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Most times a julialang.org blog post is posted to HN, I wonder whether the choice of content is well chosen to spread awareness of and interest in Julia. I wri

Most times a julialang.org blog post is posted to HN, I wonder whether the choice of content is well chosen to spread awareness of and interest in Julia. I write this as a huge Julia fan; I use Julia daily, and it is both my favorite language and the language I know best. So I already think Julia is great. But reading many Julia blogs, especially those from julialang.org, would make me think Julia is only useful for very narrow scientific applications if I didn't already know better. I like Julia because it's extremely fast and extremely expressive - and I don't just mean "expressive" as in "can be written like a dynamic/scripting language," though it can. I mostly mean that the combination of its type system and multiple dispatch allows some really elegant abstractions.

digitalzombie 10y ago
> Most times a julialang.org blog post is posted to HN, I wonder whether the choice of content is well chosen to spread awareness of and interest in Julia. Or you know.. it's Pi day.
- coldtea 10y ago
  Today yes. Doesn't address the "most times" the parent mentions...
tnecniv 10y ago
What's your working setup with Julia? I'm looking at switching over from MATLAB as soon as the semester is over.
- programmer_babu 10y ago
  Check out JuliaPro: http://juliacomputing.com/products/juliapro.html http://juliacomputing.com/products/juliapro.html
- Tarrosion 10y ago
  My setup is dead simple. I'm on Windows, so I use Notepad++ with syntax highlighting as my editor and do a lot via the REPL. I just use regular Julia, not JuliaPro. Installing packages hasn't been a problem for me, just Pkg.add("PackageYouNeed"). I've had very few problems with package setup in the past and none recently. On a 4-core CPU I have the environment variable JULIA_NUM_THREADS set to 3 so that when Julia is doing threaded worked there's still a core free for web browsing. One potential gotcha: the Julia docs will mention that you can access shell commands from the REPL by starting your line with a semicolon, e.g. ;ls. For me this only works if you start Julia from something like Git Bash, not cmd. Lots of people seem to like Juno (junolab.org) as an IDE. The team behind it has made incredible progress recently, and sometimes I use it for its GUI around the debugger, but for the most part I tend to stick to Notepad++.
rspeer 10y ago
> I like Julia because it's extremely fast ...compared to Python, under some circumstances, disregarding startup time. Don't oversell it. Don't confuse what Julia aspires to be with what it is, or you'll just turn people off when they feel they've been misled. There are extremely fast ahead-of-time-compiled languages that would have finished their computation while Julia is still JIT-ing its kernel.
- StefanKarpinski 10y ago
  Julia startup time is 0.5 seconds on a very weak laptop. That's comparable to the JVM, which is nevertheless fairly popular. You may not want to write command line tools in Julia, but there's not much else that's a serious problem since process startup time is rarely that big of a performance issue. Disregarding JIT time, Julia is as fast as compiled languages – we benchmark against C and Fortran and don't grade on a curve. This is not an aspiration, it's a well-established performance characteristic in both benchmarks [1] and real-world applications [2]. Regarding JIT time, it's important to understand that this is a fixed cost – for any computation that takes long enough to matter, the time taken by JIT will be a negligible fraction of the time. The reason to exclude JIT time when benchmarking is because most benchmarks don't take much time – tens of milliseconds, compared to which JIT is significant. But we don't actually care about the speed of things that only take tens of milliseconds – we're using benchmarks to extrapolate to things that take much longer, which is why you exclude JIT. [1] http://julialang.org/benchmarks/ http://julialang.org/benchmarks/ [2] http://juliacomputing.com/case-studies/ http://juliacomputing.com/case-studies/
  - rspeer 10y ago
    When I last used it, the time to import even two modules was many seconds. I know that's JIT time, but that breaks the flow of developing with Julia like it's a dynamic language. And the JVM is popular, yes, but nobody would call it "extremely fast", particularly for interactive use, because of its startup time. The time to parse the data I needed was many minutes, slower than Python. Restarting a Jupyter kernel would break my flow every time. The benchmarks are all for numerical computing, where the hard work is typically offloaded to a BLAS library anyway, and don't involve strings or dictionaries. Let's see a JSON parser in there and not just a Mandelbrot set.
jernfrost 10y ago
That is the area of expertise by the creators, but that puts it on the rest of us Julia fans to promote Julia as a general purpose language and talk about how we use it. I am not a scientist but I find Julia very useful for all sorts of practical stuff. E.g. people seldom talk about how great Julia is for writing shell scripts.

digitalzombie 10y ago

> Most times a julialang.org blog post is posted to HN, I wonder whether the choice of content is well chosen to spread awareness of and interest in Julia. Or you know.. it's Pi day.

coldtea 10y ago
Today yes. Doesn't address the "most times" the parent mentions...

tnecniv 10y ago

What's your working setup with Julia? I'm looking at switching over from MATLAB as soon as the semester is over.

programmer_babu 10y ago
Check out JuliaPro: http://juliacomputing.com/products/juliapro.html http://juliacomputing.com/products/juliapro.html
Tarrosion 10y ago
My setup is dead simple. I'm on Windows, so I use Notepad++ with syntax highlighting as my editor and do a lot via the REPL. I just use regular Julia, not JuliaPro. Installing packages hasn't been a problem for me, just Pkg.add("PackageYouNeed"). I've had very few problems with package setup in the past and none recently. On a 4-core CPU I have the environment variable JULIA_NUM_THREADS set to 3 so that when Julia is doing threaded worked there's still a core free for web browsing. One potential gotcha: the Julia docs will mention that you can access shell commands from the REPL by starting your line with a semicolon, e.g. ;ls. For me this only works if you start Julia from something like Git Bash, not cmd. Lots of people seem to like Juno (junolab.org) as an IDE. The team behind it has made incredible progress recently, and sometimes I use it for its GUI around the debugger, but for the most part I tend to stick to Notepad++.

rspeer 10y ago

> I like Julia because it's extremely fast ...compared to Python, under some circumstances, disregarding startup time. Don't oversell it. Don't confuse what Julia aspires to be with what it is, or you'll just turn people off when they feel they've been misled. There are extremely fast ahead-of-time-compiled languages that would have finished their computation while Julia is still JIT-ing its kernel.

StefanKarpinski 10y ago
Julia startup time is 0.5 seconds on a very weak laptop. That's comparable to the JVM, which is nevertheless fairly popular. You may not want to write command line tools in Julia, but there's not much else that's a serious problem since process startup time is rarely that big of a performance issue. Disregarding JIT time, Julia is as fast as compiled languages – we benchmark against C and Fortran and don't grade on a curve. This is not an aspiration, it's a well-established performance characteristic in both benchmarks [1] and real-world applications [2]. Regarding JIT time, it's important to understand that this is a fixed cost – for any computation that takes long enough to matter, the time taken by JIT will be a negligible fraction of the time. The reason to exclude JIT time when benchmarking is because most benchmarks don't take much time – tens of milliseconds, compared to which JIT is significant. But we don't actually care about the speed of things that only take tens of milliseconds – we're using benchmarks to extrapolate to things that take much longer, which is why you exclude JIT. [1] http://julialang.org/benchmarks/ http://julialang.org/benchmarks/ [2] http://juliacomputing.com/case-studies/ http://juliacomputing.com/case-studies/
- rspeer 10y ago
  When I last used it, the time to import even two modules was many seconds. I know that's JIT time, but that breaks the flow of developing with Julia like it's a dynamic language. And the JVM is popular, yes, but nobody would call it "extremely fast", particularly for interactive use, because of its startup time. The time to parse the data I needed was many minutes, slower than Python. Restarting a Jupyter kernel would break my flow every time. The benchmarks are all for numerical computing, where the hard work is typically offloaded to a BLAS library anyway, and don't involve strings or dictionaries. Let's see a JSON parser in there and not just a Mandelbrot set.

jernfrost 10y ago

That is the area of expertise by the creators, but that puts it on the rest of us Julia fans to promote Julia as a general purpose language and talk about how we use it. I am not a scientist but I find Julia very useful for all sorts of practical stuff. E.g. people seldom talk about how great Julia is for writing shell scripts.