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I've been wanting to get into a pure-OO language for a while now, but I'm put off by the fact that they all seem to demand an IDE and I can't find any good tutorials that aren't in video format.
I'm happy to use an IDE later, but I don't want to learn the language through one. What I'm looking for is a simple console interpreter or command-line compiler such as gcc, ghc, ghci and the python IDLE (yes, it's an IDE, but it's so minimalist that it may as well just be a commandline interpretter). I find that I learn a language faster, better and more comprehensively when I'm not trying to grapple with an IDE at the same time. So please, don't tell me that squeak is the only way to do it :P
I'm also looking for tutorials that are presented textually rather than visually. Again, I learn faster when I can stare at a page and read someone's sentance over and over tossing and turning it in my mind rather than having to pause a video, take it back 10 seconds, press play, do it again, and again, and again.
I'm interested in various languages with various degrees of OO-purity, and I plan to learn them all at some point. Any of the smalltalk dialects interest me, Self (an extreme prototype-oriented version of smalltalk (Very interesting, the more radical the better imo)), strongtalk, vanilla smalltalk (or some implementation which is as vanilla as you can get).
I'm interested in Eiffel as well, the code snippets I've seen make it seem very elegant and I've read that it actually was very innovative (introduced code-contracts and other such things). However I would give preference to a language from the smalltalk camp over one from the Eiffel side because Eiffel at face value seems to be a hybrid between OO and imperative programming. Similarly I'd rather avoid Scala (Hybrid OO and functional) and other hybrid languages. So no C#, Java, C++, D, python etc etc etc. I'm not dismissing these languages because I believe they are bad, it's just that I'm setting out to learn pure-OO and those languages are hybrid OO: Not really what I'm looking for.
Also, would anyone be able to recommend the official books? For smalltalk there's the "Blue book" AKA "Smalltalk-80: The Language and its Implementation". And for Eiffel there's "Eiffel: The Language". I ask because in my experience you can pick up so much by reading books written by the author of the language (see K&R the C programming language), and by reading books in general.
So yes, my questions: What pure-OO language would be good to start off with? How would I go about learning it without having to use an IDE? And is there an associated book written by the language author(s)?
It is not helpful to learn Smalltalk as just another language. You would be missing the point entirely.
Smalltalk's graphical environment is not just an IDE. The core of the system is simply objects. The interface provides various ways to create objects and interact with them. The language is just a convenient way to create messages to the objects. It is secondary to the objects themselves.
In other OO languages, you write your program, then you run it, which creates objects in memory. Not so in Smalltalk. You create objects in memory (e.g. class objects) and then send messages to e.g. add methods. But a class object is only created once, not every time you "run your program".
There is no such thing as "your program", in fact. There is no "main". It's just a world of objects, some longer-lived, some temporary. In fact, in the system there are objects that were created 30 years ago. Literally. The objects are just frozen to disk as a memory dump (a file which we call "image") and unfrozen later (possibly on a different machine).
That image, the world of objects, is the primary artifact in Smalltalk. There is a sources file, yes, but that's just a database of text snippets to not take up so much RAM. You cannot edit this file by hand (objects in the image use absolute file offsets into the sources file). You cannot re-create the system from the sources file - the system was bootstrapped a long time ago and from then on only modified.
It's true that superficially the Smalltalk GUI looks just like another IDE. No coincidence - Eclipse was originally written by Smalltalkers in Smalltalk. But there is the crucial difference that in regular IDEs you just manipulate text files. A text editor is a valid alternative for that. In Smalltalk, the GUI manipulates objects in memory. A text editor can not do that.
And as for what Smalltalk to use, I would recommend Squeak. Very friendly community, very nice environment, and subscribing to the original Smalltalk vision of creating a great personal computing environment for everyone.
As someone who has went through process of learning Smalltalk (at least to a decent degree), I can say that you are taking harder and riskier path, in a sense that some things may take much longer to clear up, or never actually do.
But, if you insist, you can download GNU Smalltalk, for which no GUI is a norm. It also contains all sources of the system written in Smalltalk in a chunk format and you can open your text editor on them and enjoy while slowly reading through the guts of the system.
You could also startup any other Smalltalk, like Pharo, and just stick with a workspace window - this is your equivalent of command line interpreter.
Pharo also includes ProfStef quick interactive tutorial on Smalltalk, which combines text instructions and evaluating Smalltalk expressions.
As for reading, there is Pharo By Example - free book that you can browse, download or buy hardcopy.
There is also a collection of free books in which I would recommend "Smalltalk-80: The Language and its Implementation" By Adele Goldberg and David Robson, if you are interested in the innards and detail of the language.
Late David N. Smith Smalltalk FAQ is also exelent resource.
So, there you go. And take advice, and give in to the Smalltalk IDE as soon as possible, since it makes understanding of Smalltalk much, much, faster.
Richard Gabriel gave a talk recently about a paradigm shift that occurred in the programming language community in the early 90s. He claims that most experts today are incapable of understanding many of the papers from the 80s. He has evidence to back this up. This was the first time he gave the talk, and he expects to give it many times, so I imagine that many parts of the talk will change. At first, he described this paradigm shift as engineering -> science, but then he described it as system -> language. I think that describing it as a shift from systems thinking to language thinking is a better description.
Richard Gabriel is a Lisp guy. (I'm a Smalltalk guy). Lisp is like Smalltalk in that there isn't a clear boundary between the language and the library that it uses. Arithmetic and control flow are in the libraries, not the language. (Well, Lisp has some in the language and some in the libraries, while Smalltalk has it all in the libraries, except that the compiler cheats and hard codes some of them, so there isn't really much difference in the end.) In Lisp, a program is an S-expression, and editing programs is editing S-expressions. In Smalltalk, a program is a collection of objects, and editing programs is editing objects. When you are programming, you are building a system, and you program with the system.
System thinking is different from language thinking. Language thinkers want a precise description of a language. They want a book that describes the whole thing, or (if they are academics) they want a formal semantics for the language. But system thinkers know that as soon as they start to use the system, it will change. They want to understand how the system works, but are prepared to look at the system itself to figure out the details.
These are two ways of thinking, and there are advantages and disadvantages of each. Smalltalk is a wonderful example of systems thinking. I think all software developers should know at least one system that exemplifies systems thinking. Lisp is good. Forth is another old example. Naturally, I think that Smalltalk is great and am happy to help people learn it but I think the importance of learning systems thinking is more important than the particular system you learn.
Unfortunately, learning a system is harder than learning a language. You have to do more than just learn the syntax, you have to learn the libraries, the patterns of naming and of coding, and usually the tools. (Which, if this is a system, are extensible.) That is one of the advantages of language thinking. But systems thinking has long-term advantages, because once you taylor the system to your needs then you can become very productive.
To lean smalltalk syntax, you need to read ONE page of text (see Syntax section on wiki http://en.wikipedia.org/wiki/Smalltalk).
Now, to learn a smalltalk libraries and how to use them, you need to use browser not the text editor, otherwise your will just waste a lot of time.
I think that it is like factor of 10 difference in time, between trying to understand some code by reading in textual format and navigating it using browser and! debugger.
In smalltalk system a living objects could tell a lot about themselves and help you learn how to use them much faster than if you look at it as a static chunks of text, because you won't grasp the idea at all.
I've been playing with Squeak Smalltalk (and its close cousins, Pharo and Cuis) for a while now. There's no better way to learn Smalltalk than by using the system already provided.
I've devised a series of short youtube tutorials ranging in length from 50 seconds to 15 minutes that show how to take advantage of Squeak's ultra-cool features within a few minutes of first starting the system.
In fact, the very first line of code demos the OOP-ness of Squeak. Squeak from the very start
Python is a pure OOP . Actually this is an easy mistake that newcomers make when they come to python.
Python like smalltalk follows the mantra "Everything is an object". So everything inside python is an object, including built-in types. The difference is that python unlike smalltalk and Java does not force OOP as it allows procedural programming. And this is the trap, it easy to assume that makes python less OOP , but being a snake, is so devlish that does not tell you that even functions are objects ;)
http://www.linuxtopia.org/online_books/programming_books/python_programming/python_ch10s04.html
Going back to smalltalk its IDE is the huge deal here, contrary what other smalltalker may believe. If you like me are heavily disappointed with how non flexible IDEs are you are going to love Squeak's IDE. The IDE goes a great deal making easy to navigate through all the libraries and making you understand what , where and why , something happens. I cant see the benefit of using a text editor. But you can, with file ins and file outs. But doing so you cripple smalltalk into becoming as efficient as other programming languages ;)
I am only studying squeak and pharo for a week now but even for me as a beginner the benefits of the IDE is obvious from the first minute.
The fact that code is fragmented into easy to digest methods, those methods grouped into protocols , protocols grouped to our familiar Classes and Classes grouped to packages. Hence the code is so well organized that I never feel lost, everything belongs somewhere, everything is just a click away, everything is inspectable, browseable , you just select right click and sends you there. And it shows you exactly the code you need rarely more than 10 lines long. This is the IDE. Why would you prefer a text editor that will expose to information that you don't need , don't care and is likely to confuse you ?
Then everything is inside a single image , not a collection of files, your code, your libraries, system libraries , even the language itself. Everything is at your grasp, waiting for you, begging you to test, modify it, use it and abuse it. You are part of the language and the language is part of your, if something does not fit your thinking, change it. This is the IDE. Why you want to go back to the disconnected way of files and folders ?
Then you are start being afraid with all this power, all this flexibility its not unlikely that you will do something that could completely destroy the language and the libraries. Its possible , mistakes can and will happen. Again the IDE jumps in offering you a hand of help, every change is stored in a local cvs system, every change is categorized, stored and monitored any time. No lousy undos and any kind of other nonsense . What you get is old , mature well tested version control. You can change back exactly what you want any time, nothing is lost, no mistake is irreversible.
And if you don't trust you hard driver , the vcs extends online to squeaksource . And does it let you at the mercy of command line ? Hell no . You are offered the simple yet efficient Monticello browser , which will make sure you install and unistall with no conflicts .
And of course you don't want your software to have bugs , do you ? Unit Testing tool is offered to make sure your code is reliable , stable and does exactly what you want how you want it. Again a beautiful yet brilliant GUI is utilized to make complicate tasks a button away.
And because none is perfect , there will be time you will come against the dreadful error. Are you left alone ? You guessed right , a tool again is offered. The debugger. You don't need to call it, you don't need to setup it , you don't even need to figure out how it works. Like all other tools, is simple in design yet sophisticated. Not only it will spot the error , not only will tell you what you did wrong , not only will navigate through back to most basic language elements that trigger the error offering a unique perspective on how exactly the language behave like nothing I have seen before, it also allows you to do live coding. Live coding is the ability to code a program while its code runs. Isn't that impressive and infinitely useful ?
Finally , maybe you are one of those people impossible to please, maybe you still find flaws , omissions and thinks you simple don't like. The IDE is written in smalltalk , smalltalk is written in smalltalk , and the IDE can edit itself and the language, there is nothing you can't change besides some very basic functionality of the language and the VM that is compiled C. And you will guess right if you think you can use all the above tools to do exactly that.
And the tools don't stop here , smalltalk might be not that popular as other languages but it has been here for a very long time and it has some very enthusiastic programmers that love to contribute. And frankly with such an amazing IDE and such a well designed language , while with other languages contributing to them might seem a challenge, in case of smalltalk the challenge is to resist the temptation not to contribute as the IDE makes it so easy.
By the time others still code you will finish your code and actually understand what have you done and why. Thats not a small thing at all . I wish Python had such a good IDE or any other language. But the only thing that comes abit close, from my experience , is Delphi. And even in the case of Delphi I still prefer squeak and pharo.
What I find annoying about other IDEs is that they are not IDES at all, they are nothing more than glorified editors, locked, non flexible , non editable (Unless you are willing to use another programming language and navigate through tons of source code) . Squeak , Pharo and all other smalltalk dialects offer a real elegant IDE offering you really useful tools. Other IDEs better take a deep a look at smalltalk and really understand what it means to be an IDE.
Saying all those good things, smalltalk is far from perfect. And I think its biggest weakness and flaw is lack of some enjoyable and useful documentation that can help beginners jump in head first. Squeak By Example as well Pharo By Example has been a big disappointment for me. They both are still two extremely important books that provide a extremely valuable insight in both platforms , but the quality of documentation is from mediocre to bad at times. The main reason is both books follow a non noob friendly approach. First they send you deep diving in the IDE , introducing you from chapter 1 , to debugger and even unit testing !!! For me this a big mistake, and even though I am far from new to programming had to struggle to follow up what was explained. Then the book itself , lets a lot of unanswered questions. For example the explanation of instance vs class variables is not enough, I would prefer several example that not only show the how but also the why . Several areas of the book are also full of gaps or just hard to follow.
My life got a lot easier when I found this link http://stephane.ducasse.free.fr/FreeBooks.html and from there I downloaded "Smalltalk by Example" which unlike the other book not only it does what it says in the title but makes no assumption on who you are and what you know. I can only highly recommend it. I read that the other books there that are offered freely are very good as well, I will certainly download and read all of them eventually.
Alot of help has been also #squeak at irc.freenode.net, people there has been answering my questions and helping me understand.
Squeak wiki, is ok but not enough, its also not very well organised, and I dont like that comments and discussions appear inside the wiki documentation. So documentation generally can be abit of a struggle for the begginer and certainly Smalltalk IS NOT AN EASY programming language to learn. I hear many smalltalkers say otherwise and I could not disagree more, when I compare smalltalk with python is like night and day. BUT ! Once understand smalltalk , it become much easier to program in it then any other programming language I have learned so far, and I have learned most of them. So in the end I think Smalltalk is a clear win , I also love the FFI library that lets you call any C library with ease, which unleashes serious power for smalltalk.
I dont think you need to learn the language first and then the IDE, its actually a very bad idea for the simple fact that the IDE helps you understand the language and its libraries and any type of code in it. Language and IDE is like brother and sister, yin and yang.
Well, if you decide to learn Eiffel a good book would be "Object-Oriented Software Construction" by Betrand Meyer (he created the Eiffel programming language).
The book provides great insight into object-oriented design using Eiffel. In my humble opinion is one of the best OO books around.
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I was talking with some of the mentors in a local robotics competition for 7th and 8th level kids. The robot was using PBASIC and the parallax Basic Stamp. One of the major issues was this was short term project that required building the robot, teaching them to program in PBASIC and having them program the robot. All in only 2 hours or so a week over a couple months. PBASIC is kinda nice in that it has built in features to do everything, but information overload is possible to due this.
My thought are simplicity is key.
When you have kids struggling to grasp:
if X>10 then <DOSOMETHING>
There is not much point in throwing "proper" object oriented programming at them.
What are the essentials needed to foster an interest in programming?
Edit:
I like the notion of interpreted on the PC as learning tool. Due to the target platforms more than likely being somewhat resource constrained, I would like to target languages that are appropriate for embedded work. (Python and even Lua require more resources than the target likely to have. And I actually kinda like Lua.) I suppose that is one of the few virtues BASIC has, it has been ran on systems with less than 4K for over 30 years. C may not be a bad option if there are some "friendly" tools available such as Ch.
The most important is not a lot of boiler plate to make the simplest program run.
If you start of with a bunch of
import Supercalifragilistic from <expialidocious>
public void inherited security model=<apartment>
public : main .....
And tell them they "not to worry they aren't supposed to understand that" - you are going to put off both the brightest and the dumbest.
The nice thing about python is that printing "hello world" is print "hello world"
Fun, quick results. Capture the attention span of the kid.
Interpretive shells like most scripting languages offer (command line) that lets the student just type 1 or 2 liners is a big deal.
python:
>>> 1+1
2
Boom, instant feedback, kid thinks "the computer is talking back". Kids love that. Remember Eliza, anyone?
If they get bogged down in installing an IDE, creating a project, bleh bleh bleh, sometimes the tangents will take you away from the main topic.
BASIC is good too.
Look for some things online like "SIMPLE" : http://www.simplecodeworks.com/website.html
A team of researchers, beginning at Rice, then spreading out to Brown, Chicago, Northeastern, Northwestern, and Utah, have been studying this question for about 15 years. I can't summarize all their discoveries here, but here are some of their most important findings:
Irregular syntax can be a barrier to entry.
The language should be divided into concentric subsets, and you should choose a subset appropriate to the student's level of knowledge. For example, their smallest subset is called the "Beginning Student" language.
The compiler's error messages should be matched to the students' level of knowledge. If you are using subsets, different subsets might give different messages for the same error.
Beginners find it difficult to learn the phase distinction: separate phases for type checking and run time, with different kinds of errors. For this reason, beginners do better with a language where types are checked at run time, i.e., a dynamically typed language.
Beginners find it difficult to reason about mutable variables and mutable objects. If you teach pure functional programming, by contrast, you can leverage students' experience with high-school and middle-school algebra.
Beginning students are more engaged by an interactive programming environment than by the old edit-compile-link-go model.
Beginning students are engaged by splash and by interactivity. It's good if your language's standard library provides built-in support for creating and displaying images. It's better if those images are supported within the interactive programming environment, instead of requiring a separate player or viewer. And it's even better if your standard library can support moving images, or some other kind of animation.
Interestingly, they have got very good results with just 2D images. Even though we are all surrounded by examples of 3D computer graphics, students seem to get very engaged working with just two-dimensional images.
These results have been obtained primarily with college students, and they have been replicated at over 20 universities. However, the research team has also done some work with high-school and middle-school students. The first papers on that work are just coming out, so I'm less aware of the new findings and am not able to summarize them.
When you have kids struggling to grasp:
if X>10 then <DOSOMETHING>
Maybe it's a sign they shouldn't be doing programming?
What are the essentials needed to foster an interest in programming?
To see success with no or little effort. To create something running in a matter of minutes. A lot of programming languages can offer it, including the scary C++.
In order to avoid complication with #includes, multiple source files, modularization and compilation, why not have a look elsewhere? Try to write some Excel macros or use any other software with some basic built-in scripting language to automate certain tasks?
Another idea could be to play with web pages. It is not exactly programming, but at least easy to achieve something and show to others with pride.
This has been said on SO before, but... try Scratch. It's an incredible learning tool for kids. It teaches the basics of programming concepts in a hands-on and language-independent way. After a bit of playing around with it they can get down to learning a specific language's implementation of the concepts they already understand.
The common theme in languages that are easy for beginners - especially children to pick up is that there's very little barrier to entry, and immediate feedback. If "hello world" doesn't look a lot like print "Hello, world!", it's going to be harder for people to pick up. The following features along those lines come to mind:
Interpreted, or incrementally JIT compiled (which looks like an interpreter to the user)
No boilerplate
No attempt to enforce a specific programming style (e.g. Java requiring that everything be in a class definition, or Haskell enforcing purely functional design)
Dynamic typing
Implicit coercion (maybe)
A REPL
Breaking the problem (read program) down into a small set of sections (modules) that do one thing and do it very well.
You have to get them to stop thinking like a user and start thinking like a programmer. They need to take it one step at a time. Ask them what they have to think of in order to figure out the problem them selves and then write them down as steps. If you can then you break each step even more in the same mater. When done you will have the program in english making it simpler to program for real.
I did this with a friend that just could not get it and now he can. He used to look at something that I did and be bewildered and I would say that he has done more complex stuff than this.
One of the more persistently-present arguments I have had with other programmers is whether or not one's first language should require explicit type languages. Many are of the opinion that learning a language which requires you to explicitly declare type information is one which will teach you to program typefully. Conversely, it can be said that dynamic languages might present a less demanding learning curve. It goes either way, I suppose.
My advice: start with a simple model of how a computer works. I am particular to stack machines as good tools for teaching computation.
Remember that beginners are learning two disciplines at the same time: how computers work and the abstract logic involved (the basics of Computer Science), plus how to write programs that match their intended logic (learning a specific language's syntax and idioms). You have to address both concerns in an interwoven fashion in order for the students to quickly become effective. This is also the reason experienced programmers can often pick up new languages quickly.
It's worth noting Python grew out of a project for a language named ABC, which was targeted at beginners. For example, the required colon isn't strictly required, but was found to improve readability:
if some_condition:
do_this()
I got 3 words : Karel the Robot.
it's a really really simple 'language' that is designed to teach people the basis of programming :
Look for it on the web. You can look at this, though I never tried it :
http://karel.sourceforge.net/
While this isn't related to programming a robot, I think web programming is a great place to start with kids that age. It's how I started at that exact age. It easily translates to something kids understand if they use the web at all. Start with HTML, throw in Javascript, and soon they want to be doing features requiring server-side scripting or some sort, and things progress from there.
With the kind of kids who are already interested in robotics, though, I'd actually go for a different language like the ones already described. If you want to work in a field like robotics, you don't need to be convinced to try something hard. You need to be challenged.
A few years ago I saw a presentation at Ignite! Seattle from one of the people working on the project now known as Kodu who envisioned as a programming language for children. He spent time talking about what common language features could simply be thrown out in a programming environment meant to teach fundamentals.
A lot of cherished imperative constructs, like C-style for loops, were simply left out in favor of a simple object-messaging approach. Object-oriented programming isn't hard to understand when you think about "objects" and "messages"; the hard part is when you deal with things that programmers, but not children, care about, like inheritance and contracts and sweeping abstractions. I've got this thing (noun), now act on it (verb), in this way (adverb like quickly), when thing (sees/bumps into) something (with some attribute) (that's your if). Events are really conditions, and have all of the power of conditions, but it's up to the runtime to identify when those events happen.
This kind of event and messaging driven approach probably translates even better to robots than procedural programming would, anyway, so it might be a good way to look at the problem. Try not to think about what you'd "need" to know to program in C or Pascal or something; think about what you'd want to be able to make something do.
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Closed 9 years ago.
I am learning programming. I plan on learning C and Objective-C this summer. I bought the C for Dummies book but it is a complete waste of time. It's way too many pages! Are there any good books I should read? Or should I just learn C from websites? What would be the fastest way because I really want to learn it fast and start learning Objective-C too.
Thank you
Also, how long does it take to learn C? Until I move to Objective-C 2.0
There's no need to rush. Learn at your own pace and find your optimal way of learning.
If reading is your thing, then try to read some books and take it slowly.
If you find a concept you grasp, practice. If you find a concept that you don't quite get, experiment. Once you think you understand the concept, try re-reading the material to see if you understand it the second time.
I found out that I wasn't really good at learning though books -- I generally had to get the first kick-start with a structured lessons in a classroom. A semester course at a community college on Java was able to nudge in the direction of being able to begin effectively learning on my own. See if there are any programming courses offered in your school.
(Although at your age it may be a little bit difficult to find -- I didn't get any formal classes until community college -- my high school did not offer any programming courses.)
One of the things to be careful of is learning it the wrong way.
Rushing through material, or reading poorly written, inaccurate learning material can lead to a situation where you'll need to "un-learn" the concepts and re-learn it the right way.
In that respect, the K&R book (The C Programming Language by Kernighan and Ritchie) would be the "right way" of learning, but it's not a very approachable book. That isn't to say that it is the definitive book on C -- but even after programming in C for a couple years, I still try to take read it a bite-size at a time.
But then again, I can't really think of other "great" sources for learning C. My recommendation would be to take a look at K&R and work on a few pages at a time. Don't think about reading it like a regular book -- read one section, try it out. Do it little-by-little. Once again, don't rush. Work at your own speed.
And be sure to write code. Without seeing it working, it's going to be difficult to learn programming. And don't have huge expectations at first, as most of learning C at the beginning will involve programs that deal with only text.
Once you get a handle of things, try to write clean code that is readable by others -- that should be a motivation to write clean and clear code, and it will force you to think harder about what you're doing.
It's going to be a long adventure, so take it a step at a time. Good luck!
For learning C, I highly recommend Learn C on the Mac, by Dave Mark. Not only is it aimed at beginners, but it also teaches you a lot about the important fundamentals of programming and computer science (e.g. data structures, recursion, etc.). It's very accessible, well-written, and easy to read. Plus, I found the examples engaging and interesting to work with. After that, if you really want to solidify your foundations in C, I'd recommend trying to moving on to The C Programming Language. It's a challenging book, so take it slowly. If you find yourself having too much trouble with it, I'd say you can just skip to Objective-C, and then come back to The C Programming Language later, once you've gained more familiarity with programming in general.
A lot of people will probably recommend The C Programming Language (a.k.a. "K&R") as your first book to read on C. No doubt it is a very well-written C book (and it's short too—only around 200 pages), but I'd say it'd be a little intimidating as a 12-year-old's first exposure to C: it's pretty dense and hardcore. You can tell that it's definitely aimed at an older audience with a strong background in computers/engineering. But nevertheless, if you already know the basics of programming, reading K&R will give you invaluable insight and understanding of C. You should definitely read it at some point in your programming endeavors.
Anyways, for Objective-C, if there's only one book I could recommend, it would most definitely be Cocoa Programming for Mac OS X, by Aaron Hillegass. It's really not that long (~400 pages or so, although I'd reckon that a lot of that is due to the number of illustrations in the book), and you can get some pretty cool projects up and running in an afternoon. It's very clear and easy to read, the examples are practical and interesting to follow, but most importantly, it's got this right blend of not being too intimidating while still managing to provide you with solid information. Plus, it'll teach you more than just Objective-C: I found that I had learned some very useful design patterns, for example, by learning how some of the components of Cocoa worked.
When I look at the title of this question, I am guessing you are 12.
I started programming when I was 13 (I am now 14).
I found that learning depends on what kind of a learner you are!
I hate reading, I have the attention span of a moth and I learn best from videos. Therefor, I am a "visual learner". Try to find out what kind of "learner" you are, then do it that way. Remember, the easiest way is the fastest.
PS, here is a little tip. It may be frustrating (aseptically at our age). If you get frustrated, just put it down for like 10 minutes. Then come back and do research on what your learning. Programming WILL get very frustrating at times.
EDIT:
By the way, I like to learn through video :p
Stanford University posts online the lectures, class notes, and assignments for CS193P (an iPhone development class). If you don't know C or Objective-C at all, it might be tough, but I highly recommend this if you intend to do iPhone development.
I think I've read every Cocoa and Objective-C book out there, and most enjoyed Aaron Hillegass' Cocoa Programming for Mac OS X.
I would take a look at The C Programming Language (K&R C). It's much less than 1000 pages and I think you'll find it well worth your while. As htw said, books do serve a purpose in that they provide a thorough and structured approach. K&R C in particular will give you real insight directly from the creators of C.
That's not to say you shouldn't Google things, read open source code, write little practice programs, etc. It all helps. Just remember to be patient. There's a lot out there.
Checkout out http://www.cprogramming.com/ or and online K&R type book
Don't be impatient; take your time. Follow tutorials, dissect short snippets of code, you'll get the hang of the language. Most importantly, write code yourself and learn from your bugs/errors.And follow Stack Overflow ;)
I've been where you are. It wasn't fun. This is what saved me:
(Apparently new users aren't allowed to post hyperlinks, so google for "steve summit C", use either the first or the third link, and then click "introductory C programming class notes")
It's a C class by a guy named Steve Summit. Super easy to follow, much easier than K&R, imo.
Also, it's free, and there aren't any ads. I loved it. It's how I learned C. I hope it'll do the same for you.
There is nothing so educational as a piece of code you can run and tweak. Code examples in books can be really bland and not very applicable. The exception to this rule was the Perl Cookbook which is jammed packed with really useful little snippets for your perl programs.
The topics (or 'idioms') in it were so useful and so applicable across languages that some smart folks have taken to replicating them in different languages. Each has a varied level of completeness, but it's interesting to see how different languages do the same things.
Take a look here http://pleac.sourceforge.net/ for nuggets of programming wisdom that you can shake a stick at. At the very least its interesting to see how simple things written in one language require reams of code in another.
Were I starting to learn programming again I would probably pick something easy and forgiving, a dynamic language, like Python, Ruby etc. Once you get your head around the basics in one of these (flow control, data structures etc) it will make learning C/Objective-C so much easier. Also you'll find that you'll want to write once-off tools and scripts to help you in your Objective-C development that would be tedious and time consuming to write in C but are a matter of lines in a modern dynamic language. Never hurts to have another tool in your belt.
Good luck
Honestly, I learned Java as my first programming language (I discovered it in high school and decided programming was fun and it was what i wanted to do)
I just now picked up Obj-C in a few weeks, reading a little bit from some books, but not a whole book, and using the internet a lot if i can't figure out the syntax (format/grammar of how the program should be structured and written) for something etc.
How fast you can pick up a language depends on how much you understand the fundamentals of programming. You will only get better at it with time and practice.
If you can understand the fundamentals of programming in general then you should be able to apply it to any language, the hard part is learning and remembering the syntax of different languages. Like in Java, you don't have to do memory allocations, but in C, C++ and Obj-C you do. I've never written a C or C++ program, but now that I've learned and written some programs in Obj-C (i've been making iPhone stuff, it is fun) I'm sure I could pick up C and C++ like it's nothing.
You don't have to learn C first in order to learn Obj-C is what i'm trying to say. But it never hurts to know multiple languages.
It is all about your level of understanding how a program works, how to structure one. I love objective-C because it is Object Oriented like Java so it was easier for me to understand and learn quickly, just had to get used to some of the differences in syntax
(I'm also getting close to graduating from college now so I'm surrounded by programming stuff, from procedural languages like ada to object oriented like java, and knowing the nitty gritty behind the scenes stuff that makes a program work, so understanding and learning a new language has gotten a lot easier for me, you start seeing how they relate and don't relate and it is cool)
It is great that you are starting so young. I'm sure you'll pick up on this stuff real fast, and if it is something you really enjoy, it will be even easier.
Good Luck! and have fun! programming can be so frustrating... like, spending 3 hours debugging when you find out it was because you if statement used a grater than instead of grater than or equal too or something like that. but, once you are done with the program, it is so rewarding, and then you just want to make it better and better haha.
I dunno if this helped at all, I hope it did, somehow...
=)
the way i learned quickest was to watch short video tutorials.
If you really want to start with C, I would start by just reading the first three or so chapters of C for Dummies, just to get a feel for how the language works. After that, I recommend going through web tutorials. Good web tutorials will have short code that explain specific functions, and the like.
As a 13-year old, though, I recommend starting with PHP. It's a simpler language to learn than C, but it's based off of C, so it won't be hard to make the transition, whenever you do so.
Different people have different preferred ways of learning. You can see that in the variety of responses above.
So how do you like to learn? Do you like to sit by yourself with a book and a computer? Do you like to sit in a classroom and absorb learning? Do you prefer set exercises, or mini-projects?
When I learn new programming languages, I find it helps me if I have a small application or problem to work on. I prefer to have a problem to work on. If you have a little project of your own that you always wanted to do, use that. If not, as someone above suggested, join a robotics group. Set up a web page and write some programs to do stuff for that.
Look on the web for programming challenges. Google has a fun one every year.
If you want an idea, write a sukoku checking program. Then later, write a sudoku solver!
I like to use a variety of books, rather than just sticking to one or two of the ones suggested above. Find a book whose style you like. Try a few from the library until you find one or two that really click for you.
Personally, I like O'Reilly Publishing books for their chatty and readable style. I learnt C from Deitel, which is more of a classroom style textbook, but it has lots of examples and discussion points.
As you work through examples on your computer, you might wonder how things change if you tweak the code. I learn a lot by first running the example code suggested in a text, but then changing it to see what happens. If I get what I expect, it's a sign that my understanding is pretty good. If I get something unexpected, I try to figure out how I misunderstood what I did.
One last suggestion. Why not start with Python rather than C? I hear that a lot of schools are teaching Python to their kids. The reasons I suggest this are:
Python is pretty easy. You don't have to lay out memory, declare variables and such. No tedious bookkeeping.
Python gives you a nice growth path. You can start off just writing script style programs, using the built in types like lists and dictionaries. Then you progress to using new modules as you need them, and advance into object-oriented coding using classes. There's some functional programming stuff in there too, which you can start learning once you have the basic mechanics of the language under control.
I just love visiting new parts of python all the time.
You can get a lot done in python. It comes with a whole lot of built in modules to do almost anything you like - email, web, xml, graphics, gui, etc.
:)
When I was learning to program in C, I found that Practical C Programming was a good resource. It's a very approachable book with lots of examples.
The fastest way in my view is through learn through websites.
Set a goal of what you want to do and start a simple project
Instead of reading too many books theoretically,google what you want to know to get it instantly as you go through your project.This way you get PRACTICAL knowledge.
Watch online videos as well.Check out my question on VIDEOS here
Ask whatever you don't understand on stackoverflow. We're here to help :)
Follow these steps and I can assure you that you will be a great programmer soon!
Cheers!
With others, I highly recommend Kernighan and Ritchie—perhaps the best language book ever written. I'd also recommend that you slow down and enjoy yourself: don't be wide and shallow; start out narrow and deep. If you like programming, you will want to master the craft rather than be in a hurry. This essay by Peter Norvig explains how not to be in such a rush.
P.S. I started programming at age 12 with APL/360. I had a blast and have been doing it ever since—35 years and counting. Good luck and don't forget to have fun!
By far the best way (and usually the fastest) to learn programming is to find a good mentor. That's easier said than done. But I think you'd be surprised how many people would be willing to help you out. My advice would be just don't be afraid to ask.
If I were you I would find a local FIRST robotics team and see if you can hang out for some of the coding. Odds are you'll be working on a similar problem and will have some support from people who have a decent amount of experience. That's what I would have done, anyway.
I started learning to program in Basic in about 1981 when I was 10. Not many years later it was 6502 assembly to try to get more speed out of a 1 MHz Apple IIe clone.
Pascal was a revelation in 1988 - programming without line numbers.
Modula-2, C, Eiffel, Miranda, Haskel, and Prolog at university as well as scripting in any number of languages.
C++ professionally for about 6 years.
C#, then Java, Ruby, and now back to C# for the last 18 months.
Python somewhere along the way.
My advice, pick the language that is best suited to the problem you need to solve today.
The first problem you have is to learn the basics ie how to break down a problem and express it in a clear and concise manner. I suggest you choose something other than C. I recommend Python as the online documentation is excellent and the libraries are great and you will spend more time writing interesting code and less time trying to figure out why your code stopped due to a segmentation fault.
When you've got the basic concepts under your belt, try some assembly and learn what's going on under the hood. If nothing else, you'll learn how fast CPUs really are. C is a good step after that. I also suggest you try Java or C# before Objective-C.
As to how long before moving to Objective-C, it really depends on how talented you are. If you're really good, then once you've learnt your 3rd or 4th language you'll can be more productive than most coders within 6 weeks of starting a new language (although changing language families (ie imperative, functional, object oriented) takes longer). If you're no good then don't expect to get past the first. Hopefully you make it into the first category.
In addition to whatever books and websites you end up using, you might consider looking around your area for local support groups. Many areas have a Linux user group or a group for Java or Ruby programming. Professional programmers use these groups to help each other with their programming problems, but the groups are generally friendly to young people and beginners. Don't feel embarrassed or awkward because of your age and inexperience. Most people will admire your initiative and curiosity and be happy to help you when you run into problems.
Assuming you have some basic programming knowledge, Cocoa Dev Central have a series of articles that explain basic C then Objective-C, in a somewhat-less-than-1000-pages way..
Learn C for Cocoa, then Learn Objective-C
Shouldn't take even an hour to go through. The articles don't cover anything remotely advanced, but if you're learning ObjC to write OS X applications, the ObjC bit is basically trivial, it's Cocoa that is difficult to learn!
If you want to learn Objectif-C to create iPhone application, don't waste your time on C and learn Objectif-C now, then a book on iPhone programming. It will be more than 1000 pages but if you want to program in your life, you have to be used to read these types of book.
I created an online interactive C tutorial, you can start using it without installing an IDE.
http://www.learn-c.org
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I'm at a stage where I am forced to learn Lua, so do you have any suggestions on how I do this? I don't have a lot of experience with any other scripting languages than PHP.
So, some suggestions on "head start Lua"-pages?
EDIT
As an addition to the wonderful tutorial pages, could you please suggest any "programs" I could make that will help me learn Lua? Imagine I would want to learn Pointers in C++, I'd make a Linked List. I want to touch the basics in Lua but meanwhile be open to pretty advanced stuff.
First of all work your way through the Programming in Lua, it should take you a day or two to get the gist of Lua.
However I can tell you right away on your first time through ignore coroutines and metatables, they are very powerful, but take a while to grasp. First learn the syntax, scoping (same as PHP luckily for you) and the standard libraries.
After that go back to coroutines and metatables, read them try them and by the third time through you might get it. Unless you have a very good CS background these are complex topics
Edit: The book is free online == website. Besides it is the best tutorial out there on Lua, everyone learns Lua with it.
Also: If you're purpose is Lua for World of Warcraft (probably not but just in case) you can check out this tutorial
And: Here is a tips and tricks thread on StackOverflow, might help give you some ideas of what to expect from Lua
Suggested Programs/Exercises:
Since you're initially looking at Lua for web development try to understand and improve the Data Description example in PIL. It'll give you a few good ideas and a nice feel for the power or Lua.
Then you might want to try out playing with the Data Structures chapter, although Lua has a single complex data-type, the Table, that chapter will show you Lua-like ways to make a table do anything you need.
Finally once you begin to grok metatables you should design a class system (yes with Lua you decide how your class system works). I'm sure everyone that knows Lua has made a dozen class systems, a good chapter to get you started on a class system is Object-Oriented Programming
And if you got time and know C or something like that (C# and Java included) try extending an application with Lua, but that'll take a week or two to do
Funny to see all these elaborate lists (though they are certainly correct). Back in 2002, I read about the first 20+ pages of the Lua reference manual, and started using it. It really is that simple. Lua (and ANSI C) are of the few languages that really fit in one's mind all at once - and stay there. For the others, at least I need to constantly do some relearning.
Be aware that getting to think in Lua will take time. I think mine was 6 months or so. When coming from C/C++, we tend to solve problems in certain ways. Lua might offer better means (i.e. via use of tables) but it takes a while to start seeing those. This transition to a higher abstraction level is similar to the Assembler->C shift in the 1980's. Many people still coded a while in C as if it only were a portable assembler.
There is also a large body of projects related to Lua at LuaForge.
If you happen to use Windows as your day-to-day platform, then I would recommend getting the Lua for Windows package as a nice starting point. It includes a wide array of useful modules all prebuilt and installed together with the Lua interpreter.
After your first pass through PiL and the reference manual, you will want to read Lua Programming Gems which is currently only available in a paper edition.
<plug> Do consider buying the books through the associate links at Lua's books page or LuaForge to support the projects. </plug>
Edit: As for ideas for programming projects where Lua is suited, look for problems where the table provides leverage. Tables are central to Lua, since even the global variables are just fields in a table. Tables can be indexed by values of any data type except nil, but have an especially efficient implementation if used as arrays.
One quirk that trips up people coming from a C-like background is that all things in Lua are naturally indexed starting from 1. Strings are indexed from 1, arrays start at 1, etc. Don't worry about it too much, there is nothing wrong with using a[0], but the length of the array given by #a is defined assuming that the array began with a[1].
Another quirk is that functions don't really have names. They are first class values that are usually stored in some variable that has a name. Syntax sugar makes it look like they have names, but that is just a convenience.
Metatables are a particularly Lua-ish feature of tables (and other types, but that is a really advanced topic) that are the basis for most of the schemes for doing object-oriented things in Lua.
Closures and true tail calls are other features of Lua that aren't often found in small scripting languages that can really make some idioms easy to implement.
In addition to the suggestions above, there's also the Lua wiki which is well worth a browse. There are a tremendous number of code snippets and small recipes there which can be useful.
I wrote a short quick-start guide to Lua for people using it on a project I was working on.
If you are familiar with other scripting languages it may get you up and running quickly.
The docs on Lua.org are very good and should cover most everything else you need. Lua is a pretty small language and can be learned fairly quickly.
This is a pretty general recommendation, but if you want to get started in a new programming language as a software engineer, it's fun to start doing the problems found at Project Euler in your new programming language. I've been doing this with Python recently and found it to be inspiring and bring a lot of enthusiasm to the coding.
You could install World of Warcraft and make a mod for that (it uses Lua). Actually that's probably a bad idea.
Maybe try to integrate Lua into a .NET application (assuming you are a C# programmer) and do something 'fun' with it:
Using Lua with C#
Or just browse lua.org
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My questions is simple!
Would you start learning Smalltalk if you had the time? Why? Why not?
Do you already know Smalltalk? Why would you recommend Smalltalk? Why not?
Personally I'm a Ruby on Rails programmer and I really like it. However, I'm thinking about Smalltalk because I read various blogs and some people are calling Ruby something like "Smalltalk Light". The second reason why I'm interested in Smalltalk is Seaside.
Maybe someone has made the same transition before?
EDIT: Actually, what got me most excited about Smalltalk/Seaside is the following Episode of WebDevRadio: Episode 52: Randal Schwartz on Seaside (among other things)
If you like Ruby you'll probably like Smalltalk. IIRC Seaside has been ported to the Gemstone VM, which is part of their Gemstone/S OODBMS. This has much better thread support than Ruby, so it is a better back-end for a high-volume system. This might be a good reason to take a close look at it.
Reasons to learn Smalltalk:
It's a really, really nice programming environment. Once you've got your head around it (it tends to be a bit of a culture shock for people used to C++ or Java) you'll find it to be a really good environment to work in. Even a really crappy smalltalk like the Old Digitalk ones I used is a remarkably pleasant system to use. Many of the old XP and O-O guru types like Kent Beck and Martin Fowler cut their teeth on Smalltalk back in the day and can occasionally be heard yearning for the good old days in public (Thanks to Frank Shearer for the citation, +1) - Agile development originated on this platform.
It's one of the most productive development platforms in history.
Several mature implementations exist and there's a surprisingly large code base out there. At one point it got quite trendy in financial market circles where developer productivity and time-to-market is quite a big deal. Up until the mid 1990s it was more or less the only game in town (With the possible exception of LISP) if you wanted a commercially supported high-level language that was suitable for application development.
Deployment is easy - just drop the image file in the appropriate directory.
Not really a reason, but the Gang of Four Book uses Smalltalk for quite a few of their examples.
Reasons not to learn Smalltalk:
It's something of a niche market. You may have trouble finding work. However if you are producing some sort of .com application where you own the servers this might not be an issue.
It's viewed as a legacy system by many. There is relatively little new development on the platform (although Seaside seems to be driving a bit of a renaissance).
It tends not to play nicely with traditional source control systems (at least as of the early-mid 90's when I used it). This may or may not still be the case.
It is somewhat insular and likes to play by itself. Python or Ruby are built for integration from the ground up and tend to be more promiscuous and thus easier to integrate with 3rd party software. However, various other more mainstream systems suffer from this type of insularity to a greater or lesser degree and that doesn't seem to impede their usage much.
Well, since you mentioned me by name, I feel I should chime in.
As I said in that podcast interview, and as I have repeatedly demonstrated in my blog at http://MethodsAndMessages.vox.com/, this is "the year of smalltalk". And having now done Smalltalk advocacy for the past ten months, I can see that it really is happening. More customers are turning to Smalltalk and Seaside, and the Smalltalk vendors are all working hard to capture this new influx of attention. More larger Smalltalk conferences are being planned. More job postings are being posted. More blog postings are being made.
If you turn to Smalltalk today, you are not alone. There are many others who are out there as well.
Edit
Well, a number of years later, I'm now recommending Dart instead. It's a great language originated by Google but now owned by an ECMA committee. It runs serverside in node.js style, but also clientside in modern browsers by transpiling to JavaScript. Lots of good books, blogs, help channels, IDE support, public live pastebin. I think it's definitely got legs... enough so that I'm writing courseware to teach it onsite or online, and I'm pretty sure there's a book or two in the works from me. And Gilad Bracha, an old-time Smalltalker is a major contributor to the design, so there's a lot of Smalltalk in Dart.
Smalltalk is a good language to learn, and the great thing is that it only takes a day to do it. It's a lot more than just an academic language. People are building huge, scalable, replicable applications handling billions of dollars. They just don't talk about it much. See, for instance, GemStone and Orient Overseas Container Lines:
A Shipping Industry Case Study.
Seaside is a good reason to learn Smalltalk, but I don't think you'll find it orders of magnitude better than Rails.
The thing that convinced me was GemStone. I really like Gemstone's GLASS (GemStone, Linux, Apache, Smalltalk, Seaside). The killer part of that is GemStone, which handles all the object persistence for you mostly without you thinking about it. Seeing some of their demos and hearing about what people are doing with GemStone reset my idea of what "big application" meant.
The part that bugs me the most about Rails is the object-relational mapping. That's nothing against Ruby because it sucks just as hard in GLORP (which handles ActiveRecord for Smalltalk), or Perl, or anything else. Mapping objects to database tables is just painful. With GemStone, thinking about the database disappears, so the work with the database disappears too. It's like a huge stone (or a troop of monkeys) is taken off my back.
> couldn't find a Smalltalk development environment that didn't cost both arms and a leg
Google - free smalltalk
Cincom Smalltalk, Squeak, GNU Smalltalk
Learning Smalltalk will give you a grounding in object oriented software development from the perspective of the man who invented OO (Alan Kay). The idea of a overlapping windowing environment came from Smalltalk.
A stumbling block to learning Smalltalk is that it is a message passing system with a strange syntax for flow control like:
i < 60
ifTrue: [ self walk ]
It has a very mature class library that has a consistency I've not seen too many places. The class library in all environments (even commercial Smalltalks) has available source which allows you to learn from the masters of the language. When programming Smalltalk, I always ask the question how is it done in the environment.
Smalltalk is generally implemented in an image which is a live environment for all the objects in your system.
The interactive debugger really seperates Smalltalk from Ruby.
Seaside is the web development framework and has given Smalltalk a new spotlight. It is a continuation based environment that allows for intra-hit debugging and a smooth Rich Client type development experience (top application flow can be designed in a single method). It's integration with script.aculo.us has been done in such a way that it is easily called from within Smalltalk.
Nigel, one quote I have is this:
Although it's now a long time since I did anything with it, I nominate Smalltalk, I still haven't come across anything quite like it for being able to transfer thoughts into computer code. It's not just the language: It's the wonderful browser environment, the libraries, and the culture of writing clear, well-designed code as quickly as anything else can crank out spaghetti. When the participants at JavaOne were extolling how Java was so much more productive than anything else, I needed a brown paper bag. Oh well, back to sorting out my classpaths... -- Martin Fowler (Software Development Magazine, Jan 2001)
I found it here.
Would disagree with the poster who reckons you wouldn’t use Smalltalk for large apps – that’s precisely where it shines. But I have created fairly groovy (note lowercase) prototype apps in under a week too.
I learned OO in ST starting in 92, incredibly glad I did so. It gave me a real background in OO. Thinking in classes. No types. ST has a real emphasis on messaging. If you want to know something send an object a message and get an answer. IMHO, the ethos and the IDE really encourage you to do the right thing with your coupling and cohesion.
In my Java day job, I’m stuck with files, generics, IDE’s like eclipse that are orders of magnitude less productive that any ST IDE. I was using ST the only time I finished a development ahead of schedule. In fact it was so productive, and we got so much reuse I had to be moved off to another project, as I had nothing to do! (Ok, maybe I could have spent time learning to estimate...)
Download squeak, find a good book and play. Only downside is that if your day gig is using Java or C#, you’ll end up wishing you could use ST. You’d get home sooner.
Chris Brooks
I recommend everybody to learn Lisp (Scheme) or Smalltalk.
Smalltalks have wonderful IDEs which you dont want to miss once you got over the culture shock. And yes, there are more than one free ones: Squeak, Dolphin, Smalltalk/X, and Visualworks (Non-Comercial).
Lisp may be even cleaner in its mathematic foundation, though.
regards
PS: actually I recommend learning both !
I do not know Ruby..
Smalltalk is a pure OO language. If you feel the need to really understand OO, and not just the simulated OO of most popular 'OO' languages (like C++, Java, etc), then I would recommend that you play with smalltalk.
In smalltalk everything is an object, with attributes, behavior and meta. In the simulations you have data types that you use in your objects.
I would say play with it, you will only benefit.
I'm totally in your shoes. Im using RoR and looking into Smalltalk land. Here's some pros & cons I find important:
Pros:
Mature & stable environment
Fast development cycle
Makes you think more and write less
Cons:
Requires different thinking
Still didn't quite grasp it
It's quite funny how I got to know about Smalltalk. It was this one thing that keept popping up in Google results when searching for Lisp and Erlang stuff. One day I checked it out and was amazed with nice windows environment. Few moments later I've found Aida/Web framework. I was hooked and started learning Smalltalk through web development with this framework.
Still not quite there, but it's so damn interesting I just can't sit still... :-) I'm having fun again.
Would not start learning it if I had the time. Why not? Because it would be more productive and lucrative financially to learn C# or Java.
On the other hand if your a hobbyist, and would like to go on an archeological dig, then I'd suggest spending some time looking at the What, When, Why and how of smalltalk by researching Alan Kay. Fascinating story and an incredible person (after all, he earned the Turning Award). Then maybe play with squeak a little to get a feeling for the language. After this you might have a newly found respect/understanding of blocks, closures, and Object Oriented principles.
I know and use Smalltalk, have for about 15 years, still maintaining it, and would not recommend Smalltalk to a friend. Why not? Employment is a good thing to have and keep getting. Although you can learn a lot from Smalltalk you can't easily turn that into gainfully being employed in this day and age.
Also, you appeared to be excited over Seaside and I would assume the Seaside/GemStone partnership. I've used GemStone for quite some time and the two together are very appealing. I hope they can get the market share and momentum required to be successful.
Don't! If you really start learning it, you might not want to programm in something else anymore ever.
This may be not true, if you are a lisp programmer.
Absolutely, learn Smalltalk! This is 2015 and Smalltalk is on the rise again, thanks to Pharo. Pharo is FREE. Pharo is evolving quickly into a powerful enterprise tool. At Version 4.0, and soon to be 5.0, it has matured a great deal in just four years!
Then there's Amber, which is Smalltalk for the web. It's also FREE and evolving quickly.
Despite Smalltalk's reputation, this is not your father's Smalltalk. Modern Smalltalk is exciting and promising.
It's true that Smalltalk jobs are not (yet) plentiful. But if enough of you aggregate to a new wave of Smalltalkers, then the industry will adapt to it and we'll see wider adoption of Smalltalk in business. The question is, do you have the vision?
I was taught Smalltalk in one of the first graduate college level Object-Orient Programming courses (circa 1988). The teacher thought it best to start was a "pure" OO langauge,before moving on to a more trendy one (we did a bit of C++ at the end of the semester).
By that measure, it's still best to start with pure OO, although these days we have Java & C#, both of which are "nearly-pure" OO -- close enough that you can get by ignoring the non-OO features of them, and limiting yourself to the Pure-OO subset of the langauges.
If you want a better understanding of Extreme Programming (and even Scrum) I'd say yes.
Why impatient Java programmers need to learn Smalltalk:
http://www.dafydd.net/archive/2010/why-smalltalk-isnt-just-another-language/
I've been a software engineer for quite a few years now. I've heard people bring up Smalltalk a few times, and certainly Smalltalk has been around since about 1980, but it's one of those languages that's never seemed to make it into the software mainstream. Sort of like Objective C, CLIPS, PL/I, etc--something you may have heard of, but something that most folks have never programmed in.
I probably wouldn't take the time to learn Smalltalk unless I needed to for a particular job. I looked at some Smalltalk tutorials and examples briefly a few years back, and it looks like it has some clear advantages for certain aspects of OO programming (like the message concept seems cool). But sadly, it is not mainstream, and doesn't seem to be gaining much momentum.
This thread has become very actual for me. I'm planning for a Software migration to a web-application. It's a database based software. I'm especially checking the alternatives
1) Rails
2) Seaside
If I can get the figures for the Gemstone/S as Database, I'll consider that also. So for me it means I have to learn Smalltalk (better) than before. Because it could be that it will be my work for the next 15 years. You would (and should not) work with software you don't like for that long ;-). I've the impression Gemstone/S is one of the "killer" applications. But persistence of Objects still is a very difficult field....
1) Yes! It's always good to learn a language. If you are going to learn a language, make it a powerful, influential language that can be learnt easily and quickly.
Smalltalk remains a pre-eminent language and environment for learning OO concepts.
It is all objects, all the way down. This makes for a really consistent approach to working.
Integers are instances of Class Integer. Strings are a collection of character objects. Classes are singleton instance objects for the class they define.
Control structures work by sending get messages to instances of Class Boolean.
Even anonymous methods (blocks of code, aka blocks) are objects.
Everything is done by sending a message to an object. The syntax can be fitted on a postcard.
The clarity of the concepts and their implementation in Smalltalk mean that you can develop ways of thought which transfer directly into Java, Ruby and C#. I expect it's true for Python, too.
It's so good for making the concepts clear that a major UK University used Smalltalk to train 5,000 people a year in object-oriented computing.
Squeak 5, has just been released. It has gained major performance increases from its new Cog/Spur VM, which features with progressive garbage-collection.
Pharo 4 has a lovely clean-looking desktop theme. The next version, Pharo 5, will be released soon. It will move to using the Cog/Spur VM, it will have about 5,000 classes in the release, and additional packages of classes are readily available from the net via the Configuration Browser tool.
Squeak 5 is performant even on first-gen Raspberry Pis, and is almost 50% faster on the new $5 Raspberry Pi zero. $99 buys you a Raspberry Pi 2, screen and case - running a mature, fully feature-complete IDE.
Leading edge research is being done on co-ordinated, distributed OO systems in Smalltalk (e.g. Naiad and Spoon).
Some of the world's largest corporate databases are run on Smalltalk - including tracking of 60% of the world's shipping containers, and trading systems in the world's largest bank.
You can use Smalltalk as a sort of super-powered CoffeeScript, writing in Amber Smalltalk and transpiling to JavaScript, running in the browser.
Squeak, Pharo, and Amber are all Free, Open-source, open-licenced languages and environments.
Squeak and Pharo provide write-once, run anywhere facilities for MacOS, Windows and Linux. (Possibly RiscOS, too).
Dolphin Smalltalk is targetted firmly at native Windows look-and-feel, and lets you compile closed .exes of your finished work for distribution to end users. Further development of Dolphin by the vendor has stopped, but it is completely functional, and, like all Smalltalks, designed to be massively extensible. (Did I mention that Pharo now has 5,000 classes, compared to Squeak's 3,000? Pharo is a fork of Squeak 3.9)
**There is a How-to guide for installing and starting Squeak, Amber, Pharo, Cuis and Dolphin at: **
http://beginningtosmalltalk.blogspot.co.uk/2015/11/how-to-get-smalltalk-up-and-running.html
The Seaside web framework runs on Squeak and on Pharo. It's a wonderful mature tool, as is the more traditional AidaWeb framework.
VisualAge, VisualWorks and Gemstone all provide enterprise-grade robust systems. Gemstone provides an infinitely scalable object database with transactions and persistence.
2) Yes - I do already use it.
I learnt it via the Open University, and was immediately productive in Ruby (a copy of the Pickaxe book and the library reference by my side). It helped me enormously with Java, and with Xerox Moo-code.
I have just returned to it to write apps to control manage and distribute responsive, massively multi-platform mobile apps.
I expect that soon I'll be re-writing my JavaScript mobile apps using Amber, too.
I don't really know what you're looking for.
If you are looking for a different language to write in, I'd think that would depend heavily on the libraries available. I know neither Ruby nor Smalltalk, but it seems likely that the most efficient way to write Ruby on Rails-sorts of applications may not be Smalltalk.
If you are looking to learn the ideas behind Ruby, this might be a very good move. I don't have anything quantitative, but I always felt better about using tools (such as language systems) if I knew more than just the tools, if I kmew the ideas behind them or how they worked.
If you want to learn different sorts of object-oriented languages, you might well want to learn Smalltalk (if it differs significantly from Ruby), something like Java or C++, and perhaps also the Common Lisp Object System.
If you just want to learn something different, Smalltalk may well be a good choice. I'd also suggest Common Lisp, and other people will doubtless have other suggestions (can you get a good Forth system nowadays?).
Yes, I'm interested in it. Tried to start once already, but couldn't find a Smalltalk development environment that didn't cost both arms and a leg.
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Background
Last year, I did an internship in a physics research group at a university. In this group, we mostly used LabVIEW to write programs for controlling our setups, doing data acquisition and analyzing our data. For the first two purposes, that works quite OK, but for data analysis, it's a real pain. On top of that, everyone was mostly self-taught, so code that was written was generally quite a mess (no wonder that every PhD quickly decided to rewrite everything from scratch). Version control was unknown, and impossible to set up because of strict software and network regulations from the IT department.
Now, things actually worked out surprisingly OK, but how do people in the natural sciences do their software development?
Questions
Some concrete questions:
What languages/environments have you used for developing scientific software, especially data analysis? What libraries? (for example, what do you use for plotting?)
Was there any training for people without any significant background in programming?
Did you have anything like version control, and bug tracking?
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (especially physicists are stubborn people!)
Summary of answers thus far
The answers (or my interpretation of them) thus far: (2008-10-11)
Languages/packages that seem to be the most widely used:
LabVIEW
Python
with SciPy, NumPy, PyLab, etc. (See also Brandon's reply for downloads and links)
C/C++
MATLAB
Version control is used by nearly all respondents; bug tracking and other processes are much less common.
The Software Carpentry course is a good way to teach programming and development techniques to scientists.
How to improve things?
Don't force people to follow strict protocols.
Set up an environment yourself, and show the benefits to others. Help them to start working with version control, bug tracking, etc. themselves.
Reviewing other people's code can help, but be aware that not everyone may appreciate that.
What languages/environments have you used for developing scientific software, esp. data analysis? What libraries? (E.g., what do you use for plotting?)
I used to work for Enthought, the primary corporate sponsor of SciPy. We collaborated with scientists from the companies that contracted Enthought for custom software development. Python/SciPy seemed to be a comfortable environment for scientists. It's much less intimidating to get started with than say C++ or Java if you're a scientist without a software background.
The Enthought Python Distribution comes with all the scientific computing libraries including analysis, plotting, 3D visualation, etc.
Was there any training for people without any significant background in programming?
Enthought does offer SciPy training and the SciPy community is pretty good about answering questions on the mailing lists.
Did you have anything like version control, bug tracking?
Yes, and yes (Subversion and Trac). Since we were working collaboratively with the scientists (and typically remotely from them), version control and bug tracking were essential. It took some coaching to get some scientists to internalize the benefits of version control.
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (esp. physicists are stubborn people!)
Make sure they are familiarized with the tool chain. It takes an investment up front, but it will make them feel less inclined to reject it in favor of something more familiar (Excel). When the tools fail them (and they will), make sure they have a place to go for help — mailing lists, user groups, other scientists and software developers in the organization. The more help there is to get them back to doing physics the better.
The course Software Carpentry is aimed specifically at people doing scientific computing and aims to teach the basics and lessons of software engineering, and how best to apply them to projects.
It covers topics like version control, debugging, testing, scripting and various other issues.
I've listened to about 8 or 9 of the lectures and think it is to be highly recommended.
Edit: The MP3s of the lectures are available as well.
Nuclear/particle physics here.
Major programing work used to be done mostly in Fortran using CERNLIB (PAW, MINUIT, ...) and GEANT3, recently it has mostly been done in C++ with ROOT and Geant4. There are a number of other libraries and tools in specialized use, and LabVIEW sees some use here and there.
Data acquisition in my end of this business has often meant fairly low level work. Often in C, sometimes even in assembly, but this is dying out as the hardware gets more capable. On the other hand, many of the boards are now built with FPGAs which need gate twiddling...
One-offs, graphical interfaces, etc. use almost anything (Tcl/Tk used to be big, and I've been seeing more Perl/Tk and Python/Tk lately) including a number of packages that exist mostly inside the particle physics community.
Many people writing code have little or no formal training, and process is transmitted very unevenly by oral tradition, but most of the software group leaders take process seriously and read as much as necessary to make up their deficiencies in this area.
Version control for the main tools is ubiquitous. But many individual programmers neglect it for their smaller tasks. Formal bug tracking tools are less common, as are nightly builds, unit testing, and regression tests.
To improve things:
Get on the good side of the local software leaders
Implement the process you want to use in your own area, and encourage those you let in to use it too.
Wait. Physicists are empirical people. If it helps, they will (eventually!) notice.
One more suggestion for improving things.
Put a little time in to helping anyone you work directly with. Review their code. Tell them about algorithmic complexity/code generation/DRY or whatever basic thing they never learned because some professor threw a Fortran book at them once and said "make it work". Indoctrinate them on process issues. They are smart people, and they will learn if you give them a chance.
This might be slightly tangential, but hopefully relevant.
I used to work for National Instruments, R&D, where I wrote software for NI RF & Communication toolkits. We used LabVIEW quite a bit, and here are the practices we followed:
Source control. NI uses Perforce. We did the regular thing - dev/trunk branches, continuous integration, the works.
We wrote automated test suites.
We had a few people who came in with a background in signal processing and communication. We used to have regular code reviews, and best practices documents to make sure their code was up to the mark.
Despite the code reviews, there were a few occasions when "software guys", like me had to rewrite some of this code for efficiency.
I know exactly what you mean about stubborn people! We had folks who used to think that pointing out a potential performance improvement in their code was a direct personal insult! It goes without saying that that this calls for good management. I thought the best way to deal with these folks is to go slowly, not press to hard for changes and if necessary be prepared to do the dirty work. [Example: write a test suite for their code].
I'm not exactly a 'natural' scientist (I study transportation) but am an academic who writes a lot of my own software for data analysis. I try to write as much as I can in Python, but sometimes I'm forced to use other languages when I'm working on extending or customizing an existing software tool. There is very little programming training in my field. Most folks are either self-taught, or learned their programming skills from classes taken previously or outside the discipline.
I'm a big fan of version control. I used Vault running on my home server for all the code for my dissertation. Right now I'm trying to get the department to set up a Subversion server, but my guess is I will be the only one who uses it, at least at first. I've played around a bit with FogBugs, but unlike version control, I don't think that's nearly as useful for a one-man team.
As for encouraging others to use version control and the like, that's really the problem I'm facing now. I'm planning on forcing my grad students to use it on research projects they're doing for me, and encouraging them to use it for their own research. If I teach a class involving programming, I'll probably force the students to use version control there too (grading them on what's in the repository). As far as my colleagues and their grad students go, all I can really do is make a server available and rely on gentle persuasion and setting a good example. Frankly, at this point I think it's more important to get them doing regular backups than get them on source control (some folks are carrying around the only copy of their research data on USB flash drives).
1.) Scripting languages are popular these days for most things due to better hardware. Perl/Python/Lisp are prevalent for lightweight applications (automation, light computation); I see a lot of Perl at my work (computational EM) since we like Unix/Linux. For performance stuff, C/C++/Fortran are typically used. For parallel computing, well, we usually manually parallelize runs in EM as opposed to having a program implicitly do it (ie split up the jobs by look angle when computing radar cross sections).
2.) We just kind of throw people into the mix here. A lot of the code we have is very messy, but scientists are typically a scatterbrained bunch that don't mind that sort of thing. Not ideal, but we have things to deliver and we're severely understaffed. We're slowly getting better.
3.) We use SVN; however, we do not have bug tracking software. About as good as it gets for us is a txt file that tells you where bugs specific bugs are.
4.) My suggestion for implementing best practices for scientists: do it slowly. As scientists, we typically don't ship products. No one in science makes a name for himself by having clean, maintainable code. They get recognition from the results of that code, typically. They need to see justification for spending time on learning software practices. Slowly introduce new concepts and try to get them to follow; they're scientists, so after their own empirical evidence confirms the usefulness of things like version control, they will begin to use it all the time!
I'd highly recommend reading "What Every Computer Scientist Should Know About Floating-Point Arithmetic". A lot of problems I encounter on a regular basis come from issues with floating point programming.
I am a physicist working in the field of condensed matter physics, building classical and quantum models.
Languages:
C++ -- very versatile: can be used for anything, good speed, but it can be a bit inconvenient when it comes to MPI
Octave -- good for some supplementary calculations, very convenient and productive
Libraries:
Armadillo/Blitz++ -- fast array/matrix/cube abstractions for C++
Eigen/Armadillo -- linear algebra
GSL -- to use with C
LAPACK/BLAS/ATLAS -- extremely big and fast, but less convenient (and written in FORTRAN)
Graphics:
GNUPlot -- it has very clean and neat output, but not that productive sometimes
Origin -- very convenient for plotting
Development tools:
Vim + plugins -- it works great for me
GDB -- a great debugging tool when working with C/C++
Code::Blocks -- I used it for some time and found it quite comfortable, but Vim is still better in my opinion.
I work as a physicist in a UK university.
Perhaps I should emphasise that different areas of research have different emphasis on programming. Particle physicists (like dmckee) do computational modelling almost exclusively and may collaborate on large software projects, whereas people in fields like my own (condensed matter) write code relatively infrequently. I suspect most scientists fall into the latter camp. I would say coding skills are usually seen as useful in physics, but not essential, much like physics/maths skills are seen as useful for programmers but not essential. With this in mind...
What languages/environments have you used for developing scientific software, esp. data analysis? What libraries? (E.g., what do you use for plotting?)
Commonly data analysis and plotting is done using generic data analysis packages such as IGOR Pro, ORIGIN, Kaleidegraph which can be thought of as 'Excel plus'. These packages typically have a scripting language that can be used to automate. More specialist analysis may have a dedicated utility for the job that generally will have been written a long time ago, no-one has the source for and is pretty buggy. Some more techie types might use the languages that have been mentioned (Python, R, MatLab with Gnuplot for plotting).
Control software is commonly done in LabVIEW, although we actually use Delphi which is somewhat unusual.
Was there any training for people without any significant background in programming?
I've been to seminars on grid computing, 3D visualisation, learning Boost etc. given by both universities I've been at. As an undergraduate we were taught VBA for Excel and MatLab but C/MatLab/LabVIEW is more common.
Did you have anything like version control, bug tracking?
No, although people do have personal development setups. Our code base is in a shared folder on a 'server' which is kept current with a synching tool.
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (esp. physicists are stubborn people!)
One step at a time! I am trying to replace the shared folder with something a bit more solid, perhaps finding a SVN client which mimics the current synching tools behaviour would help.
I'd say though on the whole, for most natural science projects, time is generally better spent doing research!
Ex-academic physicist and now industrial physicist UK here:
What languages/environments have you used for developing scientific software, esp. data analysis? What libraries? (E.g., what do you use for plotting?)
I mainly use MATLAB these days (easy to access visualisation functions and maths). I used to use Fortran a lot and IDL. I have used C (but I'm more a reader than a writer of C), Excel macros (ugly and confusing). I'm currently needing to be able to read Java and C++ (but I can't really program in them) and I've hacked Python as well. For my own entertainment I'm now doing some programming in C# (mainly to get portability / low cost / pretty interfaces). I can write Fortran with pretty much any language I'm presented with ;-)
Was there any training for people without any significant background in programming?
Most (all?) undergraduate physics course will have a small programming course usually on C, Fortran or MATLAB but it's the real basics. I'd really like to have had some training in software engineering at some point (revision control / testing / designing medium scale systems)
Did you have anything like version control, bug tracking?
I started using Subversion / TortoiseSVN relatively recently. Groups I've worked with in the past have used revision control. I don't know any academic group which uses formal bug tracking software. I still don't use any sort of systematic testing.
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (esp. physicists are stubborn people!)
I would try to introduce some software engineering ideas at undergraduate level and then reinforce them by practice at graduate level, also provide pointers to resources like the Software Carpentry course mentioned above.
I'd expect that a significant fraction of academic physicists will be writing software (not necessarily all though) and they are in dire need of at least an introduction to ideas in software engineering.
What languages/environments have you used for developing scientific software, esp. data analysis? What libraries? (E.g., what do you use for plotting?)
Python, NumPy and pylab (plotting).
Was there any training for people without any significant background in programming?
No, but I was working in a multimedia research lab, so almost everybody had a computer science background.
Did you have anything like version control, bug tracking?
Yes, Subversion for version control, Trac for bug tracing and wiki. You can get free bug tracker/version control hosting from http://www.assembla.com/ if their TOS fits your project.
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (esp. physicists are stubborn people!).
Make sure the infrastructure is set up and well maintained and try to sell the benefits of source control.
I'm a statistician at a university in the UK. Generally people here use R for data analysis, it's fairly easy to learn if you know C/Perl. Its real power is in the way you can import and modify data interactively. It's very easy to take a number of say CSV (or Excel) files and merge them, create new columns based on others and then throw that into a GLM, GAM or some other model. Plotting is trivial too and doesn't require knowledge of a whole new language (like PGPLOT or GNUPLOT.) Of course, you also have the advantage of having a bunch of built-in features (from simple things like mean, standard deviation etc all the way to neural networks, splines and GL plotting.)
Having said this, there are a couple of issues. With very large datasets R can become very slow (I've only really seen this with >50,000x30 datasets) and since it's interpreted you don't get the advantage of Fortran/C in this respect. But, you can (very easily) get R to call C and Fortran shared libraries (either from something like netlib or ones you've written yourself.) So, a usual workflow would be to:
Work out what to do.
Prototype the code in R.
Run some preliminary analyses.
Re-write the slow code into C or Fortran and call that from R.
Which works very well for me.
I'm one of the only people in my department (of >100 people) using version control (in my case using git with githuib.com.) This is rather worrying, but they just don't seem to be keen on trying it out and are content with passing zip files around (yuck.)
My suggestion would be to continue using LabView for the acquisition (and perhaps trying to get your co-workers to agree on a toolset for acquisition and making is available for all) and then move to exporting the data into a CSV (or similar) and doing the analysis in R. There's really very little point in re-inventing the wheel in this respect.
What languages/environments have you used for developing scientific software, esp. data analysis? What libraries? (E.g., what do you use for plotting?)
My undergraduate physics department taught LabVIEW classes and used it extensively in its research projects.
The other alternative is MATLAB, in which I have no experience. There are camps for either product; each has its own advantages/disadvantages. Depending on what kind of problems you need to solve, one package may be more preferable than the other.
Regarding data analysis, you can use whatever kind of number cruncher you want. Ideally, you can do the hard calculations in language X and format the output to plot nicely in Excel, Mathcad, Mathematica, or whatever the flavor du jour plotting system is. Don't expect standardization here.
Did you have anything like version control, bug tracking?
Looking back, we didn't, and it would have been easier for us all if we did. Nothing like breaking everything and struggling for hours to fix it!
Definitely use source control for any common code. Encourage individuals to write their code in a manner that could be made more generic. This is really just coding best practices. Really, you should have them teaching (or taking) a computer science class so they can get the basics.
How would you go about trying to create a decent environment for programming, without getting too much in the way of the individual scientists (esp. physicists are stubborn people!)
There is a clear split between data aquisition (DAQ) and data analysis. Meaning, it's possible to standardize on the DAQ and then allow the scientists to play with the data in the program of their choice.
Another good option is Scilab. It has graphic modules à la LabVIEW, it has its own programming language and you can also embed Fortran and C code, for example. It's being used in public and private sectors, including big industrial companies. And it's free.
About versioning, some prefer Mercurial, as it gives more liberties managing and defining the repositories. I have no experience with it, however.
For plotting I use Matplotlib. I will soon have to make animations, and I've seen good results using MEncoder. Here is an example including an audio track.
Finally, I suggest going modular, this is, trying to keep main pieces of code in different files, so code revision, understanding, maintenance and improvement will be easier. I have written, for example, a Python module for file integrity testing, another for image processing sequences, etc.
You should also consider developing with the use a debugger that allows you to check variable contents at settable breakpoints in the code, instead using print lines.
I have used Eclipse for Python and Fortran developing (although I got a false bug compiling a Fortran short program with it, but it may have been a bad configuration) and I'm starting to use the Eric IDE for Python. It allows you to debug, manage versioning with SVN, it has an embedded console, it can do refactoring with Bicycle Repair Man (it can use another one, too), you have Unittest, etc. A lighter alternative for Python is IDLE, included with Python since version 2.3.
As a few hints, I also suggest:
Not using single-character variables. When you want to search appearances, you will get results everywhere. Some argue that a decent IDE makes this easier, but then you will depend on having permanent access to the IDE. Even using ii, jj and kk can be enough, although this choice will depend on your language. (Double vowels would be less useful if code comments are made in Estonian, for instance).
Commenting the code from the very beginning.
For critical applications sometimes it's better to rely on older language/compiler versions (major releases), more stable and better debugged.
Of course you can have more optimized code in later versions, fixed bugs, etc, but I'm talking about using Fortran 95 instead of 2003, Python 2.5.4 instead of 3.0, or so. (Specially when a new version breaks backwards compatibility.) Lots of improvements usually introduce lots of bugs. Still, this will depend on specific application cases!
Note that this is a personal choice, many people could argue against this.
Use redundant and automated backup! (With versioning control).
Definitely, use Subversion to keep current, work-in-progress, and stable snapshot copies of source code. This includes C++, Java etc. for homegrown software tools, and quickie scripts for one-off processing.
With the strong leaning in science and applied engineering toward "lone cowboy" development methodology, the usual practice of organizing the repository into trunk, tag and whatever else it was - don't bother! Scientists and their lab technicians like to twirl knobs, wiggle electrodes and chase vacuum leaks. It's enough of a job to get everyone to agree to, say Python/NumPy or follow some naming convention; forget trying to make them follow arcane software developer practices and conventions.
For source code management, centralized systems such as Subversion are superior for scientific use due to the clear single point of truth (SPOT). Logging of changes and ability to recall versions of any file, without having chase down where to find something, has huge record-keeping advantages. Tools like Git and Monotone: oh my gosh the chaos I can imagine that would follow! Having clear-cut records of just what version of hack-job scripts were used while toying with the new sensor when that Higgs boson went by or that supernova blew up, will lead to happiness.
What languages/environments have you
used for developing scientific
software, esp. data analysis? What
libraries? (E.g., what do you use for
plotting?)
Languages I have used for numerics and sicentific-related stuff:
C (slow development, too much debugging, almost impossible to write reusable code)
C++ (and I learned to hate it -- development isn't as slow as C, but can be a pain. Templates and classes were cool initially, but after a while I realized that I was fighting them all the time and finding workarounds for language design problems
Common Lisp, which was OK, but not widely used fo Sci computing. Not easy to integrate with C (if compared to other languages), but works
Scheme. This one became my personal choice.
My editor is Emacs, although I do use vim for quick stuff like editing configuration files.
For plotting, I usually generate a text file and feed it into gnuplot.
For data analysis, I usually generate a text file and use GNU R.
I see lots of people here using FORTRAN (mostly 77, but some 90), lots of Java and some Python. I don't like those, so I don't use them.
Was there any training for people
without any significant background in
programming?
I think this doesn't apply to me, since I graduated in CS -- but where I work there is no formal training, but people (Engineers, Physicists, Mathematicians) do help each other.
Did you have anything like version
control, bug tracking?
Version control is absolutely important! I keep my code and data in three different machines, in two different sides of the world -- in Git repositories. I sync them all the time (so I have version control and backups!) I don't do bug control, although I may start doing that.
But my colleagues don't BTS or VCS at all.
How would you go about trying to
create a decent environment for
programming, without getting too much
in the way of the individual
scientists (esp. physicists are
stubborn people!)
First, I'd give them as much freedom as possible. (In the University where I work I could chooe between having someone install Ubuntu or Windows, or install my own OS -- I chose to install my own. I don't have support from them and I'm responsible for anything that happens with my machins, including security issues, but I do whatever I want with the machine).
Second, I'd see what they are used to, and make it work (need FORTRAN? We'll set it up. Need C++? No problem. Mathematica? OK, we'll buy a license). Then see how many of them would like to learn "additional tools" to help them be more productive (don't say "different" tools. Say "additional", so it won't seem like anyone will "lose" or "let go" or whatever). Start with editors, see if there are groups who would like to use VCS to sync their work (hey, you can stay home and send your code through SVN or GIT -- wouldn't that be great?) and so on.
Don't impose -- show examples of how cool these tools are. Make data analysis using R, and show them how easy it was. Show nice graphics, and explain how you've created them (but start with simple examples, so you can quickly explain them).
I would suggest F# as a potential candidate for performing science-related manipulations given its strong semantic ties to mathematical constructs.
Also, its support for units-of-measure, as written about here makes a lot of sense for ensuring proper translation between mathematical model and implementation source code.
First of all, I would definitely go with a scripting language to avoid having to explain a lot of extra things (for example manual memory management is - mostly - ok if you are writing low-level, performance sensitive stuff, but for somebody who just wants to use a computer as an upgraded scientific calculator it's definitely overkill). Also, look around if there is something specific for your domain (as is R for statistics). This has the advantage of already working with the concepts the users are familiar with and having specialized code for specific situations (for example calculating standard deviations, applying statistical tests, etc in the case of R).
If you wish to use a more generic scripting language, I would go with Python. Two things it has going for it are:
The interactive shell where you can experiment
Its clear (although sometimes lengthy) syntax
As an added advantage, it has libraries for most of the things you would want to do with it.
I'm no expert in this area, but I've always understood that this is what MATLAB was created for. There is a way to integrate MATLAB with SVN for source control as well.