Comment by ReflectedImage
1 month ago
Gradual typing is the worse of both worlds.
You get the complexity and slower development times of using statically typed languages along with the bad performance of using dynamically typed languages.
1 month ago
Gradual typing is the worse of both worlds.
You get the complexity and slower development times of using statically typed languages along with the bad performance of using dynamically typed languages.
Is this based on your experience or is it just an assumption? I only have anecdotes, but it does not reflect your claims, rather the exact opposite. A lot of the boilerplate code doesn’t need to be type annotated, but annotating the main business logic doesn’t take more time and is not more complicated, but instead type annotations help write code that is more clear, more obvious, and it adds some kind of documentation.
It really depends on how you tackle gradual typing on a project level. The easiest way to sabotage is a "any new code must be fukly type checked" requirement, because it often means you also need to add type hints to any code you call, which leads to Optional[Union[Any]] nonsense if you let juniors (or coding assistants) go wild.
As always, no fancy new tech is a substitute for competent project management.
Have you actually used this in a real codebase? Because it is the opposite of my experience in gradually adding types to a large python codebase. There's no extra complexity or slower development. It's not like you need to suddenly move to a different coding paradigm with FactoryBeanFactoryBeans... You just keep writing python like you did, but add types here and there to help clarify things and make your LSP (like ty) work better.
If anything, it speeds up development. Plus it helps give more confidence in the correctness of your code.
Yep, the software development slows down to crawl. Yes, you can still code at the same speed as you were coding in a language like Java or C# but that is considerably slower then what's possible in languages like Ruby and Python.
To give you a roughly idea, you should always expect a 3x slow down when using static typing.
An recent example is Turborepo that went from basic types in Go to proper static typing in Rust. Just adding in the proper typing caused the codebase to grow from 20,000 lines to 80,000 lines and from 3 developer months to 14 developer months.
The stronger your typing system, the slower you will develop code. Whether you realise it or not.
Nonsense. You get the simplification and faster development times of knowing some variable types statically, plus the performance improvements for the compiler which can move the type checks from runtime to compile-time. Plus all the new optimization possibilities.
Common Lisp showed you the way. But almost none looked at it. Only PHP did.
Absolutely not. Duck type based development results in working code out of the door 3x faster than static type based development. It always has since ancient times.
If performance wasn't an issue, then the static type based developers would all be fired. Either directly or by the businesses who relied on them getting driven into bankruptcy by their competitors. You would still get some niche jobs in it where they like to do formal verification of the code.
Your problem is just that your development skills from static type based development don't transfer to duck type based development. Different style of codebases needs to be handed completely differently.
I am talking about gradual typing here. Types are optional, if not given or implied they default to any. No need to annotate anything. If given they are enforced, and lead to optimized op codes and errors if violated. Some at compile-time, some at run-time. If fully typed, all errors are caught at compile-time already.
Duck typing as done with python is the worst of both worlds. No optimizations, no enforcement. Just optional external typechecks.
Of course untyped code (ie runtime types in each var) is to write faster. You only need to add types to some vars or args, and gradually improve from there. Eg ints only, because they are optimized the easiest. No need to check for strings, bigint, floats,.... Or arrays to check for overflows at compile-time and restrict to ints or strings. Massive improvements possible, in size and runtime.
Or object fields. Hash lookups vs static offsets.
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At least CPython and CRuby (MRI), the most common implementations of each language, ignore all type hints and they are not able to use them for anything during compile or runtime. So the performance argument is complete nonsense for at least these two languages.
Both Python and Ruby (the languages themselves) only specify the type hint syntax, but neither specifies anything about checking the actual types. That exercise is left for the implementations of third party type checkers.
Because the anti-types crew showed up and sabotaged it. Similar with perl and lua.
But languages with stronger and more intelligent leadership showed what's possible.
You cannot implement all the compiler optimizations for const and types in extensions. You need to fork it.
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