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In many ways, I think we're actually in agreement :p Free. Quick. Interactive. 4 lines. Done. What's the value proposition of Julia compared to that? Now y
by ACow_Adonis 9y ago
In many ways, I think we're actually in agreement :p
Free. Quick. Interactive. 4 lines. Done. What's the value proposition of Julia compared to that? Now you can argue that Julia will allow better type specification and specialisation, etc, etc. But that's not what's valued or used in your example.
Now, my mindset/domain has to engage with such, and i freak out at the implicit-ness/assumptions inherent in such code, especially with some of R's additional design choices.
In my mind, having code that crashes/errors out when something ambiguous/dangerous is encountered in your example a "good thing". But that's not what's valued in the above example.
And while Julia would allow someone to program in such a way as to specialise or raise these errors and concerns, what is valued is the ability to not think about them. And if you don't think about them, or even as a library designer, if you want to program in such a way that your user primarily doesn't want to think about them, then you're effectively very close to reinventing/reimplementing a new "R", with all its costs and benefits.
I'm just making this observation explicit, even though I actually do value the things the Julia crowd seems to value, but I'm not sure I'm in the majority, and I'm not sure you can push that down into the libraries without exposing concerns most users don't want to be exposed to.
- fspeech 9y agoDWIM (Do What I Mean) at the UI level seems a good feature to aspire to. The sanity check could (and should) be done using an independent method (say manually check a couple of things, or is that too out-of-dated?).
- x0x0 9y agoI don't think julia is going after R's niche. They're going after matlab and sklearn/pandas/numpy. so my 02 on julia's value prop: free. performant. scalable. capable. easy to use is there, but the others matter a bit more.
- dnautics 9y agojulia code tends to be extremely terse. I had to listen to unix domain sockets and spit out an aggregated result to an upstream analytics engine and I accomplished the whole thing (including spawning worker threads to listen to potentially multiple clients posting to the domain sockets), in about 65 lines of code. It's also very readable. I don't have any uptime guarantees or anything (and it requires a fairly heavyweight julia container - or a julia runtime installation - atm), so I wouldn't say it's an optimal solution moving forward, but as a glue piece I was able to show a demo and get to the point where I was debugging upstream and downstream components.