[na85]

The point of this submission being....?

The fact that someone runs statistics calculations in Fortran (a language whose most recent standard is dated 2008) should be shocking only to the recent generation of coders who have become "code hipsters." The guys looking for the Next Big Thing™ in programming languages.

These are the guys trying to cram Python into every possible goddamned use case, whether that be embedded systems or computational fluid dynamics. Whether it's the right tool for the job or not. The same guys who are implementing a Ruby interpreter in Haskell, running on a VM written in Rust. Why? Because damn it, their language of choice is shiny and new, and therefore it must be the best.

Nope. You use the best tool for the job. If you're already familiar with a language and that language is perfectly well-suited for the task at hand (in this case mathematics) then you use that language.

Fortran is old, which means it's seen a lot of development. The compiler optimizations are very, very efficient and Fortran code runs extremely fast. In fact, Fortran was explicitly designed for running mathematics algorithms on computers.

tl;dr Fortran is actually a great choice for this application and I hate hipsters.

[kyllo]

These are the guys trying to cram Javascript into every possible goddamned use case

Fixed that for you.

Yes Fortran is probably the right tool for the job in this case, but I also think that creative experimentation with programming languages, invention of new languages, new implementations of and enhancements to existing languages, are good and important, and not just a "hipster" thing. All modern programming languages and their implementations have warts and deficiences, and building a new and improved one requires a level of skill and dedication that goes far beyond hipsterism.

[rhizome]

It's a matter of taste. How many verbal languages can you speak and write? Computer languages aren't special, and polyglotism is really only a hallmark of CS-mindedness, which is actually yet another form of hipsterism. It's not a real thing, and the language that is best is the language that the programmer is most productive.

[kyllo]

That really, really depends on what the language is being used for. There are a lot of desirable qualities and features, and no single language has even close to all of them. With the vast, vast number of different programming paradigms that are effective for solving different problems, as well the various resource constraints of different computing platforms, a certain degree of "polyglotism" is absolutely necessary to be an effective, productive programmer. There's nothing "hipster" about it.

[rhizome]

That really, really depends on what the language is being used for.

The work of stats guru Jeff Sagarin.

[kyllo]

How many people in the world need to do the work of stats guru Jeff Sagarin? Is everyone else a hipster?

[rhizome]

Now that I reread, I see that your comment was less a recommendation for Fortran-using Jeff Sagarin as it was a so-what digression. I took the bait, mea culpa.

[MichaelSalib]

Um, people have been doing high performance numeric and scientific computing in python for over 15 years now. The truth is, for a lot of numeric computing, you're better off using python, which calls fortran or c code to do the heavy lifting.

Fortran can run very fast. If all you need to do is numerical calculations, that might be enough. But that's never all you need to do: you need to preprocess your input data, or deserialize it, normalize it, join it or transform it based on some rdbms data, then you do your calculations, and then you need to graph it, serialize it, etc. Most of those tasks are somewhere between excruciating and impossible in fortran, however modern a dialect you use.

[na85]

>Um, people have been doing high performance numeric and scientific computing for over 15 years now.

Have I disputed this fact somewhere?

>The truth is, for a lot of numeric computing, you're better off using python, which calls fortran or c code to do the heavy lifting.

Proof that Python can't get the job done in that particular area. Nevertheless there remain Python zealots who will tell you that it's the best for everything.

>Fortran can run very fast. If all you need to do is numerical calculations, that might be enough.

Actually it sounds like that is all he needs to do. Reading and spitting out a .csv file from Fortran is trivial, despite its clunky IO syntax.

[MichaelSalib]

Have I disputed this fact somewhere?

Yes, when you were complaining that "These are the guys trying to cram Python into every possible goddamned use case".

Proof that Python can't get the job done in that particular area.

Python can't run at all without C code. Fortunately, Python interfaces really well with C and C++ and fortran. The fact that Python lets you be way more productive using fortran tools without having to know or suffer from fotran's glaring deficiencies seems like a huge plus to me.

Reading and spitting out a .csv file from Fortran is trivial, despite its clunky IO syntax.

Not really. People who do serious analysis need to make graphs. They need to push data back into SQL databases. They need to do all sorts of interactive analyses. They need to present their results and analytics to other people, including reviewers. They need to debug their analysis. All of that stuff is much easier with python than fortran.

[sliverstorm]

People who do serious analysis need to make graphs

Which is where the aforementioned CSV files come in handy. Heard of GNUplot?

[fnordfnordfnord]

I used to work for a physicist who (still) codes in Fortran. I tried to show him Python. He said, "That's nice, use Python if that's what you like." But he always used fortran. It wasn't usually a big deal to translate between the two. He was giving out the big ideas, we were making use of them. To this day, he is still doing physics, still using fortran, still publishing papers.

[sampo]

> you need to preprocess your input data, or deserialize it, normalize it, join it or transform it based on some rdbms data, then you do your calculations, and then you need to graph it, serialize it, etc.

In large scale number crunching, like climate models, numerical weather prediction, the typical case is that input data is conceptually in a regular 2d or 3d grid, and stored in binary format files (like NetCDF or HDF), as that is more efficient and saves space.

Then the heavy lifting number crunching code runs on a cluster as a batch job, reads in the data, crunches the numbers, and writes results out again in NetCDF or HDF files.

The output files are then downloaded to a desktop PC, and graphing is done with Matlab (Python is also getting more popular) or especially in meteorology with some dedicated meteorology graphing software.

The binary format input and output is probably about as efficient as it can be. Also, heavy number crunching scientist probably don't have much use for relational databases.

[cing]

Is Fortran actually the best choice for this application? I don't know how heavy the calculations are for sports analytics, but I'm guessing it's less advanced than scientific simulations. Who cares how numerically efficient your code is if you use 10x the lines than a modern language and spend half your time struggling to maintain it.

[vonmoltke]

On the sports analytics question I don't have any knowledge or experience, but I can see operations there turning into multi-matrix statistical correlations and such.

On the subject of being the best language for the job, Fortran does not use 10x more lines than more modern languages. In fact, in many cases it uses less. When I was working on real-time signal processing algorithms we used to prototype algorithms in Fortran[1], then implement them in C. I also used to use Python with SciPy and NumPy for analysis, as well as Matlab. Matlab's huge toolbox library notwithstanding, the Fortran implementations were usually shorter, simpler, and easier to understand than any of the other languages. It was only bias and preconceived notions that kept it from being used in the real system. I would have loved to see Fortran subroutines running the algorithms underneath the C distributed framework.

[1] Until someone in management and the customer team decided to have the scientists write their algorithms directly in the real-time C. That is a rant for another day.

[na85]

Not sure why code to crunch some statistics would have a huge maintenance cost. There goes one point out the window.

As for the first, a) I touched on the fact that Fortran is a modern language and b) unless you've got examples showing two side-by-side implementations of the same algorithm with Fortran being 10x longer, then it sounds like you're just another of the aforementioned hipsters who is experiencing aversion to something just because it is not new and shiny.

[noonespecial]

The language is only half the machine. The human is the other half. The question is not if Fortran is the best choice, it's is Fortran the best choice for him.

[sampo]

> Is Fortran actually the best choice for this application?

Fortran is like fast, typed, compiled Matlab (with smaller standard library, but a lot of numerical libraries available all over internet).

Nut yes, exploratory data analysis, something interactive like NumPy + Matplotlib, Matlab or R might be better.

But NumPy + matplotlib is kinda painful to set up first to be interactive, R the language is wonky, and Matlab cost a lot of money (and the free alternative, Octave, has much more limited graphics, and they are kind of ugly, too).

Of course, Fortran has no graphing capabilities, so one needs some tool for that anyway.

[asperous]

Python is actually rather old at this point, dating back to 1991. But yes, I see your point: people treating languages like they do cellphones, expecting a new one every 2 years-- confused as to why you have still use that 5 year old junker (whose battery lasts a month).

[slurry]

should be shocking only to the recent generation of coders who have become "code hipsters." The guys looking for the Next Big Thing™ in programming languages.

This was written in 1983: http://www.pbm.com/~lindahl/real.programmers.html

It contains among other things the sentiment "Unix is a glorified video game."

Most of the things you are using right now used to be hipster.