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I love typing. But python's type annotation is absolute garbage. The fact that you need to import types should tell you what a load of shit it is. All files now have type imports. Yuck.

In addition, the only way type annotations are effective is if you use an editor that can parse types. Yuck.

Lastly, it is far too easy to create complex types with questionable value all over your code. Any time a developer wants to unravel a pre-existing complex type, it feels like working with C++. It's utter garbage.

>Lastly, it is far too easy to create complex types with questionable value all over your code. Any time a developer wants to unravel a pre-existing complex type, it feels like working with C++. It's utter garbage.

No. Having types is always better than not. If you have a complex functionality, it is going to have a complex type. But now you KNOW its complex and not have to unravel its complexity for the 5th time this month.

I had to write something like this recently:

```

pub SearchInfo {

    matches: Arc<HashMap<PathBuf, Vec<(usize, (usize, usize), String)>>>

}

```

This is complex, yes, but just by reading the type and names given to it:

1. `Arc`. So that means it can be safely shared across thread.

2. `HashMap` from `PathBuf` to `X`. So I am probably mapping file/folders to X.

3. `Vec<(usize, (usize, usize), String)>`. So the first `usize` denotes the line number. `(usize,usize)` denotes the start and end characters and the `String` is the whole line itself!

Just imagine unraveling this whole crap if its all simply a JavaScript `Object`.

I'd convert that last tuple to struct, unlike the rest of the type it's undecipherable without some kind of documentation.

It would be probably better if you haven't used naked usize, but wrapped it into a new type. When I find types get complex, I introduce type aliases or structs. That X in your signature likely deserves a name.

You can (and should) use mypy as part of your pipeline if you use type annotations, and that verifies that your types are correct without needing to use a special editor.

That doesn't work when many libraries don't use type annotations.

> You can (and should) use mypy as part of your pipeline if you use type annotations, and that verifies that your types are correct without needing to use a special editor.

As software engineers, if you are relying on CI to verify language features, you are going backwards in time.

It's not ci, it's part of your (local) build.

Not in my experience. If it's in your local build, it also needs to be in CI. Otherwise mistakes can easily slip through.

The point is it can be both places: locally during hacking and in CI to prevent accidentally pushing broken builds.

Isn't that what I just said?

Also mypy is super easy to use. You just run it on your repo root and it automatically checks everything. It's perfectly well-suited to CLI based dev workflows.

What type imports are you talking about?

https://peps.python.org/pep-0585/ has been implemented in Python 3.9.

Type annotations are not comparable to unit tests at all. Unit tests verifies correctness of the behavior, not just the types. E.g. if you have a mathematical function like min(), unit tests can verify it return the smallest of the inputs. Type annotations can at best verify that it returns a value of the same type as the input, but not if it is the smallest, largest or something random.

Type annotations are great for documentation and as a basic sanity test. They are especially useful with tools like code analysis or refactoring tools. But types are is no way a substitute for unit tests.

It tests at compile time that some function f takes A and returns B. That covers 99% of all possible input/output which you technically have to do in an untyped language. How do you make sure your function that takes an `any` doesn't crash and burn or silently sneak through and write null to the database?

> It tests at compile time that some function f takes A and returns B. That covers 99% of all possible input/output which you technically have to do in an untyped language.

Sorry, I don't understand what you are saying here. By A and B are you referring to the correct output given an input, or just to the expected data type? Because there is a big difference, as with the `min()` example.

A and B refers to the expected data type, yes.

So proving that `min(number, number)` returns a number is 99% as good as a unit test which shows that it returns the smallest number?

yes because the set of possible inputs for A -> C is basically infinite. But min(A,B)=C is only 2^64^2. Why shouldn't you test for string, object, object of object, object with a certain kind of shape, or Number class as opposed to number primitive? How can you know it will or won't work from a unit test perspective?

>inb4 just document it

that is what types are for

But the purpose of unit tests is to show that the code under test is correct, i.e. that min() return the smallest input, not just a random value of the same type. Static typing cannot do that, so it is in no way a substitute for unit tests.

Static typing is a useful tool, just not a substitute for any unit tests. The risk of static typing is when it becomes a goal in itself and you start thinking correctness means the program satisfies the type checker.

One possible answer is that you make that a feature: the database can contain null, and it means something. In some cases you will trade one problem for another, but the economics of the tradeoff in overall productivity can be favorable.

That very much depends on the type system you use. With (for example) refinement types and dependent types you can prove your code correct with zero tests needed. Examples are F*, Idris, Agda, Coq etc.

Prove the code is correct per the design, it doesn’t eliminate the possibility of design errors which can still benefit from tests (or QuickCheck like tools) to ensure that what you design does what you think it does … a critical component given how rarely you see these languages used to actually build large applications in the wild.

The key difference is that with proven correct code you actually have a formal spec you can prove properties about. Without proven correct code you don’t even have a formal spec. Just a bunch of random tests (if you are lucky) that may or may not match your informal spec.

And the argument that if you can’t prove your design correct then there is no point proving your code correct is a strange one. That’s like saying that there is no point writing tests because you can’t prove your design correct or guarantee that all tests needed will be written. Ehhhh nope. I have written and generated more than 9000 tests for a very large scale C++ applications that are used by large corporations around the world. And I haven’t had a bug in production for 5+ years. However I of course can’t prove that those tests cover everything or that my design is correct. But that doesn’t mean it isn’t worth doing.

Yeah, I feel way too many people mistake "we can't cover 100% of everything" with "it's not worth tightening the bolts". Strange conflation but a very common one indeed.

All well-formed code is always a correct version of itself (Curry-Howard correspondence). It's just that sometimes you thought it was a correct version of something else and turn out to be wrong about that.

Since dependent type systems are just another kind of code, this is still true.

  a * sin(x) + b * cos (-x)

should have been

  a * sin(x) - b * cos (x)

type isn't worth a damn here.

In a lot of situations you have related values of exactly the same type: floats, strings, integers, Widget objects, which get mixed up.

A warning about variable shadowing or unused variable can be worth more than a type diagnostic. E.g. suppose

  a * sin(x) - a * cos (x)

is written by mistake. If that causes b to be an unused local variable, we get a valuable diagnostic.

“lower down your business requirement”

I’m guessing you’ve never talked to someone requesting dev work on upwork

> It's like discovering that bidet exists or something.

They're known and readily available in the US, but never really caught on, even during and after widespread toilet paper shortages in 2020.

Probably California would ban them anyway along with toilets that actually work.

pick fp and haskell / ocaml/ racket/ common lisp

haskell