What is the difference between = and := in Scala?
I have googled extensively for "scala colon-equals", but was unable to find anything definitive.
= in scala is the actual assignment operator -- it does a handful of specific things that for the most part you don't have control over, such as
Giving a val or var a value when it's created
Changing the value of a var
Changing the value of a field on a class
Making a type alias
Probably others
:= is not a built-in operator -- anyone can overload it and define it to mean whatever they like. The reason people like to use := is because it looks very assignmenty and is used as an assignment operator in other languages.
So, if you're trying to find out what := means in the particular library you're using... my advice is look through the Scaladocs (if they exist) for a method named :=.
from Martin Odersky:
Initially we had colon-equals for assignment—just as in Pascal, Modula, and Ada—and a single equals sign for equality. A lot of programming theorists would argue that that's the right way to do it. Assignment is not equality, and you should therefore use a different symbol for assignment. But then I tried it out with some people coming from Java. The reaction I got was, "Well, this looks like an interesting language. But why do you write colon-equals? What is it?" And I explained that its like that in Pascal. They said, "Now I understand, but I don't understand why you insist on doing that." Then I realized this is not something we wanted to insist on. We didn't want to say, "We have a better language because we write colon-equals instead of equals for assignment." It's a totally minor point, and people can get used to either approach. So we decided to not fight convention in these minor things, when there were other places where we did want to make a difference.
from The Goals of Scala's Design
= performs assignment. := is not defined in the standard library or the language specification. It's a name that is free for other libraries or your code to use, if you wish.
Scala allows for operator overloading, where you can define the behaviour of an operator just like you could write a method.
As in other languages, = is an assignment operator.
The is no standard operator I'm aware of called :=, but could define one with this name. If you see an operator like this, you should check up the documentation of whatever you're looking at, or search for where that operator is defined.
There is a lot you can do with Scala operators. You can essentially make an operator out of virtually any characters you like.
I'm trying to learn shapeless (2.0.0). It seems like an amazing tool and I'm very excited about it, but I am having problems moving forward. Because there is not yet much documentation, I've been poring over examples and the source code. I am having difficulties because most examples use multiple shapeless concepts and, in the source code, one shapeless type will often make use of others, so I end up going down the shapeless rabbit hole, so to speak. I think it would be helpful to have a list of the important features of the shapeless API along with a simple description of what each one does. As I'm clearly unqualified to make such a list, I am asking you, the humans of Stack Overflow!
For each feature, please include as much as you can of the following:
The feature's name and how to import it.
A short, simple description of what it does.
Why is this feature important / why would someone bother to use it?
A simple example that uses as few other shapeless or advanced Scala concepts as possible.
By a feature of the API, I mean a single thing (e.g., a type, a function, an object, etc.), or small set of closely coupled such things, that is defined by shapeless 2.0 and can be imported and used in a program. I am not referring to general concepts such as higher order polymorphism or type-level recursion. And please only include one feature per answer. Maybe if there are enough answers and enough others also use this list, we can use the votes on the answers to rank the importance of the different features.
Note: I am aware of this feature list. I think it's great, and it has helped me a lot. However, I'm looking for something more similar to API documentation than a list of things you can do. I can understand many of the examples and infer the purposes of some features from them, but I will often get tripped up on some particular piece and be unable to figure out its function.
HList
An HList is a list-like data structure that can hold objects of multiple types. HList is actually a trait. A given HList will have a more specific type that fully specifies the types of its contents. HLists are immutable. The usual way to import HList functionality is via
import shapeless._
HLists are useful when you need an immutable collection of heterogenous objects that isn't a tuple.
HLists are constructed using HNil, which is the empty HList, and the :: operator. The following example shows how to create an HList that counts to "cat":
val hl = 1 :: 2 :: "cat" :: HNil
The type of hl above includes two Int types and a String type. Shapeless includes many useful operations on HLists, which should be the subjects of other answers.
What is the difference between = and := in Scala?
I have googled extensively for "scala colon-equals", but was unable to find anything definitive.
= in scala is the actual assignment operator -- it does a handful of specific things that for the most part you don't have control over, such as
Giving a val or var a value when it's created
Changing the value of a var
Changing the value of a field on a class
Making a type alias
Probably others
:= is not a built-in operator -- anyone can overload it and define it to mean whatever they like. The reason people like to use := is because it looks very assignmenty and is used as an assignment operator in other languages.
So, if you're trying to find out what := means in the particular library you're using... my advice is look through the Scaladocs (if they exist) for a method named :=.
from Martin Odersky:
Initially we had colon-equals for assignment—just as in Pascal, Modula, and Ada—and a single equals sign for equality. A lot of programming theorists would argue that that's the right way to do it. Assignment is not equality, and you should therefore use a different symbol for assignment. But then I tried it out with some people coming from Java. The reaction I got was, "Well, this looks like an interesting language. But why do you write colon-equals? What is it?" And I explained that its like that in Pascal. They said, "Now I understand, but I don't understand why you insist on doing that." Then I realized this is not something we wanted to insist on. We didn't want to say, "We have a better language because we write colon-equals instead of equals for assignment." It's a totally minor point, and people can get used to either approach. So we decided to not fight convention in these minor things, when there were other places where we did want to make a difference.
from The Goals of Scala's Design
= performs assignment. := is not defined in the standard library or the language specification. It's a name that is free for other libraries or your code to use, if you wish.
Scala allows for operator overloading, where you can define the behaviour of an operator just like you could write a method.
As in other languages, = is an assignment operator.
The is no standard operator I'm aware of called :=, but could define one with this name. If you see an operator like this, you should check up the documentation of whatever you're looking at, or search for where that operator is defined.
There is a lot you can do with Scala operators. You can essentially make an operator out of virtually any characters you like.
I have read that Scala's type system is weakened by Java interoperability and therefore cannot perform some of the same powers as Haskell's type system. Is this true? Is the weakness because of type erasure, or am I wrong in every way? Is this difference the reason that Scala has no typeclasses?
The big difference is that Scala doesn't have Hindley-Milner global type inference and instead uses a form of local type inference, requiring you to specify types for method parameters and the return type for overloaded or recursive functions.
This isn't driven by type erasure or by other requirements of the JVM. All possible difficulties here can be overcome, and have been, just consider Jaskell - http://docs.codehaus.org/display/JASKELL/Home
H-M inference doesn't work in an object-oriented context. Specifically, when type-polymorphism is used (as opposed to the ad-hoc polymorphism of type classes). This is crucial for strong interop with other Java libraries, and (to a lesser extent) to get the best possible optimisation from the JVM.
It's not really valid to state that either Haskell or Scala has a stronger type system, just that they are different. Both languages are pushing the boundaries for type-based programming in different directions, and each language has unique strengths that are hard to duplicate in the other.
Scala's type system is different from Haskell's, although Scala's concepts are sometimes directly inspired by Haskell's strengths and its knowledgeable community of researchers and professionals.
Of course, running on a VM not primarily intended for functional programming in the first place creates some compatibility concerns with existing languages targeting this platform.
Because most of the reasoning about types happens at compile time, the limitations of Java (as a language and as a platform) at runtime are nothing to be concerned about (except Type Erasure, although exactly this bug seems to make the integration into the Java ecosystem more seamless).
As far as I know the only "compromise" on the type system level with Java is a special syntax to handle Raw Types. While Scala doesn't even allow Raw Types anymore, it accepts older Java class files with that bug.
Maybe you have seen code like List[_] (or the longer equivalent List[T] forSome { type T }). This is a compatibility feature with Java, but is treated as an existential type internally too and doesn't weaken the type system.
Scala's type system does support type classes, although in a more verbose way than Haskell. I suggest reading this paper, which might create a different impression on the relative strength of Scala's type system (the table on page 17 serves as a nice list of very powerful type system concepts).
Not necessarily related to the power of the type system is the approach Scala's and Haskell's compilers use to infer types, although it has some impact on the way people write code.
Having a powerful type inference algorithm can make it worthwhile to write more abstract code (you can decide yourself if that is a good thing in all cases).
In the end Scala's and Haskell's type system are driven by the desire to provide their users with the best tools to solve their problems, but have taken different paths to that goal.
another interesting point to consider is that Scala directly supports the classical OO-style. Which means, there are subtype relations (e.g. List is a subclass of Seq). And this makes type inference more tricky. Add to this the fact that you can mix in traits in Scala, which means that a given type can have multiple supertype relations (making it yet more tricky)
Scala does not have rank-n types, although it may be possible to work around this limitation in certain cases.
I only have little experenice with Haskell, but the most obvious thing I note that Scala type system different from Haskell is the type inference.
In Scala, there is no global type inference, you must explicit tell the type of function arguments.
For example, in Scala you need to write this:
def add (x: Int, y: Int) = x + y
instead of
add x y = x + y
This may cause problem when you need generic version of add function that work with all kinds of type has the "+" method. There is a workaround for this, but it will get more verbose.
But in real use, I found Scala's type system is powerful enough for daily usage, and I almost never use those workaround for generic, maybe this is because I come from Java world.
And the limitation of explicit declare the type of arguments is not necessary a bad thing, you need document it anyway.
Well are they Turing reducible?
See Oleg Kiselyov's page http://okmij.org/ftp/
...
One can implement the lambda calculus in Haskell's type system. If Scala can do that, then in a sense Haskell's type system and Scala's type system compute the same types. The questions are: How natural is one over the other? How elegant is one over the other?
What are the key differences between the approaches taken by Scala and F# to unify OO and FP paradigms?
EDIT
What are the relative merits and demerits of each approach? If, in spite of the support for subtyping, F# can infer the types of function arguments then why can't Scala?
I have looked at F#, doing low level tutorials, so my knowledge of it is very limited. However, it was apparent to me that its style was essentially functional, with OO being more like an add on -- much more of an ADT + module system than true OO. The feeling I get can be best described as if all methods in it were static (as in Java static).
See, for instance, any code using the pipe operator (|>). Take this snippet from the wikipedia entry on F#:
[1 .. 10]
|> List.map fib
(* equivalent without the pipe operator *)
List.map fib [1 .. 10]
The function map is not a method of the list instance. Instead, it works like a static method on a List module which takes a list instance as one of its parameters.
Scala, on the other hand, is fully OO. Let's start, first, with the Scala equivalent of that code:
List(1 to 10) map fib
// Without operator notation or implicits:
List.apply(Predef.intWrapper(1).to(10)).map(fib)
Here, map is a method on the instance of List. Static-like methods, such as intWrapper on Predef or apply on List, are much more uncommon. Then there are functions, such as fib above. Here, fib is not a method on int, but neither it is a static method. Instead, it is an object -- the second main difference I see between F# and Scala.
Let's consider the F# implementation from the Wikipedia, and an equivalent Scala implementation:
// F#, from the wiki
let rec fib n =
match n with
| 0 | 1 -> n
| _ -> fib (n - 1) + fib (n - 2)
// Scala equivalent
def fib(n: Int): Int = n match {
case 0 | 1 => n
case _ => fib(n - 1) + fib(n - 2)
}
The above Scala implementation is a method, but Scala converts that into a function to be able to pass it to map. I'll modify it below so that it becomes a method that returns a function instead, to show how functions work in Scala.
// F#, returning a lambda, as suggested in the comments
let rec fib = function
| 0 | 1 as n -> n
| n -> fib (n - 1) + fib (n - 2)
// Scala method returning a function
def fib: Int => Int = {
case n # (0 | 1) => n
case n => fib(n - 1) + fib(n - 2)
}
// Same thing without syntactic sugar:
def fib = new Function1[Int, Int] {
def apply(param0: Int): Int = param0 match {
case n # (0 | 1) => n
case n => fib.apply(n - 1) + fib.apply(n - 2)
}
}
So, in Scala, all functions are objects implementing the trait FunctionX, which defines a method called apply. As shown here and in the list creation above, .apply can be omitted, which makes function calls look just like method calls.
In the end, everything in Scala is an object -- and instance of a class -- and every such object does belong to a class, and all code belong to a method, which gets executed somehow. Even match in the example above used to be a method, but has been converted into a keyword to avoid some problems quite a while ago.
So, how about the functional part of it? F# belongs to one of the most traditional families of functional languages. While it doesn't have some features some people think are important for functional languages, the fact is that F# is function by default, so to speak.
Scala, on the other hand, was created with the intent of unifying functional and OO models, instead of just providing them as separate parts of the language. The extent to which it was succesful depends on what you deem to be functional programming. Here are some of the things that were focused on by Martin Odersky:
Functions are values. They are objects too -- because all values are objects in Scala -- but the concept that a function is a value that can be manipulated is an important one, with its roots all the way back to the original Lisp implementation.
Strong support for immutable data types. Functional programming has always been concerned with decreasing the side effects on a program, that functions can be analysed as true mathematical functions. So Scala made it easy to make things immutable, but it did not do two things which FP purists criticize it for:
It did not make mutability harder.
It does not provide an effect system, by which mutability can be statically tracked.
Support for Algebraic Data Types. Algebraic data types (called ADT, which confusingly also stands for Abstract Data Type, a different thing) are very common in functional programming, and are most useful in situations where one commonly use the visitor pattern in OO languages.
As with everything else, ADTs in Scala are implemented as classes and methods, with some syntactic sugars to make them painless to use. However, Scala is much more verbose than F# (or other functional languages, for that matter) in supporting them. For example, instead of F#'s | for case statements, it uses case.
Support for non-strictness. Non-strictness means only computing stuff on demand. It is an essential aspect of Haskell, where it is tightly integrated with the side effect system. In Scala, however, non-strictness support is quite timid and incipient. It is available and used, but in a restricted manner.
For instance, Scala's non-strict list, the Stream, does not support a truly non-strict foldRight, such as Haskell does. Furthermore, some benefits of non-strictness are only gained when it is the default in the language, instead of an option.
Support for list comprehension. Actually, Scala calls it for-comprehension, as the way it is implemented is completely divorced from lists. In its simplest terms, list comprehensions can be thought of as the map function/method shown in the example, though nesting of map statements (supports with flatMap in Scala) as well as filtering (filter or withFilter in Scala, depending on strictness requirements) are usually expected.
This is a very common operation in functional languages, and often light in syntax -- like in Python's in operator. Again, Scala is somewhat more verbose than usual.
In my opinion, Scala is unparalled in combining FP and OO. It comes from the OO side of the spectrum towards the FP side, which is unusual. Mostly, I see FP languages with OO tackled on it -- and it feels tackled on it to me. I guess FP on Scala probably feels the same way for functional languages programmers.
EDIT
Reading some other answers I realized there was another important topic: type inference. Lisp was a dynamically typed language, and that pretty much set the expectations for functional languages. The modern statically typed functional languages all have strong type inference systems, most often the Hindley-Milner1 algorithm, which makes type declarations essentially optional.
Scala can't use the Hindley-Milner algorithm because of Scala's support for inheritance2. So Scala has to adopt a much less powerful type inference algorithm -- in fact, type inference in Scala is intentionally undefined in the specification, and subject of on-going improvements (it's improvement is one of the biggest features of the upcoming 2.8 version of Scala, for instance).
In the end, however, Scala requires all parameters to have their types declared when defining methods. In some situations, such as recursion, return types for methods also have to be declared.
Functions in Scala can often have their types inferred instead of declared, though. For instance, no type declaration is necessary here: List(1, 2, 3) reduceLeft (_ + _), where _ + _ is actually an anonymous function of type Function2[Int, Int, Int].
Likewise, type declaration of variables is often unnecessary, but inheritance may require it. For instance, Some(2) and None have a common superclass Option, but actually belong to different subclases. So one would usually declare var o: Option[Int] = None to make sure the correct type is assigned.
This limited form of type inference is much better than statically typed OO languages usually offer, which gives Scala a sense of lightness, and much worse than statically typed FP languages usually offer, which gives Scala a sense of heavyness. :-)
Notes:
Actually, the algorithm originates from Damas and Milner, who called it "Algorithm W", according to the wikipedia.
Martin Odersky mentioned in a comment here that:
The reason Scala does not have Hindley/Milner type inference is
that it is very difficult to combine with features such as
overloading (the ad-hoc variant, not type classes), record
selection, and subtyping
He goes on to state that it may not be actually impossible, and it came down to a trade-off. Please do go to that link for more information, and, if you do come up with a clearer statement or, better yet, some paper one way or another, I'd be grateful for the reference.
Let me thank Jon Harrop for looking this up, as I was assuming it was impossible. Well, maybe it is, and I couldn't find a proper link. Note, however, that it is not inheritance alone causing the problem.
F# is functional - It allows OO pretty well, but the design and philosophy is functional nevertheless. Examples:
Haskell-style functions
Automatic currying
Automatic generics
Type inference for arguments
It feels relatively clumsy to use F# in a mainly object-oriented way, so one could describe the main goal as to integrate OO into functional programming.
Scala is multi-paradigm with focus on flexibility. You can choose between authentic FP, OOP and procedural style depending on what currently fits best. It's really about unifying OO and functional programming.
There are quite a few points that you can use for comparing the two (or three). First, here are some notable points that I can think of:
Syntax
Syntactically, F# and OCaml are based on the functional programming tradition (space separated and more lightweight), while Scala is based on the object-oriented style (although Scala makes it more lightweight).
Integrating OO and FP
Both F# and Scala very smoothly integrate OO with FP (because there is no contradiction between these two!!) You can declare classes to hold immutable data (functional aspect) and provide members related to working with the data, you can also use interfaces for abstraction (object-oriented aspects). I'm not as familiar with OCaml, but I would think that it puts more emphasis on the OO side (compared to F#)
Programming style in F#
I think that the usual programming style used in F# (if you don't need to write .NET library and don't have other limitations) is probably more functional and you'd use OO features only when you need to. This means that you group functionality using functions, modules and algebraic data types.
Programming style in Scala
In Scala, the default programming style is more object-oriented (in the organization), however you still (probably) write functional programs, because the "standard" approach is to write code that avoids mutation.
What are the key differences between the approaches taken by Scala and F# to unify OO and FP paradigms?
The key difference is that Scala tries to blend the paradigms by making sacrifices (usually on the FP side) whereas F# (and OCaml) generally draw a line between the paradigms and let the programmer choose between them for each task.
Scala had to make sacrifices in order to unify the paradigms. For example:
First-class functions are an essential feature of any functional language (ML, Scheme and Haskell). All functions are first-class in F#. Member functions are second-class in Scala.
Overloading and subtypes impede type inference. F# provides a large sublanguage that sacrifices these OO features in order to provide powerful type inference when these features are not used (requiring type annotations when they are used). Scala pushes these features everywhere in order to maintain consistent OO at the cost of poor type inference everywhere.
Another consequence of this is that F# is based upon tried and tested ideas whereas Scala is pioneering in this respect. This is ideal for the motivations behind the projects: F# is a commercial product and Scala is programming language research.
As an aside, Scala also sacrificed other core features of FP such as tail-call optimization for pragmatic reasons due to limitations of their VM of choice (the JVM). This also makes Scala much more OOP than FP. Note that there is a project to bring Scala to .NET that will use the CLR to do genuine TCO.
What are the relative merits and demerits of each approach? If, in spite of the support for subtyping, F# can infer the types of function arguments then why can't Scala?
Type inference is at odds with OO-centric features like overloading and subtypes. F# chose type inference over consistency with respect to overloading. Scala chose ubiquitous overloading and subtypes over type inference. This makes F# more like OCaml and Scala more like C#. In particular, Scala is no more a functional programming language than C# is.
Which is better is entirely subjective, of course, but I personally much prefer the tremendous brevity and clarity that comes from powerful type inference in the general case. OCaml is a wonderful language but one pain point was the lack of operator overloading that required programmers to use + for ints, +. for floats, +/ for rationals and so on. Once again, F# chooses pragmatism over obsession by sacrificing type inference for overloading specifically in the context of numerics, not only on arithmetic operators but also on arithmetic functions such as sin. Every corner of the F# language is the result of carefully chosen pragmatic trade-offs like this. Despite the resulting inconsistencies, I believe this makes F# far more useful.
From this article on Programming Languages:
Scala is a rugged, expressive,
strictly superior replacement for
Java. Scala is the programming
language I would use for a task like
writing a web server or an IRC client.
In contrast to OCaml [or F#], which was a
functional language with an
object-oriented system grafted to it,
Scala feels more like an true hybrid
of object-oriented and functional
programming. (That is, object-oriented
programmers should be able to start
using Scala immediately, picking up
the functional parts only as they
choose to.)
I first learned about Scala at POPL
2006 when Martin Odersky gave an
invited talk on it. At the time I saw
functional programming as strictly
superior to object-oriented
programming, so I didn't see a need
for a language that fused functional
and object-oriented programming. (That
was probably because all I wrote back
then were compilers, interpreters and
static analyzers.)
The need for Scala didn't become
apparent to me until I wrote a
concurrent HTTPD from scratch to
support long-polled AJAX for yaplet.
In order to get good multicore
support, I wrote the first version in
Java. As a language, I don't think
Java is all that bad, and I can enjoy
well-done object-oriented programming.
As a functional programmer, however,
the lack of (or needlessly verbose)
support of functional programming
features (like higher-order functions)
grates on me when I program in Java.
So, I gave Scala a chance.
Scala runs on the JVM, so I could
gradually port my existing project
into Scala. It also means that Scala,
in addition to its own rather large
library, has access to the entire Java
library as well. This means you can
get real work done in Scala.
As I started using Scala, I became
impressed by how cleverly the
functional and object-oriented worlds
blended together. In particular, Scala
has a powerful case
class/pattern-matching system that
addressed pet peeves lingering from my
experiences with Standard ML, OCaml
and Haskell: the programmer can decide
which fields of an object should be
matchable (as opposed to being forced
to match on all of them), and
variable-arity arguments are
permitted. In fact, Scala even allows
programmer-defined patterns. I write a
lot of functions that operate on
abstract syntax nodes, and it's nice
to be able to match on only the
syntactic children, but still have
fields for things such as annotations
or lines in the original program. The
case class system lets one split the
definition of an algebraic data type
across multiple files or across
multiple parts of the same file, which
is remarkably handy.
Scala also
supports well-defined multiple
inheritance through class-like devices
called traits.
Scala also allows a
considerable degree of overloading;
even function application and array
update can be overloaded. In my
experience, this tends to make my
Scala programs more intuitive and
concise.
One feature that turns out to save a
lot of code, in the same way that type
classes save code in Haskell, is
implicits. You can imagine implicits
as an API for the error-recovery phase
of the type-checker. In short, when
the type checker needs an X but got a
Y, it will check to see if there's an
implicit function in scope that
converts Y into X; if it finds one, it
"casts" using the implicit. This makes
it possible to look like you're
extending just about any type in
Scala, and it allows for tighter
embeddings of DSLs.
From the above excerpt it is clear that Scala's approach to unify OO and FP paradigms is far more superior to that of OCaml or F#.
HTH.
Regards,
Eric.
The syntax of F# was taken from OCaml but the object model of F# was taken from .NET. This gives F# a light and terse syntax that is characteristic of functional programming languages and at the same time allows F# to interoperate with the existing .NET languages and .NET libraries very smoothly through its object model.
Scala does a similar job on the JVM that F# does on the CLR. However Scala has chosen to adopt a more Java-like syntax. This may assist in its adoption by object-oriented programmers but to a functional programmer it can feel a bit heavy. Its object model is similar to Java's allowing for seamless interoperation with Java but has some interesting differences such as support for traits.
If functional programming means programming with functions, then Scala bends that a bit. In Scala, if I understand correctly, you're programming with methods instead of functions.
When the class (and the object of that class) behind the method don't matter, Scala will let you pretend it's just a function. Perhaps a Scala language lawyer can elaborate on this distinction (if it even is a distinction), and any consequences.