That’s false for closures (or unnamed/inline) functions with context because their type is unique and so you just can’t write their type and that’s not a lang’s fault - that’s logically correct side-effect by-design.
To me this is an argument for why Go should not add type inference to function/method declarations. Go is like Rust (I guess, I haven’t used Rust) - type inference works for declaring a variable (or const) and generic type parameters but not for type declarations, methods, functions, etc. I was in the “more inference is always better” camp but now I’m thinking Go has the perfect level of inference. Except for function literals/lambdas. I really want go to infer the argument and return types when I’m passing a function literal/lambda to a function.
The thing about Rust’s type inference that seems wild to anyone who hasn’t seen Hindley-Milner/ML style type systems before is that it’s “bidirectional” (in quotes because that’s not a proper type theory term as far as I know). The type of the left-side of an assignment can determine the type (and behavior!) of the right side. For instance, this is ambiguous:
let foo = [("a", 1), ("b", 2)].into_iter().collect();
The expression creates an iterator over the (letter, number) pairs, and collect() stores the elements in a newly created container. But which container type? Here are two valid variants:
let foo: Vec<_> = [("a", 1), ("b", 2)].into_iter().collect();
This creates a vector with items ("a", 1) and ("b", 2).
let foo: HashMap<_, _> = [("a", 1), ("b", 2)].into_iter().collect();
This creates a mapping where "a" and "b" are keys, and 1 and 2 are the corresponding values.
Playground link in case you’d like to mess with this concept: https://play.rust-lang.org/?version=stable&mode=debug&edition=2021&gist=76f999f4db600415643b0c58c19c69b7
I can’t speak for OCaml, but type inference provides a lot of benefit in Rust. I already have too many keystrokes as it is, and forcing me to be explicit about everything would just add to the stress of using a keyboard.
I agree that types should be explicit at API boundaries. That’s precisely where you want to catch misuse.
As for the point about inference making code harder to read: I suppose that’s true if you spend a lot of time reading code outside of your editor where you also must know what the types are. But that just sounds like a bad workflow in general. Why are you avoiding using a better tool for the job? Modern code review tools like Github even support LSP-like features to solve this problem; and if your language isn’t supported… just pull the feature branch to review it.
It’s really weird to me to base any decisions around how much typing you have to do.
Typing is such a small part of programming I really don’t get it.
stress of using a keyboard
Can you elaborate?
Readability and maintainability are core imo.
It’s really weird to me to base any decisions around how much typing you have to do. Typing is such a small part of programming I really don’t get it.
Typing is a huge part of programming. Have you heard of RSI? People invest hundreds (sometimes thousands) of dollars in ergonomic keyboards just to overcome RSI pain. If you’re younger than 30 you might not be impacted by this, but many people who have been typing every day for over a decade are realizing it’s not sustainable without proper ergonomics.
Readability and maintainability are core imo.
I don’t think you sacrifice these by having local type inference. It’s never been an obstacle for me.
He explicitly states that its not that bad in Rust because all functions must have type annotations. Its only a problem if your functions are huge (they shouldn’t). I think thats the correct way to go. Local variables can be inferred but anything else should be annotated.
Modern code review tools like Github even support LSP-like features to solve this problem; and if your language isn’t supported… just pull the feature branch to review it.
But now your requiring more tools and effort on the reviewer over, just reading the code.
But now your requiring more tools and effort on the reviewer over, just reading the code.
This should be completely negligible if you are writing code in the same code base.
I was already assuming I was working on the same codebase. I am not going to stash my work, checkout the branch and wait for the LSP to start up (if it’s working) just to confirm that your types aren’t doing anything weird. I’d rather just have them annotated correctly in the first place and just read the PR and trust the CI.
I prefer type inference. It’s extra clutter that can often be abstracted away with good variable and method names. If it quacks the way I need it then that’s one less thing I need to hold context of in my head.
You should read the article, because it’s pretty much a direct rebuttal with justifications to this exact argument. You’ve really just re-stated what the article disputes.
Which isn’t to say you’re wrong, I’d just be interested in your response to the arguments.
My response to the article is that you’re sacrificing gains in language because some people use outdated tools. Code has more context than what is just written. Many times you can’t see things in the code unless you dig in, for example responses from a database or key value store, or literally any external api. Type inference in languages that have bad IDE support leads to a bad experience, hence the author’s views on ocaml. But in a language like Kotlin it’s absolutely wonderful. If needed you can provide context, but otherwise the types are always there, you can view them easily if you’re using a decent IDE, and type inference makes the code much more readable in the long run. I would say that a majority of the time, you do not care about the types in any application. You care about the data flow, so having a type system that protects you from mismatched types is much more important that requiring types to be specified.
Maybe I’m missing something:
Does type inference provide a practical benefit to you beyond saving you some keystrokes?
What tools do you use for code review? Do you do them in GitHub/gitlab/Bitbucket or are you pulling every code review directly into your IDE? How frequently do you do code reviews?
The article doesn’t make a persuasive case at all. It immediately backs off by acknowledging that 99% of type inference is fine, because it’s really only complaining about function signature inference, which is an extreme case that only a few obscure ML variants like Ocaml and F# support.
It’s like saying all american movies are terrible, and then clarifying that you’ve only seen White Chicks
I don’t want to infer types from my code. I’d rather infer the code from the types. Types are the spec, they are small and low in expressiveness, code is big and has infinitely more degrees of freedom than types. The bug surface area is smaller with types.
So it makes sense to use the types (simple, terse, constrained) to generate the code (big, unconstrained, longer to write, bug-prone). Inferring types from code is like building a complex machine without plans, and then using an X-ray diffractometer to extract plans from the physical object.
This is the argument.
This comes back to a perennially forgotten/rediscovered fundamental truth about coding: It is much easier to write code than read code
This is immediately followed by the next part that in any sufficiently large organization, you spend more time reading code than writing code.
Put it all together? Fractional second gains in writing that have meaningful expenses when it comes to reading aren’t worth it once you’re operating at any kind of scale.
If you and your buddy are making little hobby projects. If you have a 3 person dev team. If you’re writing your own utility for personal use… I wouldn’t expect these features to become evident at that scale.
Again, it isn’t saying that it’s something intrinsically wrong, it’s just that there is a trade off and if you really think about it, under most professional environments it’s a net negative effect on efficiency.
In Rust and Haskell you have to at least annotate the parameter types and return type of functions.
In OCaml type inference is a lot more powerful: you don’t have to annotate function signatures
Actually, Haskell and OCaml have this in common. Only Rust requires parameter types of the three.
I could do
add2 a b = a + b
main = do
putStrLn $ "5 + 3 = " ++ (show $ add2 5 3)
And that would work