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Why I'm Betting On Julia

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Re: Why I'm Betting On Julia

#151

Post by ihnorton »

dnautics wrote: post #110
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…

I had the opposite response, I played around with julia and found myself so frustrated I went back to octave. However, it was at an early stage of development and I bet there were a ton of bugs still around. I'll have to give it another shot.

Do! The improvement over the past ~6 months has been staggering.

Re: Why I'm Betting On Julia

#153

Post by wirrbel »

john_b wrote: post #133
wirrbel wrote: post #97

I don't really see the need for the author to make himself into a "cowboy" coder and point out how they ignore all those valuable insights and enlightenments of programmers. Julia is a kind-of-fine language that is designed to appeal Matlab users first of all by its syntactical looks. Just like Javascript was designed to appeal to C and Java users by imitating their look. Under the hood, Julia is quite a smart develo…

> "The part where Julia kicks in now is the point that Matlab has a lot of market ground, especially with engineers who are not extraordinarily passionate about programing. For some people the burden of learning another syntax is just too big, they are not full time programmers but spend their time more with acquiring data and using the results. I really hope that some of them who are not willing to switch to scienti…

You cannot overestimate enough how old folks growing up with Fortran just won't accept Array indizes starting at 0 instead of 1.

Then because professors demand it, colleges buy Matlab campus licenses and "encourage" their staff/students to use it, incorporate in teaching and research.

Sadly, when the student is not on campus anymore, he/she cannot reevaluate old date and in the new job they then demand a matlab license. Its the Matlab tax.

Re: Why I'm Betting On Julia

#154

Post by eonil »

exDM69 wrote: post #85
rodgerd wrote: post #40

Earlier quoted context omitted.

Well, it certainly optimises my ability to get shit done if I don't waste it on subtle type-conversion debugging.

I don't know if this an argument for or against static typing and type safety but there are two sides to this coin. In dynamic programming languages it is definitely easy to get shit done, at least initially. However as a project progresses to the point where a lot of refactoring takes place and there's more than a handful of people working on it, a good static typing language will make sure that shit keeps on gettin…

I agree.

In other words, automatic program-correctness check is a crucial feature if project goes larger. And type check is actually one of the simplest, easiest and fastest way to archive that.

But most dynamic languages doesn't provide type-check. Really sad.

Adding type annotation on dynamic language is a kind of best mix of two worlds, and Julia seems pushing this approach even further - JIT static types from type annotation.

Re: Why I'm Betting On Julia

#155

Post by zhemao »

haberman wrote: post #117

Can Julia be a competitor to R? I love R in concept (interactive environment for statistical analysis) but the language just drives me crazy in its multitude of types and the loosey-goosey ways it converts between them. A friend of mine is really proficient with R; when I walked him through some of the R patterns that are very confusing/irregular to me, he sort of laughed: he could see what I was saying but he said "…

FWIW, there is a Julia library that allows you to call out to R (https://github.com/lgautier/Rif.jl). I'm not sure how well-developed it is though. There are also a lot of R-inspired Julia libraries, such as Dataframes (https://github.com/JuliaStats/DataFrames.jl).

There is also a pretty good Julia-Python interface (https://github.com/stevengj/PyCall.jl) and bindings to Matplotlib (https://github.com/stevengj/PyPlot.jl).

Re: Why I'm Betting On Julia

#156

Post by Beliavsky »

john_b wrote: post #126
candybar wrote: post #71

I really don't like the anti-intellectual tone of the beginning. "The problem with most programming languages is they're designed by language geeks, who tend to worry about things that I don't much care for. Safety, type systems, homoiconicity, and so forth." can be rewritten as: "The problem with most software is that they are designed by computer geeks, who tend to worry about things that I don't much care for. Inf…

The language may have been grating, but as someone who also comes from more of a scientific computing background, I read this as "I want a language to be a tool that I can use to solve scientific and engineering problems with minimal conceptual overhead due to minding language features." I read it as saying "Finally, a language designed for someone like me," which I also find true personally.

"I want a language to be a tool that I can use to solve scientific and engineering problems with minimal conceptual overhead due to minding language features."

Among compiled languages, isn't that Fortran, especially since Fortran 90 on have multidimensional array operations, like Julia, Numpy, and Matlab.

Re: Why I'm Betting On Julia

#157

Post by wirrbel »

xixi77 wrote: post #136
wirrbel wrote: post #97

I don't really see the need for the author to make himself into a "cowboy" coder and point out how they ignore all those valuable insights and enlightenments of programmers. Julia is a kind-of-fine language that is designed to appeal Matlab users first of all by its syntactical looks. Just like Javascript was designed to appeal to C and Java users by imitating their look. Under the hood, Julia is quite a smart develo…

What still amazes me: While working in an ipython notebook ( http://ipython.org/notebook.html ) on some numerical calculations, I can just pull up Sympy ( http://sympy.org ) and perform some symbolic computations (Fourier transforming some function analytically or taking the derivative of some other, etc.). You can certainly do it with Matlab (provided you have purchased the symbolic toolbox of course). Oh, and have…

Sure enough there are parts of matlab where matlab is without serious competitors. I think however that a majority of needs is available for Python, although I know that I do not represent everyone's needs.

Quick google search yielded: http://networkx.github.io/ do not know how it compares though.

I switched to Sci.Python at the point where I had difficulty treating time series data with Matlab. I know there is a toolboxy-thingy from mathworks but it either was not available or I did not find the documentation. Anyway, I quickly got started with Pandas. I had prior knowledge of Python and other mainstream programming languages before.

Spyder is a Matlab-ish IDE with a variable explorer, etc. Some like the Ipython Notebook which I think is great for demonstrations and teaching, but eventually does not scale when projects grow bigger.

Re: Why I'm Betting On Julia

#158

Post by xixi77 »

cjfont wrote: post #129
xixi77 wrote: post #99

Earlier quoted context omitted.

This is about the ability to complete a project fast, which is typically about both convenience of fast prototyping, and performance (ie. you don't want to wait days for the results to be computed before changing something in the code, and you want that change to be easy). And probably few buyers who want fast cars care about aerodynamic design per se -- they care about speed; sure, if better aerodynamics is what's n…

As is usually the case with language design, performance and optimization are often on the opposite side of the scale from code learn-ability and usability. More than likely, the "huge engine" would be some other burden the language has that he doesn't want in exchange for faster prototyping.

I'd actually say both Julia and Matlab are often quite decent on both learnability, usability (at least for their purpose -- especially as the library for Julia develops), and performance. Certainly, on par with other newly-designed languages. Sure, you can go faster with Fortran, but you can do that when you see that it is really needed...

Re: Why I'm Betting On Julia

#159

Post by wirrbel »

jordigh wrote: post #109
wirrbel wrote: post #97

I don't really see the need for the author to make himself into a "cowboy" coder and point out how they ignore all those valuable insights and enlightenments of programmers. Julia is a kind-of-fine language that is designed to appeal Matlab users first of all by its syntactical looks. Just like Javascript was designed to appeal to C and Java users by imitating their look. Under the hood, Julia is quite a smart develo…

> The Matlab clones available (Octave) are generally unimpressive. I think this has to do with the big effort of copying Matlab and the need to develop the whole tool stack (parser, interpreter, libraries). Contributors are hard to find Nah, we have no shortage of contributors: http://hg.savannah.gnu.org/hgweb/octave/ http://hg.savannah.gnu.org/hgweb/octave/file/052cc933aea6/do...

love to see free software with a lot of contributors ;-)

Re: Why I'm Betting On Julia

#160

Post by xixi77 »

wirrbel wrote: post #157
xixi77 wrote: post #136

Earlier quoted context omitted.

What still amazes me: While working in an ipython notebook ( http://ipython.org/notebook.html ) on some numerical calculations, I can just pull up Sympy ( http://sympy.org ) and perform some symbolic computations (Fourier transforming some function analytically or taking the derivative of some other, etc.). You can certainly do it with Matlab (provided you have purchased the symbolic toolbox of course). Oh, and have…

Sure enough there are parts of matlab where matlab is without serious competitors. I think however that a majority of needs is available for Python, although I know that I do not represent everyone's needs. Quick google search yielded: http://networkx.github.io/ do not know how it compares though. I switched to Sci.Python at the point where I had difficulty treating time series data with Matlab. I know there is a too…

Yeah, networkx is pretty good -- I actually meant that network analysis and text processing are the two areas where I'd be quite comfortable recommending Python over Matlab.

For time series data, I'd personally pick R though, or perhaps SAS if it's large enough -- at least if any statistical analysis is involved...

I need to check out Spyder.

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