Many of the limitations associated with Haskell type classes can be solved very cleanly with lenses. This lens-driven programming is more explicit but significantly more general and (in my opinion) easier to use.
All of these examples will work with any lens-like library, but I will begin with the lens-simple library to provide simpler types with better type inference and better type errors and then later transition to the lens library which has a larger set of utilities.
Case study #1 - fmap bias
Let's begin with a simple example - the Functor instance for Either:
fmap (+ 1) (Right 2   ) = Right 3
fmap (+ 1) (Left "Foo") = Left "Foo"
Some people object to this instance because it's biased to Right values. The only way we can use fmap to transform Left values is to wrap Either in a newtype.
These same people would probably like the lens-simple library which provides an over function that generalizes fmap. Instead of using the type to infer what to transform we can explicitly specify what we wish to transform by supplying _Left or _Right:
$ stack install lens-simple --resolver=lts-3.9
$ stack ghci --resolver=lts-3.9
>>> import Lens.Simple
>>> over _Right (+ 1) (Right 2)
Right 3
>>> over _Right (+ 1) (Left "Foo")
Left "Foo"
>>> over _Left (++ "!") (Right 2)
Right 2
>>> over _Left (++ "!") (Left "Foo")
Left "Foo!"
The inferred types are exactly what we would expect:
>>> :type over _Right
over _Right :: (b -> b') -> Either a b -> Either a b'
>>> :type over _Left
over _Left :: (b -> b') -> Either b b1 -> Either b' b1
Same thing for tuples. fmap only lets us transform the second value of a tuple, but over lets us specify which one we want to transform:
>>> over _1 (+ 1)    (2, "Foo")
(3,"Foo")
>>> over _2 (++ "!") (2, "Foo")
(2,"Foo!")
We can even transform both of the values in the tuple if they share the same type:
>>> over both (+ 1) (3, 4)
(4,5)
Again, the inferred types are exactly what we expect:
>>> :type over _2
over _2 :: (b -> b') -> (a, b) -> (a, b')
>>> :type over _1
over _1 :: (b -> b') -> (b, b1) -> (b', b1)
>>> :type over both
over both :: (b -> b') -> (b, b) -> (b', b')
Case study #2 - length confusion
Many people have complained about the tuple instance for Foldable, which gives weird behavior like this in ghc-7.10 or later:
>>> length (3, 4)
1
We could eliminate all confusion by specifying what we intend to count at the term level instead of the type level:
>>> lengthOf _2   (3, 4)
1
>>> lengthOf both (3, 4)
2
This works for Either, too:
>>> lengthOf _Right (Right 1)
1
>>> lengthOf _Right (Left "Foo")
0
>>> lengthOf _Left  (Right 1)
0
>>> lengthOf _Left  (Left "Foo")
1
... and this trick is not limited to length. We can improve any Foldable function by taking a lens instead of a type class constraint:
>>> sumOf both (3, 4)
7
>>> mapMOf_ both print (3, 4)
3
4
Case study #3 - Monomorphic containers
fmap doesn't work on ByteString because ByteString is not a type constructor and has no type parameter that we can map over. Some people use the mono-foldable or mono-traversable packages to solve this problem, but I prefer to use lenses. These examples will require the lens library which has more batteries included.
For example, if I want to transform each character of a Text value I can use the text optic:
$ stack install lens --resolver=lts-3.9  # For `text` optics
$ stack ghci --resolver=lts-3.9
>>> import Control.Lens
>>> import Data.Text.Lens
>>> import qualified Data.Text as Text
>>> let example = Text.pack "Hello, world!"
>>> over text succ example
"Ifmmp-!xpsme\""
I can use the same optic to loop over each character:
>>> mapMOf_ text print example
'H'
'e'
'l'
'l'
'o'
','
' '
'w'
'o'
'r'
'l'
'd'
'!'
There are also optics for ByteStrings, too:
>>> import Data.ByteString.Lens
>>> import qualified Data.ByteString as ByteString
>>> let example2 = ByteString.pack [0, 1, 2]
>>> mapMOf_ bytes print example2
0
1
2
The lens approach has one killer feature over mono-foldable and mono-traversable which is that you can be explicit about what exactly you want to map over. For example, suppose that I want to loop over the bits of a ByteString instead of the bytes. Then I can just provide an optic that points to the bits and everyting "just works":
>>> import Data.Bits.Lens
>>> mapMOf_ (bytes . bits) print example2
False
False
False
False
False
False
False
False
True
False
False
False
False
False
False
False
False
True
False
False
False
False
False
False
The mono-traversable or mono-foldable packages do not let you specify what you want to loop over. Instead, the MonoFoldable and MonoTraversable type classes guess what you want the elements to be, and if they guess wrong then you are out of luck.
Conclusion
Here are some more examples to illustrate how powerful and general the lens approach is over the type class approach.
>>> lengthOf (bytes . bits) example2
24
>>> sumOf (both . _1) ((2, 3), (4, 5))
6
>>> mapMOf_ (_Just . _Left) print (Just (Left 4))
4
>>> over (traverse . _Right) (+ 1) [Left "Foo", Right 4, Right 5]
[Left "Foo",Right 5,Right 6]
Once you get used to this style of programming you begin to prefer specifying things at the term level instead of relying on type inference or wrangling with newtypes.