I wanted to create a scala compiler plugin that would prevents the call of some functions. For example System.exit.
The idea behind the scene is to let people write Scala scripts that would be interpreted on the fly. But I want to ensure that some dangerous actions are prohibited - the way it is done can definitely be discussed.
I started with the example in http://www.scala-lang.org/node/140 and started to replace the Apply section.
Doing some pattern matching I was able to extract a ClassSymbol for the right part of the compilation unit.
Then I wanted to do something like in the example that would be like:
classSymbol.tpe =:= global.typeOf[System]
unfortunately they don't match I get System.type on one side and System on the other.
Of course I could compare String values but I think that there is perhaps a nicer way to achieve this.
Has anyone any advice ?
Just in case a larger part of the code:
def apply(unit: global.CompilationUnit) {
for (global.Apply(fun, _) <- unit.body) {
fun.symbol match {
case method: global.MethodSymbol =>
val classSymbol = method.owner
println(classSymbol.fullName)
println(classSymbol.tpe =:= global.typeOf[System])
case _ => ()
}
}
Perhaps,
val jls = global.findMemberFromRoot(TermName("java.lang.System"))
Related
As a personal project, I am writing yet another Scala library for DynamoDb. It contains many interesting aspect such as reading and writing from an AST (just as Json), handling HTTP request, streaming data…
In order to be able able to communicate with DynamoDb, one needs to be able to read from / to the DynamoDb format (the “AST”). I extracted this reading / writing from / to the AST in a minimalist library: dynamo-ast. It contains two main type classes: DynamoReads[_] and DynamoWrites[_] (deeply inspired from Play Json).
I successfully coded the reading part of the library ending with a very simple code such as :
trait DynamoRead[A] { self =>
def read(dynamoType: DynamoType): DynamoReadResult[A]
}
case class TinyImage(url: String, alt: String)
val dynamoReads: DynamoReads[TinyImage] = {
for {
url <- read[String].at(“url”)
alt <- read[String].at(“alt”)
} yield (url, alt) map (TinyImage.apply _).tupled
}
dynamoReads.reads(dynamoAst) //yield DynamoReadResult[TinyImage]
At that point, I thought I wrote the most complicated part of the library and the DynamoWrite[_] part would be a piece of cake. I am however stuck on writing the DynamoWrite part. I was a fool.
My goal is to provide a very similar “user experience” with the DynamoWrite[_] and keep it as simple as possible such as :
val dynamoWrites: DynamoWrites[TinyImage] = {
for {
url <- write[String].at(“url”)
alt <- write[String].at(“alt”)
} yield (url, alt) map (TinyImage.unapply _) //I am not sure what to yield here nor how to code it
}
dynamoWrites.write(TinyImage(“http://fake.url”, “The alt desc”)) //yield DynamoWriteResult[DynamoType]
Since this library is deeply inspired from Play Json library (because I like its simplicity) I had a look at the sources several times. I kind of dislike the way the writer part is coded because to me, it adds a lot of overhead (basically each time a field a written, a new JsObject is created with one field and the resulting JsObject for a complete class is the merge of all the JsObjects containing one field).
From my understanding, the DynamoReads part can be written with only one trait (DynamoRead[_]). The DynamoWrites part however requires at least two such as :
trait DynamoWrites[A] {
def write(a: A): DynamoWriteResult[DynamoType]
}
trait DynamoWritesPath[A] {
def write(path:String, a: A): DynamoWriteResult[(String, DynamoType)]
}
The DynamoWrites[_] is to write plain String, Int… and the DynamoWritesPath[_] is to write a tuple of (String, WhateverTypeHere) (to simulate a “field”).
So writing write[String].at(“url”) would yield a DynamoWritesPath[String]. Now I have several issues :
I have no clue how to write flatMap for my DynamoWritesPath[_]
what should yield a for comprehension to be able to obtain a DynamoWrite[TinyImage]
What I wrote so far (totally fuzzy and not compiling at all, looking for some help on this). Not committed at the moment (gist): https://gist.github.com/louis-forite/cad97cc0a47847b2e4177192d9dbc3ae
To sum up, I am looking for some guidance on how to write the DynamoWrites[_] part. My goal is to provide for the client the most straight forward way to code a DynamoWrites[_] for a given type. My non goal is to write the perfect library and keep it a zero dependency library.
Link to the library: https://github.com/louis-forite/dynamo-ast
A Reads is a covariant functor. That means it has map. It can also be seen as a Monad which means it has flatMap (although a monad is overkill unless you need the previous field in order to know how to process the next):
trait Reads[A] {
def map [B] (f: A => B): Reads[B]
def flatMap [B](f: A => Reads[B]): Reads[B] // not necessary, but available
}
The reason for this, is that to transform a Reads[Int] to a Reads[String], you need to first read the Int, then apply the Int => String function.
But a Writes is a contravariant functor. It has contramap where the direction of the types is reversed:
trait Writes[A] {
def contramap [B](f: B => A): Reads[B]
}
The type on the function is reversed because to transform a Writes[Int] to a Writes[String] you must receive the String from the caller, apply the transformation String => Int and then write the Int.
I don't think it makes sense to provide for-comprehension syntax (flatMap) for the Writes API.
// here it is clear that you're extracting a string value
url <- read[String].at(“url”)
// but what does this mean for the write method?
url <- write[String].at("url")
// what is `url`?
That's probably why play doesn't provide one either, and why they focus on their combinator syntax (using the and function, their version of applicative functor builder?).
For reference: http://blog.tmorris.net/posts/functors-and-things-using-scala/index.html
You can achieve a more consistent API by using something like the and method in play json:
(write[String]("url") and write[String]("alt"))(unlift(TinyImage.unapply))
(read[String]("url") and read[String]("alt"))(TinyImage.apply)
// unfortunately, the type ascription is necessary in this case
(write[String]("url") and write[String]("alt")) {(x: TinyImage) =>
(x.url, x.alt)
}
// transforming
val instantDynamoType: DynamoFormat[Instant] =
format[String].xmap(Instant.parse _)((_: Instant).toString)
You can still use for-comprehension for the reads, although it's a bit over-powered (sort of implies that fields must be processed in-sequence, while that's not technically necessary).
I am a new to Scala coming from Java background, currently confused about the best practice considering Option[T].
I feel like using Option.map is just more functional and beautiful, but this is not a good argument to convince other people. Sometimes, isEmpty check feels more straight forward thus more readable. Is there any objective advantages, or is it just personal preference?
Example:
Variation 1:
someOption.map{ value =>
{
//some lines of code
}
} orElse(foo)
Variation 2:
if(someOption.isEmpty){
foo
} else{
val value = someOption.get
//some lines of code
}
I intentionally excluded the options to use fold or pattern matching. I am simply not pleased by the idea of treating Option as a collection right now, and using pattern matching for a simple isEmpty check is an abuse of pattern matching IMHO. But no matter why I dislike these options, I want to keep the scope of this question to be the above two variations as named in the title.
Is there any objective advantages, or is it just personal preference?
I think there's a thin line between objective advantages and personal preference. You cannot make one believe there is an absolute truth to either one.
The biggest advantage one gains from using the monadic nature of Scala constructs is composition. The ability to chain operations together without having to "worry" about the internal value is powerful, not only with Option[T], but also working with Future[T], Try[T], Either[A, B] and going back and forth between them (also see Monad Transformers).
Let's try and see how using predefined methods on Option[T] can help with control flow. For example, consider a case where you have an Option[Int] which you want to multiply only if it's greater than a value, otherwise return -1. In the imperative approach, we get:
val option: Option[Int] = generateOptionValue
var res: Int = if (option.isDefined) {
val value = option.get
if (value > 40) value * 2 else -1
} else -1
Using collections style method on Option, an equivalent would look like:
val result: Int = option
.filter(_ > 40)
.map(_ * 2)
.getOrElse(-1)
Let's now consider a case for composition. Let's say we have an operation which might throw an exception. Additionaly, this operation may or may not yield a value. If it returns a value, we want to query a database with that value, otherwise, return an empty string.
A look at the imperative approach with a try-catch block:
var result: String = _
try {
val maybeResult = dangerousMethod()
if (maybeResult.isDefined) {
result = queryDatabase(maybeResult.get)
} else result = ""
}
catch {
case NonFatal(e) => result = ""
}
Now let's consider using scala.util.Try along with an Option[String] and composing both together:
val result: String = Try(dangerousMethod())
.toOption
.flatten
.map(queryDatabase)
.getOrElse("")
I think this eventually boils down to which one can help you create clear control flow of your operations. Getting used to working with Option[T].map rather than Option[T].get will make your code safer.
To wrap up, I don't believe there's a single truth. I do believe that composition can lead to beautiful, readable, side effect deferring safe code and I'm all for it. I think the best way to show other people what you feel is by giving them examples as we just saw, and letting them feel for themselves the power they can leverage with these sets of tools.
using pattern matching for a simple isEmpty check is an abuse of pattern matching IMHO
If you do just want an isEmpty check, isEmpty/isDefined is perfectly fine. But in your case you also want to get the value. And using pattern matching for this is not abuse; it's precisely the basic use-case. Using get allows to very easily make errors like forgetting to check isDefined or making the wrong check:
if(someOption.isEmpty){
val value = someOption.get
//some lines of code
} else{
//some other lines
}
Hopefully testing would catch it, but there's no reason to settle for "hopefully".
Combinators (map and friends) are better than get for the same reason pattern matching is: they don't allow you to make this kind of mistake. Choosing between pattern matching and combinators is a different question. Generally combinators are preferred because they are more composable (as Yuval's answer explains). If you want to do something covered by a single combinator, I'd generally choose them; if you need a combination like map ... getOrElse, or a fold with multi-line branches, it depends on the specific case.
It seems similar to you in case of Option but just consider the case of Future. You will not be able to interact with the future's value after going out of Future monad.
import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.Promise
import scala.util.{Success, Try}
// create a promise which we will complete after sometime
val promise = Promise[String]();
// Now lets consider the future contained in this promise
val future = promise.future;
val byGet = if (!future.value.isEmpty) {
val valTry = future.value.get
valTry match {
case Success(v) => v + " :: Added"
case _ => "DEFAULT :: Added"
}
} else "DEFAULT :: Added"
val byMap = future.map(s => s + " :: Added")
// promise was completed now
promise.complete(Try("PROMISE"))
//Now lets print both values
println(byGet)
// DEFAULT :: Added
println(byMap)
// Success(PROMISE :: Added)
I have the following piece of code that I am trying to enhance:
I am using the java.nio.file package to represent a directory or a file as a Path.
So here goes:
import java.nio.file.{Paths,DirectoryStream,Files,
Path,DirectoryIteratorException}
val path: Path = Paths.get(directoryPath)
var directoryStream: Option[DirectoryStream[Path]] = None
// so far so good
try {
directoryStream = Some(Files.newDirectoryStream(pathO))
// this is where i get into trouble
def getMeDirStream: DirectoryStream[Path] =
if (!directoryStream.isEmpty && directoryStream.isDefined)
getMeDirStream.get
else
None
// invoke the iterator() method of dstream here
}
The above piece of code will not compile because I do not know what to return in the else, and right now, for the life of me, I can only come up with None, which the compiler simply does not like and I would like to learn what should be its replacement.
I want this example to be a learning lesson of Option and Some for me.
Okay, this is where I choke. I would like to check if the directoryStream is not empty and is defined, and then if this is the case, I would like to invoke getMeDirStream.get to invoke the iterator() method on it.
The API for Option tells me that invoking the get() method could result in a java.util.NoSuchElementException if the option is empty.
If the directoryStream is empty I want to return something and not None, because IntelliJ is telling me that "Expression of type None.type doesn't conform to expected type DirectoryStream[Path]".
Now, I am being all naive about this.
I would like to know the following:
What should I return in the else other than None?
Should I wrap the getMeDirStream.get in a try-catch with a java.util.NoSuchElementException, even though I am checking if the directoryStream is empty or not.?
What is the purpose of a try-catch in the getMeDirStream.get, if there is indeed such a need?
How can I clean up the above piece of code to incorporate correct checks for being isDefined and for catching appropriate exceptions?
Once I know what to return in the else (and after putting in the appropriate try-catch block if necessary), I would like to invoke the iterator() method on getMeDirStream to do some downstream operations.
Some and None are subtypes of Option, but to be more correct, they are actually two different cases of Option or data constructors. In other words, even though Scala allows you to directly invoke a Some or a None you should still regard their type to be Option. The more important thing to take from this is that you should never under any circumstance invoke Option#get as it is unsafe.
The intention of Option is to indicate the possibility that a value does not exist. If you care about the errors, then you should probably look at using Either instead (or Scalaz's Either called \/).
You can keep the computation within the Option context and then only extract the value later, or provide a default.
def fromTryCatch[A](a: => A): Either[Throwable, A] = try { Right(a) } catch { case e: Throwable => Left(e) }
val getMeDirStream: Option[java.util.Iterator[Path]] =
for {
path <- fromTryCatch(Paths.get(directoryPath)).toOption
directoryStream <- fromTryCatch(Files.newDirectoryStream(pathO)).toOption
} yield directoryStream.iterator()
Later, or right after, you can get the iterator, or provide a default value:
val iterator = getMeDirStream.getOrElse(java.util.Collections.emptyIterator[Path])
Your specific questions are difficult to address because it's unclear exactly what you're trying to achieve. In particular, when you ask what the purpose of the try block is... Well, you wrote it, so only you can answer that.
In general, you never call get on an Option. You either use pattern matching:
option match {
case Some(value) => /* ... */
case None => /* ... */
}
or you use methods like map, flatMap, and foreach (or the equivalent comprehension syntax that gpampara's code uses).
My revision of gpampara's answer:
import scala.collection.convert.wrapAll._
import scala.util.Try
import java.nio.file.{Paths, Files, Path}
val getMeDirStream: Option[Iterator[Path]] =
for {
path <- Try(Paths.get("")).toOption
directoryStream <- Try(Files.newDirectoryStream(path)).toOption
} yield directoryStream.iterator
Changes:
Using Try(...).toOption instead of Either
Using implicits in scala.collection.convert to return the result as a Scala Iterator.
Try is similar to Option. Instead of Some and None, it has Success and Failure subtypes, and the failure case includes a Throwable, whereas None is just a singleton with no additional information.
Given an Option, what is the idiomatic way to get its value or throw an exception trying?
def foo() : String = {
val x : Option[String] = ...
x.getOrException()
}
A throw "statement" is really an expression in Scala, and it has type Nothing, which is a subtype of every other type. This means you can just use plain old getOrElse:
def myGet[A](oa: Option[A]) = oa.getOrElse(throw new RuntimeException("Can't."))
You really, really shouldn't be doing this, though.
(EDIT: this is not the best or most idiomatic way to do it. I wrote it when I was not familiar with Scala. I leave it here for an example of how not to do it. Nowadays I would do as #TravisBrown)
I think it really boils down to two things:
how sure are you that the value is there?
how do you want to react if it isn't?
If at that point in your code you expect the value to be there, and in the remote case that it isn't you want your program to fail fast, then I would only do a normal get and let Scala throw a NoSuchElementException if there was no value:
def foo() : String = {
val x : Option[String] = ...
x.get
}
If you want to handle the case differently (throw your own exception) I think a more elegant way would look like this:
def foo(): String = {
val x: Option[String] = None
x match {
case Some(value) => value
case None => throw new MyRuntimeException("blah")
}
}
And of course if you want to supply your own alternative value for the case that the Option is None you would just use getOrElse:
def foo(): String = {
val x: Option[String] = None
x.getOrElse("my alternative value")
}
I hope this will help you to understand how to represent errors (and generally effects) using types.
Error handling strategies in functional Scala
Use Option to return optional values. For example - fail to find entity in storage.
Use Option(possiblyNull) to avoid instances of Some(null).
Use Either[Error, T] to report expected failure. For example - email format is wrong, cannot parse a string to a number, etc.
Model your errors as ADTs (simply speaking kind of type hierarchies) to use it, for example, on the Left of the Either to represent more complex error scenarios.
Throw Exception only to signal unexpected and not-recoverable failures. Like missing config file.
Use Either.catchOnly or Try or Cats.IO (advanced) rather than a catch block for handling unexpected failures. Hint: You can still use ADT but extend them from throwables. More about Either vs Try.
Use Validated data-type from Cats lib to accumulate errors rather than fail-fast (Either), but prefer Either's on module-level to simplify the composition of the program (to have the same types). For example - form data validation, parsing errors accumulation.
Use mentioned types and don't optimize program preemptively - since most probably, bottle-necks would be in business logic, not in effect types.
Such an approach will simplify maintenance and updates of your code since you can reason about it without going to implementation specifics (aka local-reasoning). Also - reduce bugs - you cannot miss an error in the type. And compose the program easier (with help of map, flatMap and other combinators) - since it's simpler on type level, rather than with non-local exceptions and side-effects.
More about learning functional Scala.
But be aware that sometimes with this approach types could stack up and it could become harder to compose things. Given, for example: x: Future[Either[Error, Option[T]]] What you can do:
Use map and flatMap in combination with pattern-matching to compose different values of such types, for example:
x.faltMap { case Right(Some(v)) => anotherFuture(v); case Left(er) => ... }
If it doesn't help you can try to use MonadTransformers (don't be scared of the name, it's just wrappers around the effect types like Either and Future)
Also, an option is to simplify your errors ADT by extending them from the Throwable to unify it with Future, then it'll be Future[Option[T]]
And finally, in your case one option will be:
def foo() : Either[Error, String] = {
val x : Option[String] = ...
x match {
case Some(v) => Right(v)
case None => Left(Error(reason))
}
}
Just use the .get method.
def get[T](o:Option[T]) = o.get
It will throw a NoSuchElementException if o is an instance of None.
Basically, I would work with options like this:
def addPrint(oi:Option[Int]) = oi.map(_+1).foreach(println)
addPrint(Some(41))
addPrint(Some(1336))
addPrint(None)
to avoid your specific question.
Scala now support this operation on maps using getOrElse() method, see documentation here
As pointed out already, throwing an exception in Scala is an expression as well.
So you can do the following:
myMap.getOrElse(myKey, throw new MyCustomException("Custom Message HERE")
In languages like SML, Erlang and in buch of others we may define functions like this:
fun reverse [] = []
| reverse x :: xs = reverse xs # [x];
I know we can write analog in Scala like this (and I know, there are many flaws in the code below):
def reverse[T](lst: List[T]): List[T] = lst match {
case Nil => Nil
case x :: xs => reverse(xs) ++ List(x)
}
But I wonder, if we could write former code in Scala, perhaps with desugaring to the latter.
Is there any fundamental limitations for such syntax being implemented in the future (I mean, really fundamental -- e.g. the way type inference works in scala, or something else, except parser obviously)?
UPD
Here is a snippet of how it could look like:
type T
def reverse(Nil: List[T]) = Nil
def reverse(x :: xs: List[T]): List[T] = reverse(xs) ++ List(x)
It really depends on what you mean by fundamental.
If you are really asking "if there is a technical showstopper that would prevent to implement this feature", then I would say the answer is no. You are talking about desugaring, and you are on the right track here. All there is to do is to basically stitch several separates cases into one single function, and this can be done as a mere preprocessing step (this only requires syntactic knowledge, no need for semantic knowledge). But for this to even make sense, I would define a few rules:
The function signature is mandatory (in Haskell by example, this would be optional, but it is always optional whether you are defining the function at once or in several parts). We could try to arrange to live without the signature and attempt to extract it from the different parts, but lack of type information would quickly come to byte us. A simpler argument is that if we are to try to infer an implicit signature, we might as well do it for all the methods. But the truth is that there are very good reasons to have explicit singatures in scala and I can't imagine to change that.
All the parts must be defined within the same scope. To start with, they must be declared in the same file because each source file is compiled separately, and thus a simple preprocessor would not be enough to implement the feature. Second, we still end up with a single method in the end, so it's only natural to have all the parts in the same scope.
Overloading is not possible for such methods (otherwise we would need to repeat the signature for each part just so the preprocessor knows which part belongs to which overload)
Parts are added (stitched) to the generated match in the order they are declared
So here is how it could look like:
def reverse[T](lst: List[T]): List[T] // Exactly like an abstract def (provides the signature)
// .... some unrelated code here...
def reverse(Nil) = Nil
// .... another bit of unrelated code here...
def reverse(x :: xs ) = reverse(xs) ++ List(x)
Which could be trivially transformed into:
def reverse[T](list: List[T]): List[T] = lst match {
case Nil => Nil
case x :: xs => reverse(xs) ++ List(x)
}
// .... some unrelated code here...
// .... another bit of unrelated code here...
It is easy to see that the above transformation is very mechanical and can be done by just manipulating a source AST (the AST produced by the slightly modified grammar that accepts this new constructs), and transforming it into the target AST (the AST produced by the standard scala grammar).
Then we can compile the result as usual.
So there you go, with a few simple rules we are able to implement a preprocessor that does all the work to implement this new feature.
If by fundamental you are asking "is there anything that would make this feature out of place" then it can be argued that this does not feel very scala. But more to the point, it does not bring that much to the table. Scala author(s) actually tend toward making the language simpler (as in less built-in features, trying to move some built-in features into libraries) and adding a new syntax that is not really more readable goes against the goal of simplification.
In SML, your code snippet is literally just syntactic sugar (a "derived form" in the terminology of the language spec) for
val rec reverse = fn x =>
case x of [] => []
| x::xs = reverse xs # [x]
which is very close to the Scala code you show. So, no there is no "fundamental" reason that Scala couldn't provide the same kind of syntax. The main problem is Scala's need for more type annotations, which makes this shorthand syntax far less attractive in general, and probably not worth the while.
Note also that the specific syntax you suggest would not fly well, because there is no way to distinguish one case-by-case function definition from two overloaded functions syntactically. You probably would need some alternative syntax, similar to SML using "|".
I don't know SML or Erlang, but I know Haskell. It is a language without method overloading. Method overloading combined with such pattern matching could lead to ambiguities. Imagine following code:
def f(x: String) = "String "+x
def f(x: List[_]) = "List "+x
What should it mean? It can mean method overloading, i.e. the method is determined in compile time. It can also mean pattern matching. There would be just a f(x: AnyRef) method that would do the matching.
Scala also has named parameters, which would be probably also broken.
I don't think that Scala is able to offer more simple syntax than you have shown in general. A simpler syntax may IMHO work in some special cases only.
There are at least two problems:
[ and ] are reserved characters because they are used for type arguments. The compiler allows spaces around them, so that would not be an option.
The other problem is that = returns Unit. So the expression after the | would not return any result
The closest I could come up with is this (note that is very specialized towards your example):
// Define a class to hold the values left and right of the | sign
class |[T, S](val left: T, val right: PartialFunction[T, T])
// Create a class that contains the | operator
class OrAssoc[T](left: T) {
def |(right: PartialFunction[T, T]): T | T = new |(left, right)
}
// Add the | to any potential target
implicit def anyToOrAssoc[S](left: S): OrAssoc[S] = new OrAssoc(left)
object fun {
// Use the magic of the update method
def update[T, S](choice: T | S): T => T = { arg =>
if (choice.right.isDefinedAt(arg)) choice.right(arg)
else choice.left
}
}
// Use the above construction to define a new method
val reverse: List[Int] => List[Int] =
fun() = List.empty[Int] | {
case x :: xs => reverse(xs) ++ List(x)
}
// Call the method
reverse(List(3, 2, 1))