tanlermin

Julia has all these things

Can you consider Dask integration? http://distributed.readthedocs.io/en/latest/queues.html https://github.com/dask/dask

It can handle parallel and distributed parts for you.

https://github.com/dask/dask

"Given enough time, though, I think the paradigms that Julia is exploring will make it a killer general-purpose language."

I think its already a Killer general-purpose language (except for the module system).

I'm just not sure if it is good enough to unseat incumbents when there are things like rust with its deterministic memory management or python with all its momentum and compiler technology coming along.

Not sure whether to bet on it at this point.

But it discusses potential for being appealing in the future when things settle down and new features are added.

Also apparently stackoverflow julia questions have clear exponential growth.

Do you see it replacing python for non DS? What is on Julia 2.0?

Does this obviate the issue that one has to assign the definition of meaning somewhere in the graph? ie Meaning is subjective, and it has to be inserted to propagate down.

https://github.com/dodger487/dplython also see this

careful continuing that linear extrapolation...I think it's about to hit a tipping point due to packages and tooling being much better.

Julia can do all that. its also a general programming language

Julia will be a suitable (superior) alternative soon.

Anaconda. Its the best game in town right now.

would something like conda or anaconda help?

https://docs.continuum.io/anaconda-cluster/index https://www.continuum.io/blog/developer-blog/getting-most-ou...

I can't overplay the importance of a octave like DSL.

Julia is gaining marketshare and mindshare among grad student not just due to its speed, but because it is a more fun and intuitive environment in which to code mathy stuff.

These people will in turn filter into industry and if not them, then atleast their code.

Also macros. As Julia gains more utility for run of the mill data science, Its Dplyr like DSL abilities will be very attractive.

Do you see this type system and generic function library as useful for general purpose programming as well? How would that play with mypy and type hints?

What do you mean by "goes gold"? Like 1.0?

Cython is uglier and without type inference.

I wish we could just use mypy when we feel like making our code faster :/

Can the type information be consumed by a compiler like nuitka to produce fast binaries?

Can't one write the logic in cython also?

gotcha

Check out rcall.jl

What do you think of Julia?

Is there any dynamic language suitable for real time 3d viz?

Thanks for sharing your thoughts.

I want to keep my general code and scientific code in the same language.

So python it is.

Got it.

I'm wondering what this performance cost will be and if significant, can all that brainpower at MIT etc really not find a way to mitigate it?

This is a practical question for me because I'm considering Julia for a project and my personal data language.

This is the upcoming python alternative ecosystem, also with multi dispatch:

https://github.com/libdynd/libdynd https://github.com/numba/numba https://github.com/blaze/blaze

Thanks...though the whole "GIL being a feature" is sort of a joke.

I think this is slated to be fixed soon. Any reason why it can't be done?

https://github.com/JuliaLang/julia/issues/265

Look at the commits at the bottom.

Check out dask for distributed and out of core parallel programming : http://www.slideshare.net/continuumio

Its free with a permissive license.

It is also capable of native HDFS integration, Yarn etc and can do more complex and granular parallel patterns than just map reduce. Also has a API for distributed dataframes and arrays with linear algebra ops.

DISCLAIMER: I don't work for continuum. I just want to see its projects succeed because I was a user will benefit.

Check out dask: http://www.slideshare.net/continuumio

Its free with a permissive license and actively growing.

It is also capable of native HDFS integration, Yarn etc and can do more complex and granular parallel patterns than just map reduce. Also has a API for distributed dataframes and arrays with linear algebra ops.

DISCLAIMER: I don't work for continuum. I just want to see its projects succeed because I was a user will benefit.

Yes! Check out dask: http://www.slideshare.net/continuumio

Its free with a permissive license.

It is also capable of native HDFS integration, Yarn etc and can do more complex and granular parallel patterns than just map reduce. Also has a API for distributed dataframes and arrays with linear algebra ops.

DISCLAIMER: I don't work for continuum. I just want to see its projects succeed because I was a user will benefit.

Ok. But I would do it in Numba.