I know threads about increasing Julia’s adoption among the general programmer population have been done to death. I’m not making another one of those threads. Instead, this thread would focus on the top 1% of programmers. Moreover, to maintain the focus, I would like this thread to be about what Jul…

[image] Hexen: does not allow you to stack data in memory as desired What does this mean? [image] Hexen: it is often more pleasant to call a.sin().ln() than ln(sin(a)) Is there a language that generally implements mathematical functions as member functions of numeric classes?

It’s not that there’s a lack of postfix notation, it’s just that it’s underpowered. Julia’s “postfix notation” is the pipe operator |>. The problem is that its right-hand-side must evaluate to a function, like [1,2,3] |> sum. If it’s a function call, it must return a function, etc. However, a more p…

[image] Benny: Is there a language that generally implements mathematical functions as member functions of numeric classes? Yes, Rust has syntax like this: let num: f64 = 3.141; println!("{}", num.log(10.0).sin()); Rust Playground A browser interface to the Rust compiler to exp…

[image] giordano: That’s not a compromise, that’s great. This is a long-standing dispute, similar to what number to start a natural series with, 1 or 0 =). Some algorithms are written more beautifully with index from 1, some from 0. For example, to work with a physical grid or time it is con…

[image] Hexen: Dynamic dispatching - although convenient, it carries a performance penalty due to type checking and a barrier in interprocedural optimization. That’s why Julia will always be slower than static languages with Ahead-of-Time compilation. And you will never convince a C/C++, Rust, …

[image] Hexen: In Python, it is a standard API for numpy This is false: numpy.sin , numpy.log . numpy.ndarray has quite a few member methods, but not most of the mathematical functions in NumPy, or SciPy for that matter. C++ has cmath , Ruby has Math , Kotlin has math . Rust actually stands out he…

[image] Benny: This is false: numpy.sin , numpy.log . numpy.ndarray has quite a few member methods, but not most of the mathematical functions in NumPy, or SciPy for that matter. C++ has cmath , Ruby has Math , Kotlin has math . Rust actually stands out here. I admit, I’m wrong. In Kotlin we have …

[image] ChrisRackauckas: [image] Hexen: Dynamic dispatching - although convenient, it carries a performance penalty due to type checking and a barrier in interprocedural optimization. That’s why Julia will always be slower than static languages with Ahead-of-Time compilation. And you will n…

[image] Benny: [image] Hexen: does not allow you to stack data in memory as desired What does this mean? Also curious about this one. [image] Hexen: heavy runtime - GC and the need to carry a compiler and environment make Julia unattractive for writing libraries (outside the Julia …

What do we have to attract C++ or other languages' power users to try Julia?

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giordano August 11, 2025, 10:08am 11

I think I’m mildly aware of the dispute, it’s more that I find it annoying every time someone rehashes the debate, I even create stupid packages with non-sense indexing to make fun of it.

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What do we have to attract C++ or other languages' power users to try Julia?

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