Soooo...
Semigroups, Monoids, Monads, Functors, Lenses, Catamorphisms, Anamorphisms, Arrows... These all sound good, and after an exercise or two (or ten), you can grasp their essence. And with Scalaz, you get them for free...
However, in terms of real-world programming, I find myself struggling to find usages to these notions. Yes, of course I always find someone on the web using Monads for IO or Lenses in Scala, but... still...
What I am trying to find is something along the "prescriptive" lines of a pattern. Something like: "here, you are trying to solves this, and one good way to solve it is by using lenses this way!"
Suggestions?
Update: Something along these lines, with a book or two, would be great (thanks Paul): Examples of GoF Design Patterns in Java's core libraries
The key to functional programming is abstraction, and composability of abstractions. Monads, Arrows, Lenses, these are all abstractions which have proven themselves useful, mostly because they are composable. You've asked for a "prescriptive" answer, but I'm going to say no. Perhaps you're not convinced that functional programming matters?
I'm sure plenty of people on StackOverflow would be more than happy to try and help you solve a specific problem the FP way. Have a list of stuff and you want to traverse the list and build up some result? Use a fold. Want to parse XML? hxt uses arrows for that. And monads? Well, tons of data types turn out to be Monads, so learn about them and you'll discover a wealth of ways you can manipulate these data types. But its kind of hard to just pull examples out of thin air and say "lenses are the Right Way to do this", "monoids are the best way to do that", etc. How would you explain to a newbie what the use of a for loop is? If you want to [blank], then use a for loop [in this way]. It's so general; there are tons of ways to use a for loop. The same goes for these FP abstractions.
If you have many years of OOP experience, then don't forget you were once a newbie at OOP. It takes time to learn the FP way, and even more time to unlearn some OOP tendencies. Give it time and you will find plenty of uses for a Functional approach.
I gave a talk back in September focused on the practical application of monoids and applicative functors/monads via scalaz.Validation. I gave another version of the same talk at the scala Lift Off, where the emphasis was more on the validation. I would watch the first talk until I start on validations and then skip to the second talk (27 minutes in).
There's also a gist I wrote which shows how you might use Validation in a "practical" application. That is, if you are designing software for nightclub bouncers.
I think you can take the reverse approach and instead when writing a small piece of functionality, ask yourself whether any of those would apply: Semigroups, Monoids, Monads, Functors, Lenses, Catamorphisms, Anamorphisms, Arrows... A lots of those concepts can be used in a local way.
Once you start down that route, you may see usage everywhere. For me, I sort of get Semigroups, Monoids, Monads, Functors. So take the example of answering this question How do I populate a list of objects with new values. It's a real usage for the person asking the question (a self described noob). I am trying to answer in a simple way but I have to refrain myself from scratching the itch "there are monoids in here".
Scratching it now: using foldMap and the fact that Int and List are monoids and that the monoid property is preserved when dealing with tuple, maps and options:
// using scalaz
listVar.sliding(2).toList.foldMap{
case List(prev, i) => Some(Map(i -> (1, Some(List(math.abs(i - prev))))))
case List(i) => Some(Map(i -> (1, None)))
case _ => None
}.map(_.mapValues{ case (count, gaps) => (count, gaps.map(_.min)) })
But I don't come to that result by thinking I will use hard core functional programming. It comes more naturally by thinking this seems simpler if I compose those monoids combined with the fact that scalaz has utility methods like foldMap. Interestingly when looking at the resulting code it's not obvious that I'm totally thinking in terms of monoid.
You might like this talk by Chris Marshall. He covers a couple of Scalaz goodies - namely Monoid and Validation - with many practical examples. Ittay Dror has written a very accessible post on how Functor, Applicative Functor, and Monad can be useful in practice. Eric Torreborre and Debasish Gosh's blogs also have a bunch of posts covering use cases for categorical constructs.
This answer just lists a few links instead of providing some real substance here. (Too lazy to write.) Hope you find it helpful anyway.
I understand your situation, but you will find that to learn functional programming you will need to adjust your point of view to the documentation you find, instead of the other way around. Luckily in Scala you have the possibility of becoming a functional programmer gradually.
To answer your questions and explain the point-of-view difference, I need to distinguish between "type classes" (monoids, functors, arrows), mathematically called "structures", and generic operations or algorithms (catamorphisms or folds, anamorphisms or unfolds, etc.). These two often interact, since many generic operations are defined for specific classes of data types.
You look for prescriptive answers similar to design patterns: when does this concept apply? The truth is that you have surely seen the prescriptive answers, and they are simply the definitions of the different concepts. The problem (for you) is that those answers are intrinsically different from design patterns, but it is so for good reasons.
On the one hand, generic algorithms are not design patterns, which suggest a structure for the code you write; they are abstractions defined in the language which you can directly apply. They are general descriptions for common algorithms which you already implement today, but by hand. For instance, whenever you are computing the maximum element of a list by scanning it, you are hardcoding a fold; when you sum elements, you are doing the same; and so on. When you recognize that, you can declare the essence of the operation you are performing by calling the appropriate fold function. This way, you save code and bugs (no opportunity for off-by-one errors), and you save the reader the effort to read all the needed code.
On the other hand, structures concern not the goal you have in mind but properties of the entities you are modeling. They are more useful for bottom-up software construction, rather than top-down: when defining your data, you can declare that it is a e.g. a monoid. Later, when processing your data, you have the opportunity to use operations on e.g. monoids to implement your processing. In some cases it is useful to strive to express your algorithm in terms of the predefined ones. For instance, very often if you need to reduce a tree to a single value, a fold can do most or all of what you need. Of course, you can also declare that your data type is a monoid when you need a generic algorithm on monoids; but the earlier you notice that, the earlier you can start reusing generic algorithms for monoids.
Last advice is that probably most of the documentation you will find about these concepts concerns Haskell, because this language has been around for much more time and supports them in a quite elegant way. Quite recommended here are Learn you a Haskell for Great Good, a Haskell course for beginners, where among others chapters 11 to 14 focus on some type classes, and Typeclassopedia (which contains links to various articles with specific examples). EDIT: Finally, an example of applications of Monoids, taken from Typeclassopedia, is here: http://apfelmus.nfshost.com/articles/monoid-fingertree.html. I'm not saying there is little documentation for Scala, just that there is more in Haskell, and Haskell is where the application of these concepts to programming was born.
Related
I was under the impression that there are folks out there that do write pure applications using Scalaz, but based on this example: [ stacking StateT in scalaz ], it looks like anything real would also be impossibly hairy.
Are there any guidelines or examples of real, modular, loosely-coupled, pure applications in Scala? I'm expecting that this means scalaz.effect.SafeApp and RWST over IO, but I'd like to hear from folks who have done it.
Thanks.
Edit: In the absence of an answer, I've started collecting resources as an answer below. If you have any examples or related links to contribute, please do.
i think you are mixing two different things. one is pure functional programming and second is scala type system. you can do 'pure' programming in any language, even in java. if the language is funvtional than you will have pure functional programming.
does it make your programs work faster? depends on the program - it scales better but for single threaded parts you will rather loose performance.
does it 'save your cognition'? it depends on how good you are in what you are doing. if you work with FP, monads, arrows etc on the daily basis then i assume it may help significantly. if you show the code to the OO developer he probably won't understand anything.
does it save the development time? as previously, i think it may but to be honest it doesn't matter that much. you more often read the code rather than write it
can you do useful stuff in PFP? yes, some companies makes money on haskell
and now, can it be done in scala? for sure. will anyone do it in scala? probably not because it's too easy to break the purity, because type system is too weak and because there are better, 'more pure' tools for it (but currently not on jvm)
I guess I will start collecting resources here, and update as I find more.
Functional Reactive Programming: stefan hoeck's blog, github, examples
Monadic effect worlds for interacting safely with mutable data. (tpolecat)
Mellow database access for Scala (tpolecat)
Dependency Injection without the Gymnastics (tony, rúnar)
Google search for "extends SafeApp"
I'm starting to learn Functional Programming and would like to do so with Scala, not Haskell or Lisp.
But some people claim that learning Scala as the first functional language slows down your learning of Functional Programming, because Scala allows you to program both ways, and one tends to program the procedural way when confronted with a hard problem.
How can i make sure that 'm programming in a purely functional way? Maybe, due to not being able to properly distinguish both styles, I'll inadvertently program procedurally).
I know, for example, that I should only use vals and not vars.
The other answers have made some good points, but for an attempt to quickly get down some guidelines, here's how I'd start:
Firstly, some things to completely avoid:
Don't use the var keyword.
Don't use the while keyword.
Don't use anything in the scala.collection.mutable package.
Don't use the asInstanceOf method.
Don't use null. If you ever come across null (in someone else's code), immediately wrap it in a more appropriate datatype (usually Option will do nicely).
Then, a couple of things to generally avoid:
Be wary of calling anything with a return type of Unit. A function with a return type of Unit is either doing nothing, or acting only by side-effects. In some cases you won't be able to avoid this (IO being the obvious one), but where you see it elsewhere it's probably a sign of impurity.
Be wary of calling into Java libraries - they are typically not designed with functional programming in mind, and will often require you to abandon the functional approach.
Once you've avoided these things, what can you do to move your code to being more functional?
When you're performing direct recursion, look for opportunities to generalise it through the use of higher order combinators. fold is likely your biggest candidate here - most operations on lists can be implemented in terms of a suitable fold.
When you see destructuring operations on a data structure (typically through pattern matching), consider whether instead you can lift the computation into the structure and avoid destructuring it. An obvious example is the following code snippet:
foo match {
case Some(x) => Some(x + 2)
case None => None
}
can be replaced with:
foo map ( _ + 2 )
I dare say that your goal is already misleading:
I'm starting to learn Function Programming, and I really wanna learn
Scala, not Haskell or Lisp.
If you are really interested in learning concepts of function programming, then why not use a language such as Haskell that (more or less) does not allow you to use procedural or object-oriented concepts? In the end, the language is "just" a tool that helps you learning concepts of FP, you could just as well read loads of papers about FP. At least theoretically, I think it is usually easier to learn concepts of computer science with concrete tools at hand.
On the other hand, if you are interested in learning the language Scala, then why not use all features that it offers, regardless of whether they stem from the FP or the OO world?
In order to conclude with a somewhat practical advise: You could search for FP tutorials that use Scala or for blog entries etc. that describe how to realise certain FP-concepts in Scala and try to follow them. This way, it is less likely that you make use of non-FP concepts.
You don't buy a Ferarri to deliver furniture. Scala's fundamental strength is the fact that in your words, it goes both ways:). Whether or not you are programming in a functional style is decided by the techniques you use.
The best thing you can do is thoroughly review fundamental concepts of functional programming and seek the appropriate Scala implementation of the respective concepts. But if you want to program purely functional style, then go for Haskell, Lisp, Erlang, OCaml, or whatever other purely functional dialect.
Functional programming
Introduction
Functional thinking
Scala
If you want to learn Scala, then make sure to include both OO and FP in your learning curve. Lambda expressions + OO concepts + syntactic sugar made possible by IMHO the most advanced compiler on the face of the planet lead to something quite amazing. Take advantage of it!
I think learning is non linear process, it helps to see lots of ways of doing the same thing, also be opportunistic and use any learning resources that are available for you. For example Martin Odersky the creator of Scala offers a free course called "Functional Programming Principles in Scala" https://class.coursera.org/progfun-002/class/index there are some very high quality video lectures, and some really good assignments where the automated grader will tell you that your code is not functional enough and you loose style points because you are using var instead of val
I think the thing you want to focus on is learning the Functional Programming Paradigm and for me learning a paradigm is about learning what types of problems are easy to solve in one paradigm and are hard to solve in another paradigm. Focus on the paradigm and I think you will find that learning both about Haskell and Scala will teach you the functional paradigm faster, because you will be able to ask the question what are the common features between Scala and Haskell, what are the differences .... etc
I know, for example, that I should only use vals and not vars.
That's already a good start, other non-so-functional things to avoid are mutable collections and loops.
Have a look at immutable collections and recursion instead.
Of course, once you are familiar with the functional concepts, there might also be good reasons to use scala's non-functional features.
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Closed 9 years ago.
What are the most commonly held misconceptions about the Scala language, and what counter-examples exist to these?
UPDATE
I was thinking more about various claims I've seen, such as "Scala is dynamically typed" and "Scala is a scripting language".
I accept that "Scala is [Simple/Complex]" might be considered a myth, but it's also a viewpoint that's very dependent on context. My personal belief is that it's the very same features that can make Scala appear either simple or complex depending oh who's using them. Ultimately, the language just offers abstractions, and it's the way that these are used that shapes perceptions.
Not only that, but it has a certain tendency to inflame arguments, and I've not yet seen anyone change a strongly-held viewpoint on the topic...
Myth: That Scala’s “Option” and Haskell’s “Maybe” types won’t save you from null. :-)
Debunked: Why Scala's "Option" and Haskell's "Maybe" types will save you from null by James Iry.
Myth: Scala supports operator overloading.
Actually, Scala just has very flexible method naming rules and infix syntax for method invocation, with special rules for determining method precedence when the infix syntax is used with 'operators'. This subtle distinction has critical implications for the utility and potential for abuse of this language feature compared to true operator overloading (a la C++), as explained more thoroughly in James Iry's answer to this question.
Myth: methods and functions are the same thing.
In fact, a function is a value (an instance of one of the FunctionN classes), while a method is not. Jim McBeath explains the differences in greater detail. The most important practical distinctions are:
Only methods can have type parameters
Only methods can take implicit arguments
Only methods can have named and default parameters
When referring to a method, an underscore is often necessary to distinguish method invocation from partial function application (e.g. str.length evaluates to a number, while str.length _ evaluates to a zero-argument function).
I disagree with the argument that Scala is hard because you can use very advanced features to do hard stuff with it. The scalability of Scala means that you can write DSL abstractions and high-level APIs in Scala itself that otherwise would need a language extension. So to be fair you need to compare Scala libraries to other languages compilers. People don't say that C# is hard because (I assume, don't have first hand knowledge on this) the C# compiler is pretty impenetrable. For Scala it's all out in the open. But we need to get to a point where we make clear that most people don't need to write code on this level, nor should they do it.
I think a common misconception amongst many scala developers, those at EPFL (and yourself, Kevin) is that "scala is a simple language". The argument usually goes something like this:
scala has few keywords
scala reuses the same few constructs (e.g. PartialFunction syntax is used as the body of a catch block)
scala has a few simple rules which allow you to create library code (which may appear as if the language has special keywords/constructs). I'm thinking here of implicits; methods containing colons; allowed identifier symbols; the equivalence of X(a, b) and a X b with extractors. And so on
scala's declaration-site variance means that the type system just gets out of your way. No more wildcards and ? super T
My personal opinion is that this argument is completely and utterly bogus. Scala's type system taken together with implicits allows one to write frankly impenetrable code for the average developer. Any suggestion otherwise is just preposterous, regardless of what the above "metrics" might lead you to think. (Note here that those who I've seen scoffing at the non-complexity of Java on Twitter and elsewhere happen to be uber-clever types who, it sometimes seems, had a grasp of monads, functors and arrows before they were out of short pants).
The obvious arguments against this are (of course):
you don't have to write code like this
you don't have to pander to the average developer
Of these, it seems to me that only #2 is valid. Whether or not you write code quite as complex as scalaz, I think it's just silly to use the language (and continue to use it) with no real understanding of the type system. How else can one get the best out of the language?
There is a myth that Scala is difficult because Scala is a complex language.
This is false--by a variety of metrics, Scala is no more complex than Java. (Size of grammar, lines of code or number of classes or number of methods in the standard API, etc..)
But it is undeniably the case that Scala code can be ferociously difficult to understand. How can this be, if Scala is not a complex language?
The answer is that Scala is a powerful language. Unlike Java, which has many special constructs (like enums) that accomplish one particular thing--and requires you to learn specialized syntax that applies just to that one thing, Scala has a variety of very general constructs. By mixing and matching these constructs, one can express very complex ideas with very little code. And, unsurprisingly, if someone comes along who has not had the same complex idea and tries to figure out what you're doing with this very compact code, they may find it daunting--more daunting, even, than if they saw a couple of pages of code to do the same thing, since then at least they'd realize how much conceptual stuff there was to understand!
There is also an issue of whether things are more complex than they really need to be. For example, some of the type gymnastics present in the collections library make the collections a joy to use but perplexing to implement or extend. The goals here are not particularly complicated (e.g. subclasses should return their own types), but the methods required (higher-kinded types, implicit builders, etc.) are complex. (So complex, in fact, that Java just gives up and doesn't try, rather than doing it "properly" as in Scala. Also, in principle, there is hope that this will improve in the future, since the method can evolve to more closely match the goal.) In other cases, the goals are complex; list.filter(_<5).sorted.grouped(10).flatMap(_.tail.headOption) is a bit of a mess, but if you really want to take all numbers less than 5, and then take every 2nd number out of 10 in the remaining list, well, that's just a somewhat complicated idea, and the code pretty much says what it does if you know the basic collections operations.
Summary: Scala is not complex, but it allows you to compactly express complex ideas. Compact expression of complex ideas can be daunting.
There is a myth that Scala is non-deployable, whereas a wide range of third-party Java libraries can be deployed without a second thought.
To the extent that this myth exists, I suspect it exists among people who are not accustomed to separating a virtual machine and API from a language and compiler. If java == javac == Java API in your mind, you might get a little nervous if someone suggests using scalac instead of javac, because you see how nicely your JVM runs.
Scala ends up as JVM bytecode, plus its own custom library. There's no reason to be any more worried about deploying Scala on a small scale or as part of some other large project as there is in deploying any other library that may or may not stay compatible with whichever JVM you prefer. Granted, the Scala development team is not backed by quite as much force as the Google collections, or Apache Commons, but its got at least as much weight behind it as things like the Java Advanced Imaging project.
Myth:
def foo() = "something"
and
def bar = "something"
is the same.
It is not; you can call foo(), but bar() tries to call the apply method of StringLike with no arguments (results in an error).
Some common misconceptions related to Actors library:
Actors handle incoming messages in a parallel, in multiple threads / against a thread pool (in fact, handling messages in multiple threads is contrary to the actors concept and may lead to racing conditions - all messages are sequentially handled in one thread (thread-based actors use one thread both for mailbox processing and execution; event-based actors may share one VM thread for execution, using multi-threaded executor to schedule mailbox processing))
Uncaught exceptions don't change actor's behavior/state (in fact, all uncaught exceptions terminate the actor)
Myth: You can replace a fold with a reduce when computing something like a sum from zero.
This is a common mistake/misconception among new users of Scala, particularly those without prior functional programming experience. The following expressions are not equivalent:
seq.foldLeft(0)(_+_)
seq.reduceLeft(_+_)
The two expressions differ in how they handle the empty sequence: the fold produces a valid result (0), while the reduce throws an exception.
Myth: Pattern matching doesn't fit well with the OO paradigm.
Debunked here by Martin Odersky himself. (Also see this paper - Matching Objects with Patterns - by Odersky et al.)
Myth: this.type refers to the same type represented by this.getClass.
As an example of this misconception, one might assume that in the following code the type of v.me is B:
trait A { val me: this.type = this }
class B extends A
val v = new B
In reality, this.type refers to the type whose only instance is this. In general, x.type is the singleton type whose only instance is x. So in the example above, the type of v.me is v.type. The following session demonstrates the principle:
scala> val s = "a string"
s: java.lang.String = a string
scala> var v: s.type = s
v: s.type = a string
scala> v = "another string"
<console>:7: error: type mismatch;
found : java.lang.String("another string")
required: s.type
v = "another string"
Scala has type inference and refinement types (structural types), whereas Java does not.
The myth is busted by James Iry.
Myth: that Scala is highly scalable, without qualifying what forms of scalability.
Scala may indeed be highly scalable in terms of the ability to express higher-level denotational semantics, and this makes it a very good language for experimentation and even for scaling production at the project-level scale of top-down coordinated compositionality.
However, every referentially opaque language (i.e. allows mutable data structures), is imperative (and not declarative) and will not scale to WAN bottom-up, uncoordinated compositionality and security. In other words, imperative languages are compositional (and security) spaghetti w.r.t. uncoordinated development of modules. I realize such uncoordinated development is perhaps currently considered by most to be a "pipe dream" and thus perhaps not a high priority. And this is not to disparage the benefit to compositionality (i.e. eliminating corner cases) that higher-level semantic unification can provide, e.g. a category theory model for standard library.
There will possibly be significant cognitive dissonance for many readers, especially since there are popular misconceptions about imperative vs. declarative (i.e. mutable vs. immutable), (and eager vs. lazy,) e.g. the monadic semantic is never inherently imperative yet there is a lie that it is. Yes in Haskell the IO monad is imperative, but it being imperative has nothing to with it being a monad.
I explained this in more detail in the "Copute Tutorial" and "Purity" sections, which is either at the home page or temporarily at this link.
My point is I am very grateful Scala exists, but I want to clarify what Scala scales and what is does not. I need Scala for what it does well, i.e. for me it is the ideal platform to prototype a new declarative language, but Scala itself is not exclusively declarative and afaik referential transparency can't be enforced by the Scala compiler, other than remembering to use val everywhere.
I think my point applies to the complexity debate about Scala. I have found (so far and mostly conceptually, since so far limited in actual experience with my new language) that removing mutability and loops, while retaining diamond multiple inheritance subtyping (which Haskell doesn't have), radically simplifies the language. For example, the Unit fiction disappears, and afaics, a slew of other issues and constructs become unnecessary, e.g. non-category theory standard library, for comprehensions, etc..
In Java and C++ designing program's objects hierarchy is pretty obvious. But beginning Scala I found myself difficult to decide what classes to define to better employ Scala's syntactic sugar facilities (an even idealess about how should I design for better performance). Any good readings on this question?
I have read 4 books on Scala, but I have not found what you are asking for. I guess you have read "Programming in Scala" by Odersky (Artima) already. If not, this is a link to the on-line version:
http://www.docstoc.com/docs/8692868/Programming-In-Scala
This book gives many examples how to construct object-oriented models in Scala, but all examples are very small in number of classes. I do not know of any book that will teach you how to structure large scale systems using Scala.
Imperative object-orientation has
been around since Smalltalk, so we
know a lot about this paradigm.
Functional object-orientation on the
other hand, is a rather new concept,
so in a few years I expect books
describing large scale FOO systems to
appear. Anyway, I think that the PiS
book gives you a pretty good picture
how you can put together the basic
building blocks of a system, like
Factory pattern, how to replace the
Strategy pattern with function
literals and so on.
One thing that Viktor Klang once told me (and something I really agree upon) is that one difference between C++/Java and Scala OO is that you define a lot more (smaller) classes when you use Scala. Why? Because you can! The syntactic sugar for the case class result in a very small penalty for defining a class, both in typing and in readability of the code. And as you know, many small classes usually means better OO (fewer bugs) but worse performance.
One other thing I have noticed is that I use the factory pattern a lot more when dealing with immutable objects, since all "changes" of an instance results in creating a new instance. Thank God for the copy() method on the case class. This method makes the factory methods a lot shorter.
I do not know if this helped you at all, but I think this subject is very interesting myself, and I too await more literature on this subject.
Cheers!
This is still an evolving matter. For instance, the just released Scala 2.8.0 brought support of type constructor inference, which enabled a pattern of type classes in Scala. The Scala library itself has just began using this pattern. Just yesterday I heard of a new Lift module in which they are going to try to avoid inheritance in favor of type classes.
Scala 2.8.0 also introduced lower priority implicits, plus default and named parameters, both of which can be used, separately or together, to produce very different designs than what was possible before.
And if we go back in time, we note that other important features are not that old either:
Extractor methods on case classes object companions where introduced February 2008 (before that, the only way to do extraction on case classes was through pattern matching).
Lazy values and Structural types where introduced July 2007.
Abstract types support for type constructors was introduced in May 2007.
Extractors for non-case classes was introduced in January 2007.
It seems that implicit parameters were only introduced in March 2006, when they replaced the way views were implemented.
All that means we are all learning how to design Scala software. Be sure to rely on tested designs of functional and object oriented paradigms, to see how new features in Scala are used in other languages, like Haskell and type classes or Python and default (optional) and named parameters.
Some people dislike this aspect of Scala, others love it. But other languages share it. C# is adding features as fast as Scala. Java is slower, but it goes through changes too. It added generics in 2004, and the next version should bring some changes to better support concurrent and parallel programming.
I don't think that there are much tutorials for this. I'd suggest to stay with the way you do it now, but to look through "idiomatic" Scala code as well and to pay special attention in the following cases:
use case classes or case objects instead of enums or "value objects"
use objects for singletons
if you need behavior "depending on the context" or dependency-injection-like functionality, use implicits
when designing a type hierarchy or if you can factor things out of a concrete class, use traits when possible
Fine grained inheritance hierarchies are OK. Keep in mind that you have pattern matching
Know the "pimp my library" pattern
And ask as many questions as you feel you need to understand a certain point. The Scala community is very friendly and helpful. I'd suggest the Scala mailing list, Scala IRC or scala-forum.org
I've just accidentally googled to a file called "ScalaStyleGuide.pdf". Going to read...
I'm going to be giving a short (30-40 mins) lunch-time talk on Scala to technical staff at my company. I'd like some suggestions for what would be the most appropriate content. Most people attending will have experience in Java and/or C# (plus various other languages).
What are the key things to cover? I'd like to give a brief introduction to the Scala syntax so that people don't feel lost when looking at code examples. I'll also cover some of the history behind the language and its designers. What would help people get the most out of the talk?
People are almost certainly coming to talk to get an answer to the question, "Why should I use Scala?" Anything you can provide to help them answer that will be valuable.
Keep the discussion of the history and the personalities behind Scala to a minimum.
A whirlwind tour of the syntax is useful, but keep it short.
Spend a good chunk of the talk demonstrating examples and comparisons to Java. Show cases where Scala shines. You should literally be running and executing code so that people get a real, hands-on feel for how things work.
Make sure to cover weaknesses, too! Provide an objective and balanced overview.
I gave a similar talk - mostly to those with a Java background. I felt that taking a piece of real Java (about 30 lines) and iteratively adding scala features worked pretty well. The 30 lines of Java eventually ended up as 6 (six!) of scala. The point being (of course) that 6 lines are more readable and maintainable than 30.
I converted the scala to line-by-line Java equivalent and then introduced:
Type inference
Option
Closures
Pattern-matching (on lists)
Type aliases
Tail recursion
I found that this segment took quite a long time because the audience were very interested in the minutiae of scala's syntax (especially around function-expressions). Before undertaking the pattern-matching bit, I had a slide explaining the various things you could use in a match.
Tough. One has to balance the new and the familiar. For instance:
Talk about traits, how they differ from interfaces and multiple inheritance. Note that most methods in all of Scala collections can actually be found on the trait Traversable, which has a single abstract method: foreach.
Speak of functions and partial functions, show map/filter/foreach, and how they make use of functions.
Talk about pattern matching -- show how unapply is used to enable representation independence, while at the same time case classes make the common case easy.
Above all AVOID any topic that might be difficult to understand quickly, or you may waste time on them. For example of great topics I wouldn't talk about: self types, variance, for-comprehensions.
Pick more topics than you have time for. Let the public steer the conversation towards the topcis they are more interested in. If anyone starts to boggle down a topic too much, say you'll be pleased to explain it in more details later, and ask if they would mind if you moved to another topic. On the other hand, if everyone seems to be picking up on one thing in particular, stay with it. Otherwise, it might feel like you want to hide something.
I gave a presentation on re-writing Java classes in Scala. It has lots of examples of Java -> Scala and (hopefully) makes the gains obvious. Feel free to borrow any content you want... presentation took 1hr 10minutes so you might want to cut some stuff out.
Presentation: http://www.colinhowe.co.uk/downloads/rewriting-java-in-scala.ppt
Video: http://skillsmatter.com/podcast/java-jee/re-writing-java-classes-in-scala-and-making-your-code-lovely
You could do worse than running through Jonas Bonér's presentation, Pragmatic Real-World Scala. Perhaps skip some advanced topics in there on different applications of traits and self-type annotations.