Day 1: IO — Our Ugly Friend

Here’s a program:

main = do
  text <- getLine
  putStr "Your name is: "
  putStrLn text

We can run it like this:

$ ./One
Ben
Your name is: Ben

Day 3: Maybe — Mini-Lists, or Mini-Exceptions

Maybe is like [] but “smaller” — Maybe t can store zero or one elements of type t, but not more.

There’s a category theory way of relating Maybe and []: natural transformations convert between Functors while also making sure…

Day 4: Reader, Writer, State — Wiring Together Functions

Reader, Writer and State usually come presented together, because they’re very similar: these monads wire together functions by adding in extra parameters or return values. There is no non-determinism, change in control flow, or…

Day 2: [] — Seeing the rest of a program run

Here’s a list comprehension:

> [ x * y | x <- [1,2,3], y <- [10,100]]
[10,100,20,200,30,300]

This works in do notation too, with a bit of rearranging:

Prelude> do
Prelude|   x…

Day 8: LogicT — A List Transformer

The list monad lets you perform non-deterministic searches for a solution to a problem. At each step of your program, you can provide a choice of possible values to bind to a variable, and the rest of the program will run several times, trying each possible value and…

Day 5: Set — Harder Than You Might Expect

Sets are a bit like lists, and so you can probably imagine that there should be a Monad instance for them. The first part of this post will be why that does not work in the “obvious” way, and the second part will describe a different way that does work.

Day 9: Freer — Free Monads

On day 5, I wrote about how to make a set monad — first build a sequence of instructions that describe how to build a Set, and then interpret that sequence of instructions to give a result, an actual Set.

Day 7: Haxl — The Reader Monad, When Reads Are Expensive

In the Reader monad, all you can do is query the environment by asking for the whole environment. If you only want a little bit of that environment, you can apply a function to the environment. For example, you might ask for the…

Day 10: Eff — Extensible Effects

Free monads let you take a data type that represents instructions, or (approximately the same) effects that you want to happen, and then have interpreters which understand how to make those effects actually happen.

Day 6: Conduit — Streamy Co-routines for Piping Together Computations

Lazy evaluation lets us compose two different computations without thinking too much about who is “in control”: we can generate primes lazily, and take the root of them lazily and evaluation alternates back and…