Anaphora and Lambdas

Eucalypt doesn't have a lambda syntax in itself and prefers to encourage other approaches in most cases where you would use a lambda.

  • named functions
  • function values from composites, combinators, partials
  • anaphoric expressions, blocks or strings

However, through the combination of two Eucalypt features, namely block anaphora and generalised lookup, you can express arbitrary lambdas as we'll see below.

The various alternatives are considered one by one.

Named functions

Very likely, the clearest way to square a list of numbers is to map an explicitly named square function across it.

square(x): x * x
squares: [1, 2, 3] map(square) //=> [1, 4, 9]

The drawbacks of this are: - polluting a namespace with a name that is need only once - arguably, a slightly tedious verbosity

The first can be dealt with as follows:

squares: { square(x): x * x }.([1, 2, 3] map(square)) //=> [1, 4, 9]

This exploits a feature called generalised lookup.

Why "generalised lookup"? In the simple case below, the dot signifies the "lookup" of key a in the block preceding the dot:

x: { a: 3 b: 4 }.a //=> 3

We can generalise this by allowing arbitrary expressions in place of the a by evaluating the expression after the dot in the context of the namespace introduced by the block to the left.

x: { a: 3 b: 4 }.(a + b) //=> 7

It works for any expression after the dot:

x: { a: 3 b: 4 }.[a, b] //=> [3, 4]
y: { a: 3 b: 4 }.{ c: a + b } //=> { c: 7 }
z: { a: 3 b: 4 }."{a} and {b}" //=> "3 and 4"


This is very effective for short and simple expressions but quickly gets very complicated and hard to understand if you use it too much. Nested or iterated generalised lookups are usually a bad idea.

In the squares example above, generalised lookup is used to restrict the scope in which square is visible right down to the only expression which needs it.

However in the case of a simple expression like the squaring example, a neater approach is to use expression anaphora.

Expression Anaphora

Any expression can become a function by referring to implicit parameters known as expression anaphora.

These parameters are called _0, _1 _2, and so on. There is also an unnumbered anaphorus, _, which we'll come back to.

Just referring to these parameters is enough to turn an expression into a lambda.

So an expression that refers _0 and _1 actually defines a function accepting two parameters:

xs: zip-with(f, [1, 2, 3], [1, 2, 3]) //=> [3, 6, 9]

# or more succinctly
xs: zip-with(_0 + 2 * _1, [1, 2, 3], [1, 2, 3]) //=> [3, 6, 9]


Again, anaphora intended for use in simple cases where they are readable and readily understood. The scope of the implicit parameters is not easy to work out in complicated contexts. (It does not extend past catenation or commas in lists or function application tuples.) Anaphoric expressions are not, and not intended to be, a fully general lambda syntax. Unlike explicit lambda constructions, you cannot nest anaphoric expressions.

squares: [1, 2, 3] map(_0 * _0) //=> [1, 4, 9]

In cases where the position of the anaphora in the expression matches the parameter positions in the function call, you can omit the numbers. So, for instance, _0 + _1 can simply be written _ + _, and _0 * _1 + x * _2 can be written _ * _ + x * _.

Each _ represents a different implicit parameter, which is why we had to write _0 * _0 in our squares example - it was important that the same parameter was reference twice.

Sometime you need explicit parentheses to clarify the scope of expression anaphora:

block: { a: 1 b: 2 }

x: block (_.a) //=> 1
y: block lookup(:a) //=> 1
# BUT NOT: block _.a


Even more conciseness is on offer in some cases where the anaphora can be entirely omitted. Eucalypt will automatically insert anaphora when it detects gaps in an expression based on its knowledge of an operator's type.

So it will automatically read (1 +) as (1 + _), for example, defining a function of one parameter. Or (*) as (_ * _), defining a function of two parameters. The parentheses may not even be necessary to delimit the expression:

x: foldl(+, 0, [1, 2, 3]) = 6

Again, use of sections is recommended only for short expressions or where the intention is obvious. This level of tersity can lead to baffling code if abused.

Block Anaphora

Expression anaphora are scoped by an expression which is roughly defined as something within parentheses or something which can be the right hand side of a declaration.

Sometimes however you would like to define a block-valued function. Imagine you wanted a two-parameter function which placed the parameters in a block with keys x and y:

f(x, y): {x: x y: y }

An attempt to define this using expression anaphora would fail. This defines a block with two identity functions:

f: {x: _ y: _ }

Instead, you can use block anaphora which are scoped by the block that contains them.

The block anaphora are named •0, •1, •2 with a special unnumbered anaphor , playing the same role as _ does for expression anaphora.

is the BULLET character (usually Option-8 on a Mac but you may find other convenient ways to type it). The slightly awkward character is chosen firstly because it looks like a hole and therefore makes sense as a placeholder, and secondly to discourage overuse of the feature...

The following defines the function we want

f: { x: • y: • }

...and can, of course, be used

x: [[1, 2], [3, 4], [5, 6]] map({ x: • y: • } uncurry)


Astute observers may realise that by combining generalised lookup and block anaphora you end up with something that's not a million miles away from a lambda syntax:

f: { x: • y: • }.(x + y)

Indeed this does allow declaration of anonymous functions with named parameters and can occasionally be useful but it still falls short of a fully general lambda construction because it cannot (at least for now) be nested.

String Anaphora

Analogously, Eucalypt's string interpolation syntax allows the use of anaphora {0}, {1}, {2} and the unnumbered {} to define functions which return strings.

x: [1, 2, 3] map("#{}") //=> ["#1", "#2", "#3"]


There are lots of ways to define functions but the clearest is just defining them with names using function declarations and for anything even slightly complicated this should be the default. The only things you should be tempted to define on the spot are things that are simple enough that the various species of anaphora can handle them neatly.