After a long research I decided to learn Haskell. It is very unlikely that I will ever be paid to use it, but I am pretty sure that after more than 10 years experience in programming, Haskell will greatly benefit my programming skills and thinking.
There was a recent comment by tptacek in another thread which I agree with: you really only need to know a couple of programming languages before you start hitting diminishing returns in terms of what you can implement. We should focus instead on learning new concepts or new problem domains.
I'm trying to revisit statistical modelling and pick up some machine learning basics over the next year.
and what about domains only tangentially related to computer science, like robotics, semiconductors, or digital music?
or what about domains barely related to computer science, but where coding is an invaluable skill, like medicine/genetics, manufacturing, or aerospace?
consider how many programming languages your average person knows (zero). now consider how many you know. is it objectively worth your time optimizing around that particular dimension within your skills, or are you perhaps suffering from a latent bias you have from the fact that you are a relative expert in programming?
would you rather have a carpenter who knows how to use a dozen hammers, or a wide variety of tools? is haskell a new tool, or is it just another hammer for you? with coursera you have no excuse to avoid stepping outside your comfort zone!
> would you rather have a carpenter who knows how to use a dozen hammers, or a wide variety of tools?
There's a danger in what you're suggesting, in overgeneralizing and never learning too much about one topic. Would you rather have a carpenter who's an okay carpenter, an okay musician, an okay actor, and an okay racecar driver, or a carpenter who's really good at carpenting?
well, my point is a person needs to determine on their own if learning something like haskell really makes them a better carpenter, or if they are just going leveling up their "number of programming languages" XP because that's the main XP they are familiar with.
If I had to pick a point of leverage with which to increase programming skill in minimal time, "learn a new programming language" would be far down the list if two or three for various contexts were already well mastered. "Learn Haskell", almost universally, would be near the bottom.
I agree with you that it is everybody's own decision :) Although from a slightly philosophical point of view: how can one determine what levels are beyond their own knowledge, let alone what amount of effort it would take for them to get there and if it would worth it to do so. An experienced developer can tell a beginner what they could/should learn next to step up, but how do you determine the same for yourself?
On the other hand I strongly dislike the "in minimal time" condition. After let's say 10 years or more in programming (that's me in this case) and you say that the next step one could achieve is something that comes faster than learning a new programming paradigm? My gut feeling is that it will take me about 6 months with a strong programming background. I am not talking about learning Haskell (What could it be: a week or so?) but about understanding FP, knowing (and feeling) the fp design patterns. Depending on the investment in 6 months one probably can achieve that the application of those patterns come as second nature. That's my goal. Two questions:
1) What would give greater and longer-term benefits than that? Learning Reactive Extensions? Yet another ORM framework? Node.js? Those are only tools. One can learn them in some days when a project requires it.
2) What is the rush for? Do you remember the time you learnt OO programming? I would say to learn it properly, in the beginning of your career as most of us do it, required much more effort than to learn Haskell and FP when you are already an experienced programmer. Wasn't it worth to spend all that time to learn OO principles, design-patterns, tools, languages? And if you were stuck in the OO world throughout your career, then I am pretty sure that learning FP principles, patterns and language(s) have about the same effect on your future than OO had on your present expertise.
I think that saying you can 'learn Haskell in a week' is really short sighted. You can learn to parse a Haskell program and write a guess-the-number program in a week, but learning how to write good Haskell is going to take months, if not years, especially if you want to do fancy things. Hell, I'd guess it'd take me a month or two just to learn the ins and outs of the lens library and I'm already a good Haskell programmer.
> 1) What would give greater and longer-term benefits than that? Learning Reactive Extensions? Yet another ORM framework? Node.js? Those are only tools. One can learn them in some days when a project requires it.
I think that unless something is completely and utterly trivial, you can't really learn it in 'some days'. You can get enough of an understanding of it to solve a small-medium problem with it, but you can't actually learn it. If you want to learn something really weird, try playing with higher-order polymorphism, type theory, dependent types, or something that's not 'yet another OO language/framework'.
> 2) What is the rush for? Do you remember the time you learnt OO programming? I would say to learn it properly, in the beginning of your career as most of us do it, required much more effort than to learn Haskell and FP when you are already an experienced programmer.
Not for me. Really learning Haskell as an experienced programmer took as long as it took to learn Python as a novice, and I've heard similar reports from other people. I certainly agree that if you know, say, Java, learning C# probably isn't going to maximize your 'skill increase per time'. But saying that going from Java to Haskell, or even farther to something super-weird like Agda or Forth or Prolog, is just as easy as going from Java to C# is just wrong.
Personally, the reason I'm sticking with Haskell as my current thing-to-learn as opposed to jumping to other things is that I've hit that point in the curve where the language is really opening up to me; I had a small problem recently that I wanted to solve, and I was able to use some really cool techniques that don't really have simple equivalences in other languages (the pipes library, if you're curious) to solve it in a nice way.
> I think that saying you can 'learn Haskell in a week' is really short sighted. You can learn to parse a Haskell program and write a guess-the-number program in a week, but learning how to write good Haskell is going to take months, if not years.
That was exactly my point, sorry if it wasn't clear.
> Really learning Haskell as an experienced programmer took as long as it took to learn Python as a novice, and I've heard similar reports from other people. I certainly agree that if you know, say, Java, learning C# probably isn't going to maximize your 'skill increase per time'. But saying that going from Java to Haskell, or even farther to something super-weird like Agda or Forth or Prolog, is just as easy as going from Java to C# is just wrong.
I am not saying that the "Java after C#" learning curve is the same as "Haskell after C#". It isn't. But I believe that the general experience of abstract thinking that one learns in many years must give an advantage over a novice learner. I am not talking about a script-kiddie who spent five years hacking code, or somebody who has the same one year experience 20 times instead of real 20 year experience. I believe that if you spent your development life actively then you must get a new concept easier than a beginner. And not only that. Concepts of a paradigm or language leak into others. Linq in .Net leverages "monads". Eric Meijer, one of the creators of Linq, loves Haskell and they borrowed ideas from Haskell. Now, if one is a "too pragmatic" programmer, they can use Linq for years successfully and never get closer to understand monads. However is one takes the time and looks behind the curtains, they got closer to understand at least this one concept of Haskell. And I am pretty sure that over let's say 10 years you are exposed to many ideas in some way if you keep your eyes open.
As I said, my gut feeling (can't tell how good the estimation is) is that in about six months I "get Haskell and fp". But it's not black or white: obviously spending 6 more years in the fp world would make a difference. There must be a decision made (and here I agree with gfodor) when the further gain doesn't justify the investment. I won't stop at 6th month if I don't feel the power yet :)
when I said "minimal time" I meant "minimal time per unit of skill increase." sorry this wasn't clear. the whole point is if your goal is to improve your skills as a programmer you should be optimizing your time to learn things that provide the largest skill increase per unit time.
as far as your first point goes, I agree that some type of random walk part is important to breaking out of local maxima. you can look to social cues for what might be a good thing to start learning about that is outside of your comfort zone. generally speaking since software is eating the world a good litmus test for me is if the domain seems to be amenable to automation and is also not as far along the curve as more "easy" domains to dive into like the latest newfangled way to build a web based CRUD app.
I'm heads down on golang right now and will continue to be so. I never quite acquired C - wrote plenty of code in it, but it was always a struggle. Go's just above the threshold where my mind will take it wholescale (ala Python) and it gives me the ability to write simple code and generate cross-platform binaries from it.
One app: web, windows, mac, linux. I know that can be done with other tools too, but this is the one I've chosen. I like SQL too: old guys like weird tools!
Having learned perl, ruby and python (these are all incredibly similar), and then Clojure, I've found that I really like the functional paradigm. It helped drag my attention back to thinking about data structures and functions to act on that data a lot more than a ton of bad OOP examples ever have. I'm actually excited to program now instead of feeling like, "Okay, this mess of classes I'm making is going to pay off some day..."
One negative/positive is that I now kind of recoil in distaste when I find OOP-y code that's seemingly done for the sake of jamming code into a class instead of using generic functions and data types. It's funny that there's a large swath of not so useful monad tutorials, because there's an absolute mountain of examples of classes/objects that don't make any sense at all. I didn't mean to make a tiny rant on OOP. Sorry about that.
As someone who has been using a lot of dynamic languages, I'm really interested to find out how a static type system can help me program better software.
If you're learning Haskell, be prepared to feel like a beginner for a while.
I had great learning it. I usually pick up languages fairly quickly, but Haskell eluded me for more months than I'd care to admit. There is a great community of very smart and friendly people who helped me on IRC, and a couple of pretty good books -- http://learnyouahaskell.com/ and http://www.cs.nott.ac.uk/~gmh/book.html.
I enjoyed the experience, and I certainly feel like a better programmer for it. But damn I felt daft for a few months!
I am looking forward to that experience :) Besides the technical reasons (nice syntax, pure fp, strong typing, ...) I chose Haskell to learn functional programming because it has a very good community and documentation. It's like the entire Haskell ecosystem's been built to teach FP. Actually that was kind of the intention when Haskell was born as far as I know.
After programming for 30 years (and upwards of 20 languages) I've come to believe that you really only "need" to learn 4 languages to complete your Jedi programming skills and become a master. You need one each from the following categories:
"Machine" language - this is anything turing complete that's close to the hardware, ie that forces you to think about and understand the underlying circuitry. Candidates: Assembler, C.
Static/Imperative "Object" language - put this one off for as long as you can, for it is easy but not simple, and will ensnare your mind with the belief that you are special because you are among the elite priesthood of programmers who can grasp levels of complexity mere mortals dare not even dream of. Down this path lies years of frustration, all in service of the darkside. Chances are that this category will be forced upon you first, by naive, shortsighted fools who little realize the evil they are spreading. Learn only what you need to disable the tractor beam and escape with the Deathstar layout, so that when the time is right a well planned rebel assault may remove this abomination from the universe.
Candidates: there are no candidates here, as that implies choice. One of these languages will be heaved upon you whether you like it or not - C++, Java or Visual Basic (if the darkside is particularly strong in you).
Dynamic "scripting" language - this is for that category of problems where most of the needed abstractions are well understood and well tested. Using them should involve as few words as possible.
And finally, what should be every programmer's last language,
A "language" language - these are usually known as Lisps, but I think both Alan Kay's original bootstrapping Smalltalk and Forth are acceptable here. The key feature is having a small core of concepts that can be infinitely composed into higher abstraction commands that are treated no differently from the compiler's perspective. Once you have this power, all of the interesting behaviours of languages like Haskell, Erlang, Prolog, etc, are available to you.
Candidates: Scheme/Racket, Common Lisp, Clojure, Smalltalk, Lisp.
I spent the last year doing lisp as much as I could, and I've become a right convert. I've got some C and python down already.
This year, I am currently torn between:
-Haskell (to go full blown functional crazy)
-Smalltalk (to go full blown object crazy)
-Javascript (to finally write some stuff for the web/browsers)
- Java (to sell out and lose the will to live?)
Any advice is more than welcome. I'm probably looking for the "programming language that changes the way you think" aspect, since I've already got a paying job...
PiL will present examples that will change the way you think in several different ways, which you will then be able to leverage in any other programming language (most of the time, depending on how restrictive the language is).
You have Lisp knowledge, so maybe Haskell is not the best candidate for "a new way you think". Given your background I would say you probably would enjoy Scala more than Java (targeting the same JVM). I am not sure if one can learn enough from Smalltalk to justify the effort it takes to learn an in-practice useless language. If you don't speak JavaScript yet, that's a good candidate, especially if you use your FP experience in it and not just go the OO way most people do.
You have more experience here thanks for correcting me :) What I meant was that they are not two very different worlds. I myself picked Haskell over Lisp hoping to gain the benefits that I would get from Lisp but with some advantages.
Would you also recommend the other way around? Learning Lisp after Haskell? I don't mean the syntactical differences or the real-world usage. Solely the "way of thinking".
Actually Haskell and Lisp a very two different worlds. Some basic abstractions are shared, but Functional Programming tends to be much much more advanced in Haskell. Haskell is the standard language for some branch of functional programming and has a good/great eco-system for that. It's main use seems to me to advance the state of art in Functional Programming and applications of it.
Lisp OTOH is a multi-paradigm languages with much more emphasis on OO and interactive development. Lisp is much more diverse and favors a very different programming style - slightly more pragmatic. Lisp had its main application domain in AI, but nowadays it's a bit more diverse - often it is used by individuals or small teams. One of the larger applications is the flight search engine of Google. Others are in music composition, planning and scheduling (satellites, people, logistics, ...), etc.
There are so many languages I would like to learn :
- Ada : everybody raves about it but nobody uses it ;-)
- Python : for everyday hacks, it's portable, simple and it's not Java ;-)
- Assembly : it's the root of everything
- C : my mind is overflowing with Arduino projects
- C++ : I'd love to create ISX extensions and make private bots for some MMO
- Prolog : just because
I will probably settle for Ada if John Barnes publish its book at the beginning of 2014.
Can someone make recommendations for me? Here's what I already know and what I've built with it:
- Java. My first real programming language, learned in college, used for a year and a half in enterprise work and Android, got pretty good at it, but I learned
- Objective-C for making iOS apps and I never want to write in Java again. I'm also learning C just to understand Objective-C more but I have no plans building anything with C.
Basically, my current interests/goals for learning a new language are:
- Develop a new way of thinking.
- Learn some great engineering practices.
- Build products (software) that solve real-world problems. I'm not likely to learn a new language if I can't build anything useful with it, that can potentially sell and make it as a consumer startup.
- Become full-stack. I can already easily build an iOS app (I have no interest in building responsive websites) but I find myself still having to rely on something like Parse. Which isn't so bad though because it saves me so much time.
I guess that narrows my choices down to: Ruby, Python, Go, or something else, but I'm not in a position to identify which poison is best-suited to me. I just want one that I can be really good at and meet most if not all of my goals. Any thoughts?
Very pragmatic approach. C# if you are ok with the Microsoft stack, or F# if you are a bit more advantageous and serious about the "new way of thinking". Python is also a great investment to solve real-world problems. And don't forget JavaScript. It is not just a browser language any more: there is node.js for the server side and it is the common language of most mobile frameworks that are multi-platform targeted.
You cannot go wrong with any of these. So have a look at code samples and spend some time browsing the web-sites about all of them then choose the one that appeals the most to you.
Python - I'm doing far too much stuff in PHP just because that's what I know, seems to be fairly simple to learn as well, and quick which should help in the $dayjob efficiency.
I learned Dart and TypeScript this year and both were fairly trivial to learn and use. The learning process improved my JavaScript skills because I had to think about JavaScript in new ways and got me ready for ES6 (For example, the discussions about iterators in Dart and ES6 was interesting.) Next up is ClojureScript, if I can get over the syntax.
I've started to play with Nimrod and I will definitively continue in 2014. Macros are not always easy to use but they are clean and powerful (I'm mostly a C programmer ...)
I'm picking on you, but could just as easily picked on most the other replies.
Your answer to this topic is only interesting if you explain why. Even a very brief explanation will do. As it happens, I've never heard of Elixir. Try to make me curious enough to google it.
In my case, I'll likely not try to learn any new language this year. But I am going to brush-up on the mathematics that has gotten rusty over the years. Partly because I used to like math, but now rarely get to use anything beyond basic algebra. And partly to position myself better to help my kid with homework.
I friend recommended Elixir to me, but I would rather learn Erlang properly. Erlang has a small community already, why to learn a language targeting Erlang VM that has even smaller community and much less documentation?
I'm trying to revisit statistical modelling and pick up some machine learning basics over the next year.