
>>> shiftAtomX atom
Atom {_element = "C", _point = Point {_x = 2.0, _y = 2.0}}

The above solution does not change no matter how many fields we add to Atom or Point.

Now suppose that we added yet another data structure:

data Molecule = Molecule { _atoms :: [Atom] } deriving (Show)

We could shift an entire Molecule by writing:

makeLenses ''Molecule

shiftMoleculeX :: Molecule -> Molecule
shiftMoleculeX = over (atoms . traverse . point . x) (+ 1)

Again, this works the way we expect:

>>> let atom1 = Atom { _element = "C", _point = Point { _x = 1.0, _y = 2.0 } }
>>> let atom2 = Atom { _element = "O", _point = Point { _x = 3.0, _y = 4.0 } }
>>> let molecule = Molecule { _atoms = [atom1, atom2] }
>>> shiftMoleculeX molecule  -- Output formatted for clarity
Molecule {_atoms = [Atom {_element = "C", _point = Point {_x = 2.0, _y = 2.0}},Atom {_element = "O", _point = Point {_x = 4.0, _y = 4.0}}]}

... or formatted for clarity:

Molecule
    { _atoms =
        [ Atom { _element = "C", _point = Point { _x = 2.0, _y = 2.0 } }
        , Atom { _element = "O", _point = Point { _x = 4.0, _y = 4.0 } }
        ]
    }

Many people stumble across lenses while trying to solve this common problem of working with data structures with a large number of fields or deeply nested values. These sorts of situations arise commonly in:

  • games with complex and deeply nested state
  • scientific data formats
  • sensor or instrument output
  • web APIs
  • XML and JSON
  • enterprise code where data structures can have tens, hundreds, or even thousands of fields (true story!)

Lenses

You might have some basic questions like:

Question: What is a lens?

Answer: A lens is a first class getter and setter

We already saw how to use lenses to update values using over, but we can also use lenses to retrieve values using view:

>>> let atom = Atom { _element = "C", _point = Point { _x = 1.0, _y = 2.0 } }
>>> view (point . x) atom
1.0

In other words, lenses package both "get" and "set" functionality into a single value (the lens). You could pretend that a lens is a record with two fields:

data Lens a b = Lens
    { view :: a -> b
    , over :: (b -> b) -> (a -> a)
    }

That's not how lenses are actually implemented, but it's a useful starting intuition.

Question: What is the type of a lens?

Answer: We used two lenses in the above Atom example, with these types:

point :: Lens' Atom  Point
x     :: Lens' Point Double

The point lens contains all the information we need to get or set the _point field of the Atom type (which is a Point). Similarly, the x lens contains all the information we need to get or set the _x field of the Point data type (which is a Double).

The convention for the Lens' type parameters is:

--    +-- Bigger type
--    |
--    v
Lens' bigger smaller
--           ^
--           |
--           +--  Smaller type within the bigger type

The actual definition of Lens' is:

type Lens' a b = forall f . Functor f => (b -> f b) -> (a -> f a)

You might wonder how you can fit both getter and setter functionality in a single value like this. The trick is that we get to pick what Functor we specialize f to and depending on which Functor we pick we get different features.

For example, if you pick (f = Identity):

type ASetter' a b   = (b -> Identity b) -> (a -> Identity a)

-- ... equivalent to: (b ->          b) -> (a ->          a)

... you can build an over-like function.

Similarly, if you pick (f = Const b):

type Getting b a b  = (b -> Const b b) -> (a -> Const b a)

-- ... equivalent to: (b ->       b  ) -> (a ->       b  )

... and if you apply a function of that type to id then you get a view-like function

--                                        (a ->       b  )

Those are not the only two Functors we can pick. In fact, we can do a lot more with lenses than just get and set values, but those are the two most commonly used features.

Question: How do I create lenses?

Answer: You can either auto-generate them using Template Haskell or create them by hand

In our Atom example, we auto-generated the lenses using Template Haskell, like this:

makeLenses ''Atom
makeLenses ''Point

This created four lenses of the following types:

element :: Lens' Atom String
point   :: Lens' Atom Point
x       :: Lens' Point Double
y       :: Lens' Point Double

makeLenses creates one lens per field prefixed with an underscore. The lens has the same name as the field without the underscore.

However, sometimes Template Haskell is not an option, so we can also use the lens utility function to build lenses. This utility has type:

lens :: (a -> b) -> (a -> b -> a) -> Lens' a b

The first argument is a "getter" (a way to extract a 'b' from an 'a'). The second argument is a "setter" (given a b, update an a). The result is a Lens' built from the getter and setter. You would use lens like this:

point :: Lens' Atom Point
point = lens _point (\atom newPoint -> atom { _point = newPoint })

You can even define lenses without incurring a dependency on the lens library. Remember that lenses are just higher-order functions over Functors, so we could instead write:

-- point :: Lens' Atom Point
point :: Functor f => (Point -> f Point) -> Atom -> f Atom
point k atom = fmap (\newPoint -> atom { _point = newPoint }) (k (_point atom))

This means that you can provide lenses for your library's types without depending on the lens library. All you need is the fmap function, which is provided by the Haskell Prelude.

Question: How do I combine lenses?

Answer: You compose them, using function composition (Yes, really!)

You can think of the function composition operator as having this type:

(.) :: Lens' a b -> Lens' b c -> Lens' a c

We can compose lenses using function composition because Lens' is a type synonym for a higher-order function:

type Lens' a b = forall f . Functor f => (b -> f b) -> (a -> f a)

So under the hood we are composing two higher-order functions to get back a new higher-order function:

(.) :: Functor f
    => ((b -> f b) -> (a -> f a))
    -> ((c -> f c) -> (b -> f b))
    -> ((c -> f c) -> (a -> f a))

In our original Atom example, we composed the point and x lenses to create a new composite lens:

point     :: Lens' Atom Point
x         :: Lens' Point Double

point . x :: Lens' Atom Double

This composite lens lets us get or set the x coordinate of an Atom. We can use over and view on the composite Lens' and they will behave exactly the way we expect:

view (point . x) :: Atom -> Double

over (point . x) :: (Double -> Double) -> (Atom -> Atom)

Question: How do I consume lenses?

Answer: Using view, set or over

Here are their types:

view :: Lens' a b -> a -> b

over :: Lens' a b -> (b -> b) -> a -> a

set  :: Lens' a b ->       b  -> a -> a
set lens b = over lens (\_ -> b)

view and over are the two fundamental functions on lenses. set is just a special case of over.

view and over are fundamental because they distribute over lens composition:

view (lens1 . lens2) = (view lens2) . (view lens1)

view id = id
over (lens1 . lens2) = (over lens1) . (over lens2)

over id = id

Question: What else do I need to know?

Answer: That's pretty much it!

For 90% of use cases, you just:

  • Create lenses (using makeLens, lens or plain-old fmap)
  • Compose them (using (.))
  • Consume them (using view, set, and over)

You could actually stop reading here if you are in a hurry since this covers the overwhelmingly common use case for the library. On the other hand, keep reading if you would like to learn additional tricks and features.

Accessor notation

You might be used to object-oriented languages where you could retrieve a nested field using:

atom.point.x

You can do almost the exact same thing using the lens library, except that the first dot will have a ^ right before the dot:

>>> let atom = Atom { _element = "C", _point = Point { _x = 1.0, _y = 2.0 } }
>>> atom^.point.x
1.0

You can better understand why this works, by adding whitespace and explicit parentheses:

atom ^. (point . x)

This trick uses (^.), which is an infix operator equivalent to view:

(^.) :: a -> Lens' a b -> b
x ^. l = view l x

... and you just keep adding dots after that for each lens you compose. This gives the appearance of object-oriented accessors if you omit the whitespace around the operators.

First-class

Lenses are "first class" values, meaning that you can manipulate them using ordinary functional programming techniques. You can take them as inputs, return them as outputs, or stick them in data structures. Anything goes!

For example, suppose we don't want to define separate shift functions for Atoms and Molecules:

shiftAtomX :: Atom -> Atom
shiftAtomX = over (point . x) (+ 1)
shiftMoleculeX :: Molecule -> Molecule
shiftMoleculeX = over (atoms . traverse . point . x) (+ 1)

We can instead unify them into a single function by parametrizing the shift function on the lens:

shift lens = over lens (+ 1)

This lets us write:

shift (point . x) :: Atom -> Atom

shift (atoms . traverse . point . x) :: Molecule -> Molecule

Even better, we can define synonyms for our composite lenses:

atomX :: Lens' Atom Double
atomX = point . x

-- We'll learn what `Traversal` means shortly
moleculeX :: Traversal' Molecule Double
moleculeX = atoms . traverse . point . x

Now we can write code almost identical to the original code:

shift atomX :: Atom -> Atom

shift moleculeX :: Molecule -> Molecule

... but we also get several other utilities for free:

set atomX :: Double -> Atom -> Atom

set moleculeX :: Double -> Molecule -> Molecule

view atomX :: Atom -> Double

-- We can't use `view` for `Traversal'`s.  Read on to find out why
toListOf moleculeX :: Molecule -> [Double]

That's much more reusable, but you might wonder what this Traversal' and toListOf business is all about.

Traversals

Question: What is a traversal?

Answer: A first class getter and setter for an arbitrary number of values

A traversal lets you get all the values it points to as a list and it also lets you update or set all the values it points to. Think of a traversal as a record with two fields:

data Traversal' a b = Traversal'
    { toListOf :: a -> [b]
    , over     :: (b -> b) -> (a -> a)
    }

That's not how traversals are actually implemented, but it's a useful starting intuition.

We can still use over and set (a special case of over) with a traversal, but we use toListOf instead of view.

Question: What is the type of a traversal?

Answer: We used one traversal in the above Molecule example:

moleculeX :: Traversal' Molecule Double

This Traversal' lets us get or set an arbitrary number of x coordinates, each of which is a Double. There could be less than one x coordinate (i.e. 0 coordinates) or more than one x coordinate. Contrast this with a Lens' which can only get or set exactly one value.

Like Lens', Traversal' is a type synonym for a higher-order function:

type Traversal' a b = forall f . Applicative f => (b -> f b) -> (a -> f a)

type Lens'      a b = forall f . Functor     f => (b -> f b) -> (a -> f a)

Notice that the only difference between a Lens' and a Traversal' is the type class constraint. A Lens' has a Functor constraint and Traversal' has an Applicative constraint. This means that any Lens' is automatically also a valid Traversal' (since Functor is a superclass of Applicative).

Since every Lens' is a Traversal', all of our example lenses also double as traversals:

atoms   :: Traversal' Molecule [Atom]
element :: Traversal' Atom     String
point   :: Traversal' Atom     Point
x       :: Traversal' Point    Double
y       :: Traversal' Point    Double

We actually used yet another Traversal', which was traverse (from Data.Traversable):

traverse :: Traversable t => Traversal' (t a) a

This works because the Traversal' type synonym expands out to:

traverse :: (Applicative f, Traversable t) => (a -> f a) -> t a -> f (t a)

... which is exactly the traditional type signature of traverse.

In our Molecule example, we were using the special case where t = []:

traverse :: Traversal' [a] a

In Haskell, you can derive Functor, Foldable and Traversable for many data types using the DeriveFoldable and DeriveTraversable extensions. This means that you can autogenerate a valid traverse for these data types:

{-# LANGUAGE DeriveFoldable    #-}
{-# LANGUAGE DeriveFunctor     #-}
{-# LANGUAGE DeriveTraversable #-}

import Control.Lens
import Data.Foldable

data Pair a = Pair a a deriving (Functor, Foldable, Traversable)

We could then use traverse to navigate from Pair to its two children:

traverse :: Traversal' (Pair a) a

over traverse :: (a -> a) -> (Pair a -> Pair a)

over traverse (+ 1) (Pair 3 4) = Pair 4 5

Question: How do I create traversals?

Answer: There are three main ways to create primitive traversals:

Question: How do I combine traversals?

Answer: You compose them, using function composition

You can think of the function composition operator as having this type:

(.) :: Traversal' a b -> Traversal' b c -> Traversal' a c

We can compose traversals using function composition because a Traversal' is a type synonym for a higher-order function:

type Traversal' a b = forall f . Applicative f => (b -> f b) -> (a -> f a)

So under the hood we are composing two functions to get back a new function:

(.) :: Applicative f
    => ((b -> f b) -> (a -> f a))
    -> ((c -> f c) -> (b -> f b))
    -> ((c -> f c) -> (a -> f a))

In our original Molecule example, we composed four Traversal's together to create a new Traversal':

-- Remember that `atoms`, `point`, and `x` are also `Traversal'`s
atoms                        :: Traversal' Molecule [Atom]
traverse                     :: Traversal' [Atom]   Atom
point                        :: Traversal' Atom     Point
x                            :: Traversal' Point    Double

-- Now compose them
atoms                        :: Traversal' Molecule [Atom]
atoms . traverse             :: Traversal' Molecule Atom
atoms . traverse . point     :: Traversal' Molecule Point
atoms . traverse . point . x :: Traversal' Molecule Double

This composite traversal lets us get or set the x coordinates of a Molecule.

over (atoms . traverse . point . x)
    :: (Double -> Double) -> (Molecule -> Molecule)

toListOf (atoms . traverse . point . x)
    :: Molecule -> [Double]

Question: How do I consume traversals?

Answer: Using toListOf, set or over

Here are their types:

toListOf :: Traversal' a b -> a -> [b]

over :: Traversal' a b -> (b -> b) -> a -> a

set  :: Traversal' a b ->       b  -> a -> a
set traversal b = over traversal (\_ -> b)

Note that toListOf distributes over traversal composition:

toListOf (traversal1 . traversal2) = (toListOf traversal1) >=> (toListOf traversal2)

toListOf id = return

If you prefer object-oriented syntax you can also use (^..), which is an infix operator equivalent to toListOf:

>>> Pair 3 4 ^.. traverse
[3,4]

Types

You might wonder why you can use over on both a Lens' and a Traversal' but you can only use view on a Lens'. We can see why by studying the (simplified) type and implementation of over:

over :: ((b -> Identity b) -> (a -> Identity a)) -> (b -> b) -> a -> a
over setter f x = runIdentity (setter (\y -> Identity (f y)) x)

To follow the implementation, just step slowly through the types. Here are the types of the arguments to over:

setter :: (b -> Identity b) -> (a -> Identity a)
f      :: b -> b
x      :: a

... and here are the types of the sub-expressions on the right-hand side:

                     \y -> Identity (f y)     :: b -> Identity b
             setter (\y -> Identity (f y))    :: a -> Identity a
             setter (\y -> Identity (f y)) x  ::      Identity a
runIdentity (setter (\y -> Identity (f y)) x) ::               a

We can replace setter with point and replace x with atom to see that this generates the correct code for updating an atom's point:

  over point f atom

-- Definition of `over`
= runIdentity (point (\y -> Identity (f y)) atom)

-- Definition of `point`
= runIdentity (fmap (\newPoint -> atom { _point = newPoint }) (Identity (f (_point atom)))

-- fmap g (Identity y) = Identity (g y)
= runIdentity (Identity (atom { _point = f (_point atom) }))

-- runIdentity (Identity z) = z
= atom { _point = f (_point atom) }

... which is exactly what we would have written by hand without lenses.

The reason over works for both Lens'es and Traversal's is because Identity implements both Functor and Applicative:

instance Functor     Identity where ...
instance Applicative Identity where ...

So both the Lens' type and Traversal' type synonyms:

type Traversal' a b = forall f . Applicative f => (b -> f b) -> (a -> f a)

type Lens'      a b = forall f . Functor     f => (b -> f b) -> (a -> f a)

... can both be specialized to use Identity in place of f:

(b -> Identity b) -> (a -> Identity a)

... making them valid arguments to over.

Now let's study the (simplified) type and implementation of view:

view :: ((b -> Const b b) -> (a -> Const b a)) -> a -> b
view getter x = getConst (getter Const x)

Again, we can walk slowly through the types of the arguments:

getter :: (b -> Const b b) -> (a -> Const b a)
x      :: a

... and the types of the sub-expressions on the right-hand side:

getter Const              :: a -> Const b a
getter Const x            ::      Const b a
getConst (getter Const x) ::            b

Let's see how this plays out for the point lens:

  view point atom

-- Definition of `view`
= getConst (point Const atom)

-- Definition of `point`
= getConst (fmap (\newPoint -> atom { _point = newPoint }) (Const (_point atom)))

-- fmap g (Const y) = Const y
= getConst (Const (_point atom))

-- getConst (Const z) = z
= _point atom

... which is exactly what we would have written by hand without lenses.

view accepts Lens'es because Const implements Functor:

instance Functor (Const b)

... so the Lens' type synonym:

type Lens' a b = forall f . Functor f => (b -> f b) -> (a -> f a)

... can be specialized to use (Const b) in place of f:

(b -> Const b b) -> (a -> Const b a)

... making it a valid argument to view.

Interestingly, Const implements also Applicative, but with a constraint:

instance Monoid b => Applicative (Const b)

This implies that we *can* use view on a Traversal', but only if the value that we extract is a Monoid. Let's try this out:

>>> let atom1 = Atom { _element = "C", _point = Point { _x = 1.0, _y = 2.0 } }
>>> let atom2 = Atom { _element = "O", _point = Point { _x = 3.0, _y = 4.0 } }
>>> let molecule = Molecule { _atoms = [atom1, atom2] }
>>> view (atoms . traverse . element) molecule
"CO"

This works because our traversal's result is a String:

atoms . traverse . element :: Traversal' Molecule String

... and String implements the Monoid interface. When you try to extract multiple strings using view they get flattened together into a single String using mappend.

If you try to extract the element from an empty molecule:

>>> view (atoms . traverse . element) (Molecule { _atoms = [] })
""

You get the empty string (i.e. mempty).

This is why the result of a Traversal' needs to be a Monoid when using view. If the Traversal' points to more than one value you need some way to combine them into a single value (using mappend) and if the Traversal' points to less than one value you need a default value to return (using mempty).

If you try to view a Traversal' that doesn't point to a Monoid, you will get the following type error:

>>> view (atoms . traverse . point . x) molecule
    No instance for (Data.Monoid.Monoid Double)
      arising from a use of `traverse'
    In the first argument of `(.)', namely `traverse'
    In the second argument of `(.)', namely `traverse . point . x'
    In the first argument of `view', namely
      `(atoms . traverse . point . x)'

The compiler complains that Double does not implement the Monoid type class, so there is no sensible way to merge all the x coordinates that our Traversal' points to. For these cases you should use toListOf instead.

Drawbacks

Lenses come with trade-offs, so you should use them wisely.

For example, lenses do not produce the best error messages. Unless you understand how Traversal's work you will probably not understand the above error message.

Also, lenses increase the learning curve for new Haskell programmers, so you should consider avoiding them in tutorial code targeting novice Haskell programmers.

Lenses also add a level of boilerplate to all data types to auto-generate lenses and increase compile times. So for small projects the overhead of adding lenses may dwarf the benefits.

lens is also a library with a large dependency tree, focused on being "batteries included" and covering a large cross-section of the Haskell ecosystem. Browsing the Hackage listing you will find support modules ranging from System.FilePath.Lens to Control.Parallel.Strategies.Lens, and many more. If you need a more light-weight alternative you can use the lens-simple or microlens library, each of which provides a restricted subset of the lens library with a much smaller dependency tree.

The ideal use case for the lens library is a medium-to-large project with rich and deeply nested types. In these large projects the benefits of using lenses outweigh the costs.

Conclusion

This tutorial covers an extremely small subset of this library. If you would like to learn more, you can begin by skimming the example code in the following modules:

The documentation for these modules includes several examples to get you started and help you build an intuition for more advanced tricks that were not covered in this tutorial.

You can also study several long-form examples here:

https://github.com/ekmett/lens/tree/master/examples

If you prefer light-weight lens-compatible libraries, then check out lens-simple or micro-lens:

If you would like a broader survey of lens features, then you can check out these tutorials:

Exports

These are the same types and lenses used throughout the tutorial, exported for your convenience.

data Atom Source #

Constructors

Atom 

Fields

Instances

data Point Source #

Constructors

Point 

Fields

Instances

data Molecule Source #

Constructors

Molecule 

Fields

data Pair a Source #

Constructors

Pair a a 

Instances

Functor Pair Source # 

Methods

fmap :: (a -> b) -> Pair a -> Pair b #

(<$) :: a -> Pair b -> Pair a #

Foldable Pair Source # 

Methods

fold :: Monoid m => Pair m -> m #

foldMap :: Monoid m => (a -> m) -> Pair a -> m #

foldr :: (a -> b -> b) -> b -> Pair a -> b #

foldr' :: (a -> b -> b) -> b -> Pair a -> b #

foldl :: (b -> a -> b) -> b -> Pair a -> b #

foldl' :: (b -> a -> b) -> b -> Pair a -> b #

foldr1 :: (a -> a -> a) -> Pair a -> a #

foldl1 :: (a -> a -> a) -> Pair a -> a #

toList :: Pair a -> [a] #

null :: Pair a -> Bool #

length :: Pair a -> Int #

elem :: Eq a => a -> Pair a -> Bool #

maximum :: Ord a => Pair a -> a #

minimum :: Ord a => Pair a -> a #

sum :: Num a => Pair a -> a #

product :: Num a => Pair a -> a #

Traversable Pair Source # 

Methods

traverse :: Applicative f => (a -> f b) -> Pair a -> f (Pair b) #

sequenceA :: Applicative f => Pair (f a) -> f (Pair a) #

mapM :: Monad m => (a -> m b) -> Pair a -> m (Pair b) #

sequence :: Monad m => Pair (m a) -> m (Pair a) #

traverse :: Traversable t => forall f a b. Applicative f => (a -> f b) -> t a -> f (t b) #

Map each element of a structure to an action, evaluate these actions from left to right, and collect the results. For a version that ignores the results see traverse_.