[agentultra]

This is way off topic but how far did you get with Haskell? I was a Python programmer, contributor, and speaker for ~10 years and felt I was way more productive in it than in Haskell -- but after spending the last few years with Haskell I now find the opposite to be true and hardly write Python anymore.

Haskell let's me encode more of the business logic at the type level. I've finally been able to experience what people mean when they say a type system as good as Haskell's allow you to make sure invalid states are not presentable.

I can do the same in Python, Javascript, etc but it's much more work by writing thousands of lines of test code and still not being certain where the edge cases are.

That's one area a rich type system helps with...

but I think more to the spirit of your comment: it's the behaviors that are most important. No language is sufficiently expressive enough to define what those behaviors should be, and more importantly, which behaviors are not allowed. I totally agree that whether Haskell or Python, when it comes to this problem, neither are effective! There are no compile-time or run-time errors and yet we observe incorrect behavior! That's something I've only seen formal methods able to tackle.

[mlthoughts2018]

I spent about 4 years total working professionally in Haskell, commonly using things like multi-parameter type classes, liquidhaskell, compiler extensions for fully dependent types, higher kinded types.

I’ve heard the claim, “Haskell let me encode business logic into the type system” so many times, but I think it’s totally a false promise. Usually people mean design patterns like phantom types and things, and it just leads to the same spaghetti code messes as in any other paradigm.

I’ve never found any cases where encoding this stuff into the type system actually resulted in verifiably more correct code as compared to doing the same thing with analogous patterns in dynamic typing languages and adding lightweight tests. You still end up needing approximately the same amount of test code either way.

Yet in the statically typed case, you often pay a big constant penalty of compile time overhead delaying the work cycle, even for the best incremental compilers.

[agentultra]

> I’ve heard the claim, “Haskell let me encode business logic into the type system” so many times, but I think it’s totally a false promise. Usually people mean design patterns like phantom types and things, and it just leads to the same spaghetti code messes as in any other paradigm.

Well it's working for my code base so it's not a false promise.

I find it hard going back to dynamic languages now because of how little they allow you to see the types.

> I’ve never found any cases where encoding this stuff into the type system actually resulted in verifiably more correct code

I think there is still much debate about this. Dependent type theory is the only type system I know of in which it's possible to write proofs, and therefore verify, a program... but even dependent type theory alone is a bit bothersome for the task.

In my experience it's certainly possible to write a program in Python that is reasonably correct but it takes more effort.

[mlthoughts2018]

Firstly, I didn’t mean to suggest you cannot write effective code in statically typed languages.. only that it is no easier and no more productive to do it than with dynamically typed languages.

> “In my experience it's certainly possible to write a program in Python that is reasonably correct but it takes more effort.”

I think there is a pivotal trade-off though. I’d argue that in many cases it can be less effort to write correct code in Python for three reasons,

- the simpler types of compiler checks are just inapplicable or handled by totally ignorably-low-effort unit tests in Python and don’t matter 99.9999% of the time, and have low cost in the 0.00001% of the time they do matter.

- the extra type system code and constraints it imposes introduces more extra code than what an analogous set of unit tests would have required for functionally the same level of correctness guarantee in Python.

- the extra time cost of including a compilation step in many edit cycle round trips adds up to far more effort than writing and maintaining extra tests, and disallows flexibly deciding when to get rapid feedback when that feedback matters more than whole-program correctness required by a compiler (and these points are magnified if ever working in a monorepo).