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Closed 11 years ago.
I can say that I really love Scala but now I would like to know the features you cannot live without when working with Scala? What about Scala 2.8?
If I had to go back to Java here's what I'd miss the most: closures, higher order functions, pattern matching, case classes, and the emphasis on immutability.
I've been on 2.8 for a while. If I had to go back to 2.7, the main thing I'd miss is the consistency, cleanness, and richness of the 2.8 collections API. It's waaaaaay better the 2.7 stuff. But I'd also really miss named and default arguments.
Type inference saves so much pointless typing. map and foreach and the like on collections are great, especially in combination with default-lazy iterators and really easy function syntax.
But, as someone who does a lot of scientific computing, what I'd actually miss the most is being able to write high-performance code, wrap it in efficient classes, and then use maps and mathematical operators (+, *, whatever) to manipulate those high-level constructs the way that I actually think about them.
As for 2.8 vs. 2.7--the improvement is pretty incremental from my perspective. It's a little better in many areas; there's little to point to and say, "Oh wow, that!". I expect the new specialized annotation will help me a lot, but I haven't seen it fully in action in the library yet, so I'm withholding judgment.
I enjoy writing in Scala. That's the #1 feature in my book :)
I can just get on with what I want instead of dancing through Java's hoops:
val/var means I don't have to write the type twice
Closures mean I don't have to write lots of anonymous interfaces and can re-use lots more code
Named parameters mean I don't have to remember the position of each argument - great for both reading and writing
Case classes mean I get toString and equals for free... makes debugging far easier!
A decent API for collections (e.g. map, fold) mean that I can say what I want to do instead of dancing the iteration dance
As for 2.8 vs 2.7... I've only ever really spent quality time with 2.8 ;-)
I think it is not a feature but the conciseness which Scala achieves is what I like the most.
This is of course only possible because of type inference, closures, a great type system etc.
I just do not think you can break it down to one or two features. They work together and the result, concise code, is what I would call the killer feature.
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While learning Scala, I found the concept of implicit difficult to rationalize. It allows one to pass values implicitly, without explicitly mentioning them.
What is its purpose for being and what is the problem that it seeks to solve?
At it's heart, implicit is a way of extending the behavior of values of a type in a way that's fully controllable on a local level in your program, and external to the original code that defines those values. It's one approach to solving the expression problem.
It lets you keep your core classes focused on their most fundamental structure and behavior, and factor out higher-level behaviors. It's used to achieve ad hoc polymorphism, where two formally unrelated data types can be seamlessly adapted to the same interface, so that they can be treated as instances of the same type.
For example, rather than your data model classes containing JSON serialization behavior, you can store that behavior elsewhere, and implicitly augment an object with the ability to serialize itself. This amounts to defining in an implicit instance, which specifies how your object can be viewed as "JSON serializable", rather than its original type, and it's done without editing real type of the object.
There are several forms of implicit, which are pretty thoroughly covered elsewhere. Use cases include enhance-my-library pattern, the typeclass pattern, implicit conversions, and dependency injection.
What's really interesting to me, in the context of this question, is how this differs from approaches in other languages.
Enhance-my-library and typeclasses
In many other languages, you accomplish this by monkey patching (typically where there is no type checking) or extension methods. These approaches have the downside of composing unpredictably and applying globally. In statically typed languages without a way of opening classes, you usually have to make explicit adapters. This has the downside of a lot of boilerplate. In both static and dynamic languages, you may also be able to use reflection, but usually with a lot of ceremony and complexity.
In Haskell, typeclasses exist as a first-class concept. They're global, though, so you don't get the local control over what typeclass is applied in a given situation. In Scala, you control what implicits are in scope locally, through the modules you import. And you can always opt out of implicit resolution entirely by passing parameters explicitly.
People advocate for global versus local resolution of typeclasses one way or the other, depending on who you ask.
Implicit conversions
A lot of other languages have no way to accomplish this. But it's become pretty frowned upon in Scala, so maybe this is for good reason.
There's a paper about type classes with older slides and discussion.
Being able implicitly to pass an object that encodes a type class simplifies the boilerplate.
Odersky just responded to a critique of implicits that
Scala would not be Scala if it did not have implicit parameters and
classes.
That suggests they solve a challenge that is central to the design of the language. In other words, supporting type classes is not an ancillary concern.
Its a deep question really It is something that is very powerful and you can use them to write abstract code eg typeclasses etc i can recommend some tutorials that you may look into and then we can haved a chat maybe sometime :)
It is all about providing sensible defaults in your code.
Also the magic of invoking apparently non existent methods on objects which just seems to work! All that good stuff is done via implicits.
But for all its power it may cause people to write some really bad code as well.
Please do watch Nick Partridge's presentation here and i am sure if you code along with him you will understand why and how to approach implicits.
Watch it here
Dick Walls excellent presentation with live coding
Watch both parts.
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Closed 10 years ago.
Given that the CLR generics implementation supports more features than the JVM's, such as reification, and the JVM's generics are a mere Java "compiler trick", why are higher-kinded types not possible in F# but possible in Scala? Does the CLR generics implementation somehow get in the way of things, whereas the JVM's lack of one allows you to go further than what the designers intended; somewhat like dynamic languages let you do tricks that a strongly-typed compiler would make impossible?
In principle, I'm not sure that there's anything preventing F# from including higher kinded types; the CLR doesn't natively support them, so a more indirect compilation strategy would need to be used, but that's the case for Scala on the JVM too. It may or may not be more complicated to do this on top of the CLR's reified generics, but I suspect the reason that F# doesn't include them is more philosophical. While higher kinded types would be nice, F#'s design tends to favor simple features that interoperate well with other .NET languages; higher kinded types would probably require significant effort to add to the language, would complicate type inference and other parts of the language and would definitely not interop well with C# and other .NET languages, so the costs (including opportunity costs) were probably perceived to outweigh the benefits.
Better? Conceivably.
The only difference I'm aware of is a feature of generics called "specialization." And it's available under programmer control in Scala. So... I'd have to say one can make the case that Scala is "better."
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Closed 10 years ago.
I watched a talk in live where the person said they at work are doing Scala functionally, they use case classes, transform a type to another, immutability everywhere, etc.
How does this actually work? I'd love to see a simple hello world application with pure functional approach.
Also I can't see how can I get rid of var altogether because sometimes I just need it.
There is a course on Coursera just about that.
"Hello world" is not really good to demonstrate the functional approach, as there is nothing functional about it. (In fact, as #delnan noted, writing to the standard output is considered a side effect, so this program can never be made purely functional.)
The most likely reason for you to need var is using imperative style loops, which is indeed not the functional approach. The functional equivalent would be to either use some of the available filter / transform functions on a collection, or use recursion.
Simple example: finding all strings in a list which start with 'F'. Imperative style (Java):
List<String> result = new ArrayList<String>();
for (String s : strings) {
if (s.startsWith("F")
result.add(s);
}
Imperativeness would be even more pronounced with the old style iterator loop.
In contrast, functional style could be something like:
val result = strings.filter(_.startsWith("F"))
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.
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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..