| > I don't stay plugged in beyond reading the changelog whenever a new version comes out
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> I've also noticed a distinct and crucial lack of long-term vision for Julia from the co-founders. Don't you find those two statements contradictory? There's a pretty striking contrast between your claim to ignorance and your confidently sweeping generalization (sadly, those two often do come in pairs.) > I've also read some dramatic (unverified) claims that I won't repeat here about one of them. If this is what I think it is, the claims were not substantiated in any way (even though it would be easy), and seemed quite outlandish, frankly. > I've been unfortunate enough to read some .jl code in '22, and it was dreadful. I truly don't understand how multiple dispatch makes anybody's life easier It's really hard for me to understand this opinion, given that Julia code, to me, is far more appealing than all the most common alternatives. In particular, multiple dispatch is such an obviously natural paradigm, that it's just hard to fathom why everyone don't just 'get it' right away. I mean, not taking all input argument types into account now seems to me like a completely artificial, even perverse, restriction. Why? I guess this is why people argue on in the internet. |
In that time, I was nearly obsessive in reading all the news, though I wasn’t writing any jl code at all during that time. After 1.0, I used it for a few little things here and there in my business, some basic csv munging and a few other one-off tasks. It did fine, ofc.
The claims, yeah I mean, I don’t know the parties involved personally but because we are not far apart in the social graph and I don’t need the headache this close to retirement. I love my opinions very much, but not when they involve personal controversy.
Multiple dispatch is a write-only benefit. In my line of work, I might come across different machines, different memory setups, different instruction sets, different c compilers, different latency profiles, different spoken language as documentation, etc.
I’m not a mathematician, but I clean up and leave businesses with pragmatic, clean, maintainable code after the mathematicians do their thing and move on. For me, good code is about how specifically and how clearly I can communicate an idea so that the next person (who won’t know shit about shit) can add a feature without breaking something, change a deploy, fix a small bug, update documentation, etc, without breaking things. In that regard, Julia code reads like someone’s manuscript about the issue and not a program written by a programmer.
To you, that’s desired. To me, that’s my actual worst nightmare because it means the longest mental checklist between getting onsite and leaving a finished product and getting paid.
You mention not taking all argument types, it’s just so stereotypically mathematician of an assumption that the code will just work with whatever garbage you send it.
Because maybe that function needs to run on a 32bit system somewhere, and it will fail?
Maybe some of the other methods have a bug, and you won’t notice until you use the original method with a certain type, that you hadn’t considered? Julia can’t prove this sort of thing, to my knowledge.
I’m not saying python can, necessarily, but I know that there are very strong confidence levels and that if something borks, I can arrive at the scene of the crime within a few minutes of any given stacktrace and docker image, or whatever.
I don’t mean to argue. It’s clear we disagree. That’s fine. I just can’t take Julia seriously because they treat data like math on a whiteboard, and it’s just a ridiculous way to program a computer. Like I said, it gets a lot of computing done, and a lot of people are going home paid well. It’s all good, to that end.
Edit: I likely won’t reply further, it’s really annoying to scroll back in HN to see replies without linked notifications. Be well!