Anyhow, no need to rehash the same arguments, there was a long thread here on HN about the post, you can read some of it here: https://news.ycombinator.com/item?id=37764326
I've read that F# has units, Ada and Pascal have ranges as types (my understanding is these are runtime enforced mostly), Rust will land const generics that might be useful for matrix type stuff some time soon. Does any language support all 3 of these things well together? Do you basically need fully dependent types for this?
Obviously, with discipline you can work to enforce all these things at runtime, but I'd like it if there was a language that made all 3 of these things straightforward.
Matrix dimensions are certainly doable, for example, because templates representing mathematical types like matrices and vectors can be parametrised by integers defining their dimension(s) as well as the type of an individual element.
You can also use template wizardry to write libraries like mp-units¹ or units² that provide explicit representations for numerical values with units. You can even get fancy with user-defined literals so you can write things like 0.5_m and have a suitably-typed value created (though that particular trick does get less useful once you need arbitrary compound units like kg·m·s⁻²).
Both of those are fairly well-defined problems, and the available solutions do provide a good degree of static checking at compile time.
IMHO, the range question is the trickiest one of your three examples, because in real mathematical code there are so many different things you might want to constrain. You could define a parametrised type representing open or closed ranges of integers between X and Y easily enough, but how far down the rabbit hole do you go? Fractional values with attached precision/error metadata? The 572 specific varieties of matrix that get defined in a linear algebra textbook, and which variety you get back when you compute a product of any two of them?
A lot of my frustration it is that the ergonomics of these things tend to be not great even when they are available. Or the different pieces (units, shape checking, ranges) don't necessarily compose together easily because they end up as 3 separate libraries or something.
And then there's a subtlety where units might be preserved, but x may be "absolute" where as (x - x) is relative and you can do operations with relative units you can't with absolute units and vice versa. Like the difference between x being a position on a map and delta_x being movement from a position. You can subtract two positions on a map in a standard mathematical sense but not add them.
Anecdotally, I find these are the same people who work less effectively and efficiently. At my company, I know people who mainly use Notepad++ for editing code when VSCode (or another IDE) is readily available, who use print over debuggers, who don't get frustrated by runtime errors that could be caught in IDEs, and who opt out of using coding assistants. I happen to know as a matter of fact that the person who codes in Notepad++ frequently has trivial errors, and generally these people don't push code out as fast they could.
And they don't care to change the way they work even after seeing the alternatives and knowing they are objectively more efficient.
I am not their managers, so I say to myself "this is none of my business" and move on. I do feel pity for them.
Anecdotally, I was just writing a generic BPE implementation, and spend a few hours tracking down a bug. I used debug statements to look at the values of expressions, and noticed that something was off. Only later did I figure out that I modified a value, but used the old copy — a simple logic error that #[must_use] could have prevented. cargo clippy -W pedantic is annoying, but this taught be I better listen to what it has to say.
Well, one of my coworkers pushes code quite fast, and also he is the one who get rejected more often because he keep adding .tmp, .pyc and even .env files to his commits. I guess "git add asterisk" is faster, and thus more efficient, than adding files slowly or taking time to edit gitignore.
Not so long ago I read a history here in HN about a guy that first coded in his head, then wrote everything in paper, and finally coded in a computer. It compiled without errors. Slow pusher? Inefficient?
I've read and heard stories about these folks too, apparently this was more common decades ago.
To be clear, I don't think I could pull it off with any language. It's quite impressive and admirable to get things right on the first try.
Having said that, the thing is, languages were a lot simpler back then too. I'm not convinced this is realistically even possible with today's languages unless you constrain yourself to some overly restrictive subset. Like try this with C++, and I would be shocked if you can write nontrivial programs without getting compiler errors. Like to give a trivial example, every time I write my own iterator class for a container, I miss something when I hit compile: like either a comparison operator, or subtraction, or conversion to const iterator, or post-decrement, or subscript, or some member typedef. Or try it with python, and I bet you'll call .get() on something and then forget to check for null somewhere.
I would love to be proven wrong though. If anyone knows of someone who does this with a modern language, please share.
Head, paper, keyboard is what we did in the 80s when compilers were too slow to afford throwing code at them and fix the errors later. Was that code in the HN story a substantial piece of code or some 100 lines program? Our programs used to be small.
Also you can have .env in the .gitignore, yet someone create their file as .env.local and escape the .gitignore pattern. It's easy to come after and lecturing about creating a better .gitignore pattern, but it's even easier to at the very least take a little care of your commits even if it means slower speeds.
And lo and behold, they end up with _more_ design bugs. And the sad part is that they will never even recognize that too much typing is to blame.
People are sacrificing this when they start using python in the first place
Also I would say type hints sacrifice aesthetics, not readability. Most code with type hints is easier to read, in the same way that graphs with labelled axes and units are easier to read. They might have more "stuff" there which people might think is ugly, but they convey critical information which allows you to understand the code.
That has not been my experience in the past few years.
I've always been a fan of type hints in Python: intention behind them was to contribute to readability and when developer had that intention in mind, they worked really well.
However, with the release of mypy and Typescript, engineering culture largely shifted towards "typing is a virtue" mindset. Type hints are no longer a documentation tool, they are a constraint enforcing tool. And that tool is often at odds with readability.
Readability is subjective and ephemeral, type constraints (and intellisense) are very tangible. Naturally, developers are failing to find balance between the two.
I’m working with a medium size python program at the moment. It’s mostly written by someone smart but early career, and they’ve made a rabbit warren of classes and mixins that get combined in complex ways. I’ve been encouraging him to add types - and wherever those types exist, the code becomes 100% more legible to my code editor - and ultimately to me.
I don’t think I’d bother with types in Python for small programs. But my experience is that good type hints lay out a welcome mat to anyone who comes along later to figure the code out. And honestly, a lot of the time that person is the original author, just months or years after the code was written.
This is provably wrong. See https://peps.python.org/pep-3107/#use-cases
> Documentation for parameters and return values ([23])
> Let IDEs show what types a function expects and returns ([16])
> For example, one library might use string-based annotations to provide improved help messages, like so:
def compile(source: "something compilable",
filename: "where the compilable thing comes from",
mode: "is this a single statement or a suite?"):I use type hint press dot button get auto completes
The other side is those people who do not find those kind of bugs annoying, or they simply don't get hit by such bugs at a rate that is high enough to warrant using a strong type system. Developers who spend their time prototyping in ipython also get less out of the strong types. The bugs that those developers are concerned about are design bugs, like finding out why a bunch of small async programs reading from a message buss may stall once every second Friday, and where the bug may be a dependency of a dependency of a dependency that do not use a socket timeout. Types are similar not going to help those who spend the wast majority of time on bugs where someone finally says "This design could never have worked".