Monadish

January 18, 2016

This is a very informal introduction to monads using Java 8.

Java is not a great language for an introduction to monads, but it's the most widely readable by the audience, so it will do.

Seriously, this is going to be really tedious in Java. We're doing it for the familiarity. Try not to let it sour you on the underlying ideas.

We'll back our way into monad comprehension by starting with the implementation, and working in reverse through the laws, and toward the theory.

TL;DR

A generic data structure Foo<A> is* a monad when:

* Is a monad vs. has a monad

Since Java is an OO language, we can build the constructor and flatMap method right into the Foo class, and say that Foo is a monad.

In languages with ad-hoc polymorphism (e.g. Haskell, Scala), we tend pull these out into module functions that act on Foo instances, and say that Foo has a monad.

This is also possible in Java:

class FooMonad {
  public static <A> Foo<A> pure<A>(A a) {
    return new Foo<>(a);
  }
  public static <A,B> Foo<B> flatMap<A>(Foo<A> a, Function<A, Foo<B>> f) {
    // ...
  }
}

We'll use the first approach here, because it's a bit more readable for folks with an OO background.

What's in the box?

Let's start with a simple, if not very useful, data structure called Box:

class Box<A> {

  private final A value;

  public Box(A value) {
    this.value = value;
  }

}

A Box<A> just holds a value of type A. It doesn't even make the valuable visible to anyone. How selfish.

The shape of a monad

Let's make it a monad.

class Box<A> {

  private final A value;

  public Box(A value) {
    this.value = value;
  }

  public <B> Box<B> flatMap(Function<A,Box<B>> f) {
    return f.apply(value);
  }

}

We added flatMap. Yep, that's it. To be a monad, Box needs two things:

  1. A way to construct a Box<A> given an A
  2. A way to apply a function of type (A) -> Box<B> to a Box<A> to get a Box<B>

Because Box is so simple, it's hard to come up with compelling, practical examples of when we would need to apply a function of type (A) -> Box<B>, but bear with me -- later examples will do a better job of this.

Here's an example anyway:

new Box<Integer>(6).map((x) -> new Box<>(x * 7)));
// Box(42)

For now, assume that it's common to need to apply functions of this shape to data structures like Box.

50,000 watts of functor

You may have encountered mappable data structures in other languages. These are functors. It turns out that every monad is also a functor.

If you have both:

  1. A way to construct a Box<A> given an A
  2. A way to apply a function of type (A) -> Box<B> to a Box<A> to get a Box<B>

You can write a function map:

public <B> Box<B> map(Function<A,B> f) {
  return flatMap((x) -> new Box<>(f.apply(x)));
}

This generic implementation will work for any monad. If we want to, we can clean it up (and optimize it) by foregoing flatMap:

public <B> Box<B> map(Function<A,B> f) {
  return new Box<>(f.apply(value));
}

Now you can take a Box<A>, apply a function (A) -> B, and get a Box<B>.

Here's an example:

new Box<Integer>(6).map((x) -> x * 7);
// Box(42)

What else?

That's pretty much it. There's some other junk to learn, such as the monad laws, but that's about all there is to it.

The rest of your journey will be gaining familiarity with different common monads, and developing an intuition for how to put them to work.

This is dumb

Yeah, I agree. I wouldn't really use Box for anything. But it's a nice, clean way to show what flatMap looks like.

Think outside the Box

Let's look at some actually useful monads.

Call me Option

Option, also known as Maybe, is a collection of either zero or one elements. It has two implementations: None for when it's empty, and Some for when it contains an element.

Here's an implementation without any of them fancy monads:

interface Option<A> {
  public A getOrElse(A fallback);
}

An Option<A> might contain an A.

class Some<A> implements Option<A> {

  private final A value;

  public Some(A value) {
    this.value = value;
  }

  public A getOrElse(A y) {
    return this.value;
  }

  public String toString() {
    return "Some(" + value.toString() + ")";
  }

}

Some<A> is an Option<A> that contains an A.

class None<A> implements Option<A> {

  public A getOrElse(A fallback) {
    return fallback;
  }

  public String toString() {
    return "None";
  }

}

None<A> is an Option<A> that does not contain an A.

Now let's add flatMap implementations.

We'll also add map, but remember that it's not very interesting when we already have flatMap, because we can implement map using flatMap and a constructor.

interface Option<A> {

  // ...

  public <B> Option<B> map(Function<A,B> f);

  public <B> Option<B> flatMap(Function<A,Option<B>> f);

}

An Option<A> can be transformed into an Option<B> either by applying a function (A) -> B or by applying a function (A) -> Option<B>.

class Some<A> implements Option<A> {

  // ...

  public <B> Option<B> map(Function<A,B> f) {
    return new Some<>(f.apply(value));
  }

  public <B> Option<B> flatMap(Function<A,Option<B>> f) {
    return f.apply(value);
  }

}

Some<A> has an A, so we can apply f to it in map and flatMap to get a new Some<B>.

class None<A> implements Option<A> {

  // ...

  public <B> Option<B> map(Function<A,B> f) {
    return new None<>();
  }

  public <B> Option<B> flatMap(Function<A,Option<B>> f) {
    return new None<>();
  }

}

None<A> has no A to operate on, so map and flatMap just return None<B>s directly.

s/Exception/Option/

Let's parse some integers, and try to do stuff with them.

public static Option<Integer> parseInt(String value) {
  try {
    return new Some<>(Integer.parseInt(value));
  } catch (Exception e) {
    return new None<>();
  }
}
parseInt("6");
// Some(6)

parseInt("six");
// None

Option::map

parseInt("6").map((x) -> x * 7);
// Some(42)

parseInt("six").map((x) -> x * 7);
// None

Option::flatMap

parseInt("6").flatMap((x) -> parseInt("7").map((y) -> x * y));
// Some(42)

parseInt("6").flatMap((x) -> parseInt("seven").map((y) -> x * y));
// None

parseInt("six").flatMap((x) -> parseInt("7").map((y) -> x * y))
// None

parseInt("six").flatMap((x) -> parseInt("seven").map((y) -> x * y))
// None

None! What it is good for?

In the above examples, we can safely try to parse and multiply some numbers, but if any of them fail to parse, all we get back is a None, so we don't know much about what went wrong.

It would be nice to know whether the first number failed to parse, or the second number failed to parse, or both of them failed to parse. We need more information than simply None, and we need to collect that information as we go.

More like mehnad

It turns out we don't need flatMap to do this. That is to say: we don't need a monad. We need an applicative functor.

Like unto map

Functors give us map:

class Foo<A> {
  // ...
  public <B> Foo<B> map(Function<A,B> f);
}

Applicatives build on functors with a new function, ap:

class Foo<A> {
  // ...
  public <B> Foo<B> ap(Foo<Function<A,B>> f);
}

While a functor lets us apply a raw function to the value encapsulated by an instance of Foo, an applicative lets us apply a function that is itself encapsulated by an instance of Foo.

Validation

Validation, like Option, has two implementations. One contains a value in the case of some successful operation, and the other contains a list of errors in the case of zero or more failures.

Let's start without map and ap.

interface Validation<A> {

  public Option<A> getValue();

  public Option<List<String>> getErrors();

}

A Validation<A> might contain a value A, or it might contain a list of errors. In practice, this would be a list of instances of an Error class that we define. For simplicity we'll just use Strings.

class Success<A> implements Validation<A> {

  private final A value;

  public Success(A value) {
    this.value = value;
  }

  public Option<A> getValue() {
    return new Some<>(value);
  }

  public Option<List<String>> getErrors() {
    return new None<>();
  }

  public String toString() {
    return "Success(" + value.toString() + ")";
  }

}

A Success<A> contains a value A, and no errors.

class Failure<A> implements Validation<A> {

  private final List<String> errors;

  public Failure(String error) {
    this.errors = Arrays.asList(error);
  }

  public Failure(List<String> errors) {
    this.errors = errors;
  }

  public Option<A> getValue() {
    return new None<>();
  }

  public Option<List<String>> getErrors() {
    return new Some<>(errors);
  }

  public String toString() {
    return String.format("Failure(%s)", errors);
  }

}

A Failure<A> contains a list of errors, and no value A.

Now let's add map and ap.

interface Validation<A> {

  // ...

  public <B> Validation<B> map(Function<A,B> f);

  public <B> Validation<B> ap(Validation<Function<A,B>> f);

}

A Validation<A> can be transformed into a Validation<B> either by applying a function (A) -> B or by applying a function (A) -> Validation<B>.

class Success<A> implements Validation<A> {

  // ...

  public <B> Validation<B> map(Function<A,B> f) {
    return new Success<B>(f.apply(value));
  }

  public <B> Validation<B> ap(Validation<Function<A,B>> f) {
    Option<B> ob = f.getValue().map((g) -> g.apply(value));
    Option<Validation<B>> ovb = ob.map((b) -> new Success<>(b));
    return ovb.getOrElse(new Failure<>(f.getErrors().getOrElse(new ArrayList<String>())));
  }

}

Success::map returns a new Success, but Success:flatMap could fail, since f is itself a Validation.

class Failure<A> implements Validation<A> {

  // ...

  public <B> Validation<B> map(Function<A,B> f) {
    return new Failure<>(errors);
  }

  public <B> Validation<B> ap(Validation<Function<A,B>> f) {
    List<String> errors2 = new ArrayList<String>();
    errors2.addAll(errors);
    errors2.addAll(f.getErrors().getOrElse(new ArrayList<String>()));
    return new Failure<>(errors2);
  }

}

Doing anything with a Failure returns a new Failure, but since it includes a list of errors, we can add to that list when we encounter additional errors.

s/Exception/List<String>/

public static Validation<Integer> parseInt(String value) {
  try {
    return new Success<>(Integer.parseInt(value));
  } catch (Exception e) {
    return new Failure<>(String.format("could not parse \"%s\" as an integer", value));
  }
}
parseInt("6") = Success(6)

parseInt("six") = Failure([could not parse "six" as an integer])

Validation::map

parseInt("6").map((x) -> x * 7);
// Success(42)

parseInt("six").map((x) -> x * 7);
// Failure([could not parse "six" as an integer])

Validation::ap

parseInt("6").ap(parseInt("7").map((x) -> (y) -> x * y));
// Success(42)

parseInt("6").ap(parseInt("seven").map((x) -> (y) -> x * y));
// Failure([could not parse "seven" as an integer])

parseInt("six").ap(parseInt("7").map((x) -> (y) -> x * y));
// Failure([could not parse "six" as an integer])

parseInt("six").ap(parseInt("seven").map((x) -> (y) -> x * y));
// Failure([could not parse "six" as an integer, could not parse "seven" as an integer])

If you're not squinting yet

Let's look at the monadic approach to dependency injection.

Reader

class Reader<A,B> {

  private final Function<A,B> f;

  public Reader(Function<A,B> f) {
    this.f = f;
  }

  public B run(A x) {
    return f.apply(x);
  }
}

Reader is a wrapper around a function f. Think of it as an abstraction of a function.

class Reader<A,B> {

  // ...

  public <C> Reader<A,C> map(Function<B,C> g) {
    return new Reader<A,C>((x) -> g.apply(f.apply(x)));
  }

  public <C> Reader<A,C> flatMap(Function<B,Reader<A,C>> g) {
    return new Reader<A,C>((x) -> g.apply(f.apply(x)).f.apply(x));
  }

  public <C> Reader<A,C> andThen(Reader<A,C> r) {
    return flatMap((x) -> r);
  }
}

Reader lets us compose the wrapped function with other stuff to build more complex function abstractions.

Function abstraction

Consider a familiar-looking Database class that lets us get and set some data in a database:

class Database {

  private Map<Long, Double> balances = new HashMap<>(); // imaginary SQL table

  public Double getBalance(long accountId) {
    // imaginary SQL code here
    if (balances.containsKey(accountId)) {
      return balances.get(accountId);
    } else {
      return 0D;
    }
  }

  public Double setBalance(long accountId, double newBalance) {
    // imaginary SQL code here
    Double oldBalance = getBalance(accountId);
    balances.put(accountId, newBalance);
    return oldBalance;
  }

}

Let's also add some transaction methods that we'll use later:

class Database {

  // ...

  public long beginTransaction() {
    System.out.println("starting transaction");
    // imaginary SQL code here
    return 1L; // imaginary transaction id
  }

  public void commitTransaction(long transactionId) {
    System.out.println("committing transaction");
    // imaginary SQL code here
  }

  public void rollbackTransaction(long transactionId) {
    System.out.println("rolling back transaction");
    // imaginary SQL code here
  }

}

Now consider a use case in which we need to get data from the database, and then use that information to set some data in the database. This needs to happen in a single logical transaction to ensure consistency.

Normally we would need to do some state gymnastics to get the transaction right. We would make some global lock variable, or a ThreadLocal with a reference to a transaction. Nasty.

With Reader, we simply build up an abstraction of a single logical function that gets data, does something, then sets data, all as one operation.

class DatabaseReader<A> extends Reader<Database, A> {

  public DatabaseReader(Function<Database, A> f) {
    super(f);
  }

}

A DatabaseReader<A> is a Reader<Database, A>, but that's not all:

class DatabaseReader<A> extends Reader<Database, A> {

  // ...

  @Override
  public A run(Database db) {
    long transactionId = db.beginTransaction();
    try {
      A a = f.apply(db);
      db.commitTransaction(transactionId);
      return a;
    } catch (Exception e) {
      db.rollbackTransaction(transactionId);
      throw e;
    }
  }

}

When we run a database action, we want it to happen within the context of a transaction, so DatabaseReader has a customized run implementation that starts a transaction, runs the underlying database-dependent function, then commits (or rolls back) a transaction.

When composing DatabaseReaders together, we don't want to lose our custom run implementation, so we have a few more things to override -- any function in Reader that constructs a new Reader:

class DatabaseReader<A> extends Reader<Database, A> {

  // ...

  @Override
  public <B> Reader<Database,B> map(Function<A,B> g) {
    return new DatabaseReader<B>((x) -> g.apply(f.apply(x)));
  }

  @Override
  public <B> Reader<Database,B> flatMap(Function<A,Reader<Database,B>> g) {
    return new DatabaseReader<B>((x) -> g.apply(f.apply(x)).f.apply(x));
  }

}

Now we can use DatabaseReader to build up arbitrarily complex sequences of database actions, and when ready, run them all together in a single transaction.

Let's make a few useful database actions that we can use later.

class DatabaseReader<A> extends Reader<Database, A> {

  // ...

  public static DatabaseReader<Double> getBalance(long accountId) {
    return new DatabaseReader<>((db) -> db.getBalance(accountId));
  }

  public static DatabaseReader<Double> setBalance(long accountId, double balance) {
    return new DatabaseReader<>((db) -> db.setBalance(accountId, balance));
  }

  public static Reader<Database, Double> awardBonus(long accountId, double amount) {
    return DatabaseReader.getBalance(accountId).
      flatMap((x) -> DatabaseReader.setBalance(accountId, x + amount));
  }

}

Bonus, not bogus

Let's look at ReaderDemo. We'll start with some utility functions for formatting money.

public static String formatUSD(Double amount) {
  return "$" + String.format("%1$,.2f", amount);
}

public static double logBalance(double balance) {
  System.out.println("balance: " + formatUSD(balance));
  return balance;
}

Now let's put together a database action.

long accountId = 1;

Reader<Database, Double> readerDemo =
  DatabaseReader.getBalance(accountId).
    map(ReaderDemo::logBalance).
    andThen(DatabaseReader.setBalance(accountId, 100.0)).
    andThen(DatabaseReader.getBalance(accountId)).
    map(ReaderDemo::logBalance).
    andThen(DatabaseReader.awardBonus(accountId, 10.0)).
    andThen(DatabaseReader.getBalance(accountId)).
    map(ReaderDemo::logBalance);

readerDemo is a DatabaseReader<Double>, which is a Reader<Database, Double>. This means it's a big abstraction of a bunch of functions that need a Database to run, and when that happens, it finally returns a Double.

So it's an abstraction. How do we make it concrete? How do we make all of these Database-dependent functions run, and run within a transaction? We use DatabaseReader::run:

Database db = new Database();

readerDemo.run(db);
// starting transaction
// balance: $0.00
// balance: $100.00
// balance: $110.00
// committing transaction

Deimos

Make sure you have Java 8 installed:

$ java -version
openjdk version "1.8.0_60"

Then fire up sbt and run the demos:

$ ./sbt "run-main BoxDemo"
box(6) map multiply(7) = Box(42)
box(6) flatMap multiplyAndBox(7) = Box(42)
$ ./sbt "run-main OptionDemo"
parseInt("6") = Some(6)
parseInt("6").map((x) -> x * 7) = Some(42)
parseInt("6").flatMap((x) -> parseInt("7").map((y) -> x * y)) = Some(42)
parseInt("six") = None
parseInt("six").map((x) -> x * 7) = None
parseInt("6").flatMap((x) -> parseInt("seven").map((y) -> x * y)) = None
parseInt("six").flatMap((x) -> parseInt("7").map((y) -> x * y)) = None
parseInt("six").flatMap((x) -> parseInt("seven").map((y) -> x * y)) = None
$ ./sbt "run-main ValidationDemo 6 7"
parseInt("6") = Success(6)
parseInt("6").map((x) -> x * 7) = Success(42)
parseInt("6").ap(parseInt("7").map((x) -> (y) -> x * y)) = Success(42)
parseInt("six") = Failure([could not parse "six" as an integer])
parseInt("six").map((x) -> x * 7) = Failure([could not parse "six" as an integer])
parseInt("6").ap(parseInt("seven").map((x) -> (y) -> x * y)) =
  Failure([could not parse "seven" as an integer])
parseInt("six").ap(parseInt("7").map((x) -> (y) -> x * y)) =
  Failure([could not parse "six" as an integer])
parseInt("six").ap(parseInt("seven").map((x) -> (y) -> x * y)) =
  Failure([could not parse "six" as an integer, could not parse "seven" as an integer])
$ ./sbt "run-main ReaderDemo"
starting transaction
balance: $0.00
balance: $100.00
balance: $110.00
committing transaction