This library encourages you to do memoization
in three separate steps:

Create a memoizable function

Create or select an appropriate memoizer

Run the memoizer on the memoizable function

Let's start with the first.
When you create a memoizable function,
you should use the `self`

convention,
which is that the first input to the function is `self`

,
and all recursive calls are replaced with `self`

.
One common convention that goes well with the `self`

convention
is using a helper function `go`

, like so:

```
fib :: Memoizable (Integer -> Integer)
fib self = go
where go 0 = 1
go 1 = 1
go n = self (n-1) + self (n-2)
```

Now for the second. For this example,
we need a Memoizer that can handle an `Integer`

input,
and an `Integer`

output. `Data.MemoCombinators`

provides
`integral`

, which handles any `Integral`

input, and
any output. `Data.MemoUgly`

provides `memo`

,
which can memoize any function `a -> b`

, given an `Ord`

instance
for `a`

.

Third, let's run our memoizers!
Since we have decoupled the definition of the memoized function
from its actual memoization, we can create multiple
memoized versions of the same function if we so desire.

```
import qualified Data.MemoUgly as Ugly
import qualified Data.MemoCombinators as MC
fibUgly :: Integer -> Integer
fibUgly = runMemo Ugly.memo fib
fibMC :: Integer -> Integer
fibMC = runMemo MC.integral fib
```

You could easily do the same with `Data.MemoTrie.memo`

,
`Data.Function.Memoize.memoize`

, etc.

Using this technique, you can create local memoized functions
whose memo tables are garbage collected as soon as
they are no longer needed.