Functions are common in most programming languages. Some languages also have methods, which are similar to functions. Their biggest difference is that we call methods with a special “method call” syntax. Whereas function call syntax often looks like f(x, y)
, method call syntax often looks like x.f(y)
.
Functions
Here’s a Rust program in which we define a rectangle type and a function that scales a rectangle’s dimensions by some factor.
struct Rect {
width: u32,
height: u32,
}
fn scale(rect: Rect, by: u32) -> Rect {
Rect {
width: rect.width * by,
height: rect.height * by,
}
}
let r1 = Rect { width: 3, height: 4 };
let r2 = scale(r1, 5);
assert_eq!(r2.width, 15);
assert_eq!(r2.height, 20);
Suppose we now want to perform a chain of rectangle manipulation operations, one after the other. We might do something like this:
let r2 = scale(increase_width(reflect(decrease_height(r1, 4)), 7), 5);
This is not very easy to read, because:
- This single line of code is very long.
- Functions that are called last appear first in the program text, and vice versa.
We can somewhat fix the first problem by splitting the code into many lines, but it’s still not great.
let r2 = scale(
increase_width(
reflect(
decrease_height(r1, 4),
),
7,
),
5,
);
We can also kind of fix both problems by introducing many intermediary variables, but then we have to come up with awkward names for the variables:
let shorter = decrease_height(r1, 4);
let reflected = reflect(shorter);
let wider = increase_width(reflected, 7);
let r2 = scale(wider, 5);
Methods
To fix both problems, we can change the definition of the function to be a method instead. We must choose a type that this method will be “on”, in this case Rect
. Then, once we define the method, we call it with a special method call syntax: instead of e.g. scale(rect, 5)
we do rect.scale(5)
.
impl Rect {
fn scale(self, by: u32) -> Rect {
Rect {
width: self.width * by,
height: self.height * by,
}
}
}
let r1 = Rect { width: 3, height: 4 };
// method call syntax
let r2 = r1.scale(5);
assert_eq!(r2.width, 15);
assert_eq!(r2.height, 20);
Now, using methods, the order that the calls occur matches the order they appear in the program. It’s also easier to split the program across multiple lines for legibility:
let r2 = r1
.decrease_height(4)
.reflect()
.increase_width(7)
.scale(5);
Limitations of defining methods
However, there are often limitations on where we can define methods. Many languages that support methods only allow defining methods “nearby” the definition of the type itself. So we often cannot, for instance, define a method on a type in a separate file from where the type is defined.
So suppose our Rect
library was written by someone else and we’re importing it for our own use. We’d like to define and use a shrink
operation, kind of like the opposite of scale
. The Rect
library doesn’t define a shrink
method, so we define it ourselves. But we have to define it as a function, not a method.
Now, when using our function, we must interrupt the flow of the chain of methods calls from before:
let r2 =
shrink(
r1
.decrease_height(4)
.reflect(),
2,
)
.increase_width(7)
.scale(5);
This mix of styles hurts readability.
Monkey patching
To counteract this, some languages, like Ruby, allow anyone to define any new method for any type. This is called monkey patching.
However, this too can cause issues. Here’s one plausible example:
- Suppose I define my own
shrink
method forRect
. - Later, I update my version of the
Rect
library, and the new version comes with their own version ofshrink
, which is different from mine. - A new developer comes along, reads the public docs for
shrink
, and usesshrink
in their code, expecting it to behave as publicly documented. - The code actually calls my version of
shrink
, since my monkey-patch now overrides the existing definition onRect
. - The developer is confused as to why their code is broken.
As another example, try going on StackOverflow and searching for ruby-tagged questions. Some common methods like blank?
and present?
actually only work when using the Ruby on Rails library. This is because Rails defines these methods as monkey patches on common Ruby classes.
To combat these issues, Ruby introduced refinements, which is a way to restrict the scope of monkey patching.
Wrapper types
Another alternative is to define a new wrapper type around the real type, then define methods on the wrapper type. This is what jQuery does:
- Given a native DOM value, or CSS selector for such values, the
$
function returns a jQuery value that wraps those values. - Then, methods on that jQuery value themselves return jQuery values.
This allows for chaining:
$("button")
.css("color", "red")
.find(".icon")
.parent()
.css("color", "green")
.slideUp(2000);
However, it can be inconvenient to have to wrap the actual value. In our Rect
example, we’d have to:
- Create a new
WrappedRect
type, that contains aRect
. - Define our own methods on it, like
shrink
. - Define “forwarder” methods on it (
scale
,reflect
, etc) that just call the underlying methods on theRect
.
Unified function call syntax
Let’s take a step back and remember what we really want.
We’ve seen how using the method call syntax can improve readability of long chains of operations. This is because:
- The data flows in the order that we read the code in.
- The code is easy to split across many lines.
To use the method call syntax, we must define operations as methods, not functions. And so we’ve investigated ways to define our own custom operations as methods.
However, what if we allowed using the method call syntax for regular functions? Let us define the method call syntax rect.scale(5)
to be exactly equivalent to as if we had written the call like a regular function call, scale(rect, 5)
.
We can then get rid of the method versus function distinction entirely, and define all functions as regular functions.
This idea is called unified function call syntax (UFCS).
// defined like a function
fn scale(rect: Rect, by: u32) -> Rect {
Rect {
width: rect.width * by,
height: rect.height * by,
}
}
let r1 = Rect { width: 3, height: 4 };
// can call like a function...
let r2 = scale(r1, 5);
// ...or like a method.
let r3 = r1.scale(5);
With UFCS, the .
acts a bit like the pipe operator from functional programming.
Now we can choose to use the .
syntax with our own functions or library defined functions. We can choose to use the regular call syntax as well. The decision is no longer made for us based on whether we defined the operation as a “method” or a “function”. Rather, it is up to the caller to decide which call syntax makes the code more legible.
Scoping considerations
With methods, we can treat types as a namespace for their methods. When we call a method on a value of some type, we look up the type of the value, and then find the method with that name defined on that type.
With UFCS, however, because we only have regular functions not defined “on” types, we can’t look up methods like this anymore.
There are a few things we could do instead.
- We could require explicitly importing every function. This can get tedious.
- We could allow functions defined in the same file as the type to be implicitly imported when the type is imported. But, this may get confusing if we then call those functions with the regular function call syntax. We might expect functions to only be in scope on types via the method call syntax, as in existing languages.
Additionally, what happens if we have two different types, each with identically named methods? In languages with proper methods, again, since the methods are “on” the types themselves, this is not an issue, but it may be an issue here.
A possible solution would be to allow a form of ad-hoc polymorphism. This allows many functions to exist with the same name, as long as they have different types. Then the compiler could select the appropriate function to call based on the types of the function arguments.