When I first learned about the Julia programming language, there were a few things that gave me the "wat" moments. One of those surprises involves both the naming and meaning of functions.
Interestingly, my naive question triggered over 200 follow-up posts in the Julia Discourse forum. 200! That's one of my best records for motivating fellow developers! 😄
Let's first take a look at a very simple example.
Suppose that I have a
CalendarApp
module that contains the following code:struct Meeting
subject::String
start_time::DateTime
end_time::DateTime
end
Then, I want to create a function that calculates the length of a meeting. Super simple, right? Let's go for it:
length(m::Meeting) = Hour(m.end_time - m.start_time)
When I code, I like a REPL-based development workflow so I can test new code quickly:
julia> covid_meeting = Meeting("COVID Response Committee",
DateTime(2020, 6, 14, 8, 0, 0),
DateTime(2020, 6, 14, 10, 0, 0))
Meeting("COVID Response Committee", 2020-06-14T08:00:00, 2020-06-14T10:00:00)
julia> println(length(covid_meeting))
2 hours
So far so good! Now, try to use
length
function to determine the length of an array.julia> length([1,2,3])
ERROR: MethodError: no method matching length(::Array{Int64,1})
You may have intended to import Base.length
Closest candidates are:
length(::Meeting) at REPL[3]:1
Wat! That's right. Here we get the exact "wat" moment. What happened to the regular
length
function? The answer is quite simple. There are actually two
length
functions around. One of them is defined in Base
module for which everyone is familiar with, and the other one is just defined above.Here's my own
length
function:julia> length
length (generic function with 1 method)
Now, restart the REPL to clear things up and try again:
julia> length([1,2,3])
3
julia> length
length (generic function with 81 methods)
Now, I am able to access the original
length
again. You may also notice that this length
function is attached to 81 methods.So, how did that happen? It seems that I might have hidden the original
length
function by defining our own length
function earlier. Out of curiosity, I can define my own function again:julia> struct Meeting
subject::String
start_time::DateTime
end_time::DateTime
end
julia> length(m::Meeting) = Hour(m.end_time - m.start_time)
ERROR: error in method definition: function Base.length must be explicitly imported to be extended
Man, now it's doing the exact opposite! It doesn't even let me define
length
function anymore! This is the second "wat" moment for the same problem.
It might worth a quick discussion here about why I did what I did. And, why I thought I was right.
First of all, I came from an object-oriented programming background. To be more precise, I had many years of experience developing in the Java language.
How would the same problem look in OOP? Well, in the object-oriented world, there is probably some kind of
Array
class that defines a length
method. In this case, I would also define a Meeting
class with a length
method. For instance:my_array.length(); // invokes the length method defined in Array class
my_meeting.length(); // invokes the length method defined in Meeting class
When I call the method, there is no ambiguity. These are just two different methods from two different classes.
But wait... Didn't I just do the same thing in Julia? If I look at the signature of my
length
function, it accepts an argument of data type Meeting
. So, why couldn't Julia just call my function when I pass a Meeting
object, and call the regular length
function when I pass an array?Here is my primary misconception.
Multiple dispatch only works for a single function. What I have done above actually introduced a second
length
function, and that function is attached to a single method.More precisely, the two
length
functions are defined in their own modules. Let me prefix with their respective namespaces and the number of methods:Base.length # 81 methods
CalendarApp.length # 1 method
As I want multiple dispatch to kick in, I just need to make sure that I define a new method for the
Base.length
function rather than defining my own function. This is also called extending a function. There are two ways to archive that.Option #1 (preferred): prefix the function name with the module name.
Base.length(m::Meeting) = Hour(m.end_time - m.start_time)
Option #2: import the length function before defining it.
import Base: length
length(m::Meeting) = Hour(m.end_time - m.start_time)
Now, let's start a new REPL and try again:
julia> struct Meeting
subject::String
start_time::DateTime
end_time::DateTime
end
julia> Base.length(m::Meeting) = Hour(m.end_time - m.start_time)
julia> length
length (generic function with 82 methods)
Alright, the
length
function now has 82 methods attached.Let's confirm its functionality.
julia> covid_meeting = Meeting("COVID Response Committee",
DateTime(2020, 6, 14, 8, 0, 0),
DateTime(2020, 6, 14, 10, 0, 0))
Meeting("COVID Response Committee", 2020-06-14T08:00:00, 2020-06-14T10:00:00)
julia> length(covid_meeting)
2 hours
julia> length([1,2,3])
3
Voila! Problem solved!
There is already a simple solution once I understand how multiple dispatch works in Julia.
So, how did I trigger 200+ follow-up posts in Discourse?
The main controversy is why I have to be explicit about extending
Base.length
. Since Base.length
has a name of length
, and CalendarApp.length
has a name of length
, why wouldn't Julia just automatically merge them?The whole thread of discussion in Discourse goes about how it can be more convenient and less confusing for new Julia users when the functions can be merged automatically. I will now argue (against my original opinion in the Discourse thread) that it is a bad idea to do so.
Here is the main reason: just because two functions have the same name doesn't imply that they mean the same thing.
Every function is designed to have a specific meaning. In English, the meaning of
length
function is pretty much aligned with what one commonly know what a length is. To be clear, I will just show the first definition from Dictionary.com:
Length (Noun): the longest extent of anything as measured from end to end.
So, the length concept refers to a measurement. As with any kind of measurement, it means that I should expect it to return a numerical value.
Hence, when anyone calls the
length
function, a number is expected to be returned.This is literally an implicit contract.
Enforcing the same meaning for all
length
methods turns out to be a very useful thing. Right off the bat, I can display a graphical user interface that shows a bar that represents a measurement. The same component works regardless of whether the object is an array, a String
, or a Meeting
! This is also the main reason why Julia packages interoperate so well with each other!
As long as there is consistent names and meanings, we can build very powerful abstraction and interfaces. Then, everything just works with each other in harmony.
You don't buy it yet? Just take a look at the various types of Julia array implementations. These arrays can be used anywhere a regular array is accepted.
Now, what happens if I ignore the implicit contract and define the length of a meeting to be a string? For instance:
function Base.length(m::Meeting)
if m.end_time - m.start_time > Hour(1)
return "Long"
else
return "Short"
end
end
Well, it's probably fine because
Meeting
is my own data type. However, it also means that I should not let anyone else use
Meeting
. Why? That's because another developer will probably get very confused to experience my length
function returning a string rather than a number, and that could cause serious problems.Remember the GUI component I talked about earlier? It's going to be so broken.
Not keeping a consistent meaning (implicit contract) for a function is a recipe for failure. It severely limits the reusability of functions.
If I insist that my
length
function should return a string, then I really have two options.First, I can define my own function and not extend from
Base.length
. Second, I could choose a different name for the function.In the first scenario, I would be able to access both
length
functions. The caveat is that I will have to use Base.length
and CalendarApp.length
instead of the short form.This is needed to remove the ambiguity about which function I'm referring to.
The best practice, however, is to avoid naming functions with the same name that has already been used in Base. Why?
Because the Base module is standard library that everyone uses, it's probably not a good idea to define a function with the same name but different meaning.
Now, suppose that I am using a different module rather than Base. As an example, I'm going to pick on one of my favorite packages Distributions.jl.
A typical Julia user would do the following:
using Distributions
I do that, too, when I need to use it interactively. However, if I need to use it in my app, then I would want to import only the functions that I need into my namespace. For example, let's say I want to calculate the mean and mode of some randomly-generated data, I would do this:
using Distributions: mean, mode
This is actually quite important!
First, by bringing only known functions into my namespace, it reduces the chance of function name collision. Just take a look at the huge number of exported names by Distributions.jl.
Second, I'm making my code future-proof. Let's say I have already defined a function named
dist
in my module. My code will still work even if Distribution.jl happens to define and export their own dist
in a future version. So, I don't need to worry naming conflict because I have only imported mean
and mode
into my namespace.Naming things properly is super important. Besides choosing the right word, it is also important to mean what you mean.
Over the years, I have developed a habit to ensure writing code that means what I mean. And, it's actually super simple.
Just write documentations.
In Julia, I would write a doc string for every function at the same time that I code that function. Sometimes I change the function name to match my doc string. At other times, I change the doc string to match my function name.
It is quite amazing how effective this can be. I encourage you to give that a try today!
Thank you for reading.
P.S. For more tips in writing good code in Julia, consider picking up my book Hands-on Design Patterns and Best Practices with Julia.
Lead image by Romain Vignes on Unsplash
Previously published on: https://ahsmart.com/pub/the-meaning-of-functions/