Julia 1.0 Released After a Six-Year Wait (insidehpc.com) 131
An anonymous reader quotes InsideHPC:
Today Julia Computing announced the Julia 1.0 programming language release, "the most important Julia milestone since Julia was introduced in February 2012." As the first complete, reliable, stable and forward-compatible Julia release, version 1.0 is the fastest, simplest and most productive open-source programming language for scientific, numeric and mathematical computing. "With today's Julia 1.0 release, Julia now provides the language stability that commercial customers require together with the unique combination of lightning speed and high productivity that gives Julia its competitive advantage compared with Python, R, C++ and Java."
The Register reports: Created by Jeff Bezanson, Stefan Karpinski, Viral Shah, and Alan Edelman, the language was designed to excel at data science, machine learning, and scientific computing.... Six years ago, Julia's creators framed their goals thus:
"We want a language that's open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that's homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled...."
In a julialang.org post announcing the milestone, the minders of the language claim to have achieved some of their goals.
The Register reports: Created by Jeff Bezanson, Stefan Karpinski, Viral Shah, and Alan Edelman, the language was designed to excel at data science, machine learning, and scientific computing.... Six years ago, Julia's creators framed their goals thus:
"We want a language that's open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that's homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled...."
In a julialang.org post announcing the milestone, the minders of the language claim to have achieved some of their goals.
Really impressive (Score:4, Funny)
.x d (Score:3)
Heretic! Splitter! Dimensional fractionator!
The Mandelbrot law is supreme!
Re:Really impressive (Score:5, Funny)
I am wondering if they have a Code of Conduct for the language?
This language is polite and respectful.
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This is really impressive from the technical standpoint, but I am wondering if they have a Code of Conduct for the language?
The main requirement in the code of conduct is that you must be willing to accept and respect homoiconic activity.
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a Code of Conduct for the language?
They used to have one, and strings were only allowed to use valid, legal, properly enumerated Unicode. But they abandoned that because it didn't really allow for remediation.
Now they simply flag offensive strings, and leave it up to the application programmer to remediate.
So if you're using Julia you will need to write your own code that conducts invalid Unicode to the appropriate remedial function. Or not.
Way ahead of ya (Score:2)
Way ahead of ya [fyngyrz.com]
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You forgot to add the "except if", "only when" and "throw tantrum" clauses.
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"Fuck you you fucking SJW bitch. This is why women are not welcomed in the open source community because you fucking cunts make everything WORSE."
Oh Romeo, my Romeo, is that you?
No native compiler (Score:1)
Therefore it's slow like Java and Python. That's not a bad thing if your app is I/o bound or quick development time is more of a priority.
But it failed it's goal of overtaking Java and Python if it's JIT compiled as you might as well use them instead
Re:No native compiler (Score:5, Informative)
Didn't RTFM? Julia has several backends including LLVM. Performance is more than respectable. [julialang.org] In particular, puts Python to shame and close to Java + JIT but without the JIT lag, load time and memory footprint annoyance.
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*Any language* puts Python to shame... except Python plus native compiled number crunching libraries. You know, the ones everybody uses.
Fascinating, how Python apologists are able to convince themselves that its horrible performance is not a reason to use a different tool. Thus the idiocy continues.
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Don't worry the hardware will take care of performance issues by the time the product ships*
*Am I joking or not ?
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Why do you think performance is the most important consideration for programming language choice?
The idiocy is in believing that everyone's needs are the same.
For the things that are usually done with Python, it would not matter if the interpreter was further 10 times slower.
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> Maybe not the MOST important, but I sure don't like waiting for the computer any longer than is strictly necessary.
No one does. But people like even less to wait for people writing code. It takes much longer to write C++ code and it takes longer to compile it as well. Fast, optimized native code is valuable only if your program is going to be used on larger amounts of data, performing intensive computations or used by a large number of people. Most code is not written for these cases.
Most code is writt
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50 hrs, not 500 hrs.
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> Yes, but a poor design may make it difficult or impossible to optimize later.
Which is fine. Optimization is possible to a reasonable degree, but not completely. A 40 or 400 times slower program is only perhaps 2-4 times slower after Cython, Numba, ShedSkin etc - a very reasonable trade-off. Further that, Python is meant to be used with a splash of C for those few core data structures and algorithms, not replace it. Have a lot more custom stuff that needs native performance? Python was never meant for t
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It does look respectable but that graph isn't the full story, is it? In my field we use a lot of Python and MATLAB (also some R). Python can be sped up with Cython (often dramatically). MATLAB makes it easy to integrate C or C++ via MEX files. If you were using one of those languages and really needed to speed up the sorts of things being profiled in the Julia benchmarks then you have a simple way of doing it. Usually you're just optimising an inner loop and can leave the rest of the code unchanged. In prac
Re:No native compiler (Score:5, Informative)
It's natively compiled, just not statically compiled.
If compiles optimised versions of your functions as needed. So you can define a function that works on any supported numeric type, and when you call it with doubles, it will compile and cache a version of the code optimised specifically for doubles.
As a result, it is very fast for numeric code, without having to create separate function definitions for each supported type.
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I think that's called a "specializing compiler", like Psco/PyPy but not JIT. I don't juch like JITs, actually. A good fit for LISP but not much else.
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You mean it has a template library? C++ has that for as long as I can remember.
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Templates are fine (for some definition of fine) for static type systems where types can be decided and code specialized at compile time.
Julia is however dynamic and uses different mechanism.
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No, it doesn't use a template library. Or in a sense, all your code is templates.
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It is a lot more like Perl; it runs fast, and you can write it fast too. But reading it is going to take time.
That tradeoff isn't going to go away, it is baked into the range of problems we want to solve with the same tool. The less verbose the language is, the more of the complexity is hidden. That makes it expert-friendly, but it also makes collaboration more difficult.
I prefer the Ruby solution; it can't do everything. Lots of stuff that is hard you would write in C instead. And it has an excellent C int
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If reading types is the hard part, you're only one step past Hello World anyways.
I think xkcd already has this covered (Score:2, Flamebait)
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https://xkcd.com/927/ [xkcd.com]
Except this is a HPC programming language, not a one-size-fits-all HTML5-style standard.
Re:I think xkcd already has this covered (Score:5, Insightful)
Roughly, one should think of this more as a 'next gen fortran' than 'oh this will replace all your programming'.
Python with numpy has been respectable, but there's room for a language built from the ground up around technical computing.
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We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell.
Sounds like a one-size-fits-all attempt to me.
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I say the larger content seems to be clearly oriented around scientific computing.
There is a fair amount of ill-advised 'marketing' sort of propaganda that is misleading in their pages however, which is unfortunate as I think the core goal and how they go about it seems respectable enough.
Are petascale computers programmed in assembly? (Score:3)
Otherwise claiming "Julia is the only high-level language that has run at petascale" is a bit of an exaggeration.
Re:Are petascale computers programmed in assembly? (Score:4, Insightful)
it's just a lie, C++ and Fortran are also used. We can argue if C is "high level" or "medium" level...
First impression (Score:5, Interesting)
My first impression of Julia was favorable. I fired up the command line interpreter and typed in 2 + 2. Prints out 4, just like Python. Then typed in 2**4:
Wow, I like that. I managed to define a function, f(n) = n * n, without reading the manual but didn't get much further without reading the docs docs. But great start, I already see this as a reasonable alternative to what I usually use Python for: a desktop calculator.
Initial impression matters. Now, with a postive one, I will go deeper and see if Julia is really what I should be coding one-offs in, instead of Python or Go.
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So do you think exponentiation should be right- or left-associative? What should 2^4^2 compute to in Julia?
Woot! (Score:2, Insightful)
I want a tool that puts nails in like a hammer, screws screws like a screwdriver, lifts steel like a crane, cuts wood like a saw, digs dirt like a backhoe, shoots animals like a gun, stabs children like a knife...
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Here, take these handcuffs.
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Here, take these handcuffs.
Username checks out.
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It is called your imagination, and you're already using it!
Re: Woot! (Score:1)
You mean like a backhor with a quick attachment system? They make attachments for sawing wood/trees, screwing augers, putting in large nails (mainly for soil reinforcement), lifting stuff, digging. You might need duct tape to attach a knife, but it would still be stabby.
Cheat sheet (Score:5, Informative)
Cheat sheet [github.io]
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Thanks for the clarification. It's still an excellent starting point.
No classes, No goto (Score:3)
Good or bad? Hard to say, but I would rather have these things than not. It is currently the fashion to leave out classes and provide similar functionality with interfaces or equivalent, but I find that a sticking point. Let's see how it goes.
There are situations where goto is far preferable to fiddling with local logic variables and such. Sure, goto can be tricky to implement with respect to local scope and such, but leaving it out to avoid work... doubtful. Leaving out goto for purity reasons... beyond doubtful.
Re:No classes, No goto (Score:5, Informative)
Classes are definitely included in the language. Specifically they're included by strong typing and type-specialized functions. A type specialized function is a "class method" that dispatches on more than just the first (usually implicit) argument.
Goto is implemented via the @goto macro.
Re:No classes, No goto (Score:5, Informative)
Classes are definitely included in the language.
Julia has no classes [github.io]
It does have compound types and extensible types (subtypes). Instead of class methods it has parametric polymorphism, a flavor of generics somewhat resembling interfaces. While this seems nice and natural as far as it goes, I am not sure how far it goes. Jury is out.
I absolutely hate the case conventions for identifiers. Why does every language of the month need to come with at least one blatantly stupid, avoidable idiocy guaranteed to trigger a large proportion of its intended audience? This is a minor thing but not something I could ever used to. A prime candidate for "sorry that was dumb, let's just fix it now before it festers".
At least, no significant indents, thanks for that.
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Why does every language of the month need to come with at least one blatantly stupid, avoidable idiocy guaranteed to trigger a large proportion of its intended audience?
Because having neckbearded snowflakes whining about their tender technical opinions doesn't actually help the language designers with any part of what they're doing. It doesn't solve technical problems, it doesn't encourage adoption, it doesn't even produce useful criticisms. If you make sure to include some aesthetics from different camps and mix them together in an innocuous way, you can make nearly everybody go "ewwww" a little bit, and then the ones who freak out will escort themselves out the door. It
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Because having neckbearded snowflakes blah blah dribble woof...
Wow, great job contributing to the conversation. Your dog beats you or what?
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Well, I understand that you take those words personally, and so are offended, but what else did your comment add? My comment was clearly directed at anybody reading, and attempted to explain the matter.
Your reply doesn't contain any substantive content at all; it isn't even directed at the general readership, but instead seems to be a personal response. And yet, it contains no information that could be useful to me. You didn't even think to include anything more than, "I'm triggered by the word neckbeard."
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I understand that you take those words personally, and so are offended
You conflate others "being offended" with you "being offensive".
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I was saying that you are being offensive. You get that a lot, right?
Re:No classes, No goto (Score:4, Interesting)
The instances where goto is useful can often be boiled down to a few different cases.
IMHO it would be better to have specific language support for those cases than a generic statement. Having a generic goto (or even only a break label-statement) would encourage it to be used for things that it wasn't intended for, and such code would not be as readable.
* Breaking out of nested loops. Something like break label or multibreak number.
* Clause after a loop has reached its end and not broken. Python reuses else for this.
* Error handling: A type of exception handling. It could be simplified by using labels instead of throwing and catching objects of specific types.
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Julia has a goto macro, I like the idea but have not yet tried it. If it works (I don't see why it should not) then nice solution.
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Well, surprise, the @goto macro has oddball limitations, never mind the ugly punctuation. Just give me a real goto without the awkward half measure please, thanks.
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You can't have an unrestricted goto and also good support for distributed computing. Did nobody tell you that they're ambitious, and they want their language to be usable on hard problems?
You can't have a Real Goto with a portable language anyways; the language must restrict it to the lowest common denominator, because different CPUs have different types of JMP variants available. Not even C can give you a generic version that is unrestricted.
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You can't have an unrestricted goto and also good support for distributed computing.
Nice handwave. I suppose you win whatever argument this is by having your own private defintion of "unrestricted". And even then you are most probably full of crap.
Re: No classes, No goto (Score:1)
You missed out finite state machines
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> Having a generic goto (or even only a break label-statement) would encourage it to be used for things that it wasn't intended for, and such code would not be as readable.
Goto is not the problem. When you see a goto it is perfectly clear what happens. The problem is the label. When reading code and there is a label then, suddenly, the flow of control is broken. It is no longer clear what the control flow is. The label indicates that processing may arbitrarily appear at that point and it will require an
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Until branches of mathematics starts using classes and gotos in their theorems, they probably aren't useful in a language for doing mathematics.
I know, right? That's why Julia doesn't have exceptions, modules, macros or coroutines. Oh wait.
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As other people have pointed out, Julia already has things specific to it that fit the role of classes, that have mathematical analogues, without being like classes
How insightful. Yes Julia has things that are somewhat like shitty classes.
features, like coroutines which are a better form of goto, why are you whining?
Why are you an ass? Civil discourse does not use words like "whining". And if you think that coroutines are a form of goto then you are stupid too.
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If you don't think coroutines aren't a form of goto, then maybe consider you need to learn more. goto is a limited and poor form of flow control for "jumping" in an out of certain
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If you don't think coroutines aren't a form of goto, then maybe consider you need to learn more.
Idiot.
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If you don't think coroutines aren't a form of goto, [...]
Lambda: The Ultimate Goto [readscheme.org]
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Yes Julia has things that are somewhat like shitty classes.
NBG set theory has classes. Java, C++, C#, and everything else descended from Simula has shitty things that are kind of like classes but not really.
Haskell typeclasses and C++ "concepts" (which aren't in the language yet) are much closer to mathematical classes.
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A master of grammar, you, yes that's it. Maybe make your insightful argument even stronger by adding in some more lolcat. And needless to say I am astounded by the depth of your understanding of computer science and the deep insights you contributed to the thread, they just keep coming, how do you do it? Absolutely in awe.
Plotting is Broken (Score:2, Interesting)
For a technical computing language, One of the major overnights was plotting. It is a mess. There were about 6 different plotting libraries, each with different interface. The most popular was to install python and use Matplotlib.
There has been an attempt to wrap all of them up into plots.jl but you end up with something that never quite covers what you need.
It also uses array indexa starting from 1......
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Yes it does have 1-based indexing. But then it's a language made by mathematicians, and like most of them (Fortran, Matlab, Octave, R, Maple, Mathematica) they usually index from 1. There are pros and cons, but ultimately it's just down to personal preference (personally I prefer 1-based indexing).
However Julia does support arbitrary starting indices, whether it's from 0, or say you wanted to index by year and start from 1960. It's not something I've tried, but I watched a presentation on it once and it see
Yes but... (Score:1)
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Julia isn't a replacement for Python. Julia is a replacement for Fortran.
Numpy is a poor replacement for Fortran.
Licenses (Score:2)
"We want a language that's open source with a liberal license..."
I'm not a programmer, and I can easily prove that if necessary.
Are there programming languages with restrictive licenses? What sorts of jobs would you be unable to do because of those licenses?
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They're just language designers, why should they be expected to have narrowly parsed understanding of the words they use?! LOL
Java would be an example of a language with restrictive IP conditions that is limiting its adoption. You can still do smart phone apps, and internal tools you're not distributing outside the company.
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The "language" consists of the compiler (the contents of src/), most of the standard library (base/), and some utilities (most of the rest of the files in this repository).
https://github.com/JuliaLang/j... [github.com]
Probably someone watching Oracle asserting ownership of the Java base classes. Use was allowed, but not alterations or compatible implementations.
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There are other trade-offs that you can have, like slow compilation times, or ability to get speed only on specific domains. Check out projects like Stalin ( https://en.wikipedia.org/wiki/... [wikipedia.org] ). And btw, as someone who has an Msc in CS and published an article in an important convention, I know enough "foundations of computer science".
Their want list sounds like (Score:4, Insightful)
A leprechaun riding atop a unicorn handing out buckets of gold.
If they pull it all off in a single language, more power to them.
Re:Their want list sounds like (Score:4, Funny)
I'm sure they can handle the unicorn and the buckets of gold, but if you want leprechaun support you're going to need a Haskell interface.
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What have you been smoking. The champ there is C. Always will be C unless you go to assembler, which C is turned into.
FORTRAN was just one of the first languages and a really big step up from assembler. Lacks a lot of critical things, however.
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Julia and C don't prevent you from choosing a type. Neither Ada nor any other language can magically solve the problem. I'm just talking about defaults. The programmer still has to decide if it's more important for a function to scale with hardware or run the same everywhere. It's never an easy choice at any level. You could say, "every programmer should make this choice", and I sometimes see C littered with special types for this reason--this function should scale with hardware, this one shouldn't, et
how good is the multithreading? (Score:4, Insightful)
The multithreading support in Julia 1.0 still says "experimental". So does it have usable threads or not? How good is the thread implementation? Comparable to Java? To C++? Are the standard data structures thread safe? How many spurious locks are there?
Any stories to tell? (Score:2)
I would like to hear from people who switched from the more mainstream numpy and tensorflow for linear algebra.. to Julia.
What were your experiences? Was the worflow much more productive? What were the other gains?
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Am I misunderstanding, or did you just say that mainstream programmers are using tensorflow as a linear algebra library?
If not: Phew.
If so: What the hell is wrong with people?
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Tensorflow is a well-known. That is all I meant.
https://simplyml.com/linear-al... [simplyml.com]
Most probably just use Numpy.
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((Yes Lisp) is) (so frig)) in )))
(Awesome. (((And (So Simple) even) A
(((Child could ) use )(it probably).)
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((Yes Lisp) is) (so frig)) in )))
(Awesome. (((And (So Simple) even) A
(((Child could ) use )(it probably).)
((Yes Lisp) is) (so frig)) in )))
(Awesome. (((And (So Simple) even) A
(((Child could ) use )(it probably).)
Lisp code doesn't look like that.
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Better default data structures, better numerical support, more approachable for end users.
What are these "default" data structures in Lisp that you refer to?
How would you contrast the numerical support in Lisp with what's in Julia?