Slashdot Mirror
Should Undergraduates Be Taught Fortran?
Mike Croucher writes "Despite the fact that it is over 40 years old, Fortran is still taught at many Universities to students of Physics, Chemistry, Engineering and more as their first ever formal introduction to programming. According to this article that shouldn't be happening anymore, since there are much better alternatives, such as Python, that would serve a physical science undergraduate much better. There may come a time in some researchers' lives where they need Fortran, but this time isn't in 'programming for chemists 101.' What do people in the Slashdot community think?"
But only if they have to do it on punch cards, like I did. Give each student a can of WD40 to keep the machines working smoothly, too.
--No one-- should be taught FORTRAN. Ever...
*sobs in fetal position*
Are there any cheap but quality tutorial for Fortran? O'Reilly has no contemporary introduction to the language and their last book on Fortran, Migrating to Fortran 90 , came out nearly two decades ago.
Fortran is still one of the best, fastest, most optimized tools for number crunching. It's also very easy to write simple programs in it. No way I'd use Python for serious large data set numerical calculations.
Ironically we're doing an implementation of a "new" HR system and a big chunk of it was written in Cobol. We have one guy past retirement age who knows it, but otherwise the bulk of our developers just know those fancy new languages.
Some of those older languages have a surprising amount of life left in them, out in the real world.
Isn't as hard to write fast python code as fortran code? When you're paying large money for supercomputer time, your multi-day molecular dynamics simulations better run quickly.
The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.
Does it really matter what language they're taught in? They should be learning the concepts of programming, not just a language. However, FORTRAN has the benefit of already having a large existing code base and deployment in the field in which students in those particular disciplines are studying. There's no reason for them NOT to learn it, and if they feel like learning Python later, then then may. Python isn't the solution for every god damned thing in the world, even if it can do it.
What do people in the Slashdot community think?
The easy route is just to let them teach what they want to. Professors will talk and push whatever they feel is valuable and they sure the hell aren't going to listen to a Slashdot user half their age that will get on his knees and write Java for an extra buck. If you get a whack job professor teaching only archaic languages, the University will probably hear complaints from alums about getting into the job market and wishing they had learned R instead of Fortran. I don't know about the other engineering programs but I'd sure rather be a master with R than Fortran. Is Fortran more efficient? Depends on if you're talking about cycles or amount of time it takes to write a quadratic sieve for prime numbers.
... maybe even Ruby?
I had to learn C and I actually like plain jane C in all its simplicity. I think colleges should stick to a low level language for numerical computation courses (in my case C but I believe Fortran would function fine), an intro course to an interpreted language like lisp scheme perl whatever and should of course offer full courses in whatever is the latest craze for usable languages like C++, Java
I wager this will be a hot debate and I think it's fine if people want to teach Fortran, I learned scheme and I've never used it in my professional work! Just so long as when they enter the job market, they're prepared.
My work here is dung.
i spoke to someone studying engineering in 1990 who was being taught fortran. they were using a mathematical library that would solve partial differential equations, by presenting the user with the actual mathematical formulae to them.
these kinds of libraries are staggeringly complex to write, and they have been empirically proven over decades of use to actually work.
to start again from scratch with such libraries would require man-centuries or possibly man-millenia of development effort to reproduce and debug, regardless of the programming language.
so it doesn't matter what people in the slashdot community think: for engineers to use anything but these tried-and-tested engineering libraries, that happen to be written in fortran, would just be genuinely stupid of them.
If all you need is to crunch numbers, Fortran is a good choice even today.
It might not be the best language to introduce someone to computer science, but it is very powerful for anything that has to do with matrix operations.
A few years ago in a physics graduate course we had a simulation project which left the choice of language to the student.
We compared performance between implementations in C C++ and Fortran.
Fortran was consistently faster by a big margin.
It's also very easy to learn.
That said, I do most of my coding in C.
As of Postgres v6.2, time travel is no longer supported.
No.
You make a persuasive argument, but on the other hand, yes.
There's no problem for teaching Fortran if it's the right tool for the job. It was 13 years ago that I took Fortran in College. It went great with physics and modeling courses. These days I write web-based database apps in Java/Perl/whatever language-du-jour is required of me, but I wouldn't want to use many of these languages for scientific purposes. I'll leave that to Fortran and C.
Addlepated - punk & metal
Yes, everything should be written in a fresh, clean language.
I nominate VBScript.
"If still these truths be held to be
Self evident."
-Edna St. Vincent Millay
Python is scripting. FORTRAN is programming. MPI is vastly more supported by FORTRAN than any other language - grow MPI support for C++ or Object C, and then FORTRAN can go away.
I work at a university research lab and Fortran is still very much present. If nothing else, students need to be able to work with legacy code. I agree, however, that new projects should make use of more modern languages. Special consideration should be given to functional programming which naturally fits many science problems and is easily parallelizable due to its "no side effects" philosophy.
It's called Scheme.
Meta will eat itself
They ditched those line length limitations, special columns etc. twenty years ago. I suppose that is the burden of being the oldest computer language in use today: lots of people evaluate it on the basis of what the language was way back when they learned it.
In my opinion, yes. I am an undergrad Physics student (senior) and had my first contact with Fortran in my third semester, in a course called Computational Physics I. We learned the basics of Fortran 77/90 and how to solve some numerical problems using it. We also simulated some interesting problems that amazes undergrad students such as chaotic oscillators, Magnus effect in action and a few other simple yet curious systems. I had already some programming experience, but most other students didn't. They got it quite quickly and I think this is due Fortran's simplicity.
Even if you are never going to use Fortran in your own projects, you will stumble on it now and then if you are going seriously into applied and theoretical research field. NASA, for example, has tons of production code written in Fortran and even new codes are written on it. Many many Physics and Chemistry groups around the world have their most important codes in Fortran, and sometimes they use clever hacks to make the code faster, so a minimum understanding of it is necessary. I work with a Computational Chemistry group and much of the code they still develop, even for new applications, is Fortran. It is good and solid code, they are very experienced on it, and they are not willing to change to another technology so easily.
As a first language I don't know if Fortran is the best, maybe Python or Java would be my choice in this case, but it is definitely worth learning.
> It's also very easy to write simple programs in it.
99% of programs are not simple any more...
> No way I'd use Python for serious large data set numerical calculations.
No way I'd us Fortran for serious large data set numerical calculations...
First I use Python - it is fastest to write and debug and has advanced data structures that simplify algorithms...
What good is that my program run one day shorter if it took me 2 weeks more to write and debug...
If I need to optimize - I am moving the internal part to C - it optimizes almost as well as Fortran...
There is Also NumPy ...
The key thing is that it is algorithms what are more important - and these are easier to write/learn
in Python - so it students should learn Python first and only some need to learn fortran..
Are you serious? Python?
I am somewhat a Python fan boy. I love it. Its freaking wonderful for prototyping and really has a great, natural flow that reminds me a lot of pseudocode I might just invent on a napkin. Great language. But its also a factor of 30 times slower than a compiled language like C.
(http://www.osnews.com/story/5602/Nine_Language_Performance_Round-up_Benchmarking_Math_File_I_O/page3/)*
And Fortran is able to do optimizations (due to differences in the language for evaluation of expressions) that C is unable to do. This has to do with guarantees of ordering that Fortran does not give that C does. My point is that Fortran is even faster than C. Why do you think its still around?
The physical sciences aren't using a fast language because they are bored, or obsessed with speed for the hell of it. They use them because the problems they solve are typically deep into polynomial space, like O(n^3) or O(n^4). Having something 30 times faster means they can run 30 simulations instead of just 1. It makes a big difference to them.
I think the author of this article has lost some of this perspective.
That said, what this article should have tackled is, what do we want to teach engineering students about computer science? Right now, they take a class that teaches them C++, Java, Python, or whatever. They get some procedural programming skills with maybe a little tiny bit of object-oriented stuff (without really covering OO fundamentals IMHO, which are a more advanced topic) and they are thrown into a world where they are writing code in C for embedded controllers or Fortran for computational codes. As a result, there is a huge body of code out there written by people who know how to get the job done, but don't exactly write code that is very maintainable. They relearn the lessons of CS he hard way over 10-20-30-40(?) years of experience. Are we really giving these young students (who are not CS majors) what they need? What kind of curriculum would be ideal for someone who is going to end up writing code for something like a robot control system in C?
* I didn't really look too closely at this particular source, but I've seen numerous benchmarks all saying the same thing. If you want a surprise, go look at how LISP stacks up compared to C. It is better than you think.
I did my graduate studies in a university electromagnetics lab. Two of the professors main research area was FEA. By default, we still ended up learning some even if it wasn't our research area. Most the students were pro Matlab, where as the professors were pro Fortran. As a result, if you were doing FEA for your research, you were learning fortran. If you are doing small simulations, then go ahead and use Matlab, since it will be easier to code and debug. Once you start creating 3D meshes, the number of unknowns becomes huge. At that point a compiled language is a better choice. At least fortran has complex numbers native to the language, so its implementation is a bit more elegant than say C/C++.
IMO universities should be teaching core principles and methods, not attempting to impart up-to-date job skills.
If you are going to teach FORTRAN because it's of use in the real world, then why stop there? Why not also (god forbid) teach .NET. JavaScript, C#, etc. May as well teach them Excel macros and how to interact with Microsoft Clippy while you're at it.
No!
Teaching programming should be done in a langauge that imparts the principles easily and teaches good habits. You could do a lot worse than Pascal which was often used in this role, or maybe today just C++. I'd argue against Java and scripting languages as the core language since they are too high level to learn all the basics. You could throw in Perl, Python or any modern scripting langauge as a secondary, and for a Computer Science (vs. Physics, Engineering, etc) it's appropriate to teach a couple of other styles of programming - e.g. assembler, and functional programming.
While used extensively in a number of scientific research programs, it isn't used commercially in any great amount, if at all. Unless the student is planning to work in an area where the language is used, there aren't any great benefits to knowing it. College should be more about leaning the discipline of software engineering, not learning a multitude of programming languages. C or Java serve that purpose perfectly well and have extensive use in the non-academic world. It it is needed at some point, learning it won't be terribly difficult if one is already conversant with other languages.
I used fortran 30 years ago, stopped using 25 years ago, and, outside of a few PhDs who use it where I work, nobody uses it for anything.
Nail guns have been around for a while, but a lot of houses still get built with hammers.
If a simple tool does a job efficiently and effectively then why "change for the sake of change"?
I'm a fiscal conservative, it's a pity we don't have a political party anymore
I am a manager in a highly technical organization that relies on computer codes to do our job. In my experience, there isn't ENOUGH FORTRAN teaching in the college level. Maybe its location based, but most of our new-hires (we get most from the northeast, but still get a noticeable amount from as far away as University of Washington, Univ of Hawaii, and USC) actually are NOT taught FORTRAN and instead are taught something object-oriented, typically C++ or Java. I know for a fact that Penn State suggests C++ for all undergrad engineers (FORTRAN is offered though - the classes hold less than 50% total students than does the C++ course). In my organization we also have a 'double-hump' age distribution: lots of people ready to retire (or could have retired 5 years ago...) and lots of people who are within 5 years of their first day on the job. This creates a problem of knowledge management; our new guys need to know the details of the FORTRAN code they are using every day to the extent that our ready-to-retire guys know it, and fast. If they are not taught FORTRAN, this creates an even larger learning curve for them which isn't desirable. So one option would be to 'rewrite the code for the future generation'.. We definitely do not have the resources to rewrite our workhorse codes that have been in use and development since the 70s. I don't know if an organization as large as Microsoft could rewrite Windows in a new language. Also, we can't retire our old codes because they are still actively needed to respond to emergent issues (it is easier to maintain the codes than it is to make a new model to be inputted into a new code). So, our hands are tied (mine specifically!) and my organization actually needs MORE FORTRAN programmers coming from the university just to maintain the status quo.
Fortran hasn't had those limitations for decades - Fortran 90 and later are ideal languages for expressing mathematical algorithms and crunching numbers
Fortran hasn't had those limitations for decades - Fortran 90 and later are ideal languages for expressing mathematical algorithms and crunching numbers. The handling of arrays, matrices are just what they should be.
I wouldn't use Fortran as a general purpose language - having used Python for more 10 years I shudder at using Fortran for string handling, databases, user interfaces and more - but as a tool for expressing math it's the best, and also the most widely used. The alternative would be matlab (much of the syntax isn't that different).
I'm an ME student at Rose-Hulman and we're taught Matlab in two quarters. I've used it for a few other classes, though I've also elected to take a couple of Java courses so I can't say I learned anything from the Matlab courses beyond Matlab syntax.
As for Python, I've never used it, but I've heard it's basically pseudo-code. If Python isn't likely to be used by the students in a real job, I don't see why you'd teach it to them. It makes sense to use for an introductory CS course with the intention of then rapidly teaching students Java or C or something, but if one class is all students will have to prepare them for when an employer asks them to write up a quick program, I'd give them a full immersion with the 'real thing'. In my Matlab courses you have the whole array from students that could just as well be CS majors to those who never feel comfortable with programming. If you teach them Python, only to tell them anything they'd do at work would be more complicated, the latter half of the students would never feel ready to program on the job.
My webcomic
The Mayan Long Count Calendar turns over in 2012. Mayan date 12.19.19.17.19 will occur on December 20, 2012, followed by the start of the fourteenth cycle, 13.0.0.0.0, on December 21st.
The event was first flagged by megalith scientist Terence McKenna. The end of the thirteenth cycle would break many megalith calculations — which conventionally use only the last four numbers to save on standing stones — with fears of spiritual collapse, disruption of ley lines, Ben Goldacre driving the chiropractors back into the sea and the return of the great god Quetzalcoatl and the consequent destruction of all life on earth.
Megalith programmers from 4000 years ago are being dredged up from peat bogs and pressed into service to get the henges updated to handle the turnover in the date. "It could be worse," said one. "I could still be programming COBOL."
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This was clearly written by someone who doesn't actually do any scientific computing.
As hard as it may be for some CS-types (myself included) to believe, Fortran is still the language for scientific computing. I've worked at flight simulation companies for two different companies (and 5 different groups) for the last 15 years. The math required to simulate a flying aircraft in realtime is ungodly hairy. It also has to get done fast. We typically have 50 or so different simulation models (plus all the I/O) that have to run to completion 60 times a second. That's about 17ms, or 8ms if we want %50 spare. In addition, for a realtime app like a simulatior it needs to take the same time to execute every time (no runtime dynamic allocations, GC, etc.) or things "jitter".
Everywhere I've worked, with the exception of Ada mandated jobs, had this code done in Fortran. Yes that includes today. We are today writing new Fortran, and we are not alone. When we request models from the aircract manufacturers, they come in Fortran (or occasionally Ada). Fortran is still, and quite possibly always will be, the language for Scientific Computing.
Suggesting non-CS math and science students learn some other programming language instead is just wrong. Further suggesting that it should be the author's favorite hip new interpreted languge is just laughable.
I spent an entire summer doing exactly that (data entry on an 029). I spent every penny I made on AD&D :-)
There are only 6,863,795,529 types of people in the world.
Freefem++ (GPL code) however is C++ and solves PDE's by writing the weak formulation. I never saw fortran recently.
Even the famous VODE fortran code to solve ODE's has been rewritten to C++. It's now called sundials (BSD code), and guess what, there is a python implementation, pysundials.
IMO universities should be teaching core principles and methods, not attempting to impart up-to-date job skills.
IMIO, Fortran is not about "imparting up to the date job skills" as much as showing students a powerful tool to accomplish a high-level task that they'd otherwise have to learn more programming to do - and that takes from time spent with the science they are trying to learn.
Just because something is real does not make it a "trade skill" with al of the scorn you heaped upon it bountifully.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
Unlike Pascal, Prolog, Smalltalk and the rest of the fad languages, Fortran is still here, and it will still be here when Python is long-forgotten.
I would suggest teaching them C, but it may be too complex for a first language.
Python will be 20 years old soon and is used in many, many contexts. Whatever your opinion of FORTRAN or Python's applicability for engineering students in particular, calling Python a fad is disingenuous.
I'm an engineer with a large aerospace firm. All our major programs are in Fortran and have to be used, modified, and maintained. I remember a few years ago we hired a new grad from MIT; she had studied Basic, Pascal, and C; so of course we had to teach her Fortran so she could do her work. The engineering world is heavily dependant upon Fortran, and to not know it puts you at a huge disadvantage.
Except I'm pretty sure that there are modern languages and libraries that can handle this without Fortran. I don't have much experience with it myself, but I'm pretty sure that's exactly what MATLAB is for, for one.
Dude, what do you think the libraries Matlab uses are written in? Check out netlib to get an idea, ATLAS, BLAS, LAPACK, LINPACK, etc. Matlab stands on the shoulders of the giants of scientific computing (implemented for the most part in Fortran).
... You're WAY behind the times.
I got a buddy who is an astrophysicist and worked at NASA, and he tells me his department ditched FORTRAN years ago in favor of Python+Numeric.
I hear you about the need for badass number crunching tools. It's your assumption that only FORTRAN fits that particular bill which is erroneous.
Not to say that FORTRAN doesn't have its use. It's just that other tools have since become better at some of those.
Python Numeric homepage. Check it out.
-- B.
This sig does in fact not have the property it claims not to have.
The Elders feel that if they had to go through it, so do the young'uns gol durn it!
Seriously, though - as far as I know, Fortran has always been the language of those humonguous numerical models because of its optimizations with regard to array handling. I think it makes perfect sense as a first (or second) language for science majors. However I imagine the person asking this question is likely one of the young'uns being forced to learn it; and that person doesn't really have the perspective as to *why* this is so. After all, he's been hacking around in C and Python for years - they're in his comfort zone and have been good enough for the sorts of things he's been dealing with.
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...And we liked it.
I'm a scientist who does the bulk of his programming in Python. Numpy (the numerical package for Python) runs at only a 30% overhead over C. When that's not fast enough, I drop into C/C++ for bottlenecks and wrap that back into Python (using the Python C API more often than swig/boost). When there's a great Fortran library that's fast and battle tested, I wrap that into Python using F2Py--and I don't even know that much Fortran.
Just like it's good to know more than one spoken language, it's good to know more than one programming language. It's a mistake to think one programming language fits all needs. That said, it can also be helpful to know one really well, and others enough to convert them into your primary language. For me, Python fills that role very adequately, and I would highly recommend it be a part (read: part) of the undergraduate programming curriculum.
Matlab stops being a 'slow' language once you learn how to use it.
Matlab stands for MATtrix LABoratory. It loves to do matrix algebra more than any other kind. The worst offenders I see are people that try to use for loops for everything.
for i=1:10
y(i)=sin(i);
end
is much slower than:
y=sin(1:10).
And it just scales up from there. There were only a very few times I've ever had to use for loops and that's because of memory issues (on Win32).
Unless your current state depends on the previous one, there is no reason to use a for loop.
-
I never learned FORTRAN, but I make my living on Matlab. Matlab is good for quick turn around. If I need to make a script NOW that does X for me, I can turn it around in a few minutes. No compiling, etc. If I really want speed, I can write MEX (compiled) code.
Back when I was in college, I maintained a Fortran77 program that was a custom built TCP/IP client-server system. But wait! F77 didn't know what a socket was! right. The network code was written in C and compiled into object code which was directly linked into the F77 project.
Great. So there are these massive libraries written in Fortran to do wonderful things. Best case scenario is you can link them directly into your language of choice. Worst case, call them from the scripted language of your choice with a wrapper
Bottom line? Program in what you are comfortable with. Would your peers would frown on your efforts if you learned anything but ALGOL? Fine. Use ALGOL. There are valuable lessons to be learned in any language. Strong vs weak typed, functional vs object oriented, structure, best practices
The surest way to corrupt a youth is to instruct him to hold in higher esteem those who think alike than those who think differently. - Nietzsche
"Glory is fleeting, but obscurity is forever." - Napoleon Bonaparte
It's definitely not a language for amateurs in the sense of people who like to fiddle with the system, are interested in how the compiler works, or who just want to make gee-whizz web mashups. It's a language for people who don't care a rat's *ss about computers or programming, but who need to get their calculations done without wasting time on fiddling with pointers and who need reliable answers without being bitten by silent array-boundary overflows to boot. So Slashdot might not be the best place to ask for an opinion.
Besides, most of today's numerical libraries (BLAS, LAPACK, ATLAS, EISPACK, FFT) are written in Fortran. If you want to use them, you could do worse than learn Fortran.
True, it's not a language you'd want to do sophisticated datastructures in, or tree-searches or text-processing or payroll accounting or database manipulation. But especially chemists (and to a lesser extent physicists) have more call for numerical software than they have for non-numerical software.
So no. It's not at all ridiculous to teach Fortran as a first programming language to non-computer-science students. Alongside Matlab (or Octave or Scilab) it will do fine for chemists.
That was my thought. An general purpose, interrupted scripting language for scientific computing? Say what? I've never seen anyone do any sort of scientific research programming with Python, unless it was a control script or GUI interface to something written in Fortran or a C derivative. What's the point of running on the kind of huge multi-CPU systems they use for scientific modeling, if you're going to use a an interrupted language?
I don't need a million points of light, just two points of multi-mode fiber and a 10 Gig-E router.
Ok here goes:
Should science undergraduates be taught Fortran? Yes
Should it be the FIRST language, NO, not any more
So much of science, especially physics, is done on computers now - as both a software engineer and someone transitioning into Physics I ran into many people that had severe problems learning FORTRAN and applying it to problems. I really feel science students should have a couple of general courses in programming in C before moving on to other languages or even programming classes specific to their science. Here's the reasoning:
A) Science students need to learn programming basics away from the pressure of also learning within their science field at the same time - if your learning the science at the same time, the actual basic programming concepts get lost and muddied with the science being learned.
B) It can allow a science major to learn the concepts of programming in a general purpose language without muddying it with a lot of OS specific, library specific, attitude specific usage (aside from the compiler use)
C) There is a C compiler on almost every system you will most likely use in your lifetime as a scientist
D) C has enough structure to be "readable", but doesn't have so many constraints that it has problems being fast
E) C syntax is the basis for many other programming languages including Python and Java (both of which are heavily used in science as well)
and finally if a science major has a good understanding of programming concepts they can know what to look for when they're learning a new language (whatever it might be) - they will know that they have to learn the syntax for control structures in the new language (for, while, if, etc) as well know they'll have to find out more esoteric language specific concepts like how do I create functions and libraries? How do I use them?
ALL THAT being said, yes FORTRAN is a critical language to know with the sciences, because of the availability of libraries. HOWEVER, many of those libraries are now available in other languages and/or can be called from a different language via an abstraction (a concept that would be taught in a more general computing course)
Evidently, you don't go out that much. People use interpreted languages in science all the time. At least I do. Where I sit, there is quite a bit of spare capacity waiting. When I try to figure something out it is way more reasonable to write a program in three-four hours and have it run overnight than to write it in two days and have it run in (say) thirty minutes.
I would like to die like my grandfather did - sleeping. And not screaming in terror, like his passengers.
It doesn't matter what language Engineers and physicists learn as undergrads, the language isn't what matters. It's the numerical methods that matter.
In fact, I think it's good that they learn FORTRAN because so much of the code they'll work with in industry is written in FORTRAN.
In my first programming class we spent the vast majority of the time learning numerical methods like taylor expansions and how to write them. In the very last few lectures we talked about what OOP did one homework assignment where we wrote and used a class. This was the right way to go because for an engineer, because the mathematics are far more important than the structure.
I've seen aerodynamic, structural, and acoustic calculations where the mathematics make your head spin, but it only takes two or three functions to write the numerical method to solve the equations. This is the kind of program engineers need to be good at.
Not all scientific programming is heavy duty number crunching -- I'd suggest that only a minority is. My postgrad research proposal (involving Monte-Carlo simulation) said that I'd use Python for the framework and would swictch to C/C++ where Python got too slow. Python never did get too slow, and I never needed a single line of a C-derivative language. I also used Python for some continuation of Robert Axelrod's classic work on game theory (is that science, math, or psychology?).
Anyway, you're making the classic assumption that undergrads are taught the language for the sake of the language; that it will be the language they will use in the real world. Rather (even in the sciences, not just in computing) it's programming that's being taught, and the language is simply a means to an end. It's futile to try to double-guess what they will be using when they get out into the real world; even if you look at what's in demand now, no language has a monopoly and the language-of-the-moment will change anyway during their career. The person who can program Python will pick up any other procedural language quickly enough, because Python has pretty much all of the relevant constructs, and Python has the advantage of being easy to learn. FORTRAN certainly isn't easy to learn (I did my undergraduate project in FORTRAN), and even the newer versions of FORTRAN that have things like Object Orientation don't present the constructs as clearly as modern languages such as Python. I agree that Python is unlikely to be the only language they'll ever need (don't try saying that on the Python mailing list, though!) but it's at least a contender for the best first language.
Quidnam Latine loqui modo coepi?
One thing that Python doesn't teach is static typing. I'd say having 2 languages (one static typing, one dynamic) and talking about the advantages of both. Hell, you could even use Boo as the statically typed language, which is very close to Python.
A resounding YES to undergrads being taught FORTRAN. I am a graduate student in Meteorology and FORTRAN is alive and kicking in the meteorological community. It is a vital part of many of our programs and models. Perl and Cshell are also very important but I wouldn't be able to do major parts of my thesis without the aid of FORTRAN. The undergrads at my graduate school are required to take FORTRAN (especially if they are in the met program) and they use it in their upper-level core classes. I wish I'd taken the FORTRAN class at my undergrad so I wouldn't have had to catch up during my thesis. Knowing FORTRAN definitely helped me grasp other languages faster.
âoeQuestion with boldness even the existence of God.â - Thomas Jefferson
If it were a computer science course then I'd say that something in the Lisp family, something in the OCAML or Haskell family, and somthing from the Prolog family. I agree that they're likely to encounter static typing at some point but this isn't a computer science course so it shouldn't try to teach everything, and static typing shouldn't come as too much of a shock. Heck, my first language was FOCAL, and I managed to learn to cope with it.
Quidnam Latine loqui modo coepi?
Fortran is very important in the world of modelling and high speed computation. When I was an undergrad Fortran was taught for the physical sciences but the computer science dept refused to teach it so it was being taught by some geophysical modellers. I'm not sure that the university even offers Fortran anymore.
However, frustrated by that, the dept of physics and astronomy now has two courses in computational physics (both in Fortran) taught by modellers from the department. They deal with real world issues (well, real world modelling issues when applied to a spherical cow right?). Only one course is mandatory but both courses are very popular.
For myself, I use several modelling programs that are purely Fortran that I've had problems dealing with. I'm glad I did take a bit of Fortran though I am much more fluent in other languages these days. In fact my wife, in the private sector, has proprietary software that they use for modelling digital elevations and gravity fluctuation that is written purely in Fortran as well - simply for speed. Until someone invents a real quantum computer, I don't think Fortran in the physical sciences is going anywhere.
A program language should be taught on the basis that it teaches the student programming and not that it jigsaws them into the world of business. I student that can transcend languages is likely to be a better programmer anyways, as they'll have more tools and models with which to get a task done. Note that some languages are more suitable than others. For example, Python is useful in the academic setting, where a quick turnaround is important for meeting deadlines and finding solutions. In the business world, languages like C/C++/Cobol/Java might be more suitable for performance or legacy code. That being said, any student interested in programming should be taught languages that are based on different paradigms like structural, functional, object oriented, or shits-n-giggles code (intercal, befunge), that will ultimately enable the student to learn other languages which were not taught, more easily.
My favorite class with respect to this was assembly. It was fairly easy to pick up and taught you how the computer interpreted commands at a relatively low level.
Lets say that you are working on a project to evaluate the effects of theoretical gravity waves through a nebulae. You have a choice
And oh, you have to publish results in 2 months in order to get your next NSF grant.
Yes, the new code might be all object orienty, and you can use the latest IDE to develop in, and you can hire a bunch of fresh young (cheap) grad students that are familiar with the latest python, perl, C#, etc. development and they can bang out thousands of lines of code a day. But are you really really sure that that freshly written eigenvalue routine produces the correct result? Has that new compiler been tested on the super-computer you have limited access to, can it even take advantage of all the power of that system?
I'm not saying that FORTRAN compilers are not bug free, but I suspect that the chances of finding a basic compiler or runtime library bug is lower in FORTRAN then in say Perl 6.
A couple of years ago my son spent some time doing some intern coding work for a private atmospheric research group. The group was/is doing bleeding edge research. My son was helping out one of the researchers in updating code that handled 2D models to 3D models. All the code was in FORTRAN and there was no desire to move away from it.
That's because a married man has to spend so much time trying to figure out how to keep his staggeringly complex wife happy.
Say what? I've never seen anyone do any sort of scientific research programming with Python
My research lab (satellite data processing) is all python and the psychology department in my school is thinking of switching over to python. There are tons of great scientific computing libraries either written or wrapped in python. It's a great language for social science research because it's so simple and clean, and the libraries make it easily extensible to the hard science crowd. I'm working with pretty big data sets at the moment and don't find python that slow in comparison, plus it simplifies so much of the data organization/sorting/filtering tasks.
open source modern art: laser taggi
I guess it depends on the type of scientific computing you are doing. If you need a cluster to crunch numbers, don't use python. However, there are huge areas in scientific computing where: 1) speed isn't the primary concern or 2) languages like python are fast enough. Also, python has some pretty significant scientific computing tools like scipy (see http://www.scipy.org/), visualization using matplotlib (see http://matplotlib.sourceforge.net/ ), etc. I personally know a lot of people doing scientific computing and general research who use python.
If speed was the only concern, people wouldn't be using tools like Matlab, IDL, python, and the like. Obviously, a significant number of people doing scientific computing find these tools fast enough.
My friend at cern working on programs for the LHC has to do everything in c++ or python. So python might be a good one to learn. I love fortran 90/95 its a good language that only has a hint of the unpleasantness that was fortran 66. As, I'm sure others have posted there are some very high performance libraries/compilers for fortran number crunching. But, its not that hard to pick up if you know c/python.
But it was pretty funny taking that FORTRAN class with some cs students who only knew ADA. They were sort of freaked out by its "modern" features and "easy" string handling. It was right then and there that I realized I had dodged a major bullet by not becoming a cs major at the school.
Well.. maybe. Or Maybe not. But Definitely not sort of.
Python? As an intro language? And I thought people were misguided teaching Java as the first (and often only) language.
Second, while some of these scientific programs can run overnight, a lot of them will take a day or more to run, even when compiled and on a super or parallel computer. I don't know of any highly optimized Python compilers for big metal. Fortran is still the number one language for performance computing.
Third, there seriously needs to be major scientific libraries pre-existing for the language to be useful. An added benefit is being able to support more than one floating point number format.
Finally, the number one most important reason that Fortran is used in the sciences, is because everyone else uses it in the field. Seriously, what good is Python if all your prof's and advisor's and boss's programs that you need to maintain are in Fortran 66? It's faster to learn Fortran than to port it all. This is part of the "dusty deck" problem, where decades old libraries still have to be used and supported. This applies to many languages - many languages are popular precisely because they are popular, not because of inherent elegance or suitability.
In the sciences, the students are not being taught programming for the sake of programming, and they're not even being taught to write good programs necessarily. They're being taught to program as a mere tool for the important stuff being taught. Some classes may not even care what language you use, as long as you can read and understand the sample programs and the math library is correct.
Being in the sciences and not knowing Fortran will be a drawback. In some areas it may not be as big a drawback, but it will be there. This is like trying to do embedded systems without knowing C.
one aim should be to make tools that will serve skilled professionals--not to lower the level of expressiveness to serve people who can hardly understand the problems, let alone express solutions.
But shouldn't we keep an eye toward eventually moving into a Star Trek-like future, where anyone can ask things like, "Computer: is there a compound that is superconducting at 50 deg C? If so, what is the formula?" And the 48-core, terahertz processor cranks through sophisticated molecular models to find the answer.
That that is is that that that that is not is not.
I think you are mistaken regarding what most undergraduate science students actually do (they are not maintaining/upgrading old fortran libraries). Most of the high performance capability that undergrads need involves matrix computations, FFTs, convolution, etc., all of which are included in the python numpy/Numeric module (which is a wrapper around fortran libraries, so they're just as efficient). And since they'll likely spend as much time analyzing data as producing it, python + numpy + matplotlib is a perfectly suitable solution.
I'm not suggesting that fortran isn't of value to some scientists in some situations but many science students will never have to touch fortran code unless they're forced to take a class that teaches it. As you said: "They're being taught to program as a mere tool for the important stuff being taught." Which is why it makes sense that their intro language is one that is easy to learn, supports multiple programming paradigms, has efficient numerical libraries, has easy-to-use visualization tools, an interactive interpreter, and can be used as a general purpose programming language. And while I personally prefer python for a high level language, there are others that could serve the same purpose.