[rollcat]

It feels like we're going in cycles. C was somewhat lax with type checking, thus C++ and Java were both made more strict. Looking to escape the tyranny of static typing, the rise of Python, Ruby, or JavaScript instead left us with a desire that Rust, Go, and TypeScript now fulfill. I wonder what's the next step? LLMs are extremely broad in what they accept, but don't exactly fill the same niches.

[f1shy]

I always saw C++ and Java addressing other issues, like low level memory management, and higher level abstractions like objects. Not so much type policy. Anyways I see a strong tendency in lots of programmers dismissing anything that is not type static-strict-safe, and others advocating for a more relaxed system.

[nurettin]

I see C++ as a scientific DSL definition language. It lets you create an abstraction and define arithmetic operators, iterators and even lets you control dereference and call semantics. The standard helps this scheme by defining return value optimization.

[za3faran]

golang isn't in the same league as the other languages mentioned. And Java and C# have come a long way since to be expressive as well as lesser syntax heavy (type inference, records, pattern matching, string templates, etc.)

[tomrod]

I'm holding out hope for a Fortran resurgence.

It's a tiny hope. But a hope nonetheless. Fortran is fun.

[haneefmubarak]

I'm curious - what do you particularly like about Fortran that isn't otherwise broadly available? Is it a matter of cultural idioms, a unique composition of features, or something else entirely?

[f1shy]

Not OP, but I know a good use case: where I work we do lots of math and signal processing. It is done in matlab, which is great, but then we need to run it in some embedded processor. Using the C++ generated by matlab is beyond any hope. Had the code be written in Fortran (which is very possible, and would make the code clearer) it would run very fast. Now we had a team of people translating matlab to C++

[teleforce]

Check out D language, it should be suitable for math, signal processing, data science, embedded, etc, and it's intended to be better than Fortran, C and C++ [1].

[1] Is Fortran easier to optimize than C for heavy calculations?

https://news.ycombinator.com/item?id=37606477

[haneefmubarak]

I know that Fortran is highly used in the numeric world, especially due to widespread libraries such as LAPACK and BLAS, amongst others; in your opinion, what are the characteristics that make such code much more clear when written in Fortran as opposed to C or C++?

Also, do you prefer a specific version of Fortran, or is the latest one fine?

[targafarian]

A couple big things: Fortran natively performs operations on arrays directly like Matlab or Numpy in Python (Matlab was originally a REPL-style front-end to Fortan), and Fortran compilers tend to yield quite fast code (though specific cases will have another language outperform Fortran).

You can read more about the language and its high-level features here: https://fortran-lang.org

That website/community was created in part by the original author of the Python Sympy library, Ondřej Čertík. He is also working on his own Fortran compiler that you can use via webassembly to play around with Fortran; find links if you want to play here: https://lfortran.org

I've only dabbled a little, but I like the general idea, and I appreciate a F/OSS Fortran compiler being developed like this alongside actively seeking to grow the Fortran community & push the language & its libraries forward.

I expect more widespread adoption of Fortran to be quite a ways out, but what Ondřej is doing for Fortran is necessary (not sufficient) for such adoption to be the case.

[f1shy]

It is not about the language. Is about the people using it. They are typically not CS people. You cannot expect they program all the languages. They know typically python, matlab, and fortran. Of the 3, the one that would perform better is Fortran.

[4m1rk]

Can you give an example? I'm always curious what could be more readable than calling a few functions and composing them using properly named variables.

[drbaba]

Modern Fortran (2008+) has built-in support for matrices, complex numbers, co-arrays (parallel programming), array slicing, etc. This makes it easy to write performant compiled code if you mostly deal with numerics.

Fortran has also added support for e.g. object-oriented programming, pure functions (no side effects for better optimization), and pointers. So idiomatic modern Fortran code looks very different from the “Fortran 77” code that many people might think of when they hear the name :).

[f1shy]

I would really like to see more fortran.

[jules22]

What does a modern Fortran bring that Julia does not? Small binaries?

[xmcqdpt2]

Language stability, and easy C ABI for embedding into other programs. Julia isn't really a language for embedding afaik.

[jules22]

Sure, not in the traditional sense. Since it does not make small standalone libraries, even though possible, I would not make a native extension with it. But juliacall works fine for Python and R. Quite seamless.

[jules22]

Nim/Julia, IMO.

However....

Nim is unlikely to go mainstream. It's not the next Rust and not for technical reasons.

Julia won't budge Python out of the top slot anytime soon, although it should in many scenarios past simple scripting.

[fiedzia]

Python is very strict about type checking, it just does it at runtime.

The next step is Idris, where you define starting and desired type and start interactive shell to figure out right way to get there.