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Why I'm Betting On Julia

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Re: Why I'm Betting On Julia

#61

Post by volaski »

Mikeb85 wrote: post #18
tesmar2 wrote: post #8

> but it's poised to do for technical computing what Node.js is doing for web development I stopped right there. Node.js has only a few great use cases where it shines and in the real world, the vast majority of shops have not switched to using it.

> Node.js has only a few great use cases where it shines and in the real world, the vast majority of shops have not switched to using it. Of course not. 'Switching' is usually more pain than it's worth, especially if your previous solution works. New start-ups are likely the ones who will be using it, just as Rails took off in the start-up world. Likewise, R and Python are going to continue to be in use in existing p…

Rails took off among startups because it made it so much more efficient to iterate on design, but node.js is nothing like that. I actually tried node.js for a while and came back to rails because it's simply not convenient enough. Like the guy below said, it's great for certain use cases but overall it doesn't bring much else to the table.

Re: Why I'm Betting On Julia

#62

Post by StefanKarpinski »

shele wrote: post #27

"Julia was not designed by language geeks — it came from math, science, and engineering MIT students" This statement is built on a false dichotomy. And it is not really true for Julia, take the type system for example, sophisticated AND unintrusive.

Jeff and I were slightly miffed at being called "not language nerds" ;-)

Re: Why I'm Betting On Julia

#63

Post by Toenex »

Pxtl wrote: post #50
kevinalexbrown wrote: post #48

When out with friends recently, one of them mentioned how awesome Julia is. I was surprised to hear someone talk about it, even from another person in science. She turned and gushed about how awesome it was, how supportive the community was, even though she was "not really someone who likes programming." And she liked it so much she was telling her friends about it at a bar! If you make a programming language that pe…

To be fair, there's also Python+NumPy and R in that space, not just Matlab. Besides the "tinker with LLVM" thing, what does Julia offer that Python (or Cython for speed)+NumPy does not?

Agreed, Python with NumPy is definitely a key player in this space, probably more significant these days than Matlab. Don't forget Octave which continues to hold it's place as a Open Matlab compatible(ish) option. Whilst I'm a fan of R for experimentation and prototyping it is often let down by poor performance, particularly on matrix calculations. R's forte is really in providing reference implementations of an amazing array of statistical methods, often by the author of the technique.

One of advantages of Julia touted by the authors is that much of the Julia system is written in the Julia language making it easy for users to understand many of the algorithms and contribute to the system. In practice I don't know how true that is (it seemed to spend a long time compiling C/C++ code when I last built it) but I can see the rationale.

Re: Why I'm Betting On Julia

#64

Post by 3JPLW »

sdegutis wrote: post #36
sdegutis wrote: post #33

Wait a minute! Can you embed Julia into a C program like Lua? Can it interface with complex C types cleanly?? This might be the scripting language I'v been looking for in my side project!

Wow. Okay, yes. It can be embedded[1]. It can call C code[2]. Julia may have just saved my project (which was dying because it needed a good scripting language that was fast)! [1]: http://docs.julialang.org/en/latest/manual/embedding/ [2]: http://docs.julialang.org/en/latest/manual/calling-c-and-for...

And embedding (and its documentation) will likely get much better very soon.

https://github.com/JuliaLang/julia/pull/4997

Re: Why I'm Betting On Julia

#65

Post by collyw »

elteto wrote: post #12

To each its own I guess, but I wanted to say that I don't see "safety, type systems and homoiconicity" and other theoretical "geek" stuff as orthogonal to a programming language's ease of use, productivity and expressiveness. If anything they complement each other. The theory behind it provides a consistent framework so that you minimize the mixing of different paradigms and you can express ideas in a more consistent…

Was Perl not a language that just had stuff thrown in? It wasn't difficult to use, but difficult to master I would say.

Re: Why I'm Betting On Julia

#66

Post by bryanlarsen »

SonicSoul wrote: post #52
bryanlarsen wrote: post #34

Earlier quoted context omitted.

The main reason we at clara.io use Node is so that front-end code can run in the back end. Imports, Exports and Renders are done by workers that are essentially headless clients that happen to have access to first and third party binary libraries.

what's the benefit of this? performance?

not having to write the same code twice.

Re: Why I'm Betting On Julia

#67

Post by synparb »

Pxtl wrote: post #50
kevinalexbrown wrote: post #48

When out with friends recently, one of them mentioned how awesome Julia is. I was surprised to hear someone talk about it, even from another person in science. She turned and gushed about how awesome it was, how supportive the community was, even though she was "not really someone who likes programming." And she liked it so much she was telling her friends about it at a bar! If you make a programming language that pe…

To be fair, there's also Python+NumPy and R in that space, not just Matlab. Besides the "tinker with LLVM" thing, what does Julia offer that Python (or Cython for speed)+NumPy does not?

I remember there being talk of eventually being able to call Julia from within Python. I've also been quite happy using Numba as an alternative to Cython for some things when I need speed. It's a lot more light-weight with less boilerplate, although still a little rough around the edges.

Re: Why I'm Betting On Julia

#68

Post by collyw »

Blahah wrote: post #58

Just yesterday I decided to start seriously developing in Julia. High-level languages are a bottleneck for computational biology. We need to be able to write things fast, and have them run fast. So far no language really does this. But Julia looks like the one. I'm going to put together a BioJulia team is anyone is interested in playing.

Python is very popular. I need to explore Pandas / Numpy more, but I was under the impression that they are closely linked to the underlying C arrays to provide high performance.

In my opinion the problem with computational biology is that most biologists are not keen to improve beyond a basic level of programming.

Re: Why I'm Betting On Julia

#69

Post by Toenex »

3JPLW wrote: post #60
Pxtl wrote: post #50

Earlier quoted context omitted.

To be fair, there's also Python+NumPy and R in that space, not just Matlab. Besides the "tinker with LLVM" thing, what does Julia offer that Python (or Cython for speed)+NumPy does not?

Everyone's answer to that question will be different. In my opinion, there's lots of things to love about Julia. First class arrays and array literals. It's a wonderful thing… like Matlab but very smartly designed. The type dispatch system makes so much sense for mathematical work. It's simply how math is done. And Stefan Karpinski (co-creator) often compares it to linguistic grammars, too, which may be a stretch but…

Interesting that you mention IJulia. My concern with it is that when you are trying to develop a new technique or algorithm, the idea of introducing extra layers of code running in another system (in this case IPython) seems like a lot to deal with. Maybe I'm just a wimp ;)
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