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Julia 1.9

julialang.org

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Re: Julia 1.9

#131

Post by tastyminerals2 »

krastanov wrote: post #123
tastyminerals2 wrote: post #106

Earlier quoted context omitted.

So, you mean that loading a bigger project in Julia was more or less equal to compiling it with some language like C++? And you had to do it every single time in order to work with the project? This doesn’t sound too good tbo.

That used to be the case before this version, indeed. It was due to how incredibly difficult it is to cache code efficiently in a language that (1) dynamically compiles things and (2) supports multimethods. Point 1 is crucial for the high performance, and point 2 is crucial for the incredible composability of libraries and reuse of code. To my knowledge julia is the first language to solve both with UX that is gettin…

Come on. Julia is >10 years old. This was a language design decision many years ago, the shortcomings of which have been addressed much later when it started to be clear that it is a problem. Native code caching is available only since 1.9. This is great that the team worked hard on them, but if this was not an issue right from the start, Julia could have been in a different place today.

Hence, my ranting.

Re: Julia 1.9

#132

Post by affinepplan »

krastanov wrote: post #124
tastyminerals2 wrote: post #114

I like to explore alternatives to Python and Julia has been one of the tools I am waiting to become mature enough to actually invest some time in. But every time I start reading threads, I see the comments from actual users reporting about half an hour minutes and “coffee time” project compilation. Then the dreaded ecosystem problem. Then I think to myself, well, it’s not the time yet. Also, I wish Julia was as popul…

Could you elaborate on the ecosystem problem? For my corner of the world, Julia probably has one of the highest quality ecosystem (differential equations, physics modeling, autodiff through very complicated code, probabilistic programming, SIMD/multithreading, and wonderful plotting libraries (the Makie.jl ecosystem) and good data wrangling capabilities (the Dataframes.jl ecosystem)). I am curious what are the fields…

> I am curious what are the fields where it is less well developed?

Data engineering and cloud integration is a big one. It has very few tools in that domain, and I say this as a heavy Julia user (hobby).

Re: Julia 1.9

#133

Post by majoe »

I really like "Julia, the programming language" and had a great experience using it on the few occasions, where it made sense. But whenever a colleague asks me, if I can recommend it, I have to say "no". The crux is, that its "just-ahead-of-time" compiler disqualifies it for a lot of use cases: I actually would prefer it over Python for small scripts, but the compilation overhead is too long. On the other hand I would use it over C++ for some applications, when it could easily produce portable binaries.

With the steady progress in improving precompilation, I'm optimistic to use it more often in the future, though.

Re: Julia 1.9

#134

Post by krastanov »

tastyminerals2 wrote: post #131
krastanov wrote: post #123

Earlier quoted context omitted.

That used to be the case before this version, indeed. It was due to how incredibly difficult it is to cache code efficiently in a language that (1) dynamically compiles things and (2) supports multimethods. Point 1 is crucial for the high performance, and point 2 is crucial for the incredible composability of libraries and reuse of code. To my knowledge julia is the first language to solve both with UX that is gettin…

Come on. Julia is >10 years old. This was a language design decision many years ago, the shortcomings of which have been addressed much later when it started to be clear that it is a problem. Native code caching is available only since 1.9. This is great that the team worked hard on them, but if this was not an issue right from the start, Julia could have been in a different place today. Hence, my ranting.

I think the dynamical recompilation that made code caching difficult is from 0.6, the last release before 0.7 (the first stable release). From 0.1 (2012 or 2013) to 0.7 julia evolved drastically. They stabilized only in 2018ish. This seems like a pretty reasonable timeline for something no other language has done before (although, as I mentioned, pytorch/jax/tensorflow have some limited similarities, and similar problems).

Re: Julia 1.9

#135

Post by jakobnissen »

majoe wrote: post #133

I really like "Julia, the programming language" and had a great experience using it on the few occasions, where it made sense. But whenever a colleague asks me, if I can recommend it, I have to say "no". The crux is, that its "just-ahead-of-time" compiler disqualifies it for a lot of use cases: I actually would prefer it over Python for small scripts, but the compilation overhead is too long. On the other hand I woul…

Yeah I agree. It's good for specific use cases where the JIT latency doesn't matter too much - which means either interactive work, or long-running computations. So, mostly science/engineering work, and perhaps stuff like generative art, building wbsites and stuff.

When latency is much better and/or it can compile static binaries, the use case of Julia will hopefully broaden

Re: Julia 1.9

#136

Post by cjalmeida »

cookieperson wrote: post #118
tastyminerals2 wrote: post #114

I like to explore alternatives to Python and Julia has been one of the tools I am waiting to become mature enough to actually invest some time in. But every time I start reading threads, I see the comments from actual users reporting about half an hour minutes and “coffee time” project compilation. Then the dreaded ecosystem problem. Then I think to myself, well, it’s not the time yet. Also, I wish Julia was as popul…

Honestly, I'd stick with python or learn a statically compiled language to broaden your world. I spent years in the Julia situation and it's more of a cult than anything else. If you ever end up with a job asking for Julia(not likely), you can pick it up in a week or so of free time after some muscle memory kicks in.

Cult? That's a very bad take. It's a tool, great for some stuff, rough edges here and there.

People invest huge amount of effort fixing Python's shortcomings (pyspark, tf, jax, mojo) requiring a completely different way of thinking modulo the syntax. And nobody is talking about the "cult of the snake"

Re: Julia 1.9

#137

Post by krastanov »

NeuroCoder wrote: post #87

I didn't even know some of these things were being worked on until recently. I totally understand why devs don't treat development like a Twitter feed, posting every thought that pops into their head instead of working. However, it would be really interesting to follow some of these developments without having to deep lurk all the PRs. Sorry, pretty shallow complaint. Great work!

I have been a fly on the wall in the ttfx channel on their slack. And there are a few other channels about julia internals. I do not have anything to contribute there, but it is fascinating to learn various julia internal details from listening in on these threads.

Re: Julia 1.9

#138

Post by adgjlsfhk1 »

tastyminerals2 wrote: post #117
adgjlsfhk1 wrote: post #115

Earlier quoted context omitted.

It isn't. That said, it's not as bad as it sounds at first because there are tools like Revise.jl which let you change code without recompiling.

I see. It’s a separate library, right? :) I hope this information is part of Julia tutorial.

It's a separate library, but I'm pretty sure it's used by ~85% of julia users.

Re: Julia 1.9

#139

Post by cookieperson »

freilanzer wrote: post #130
cookieperson wrote: post #113

Earlier quoted context omitted.

You're incredibly lucky. Even minor version bumps have left me up shit creek in production with deadlines.

Why do you update a programming language version in production with deadlines in the first place?

Because it has a new feature that's save the day(if it worked), fixes bugs in a janky patched Julia version, and production in the data science world looks different in research and development phases then it does for software. Production in r and d can simply be, boss wants to see the pros and cons next week with a successful run. Only with Julia have I run into these kinds of predicaments

Re: Julia 1.9

#140

Post by tastyminerals2 »

krastanov wrote: post #134
tastyminerals2 wrote: post #131

Earlier quoted context omitted.

Come on. Julia is >10 years old. This was a language design decision many years ago, the shortcomings of which have been addressed much later when it started to be clear that it is a problem. Native code caching is available only since 1.9. This is great that the team worked hard on them, but if this was not an issue right from the start, Julia could have been in a different place today. Hence, my ranting.

I think the dynamical recompilation that made code caching difficult is from 0.6, the last release before 0.7 (the first stable release). From 0.1 (2012 or 2013) to 0.7 julia evolved drastically. They stabilized only in 2018ish. This seems like a pretty reasonable timeline for something no other language has done before (although, as I mentioned, pytorch/jax/tensorflow have some limited similarities, and similar prob…

I see. Right, 2017 was the first time I tried Julia and never came really back. Then the Torch, TF, Keras, PyTorch era started and kept ML engineers busy while I think Julia couldn’t keep up. Well, there is Flux. Not sure how it compares.
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