parSequence and parTraverse in tagless final - scala

Using tagless final (without using IO, but rather a generic F) how can I abstract over something like this:
def doSomething(s: String): IO[Unit] = ???
List("authMethods", "secretEngines", "plugins", "CAs", "common").parTraverse(doSomething)
The closest I can get is using parTraverseN from the Concurrent object, but I assume this will run concurrently instead of in parallel (as in parallelism). It also forces me to choose an n where as parTraverse does not.
The size of the list is just an example, it could be way bigger. doSomething is a pure function, multiple executions of it can run in parallel without problems.
Ideally, given that doSomething returns IO[Unit] I would like to abstract over parTraverse_ to an F with the correct typeclass instance.

Here's a similar complete working example:
import cats.Applicative
import cats.instances.list._
import cats.syntax.foldable._
trait Service[F[_]] {
val items = List("authMethods", "secretEngines", "plugins", "CAs", "common")
def doSomething(s: String): F[Unit] = ???
def result(implicit F: Applicative[F]): F[Unit] =
items.traverse_(doSomething)
}
If you want to use parTraverse_ here, the minimal changes necessary would look something like this:
import cats.{Applicative, Parallel}
import cats.instances.list._
import cats.syntax.parallel._
trait Service[F[_]] {
val items = List("authMethods", "secretEngines", "plugins", "CAs", "common")
def doSomething(s: String): F[Unit] = ???
def result(implicit F: Applicative[F], P: Parallel[F]): F[Unit] =
items.parTraverse_(doSomething)
}
Alternatively you could use Parallel.parTraverse_(items)(doSomething) and skip the syntax import. Both approaches require a Foldable instance for List (provided here by the cats.instances.list._ import, which will no longer be necessary in Cats 2.2.0), and a Parallel instance for F, which you get via the P constraint.
(Note that the Applicative constraint on result is no longer necessary in the second version, but that's only because this is a very simple example—I'm assuming your real code relies on something like Sync instead, and will need both that and Parallel.)
This answer needs a couple of footnotes, though. The first is that it might not actually be a good thing that parTraverse_ doesn't make you specify a bound in the way that parTraverseN does, and may result in excessive memory use, etc. (but this will depend on e.g. the expected size of your lists and the kind of work doSomething is doing, and is probably outside the scope of the question).
The second footnote is that "parallel" in the sense of the Parallel type class is more general than the "parallel" in the parallel-vs.-concurrent distinction in the Cats "Concurrency Basics" document. The Parallel type class models a very generic kind of logical parallelism that also encompasses error accumulation, for example. So when you write:
I assume this will run concurrently instead of in parallel (as in parallelism).
…your assumption is correct, but not exactly because the parTraverseN method is on Concurrent instead of Parallel; note that Concurrent.parTraverseN still requires a Parallel instance. When you see par or the Parallel type class in the context of cats.effect.Concurrent, you should think of concurrency, not "parallelism" in the "Concurrency Basics" sense.

Related

What is a "<refinement>" type gotten through a TypeTag?

I have a method:
import scala.reflect.runtime.universe.{TypeTag,typeOf}
def print[T:TypeTag] = println(typeOf[T].typeSymbol.name.toString)
Most of the time, print[MyClass] prints MyClass when invoked, but sometimes, it prints <refinement>?
I am working on a fairly complex system (multiple interconnecting jars, 100K lines of code), and I cannot seem to identify what determines if it is the one behaviour or the other. But if I knew what <refinement> means, or what triggers that, maybe I could?
Refinements could be explained as anonymous class type. E.g.
import scala.reflect.runtime.universe.{TypeTag,typeOf}
def print[T:TypeTag] = println(typeOf[T].typeSymbol.name.toString)
class C
trait T
print[C with T]
type A = C with T
print[A]
Output will be <refinement> in both cases.

Reader monad in Scala: return, local, and sequence

I'm using the Reader monad in Scala as provided by the scalaz library. I'm familiar with this monad as defined in Haskell. The problem is that I cannot find the functions equivalent to return, local, and sequence (among others).
Currently I use constructs that I do not like since I'm repeating myself or making my code a bit obscure.
Regarding return, I'm currently using:
Reader{_ => someValue}
I'd rather just use a construct like unit(someValue), but I could not find anything on the internet. There are tutorials like this one that use the approach above, and which I consider not optimal.
Regarding local I also have to do something similar: instead of typing something like: local f myReader I have to unfold its definition:
Reader{env => myReader.run(f(env))
Finally, sequence is a bit closer to what I would expect (being a Haskell refugee doing Scala):
readers: List[Reader[Env, T]]
readerTs: Reader[Env, List[T]] = readers.sequenceU
My problem with this implementation is that, being relatively new to Scala, the type of sequenceU
final class TraverseOps[F[_],A] private[syntax](val self: F[A])(implicit val F: Traverse[F]) extends Ops[F[A]] {
//...
def sequenceU(implicit G: Unapply[Applicative, A]): G.M[F[G.A]]
appears like rather obscure, and seems like black magic. Ideally I would like to use a sequence operations on Monads.
Is there a better translation of these constructs to Scala available on scalaz or similar library? I'm not married to any Functional library for Scala, so any solution using other libraries will do, although I'd rather have an answer using scalaz, since I already implemented my code using it.
To make the things simpler, I fill in some types. Changing them to defs with generic types should still work.
Also I extracted the ReaderInt type, to avoid confusion with type lambdas.
return / pure / point
Scala does not have automatic typeclass resolution, so you need to provide them implicitly. For Kleisli (being a monad transformer for reader),
Kleisli[Id, ?, ?] is enough
implicit val KA = scalaz.Kleisli.kleisliIdApplicative[Int]
type ReaderInt[A] = Kleisli[Id.Id, Int, A]
val alwaysHello = KA.point("hello")
or with imported syntax:
import scalaz.syntax.applicative._
val alwaysHello = "hello".point[ReaderInt]
So as a general rule, you
1) import the applicative intance, which usually located in scalaz.std.something.somethingInstance
2) import scalaz.syntax.something._
3) then you can write x.point[F], where F is your applicative.
local
Not sure, that it answers your question, but Kleisli has a local method.
val f: String ⇒ Int = _.length
val alwaysEleven = alwaysHello local f
sequencing
The same way, you are free to choose to use syntax for or to specify type classes explicitly.
import scalaz.std.list.listInstance
val initial: List[ReaderInt[String]] = ???
val sequenced: ReaderInt[List[String]] = Traverse[List].sequence[ReaderInt, String](initial)
import scalaz.syntax.traverse._
val z = x.sequence[ReaderInt, String]
I prefer not to use sequenceU, which uses Unapply typelcass to infer the G type, because sometimes scala has troubles of figuring out the right one.
And I personally do not find it messy to put in some types myself.
It may worth to look into cats, though it does not have much yet.

Scala scalaz.Monad[scala.concurrent.Future], what about the execution context?

I see a couple of questions which make use of the scalaz Monad for what looks like a scala Future.
Here and here. I havent seen a satisfactory way of resolving this as an implicit type class without using a global execution context, however I feel that the import of these type classes shouldnt have to have static knowledge of the context.
Is there something I am missing here?
(Im assuming they are not using scalaz.concurrent.Future)
The ExecutionContext just needs to be implicitly available at the call site where your Monad is known to be Future. I agree there is some awkwardness surrounding potentially multiple different definitions of your type class existing in your program, but there is no need to depend on an implementation of it statically.
import scala.concurrent.Future
import scalaz._
import Scalaz._
def foo[A, T[_]: Traverse, M[_]: Monad](t: T[M[A]]): M[T[A]] =
implicitly[Traverse[T]].sequence(t)
def bar(l: List[Future[Int]])(implicit ctx: ExecutionContext): Future[List[Int]] =
foo(l)
https://github.com/scalaz/scalaz/blob/v7.1.0/core/src/main/scala/scalaz/std/Future.scala#L8

Lazy eager map evaluation

There are basically two options to evaluate a map in Scala.
Lazy evaluation computers the function that is passed as a parameter when the next value is needed. IF the function takes one hour to execute then it's one hour to wait when the value is needed. (e.g. Stream and Iterator)
Eager evaluation computes the function when the map is defined. It produces a new list (Vector or whatever) and stores the results, making the program to be busy in that time.
With Future we can obtain the list (Seq or whatever) in a separate thread, this means that our thread doesn't block, but the results have to be stored.
So I did something different, please check it here.
This was a while ago so I don't remember whether I tested it. The point is to have a map that applies concurrently (non-blocking) and kind of eagerly to a set of elements, filling a buffer (the size of the number of cores in the computer, and not more). This means that:
The invocation of the map doesn't block the current thread.
Obtaining an element doesn't block the current thread (in case there was time to calculate it before and store the result in the buffer).
Infinite lists can be handled because we only prefetch a few results (about 8, depending on the number of cores).
So this all sounds very good and you may be wondering what's the problem. The problem is that this solution is not particularly elegant IMHO. Assuming the code I shared works in Java and or Scala, to iterate over the elements in the iterable produced by the map I would only need to write:
new CFMap(whateverFunction).apply(whateverIterable)
However what I would like to write is something like:
whateverIterable.bmap(whateverFunction)
As it is usual in Scala (the 'b' is for buffered), or perhaps something like:
whateverThing.toBuffered.map(whateverFunction)
Either of them works for me. So the question is, how can I do this in an idiomatic way in Scala? Some options:
Monads: create a new collection "Buffered" so that I can use the toBuffered method (that should be added to the previous ones as an implicit) and implement map and everything else for this Buffered thing (sounds like quite some work).
Implicits: create an implicit method that transforms the usual collections or the superclass of them (I'm not sure about which one should it be, Iterable maybe?) to something else to which I can apply the .bmap method and obtain something from it, probably an iterable.
Other: there are probably many options I have not considered so far. It's possible that some library does already implement this (I'd be actually surprised of the opposite, I can't believe nobody thought of this before). Using something that has already been done is usually a good idea.
Please let me know if something is unclear.
What you're looking for is the "pimp-my-library" pattern. Check it out:
object CFMapExtensions {
import sanity.commons.functional.CFMap
import scala.collection.JavaConversions._
implicit class IterableExtensions[I](i: Iterable[I]) {
def bmap[O](f: Function1[I, O]): Iterable[O] = new CFMap(f).apply(asJavaIterable(i))
}
implicit class JavaIterableExtensions[I](i: java.lang.Iterable[I]) {
def bmap[O](f: Function1[I, O]): Iterable[O] = new CFMap(f).apply(i)
}
// Add an implicit conversion to a java function.
import java.util.function.{Function => JFunction}
implicit def toJFunction[I, O](f: Function1[I, O]): JFunction[I, O] = {
new JFunction[I, O]() {
def apply(t: I): O = f(t)
}
}
}
object Test extends App {
import CFMapExtensions._
List(1,2,3,4).bmap(_ + 5).foreach(println)
}

Good example of implicit parameter in Scala? [closed]

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So far implicit parameters in Scala do not look good for me -- it is too close to global variables, however since Scala seems like rather strict language I start doubting in my own opinion :-).
Question: could you show a real-life (or close) good example when implicit parameters really work. IOW: something more serious than showPrompt, that would justify such language design.
Or contrary -- could you show reliable language design (can be imaginary) that would make implicit not neccessary. I think that even no mechanism is better than implicits because code is clearer and there is no guessing.
Please note, I am asking about parameters, not implicit functions (conversions)!
Updates
Global variables
Thank you for all great answers. Maybe I clarify my "global variables" objection. Consider such function:
max(x : Int,y : Int) : Int
you call it
max(5,6);
you could (!) do it like this:
max(x:5,y:6);
but in my eyes implicits works like this:
x = 5;
y = 6;
max()
it is not very different from such construct (PHP-like)
max() : Int
{
global x : Int;
global y : Int;
...
}
Derek's answer
This is great example, however if you can think of as flexible usage of sending message not using implicit please post an counter-example. I am really curious about purity in language design ;-).
In a sense, yes, implicits represent global state. However, they are not mutable, which is the true problem with global variables -- you don't see people complaining about global constants, do you? In fact, coding standards usually dictate that you transform any constants in your code into constants or enums, which are usually global.
Note also that implicits are not in a flat namespace, which is also a common problem with globals. They are explicitly tied to types and, therefore, to the package hierarchy of those types.
So, take your globals, make them immutable and initialized at the declaration site, and put them on namespaces. Do they still look like globals? Do they still look problematic?
But let's not stop there. Implicits are tied to types, and they are just as much "global" as types are. Does the fact that types are global bother you?
As for use cases, they are many, but we can do a brief review based on their history. Originally, afaik, Scala did not have implicits. What Scala had were view types, a feature many other languages had. We can still see that today whenever you write something like T <% Ordered[T], which means the type T can be viewed as a type Ordered[T]. View types are a way of making automatic casts available on type parameters (generics).
Scala then generalized that feature with implicits. Automatic casts no longer exist, and, instead, you have implicit conversions -- which are just Function1 values and, therefore, can be passed as parameters. From then on, T <% Ordered[T] meant a value for an implicit conversion would be passed as parameter. Since the cast is automatic, the caller of the function is not required to explicitly pass the parameter -- so those parameters became implicit parameters.
Note that there are two concepts -- implicit conversions and implicit parameters -- that are very close, but do not completely overlap.
Anyway, view types became syntactic sugar for implicit conversions being passed implicitly. They would be rewritten like this:
def max[T <% Ordered[T]](a: T, b: T): T = if (a < b) b else a
def max[T](a: T, b: T)(implicit $ev1: Function1[T, Ordered[T]]): T = if ($ev1(a) < b) b else a
The implicit parameters are simply a generalization of that pattern, making it possible to pass any kind of implicit parameters, instead of just Function1. Actual use for them then followed, and syntactic sugar for those uses came latter.
One of them is Context Bounds, used to implement the type class pattern (pattern because it is not a built-in feature, just a way of using the language that provides similar functionality to Haskell's type class). A context bound is used to provide an adapter that implements functionality that is inherent in a class, but not declared by it. It offers the benefits of inheritance and interfaces without their drawbacks. For example:
def max[T](a: T, b: T)(implicit $ev1: Ordering[T]): T = if ($ev1.lt(a, b)) b else a
// latter followed by the syntactic sugar
def max[T: Ordering](a: T, b: T): T = if (implicitly[Ordering[T]].lt(a, b)) b else a
You have probably used that already -- there's one common use case that people usually don't notice. It is this:
new Array[Int](size)
That uses a context bound of a class manifests, to enable such array initialization. We can see that with this example:
def f[T](size: Int) = new Array[T](size) // won't compile!
You can write it like this:
def f[T: ClassManifest](size: Int) = new Array[T](size)
On the standard library, the context bounds most used are:
Manifest // Provides reflection on a type
ClassManifest // Provides reflection on a type after erasure
Ordering // Total ordering of elements
Numeric // Basic arithmetic of elements
CanBuildFrom // Collection creation
The latter three are mostly used with collections, with methods such as max, sum and map. One library that makes extensive use of context bounds is Scalaz.
Another common usage is to decrease boiler-plate on operations that must share a common parameter. For example, transactions:
def withTransaction(f: Transaction => Unit) = {
val txn = new Transaction
try { f(txn); txn.commit() }
catch { case ex => txn.rollback(); throw ex }
}
withTransaction { txn =>
op1(data)(txn)
op2(data)(txn)
op3(data)(txn)
}
Which is then simplified like this:
withTransaction { implicit txn =>
op1(data)
op2(data)
op3(data)
}
This pattern is used with transactional memory, and I think (but I'm not sure) that the Scala I/O library uses it as well.
The third common usage I can think of is making proofs about the types that are being passed, which makes it possible to detect at compile time things that would, otherwise, result in run time exceptions. For example, see this definition on Option:
def flatten[B](implicit ev: A <:< Option[B]): Option[B]
That makes this possible:
scala> Option(Option(2)).flatten // compiles
res0: Option[Int] = Some(2)
scala> Option(2).flatten // does not compile!
<console>:8: error: Cannot prove that Int <:< Option[B].
Option(2).flatten // does not compile!
^
One library that makes extensive use of that feature is Shapeless.
I don't think the example of the Akka library fits in any of these four categories, but that's the whole point of generic features: people can use it in all sorts of way, instead of ways prescribed by the language designer.
If you like being prescribed to (like, say, Python does), then Scala is just not for you.
Sure. Akka's got a great example of it with respect to its Actors. When you're inside an Actor's receive method, you might want to send a message to another Actor. When you do this, Akka will bundle (by default) the current Actor as the sender of the message, like this:
trait ScalaActorRef { this: ActorRef =>
...
def !(message: Any)(implicit sender: ActorRef = null): Unit
...
}
The sender is implicit. In the Actor there is a definition that looks like:
trait Actor {
...
implicit val self = context.self
...
}
This creates the implicit value within the scope of your own code, and it allows you to do easy things like this:
someOtherActor ! SomeMessage
Now, you can do this as well, if you like:
someOtherActor.!(SomeMessage)(self)
or
someOtherActor.!(SomeMessage)(null)
or
someOtherActor.!(SomeMessage)(anotherActorAltogether)
But normally you don't. You just keep the natural usage that's made possible by the implicit value definition in the Actor trait. There are about a million other examples. The collection classes are a huge one. Try wandering around any non-trivial Scala library and you'll find a truckload.
One example would be the comparison operations on Traversable[A]. E.g. max or sort:
def max[B >: A](implicit cmp: Ordering[B]) : A
These can only be sensibly defined when there is an operation < on A. So, without implicits we’d have to supply the context Ordering[B] every time we’d like to use this function. (Or give up type static checking inside max and risk a runtime cast error.)
If however, an implicit comparison type class is in scope, e.g. some Ordering[Int], we can just use it right away or simply change the comparison method by supplying some other value for the implicit parameter.
Of course, implicits may be shadowed and thus there may be situations in which the actual implicit which is in scope is not clear enough. For simple uses of max or sort it might indeed be sufficient to have a fixed ordering trait on Int and use some syntax to check whether this trait is available. But this would mean that there could be no add-on traits and every piece of code would have to use the traits which were originally defined.
Addition:
Response to the global variable comparison.
I think you’re correct that in a code snipped like
implicit val num = 2
implicit val item = "Orange"
def shopping(implicit num: Int, item: String) = {
"I’m buying "+num+" "+item+(if(num==1) "." else "s.")
}
scala> shopping
res: java.lang.String = I’m buying 2 Oranges.
it may smell of rotten and evil global variables. The crucial point, however, is that there may be only one implicit variable per type in scope. Your example with two Ints is not going to work.
Also, this means that practically, implicit variables are employed only when there is a not necessarily unique yet distinct primary instance for a type. The self reference of an actor is a good example for such a thing. The type class example is another example. There may be dozens of algebraic comparisons for any type but there is one which is special.
(On another level, the actual line number in the code itself might also make for a good implicit variable as long as it uses a very distinctive type.)
You normally don’t use implicits for everyday types. And with specialised types (like Ordering[Int]) there is not too much risk in shadowing them.
Based on my experience there is no real good example for use of implicits parameters or implicits conversion.
The small benefit of using implicits (not needing to explicitly write a parameter or a type) is redundant in compare to the problems they create.
I am a developer for 15 years, and have been working with scala for the last 1.5 years.
I have seen many times bugs that were caused by the developer not aware of the fact that implicits are used, and that a specific function actually return a different type that the one specified. Due to implicit conversion.
I also heard statements saying that if you don't like implicits, don't use them.
This is not practical in the real world since many times external libraries are used, and a lot of them are using implicits, so your code using implicits, and you might not be aware of that.
You can write a code that has either:
import org.some.common.library.{TypeA, TypeB}
or:
import org.some.common.library._
Both codes will compile and run.
But they will not always produce the same results since the second version imports implicits conversion that will make the code behave differently.
The 'bug' that is caused by this can occur a very long time after the code was written, in case some values that are affected by this conversion were not used originally.
Once you encounter the bug, its not an easy task finding the cause.
You have to do some deep investigation.
Even though you feel like an expert in scala once you have found the bug, and fixed it by changing an import statement, you actually wasted a lot of precious time.
Additional reasons why I generally against implicits are:
They make the code hard to understand (there is less code, but you don't know what he is doing)
Compilation time. scala code compiles much slower when implicits are used.
In practice, it changes the language from statically typed, to dynamically typed. Its true that once following very strict coding guidelines you can avoid such situations, but in real world, its not always the case. Even using the IDE 'remove unused imports', can cause your code to still compile and run, but not the same as before you removed 'unused' imports.
There is no option to compile scala without implicits (if there is please correct me), and if there was an option, none of the common community scala libraries would have compile.
For all the above reasons, I think that implicits are one of the worst practices that scala language is using.
Scala has many great features, and many not so great.
When choosing a language for a new project, implicits are one of the reasons against scala, not in favour of it. In my opinion.
Another good general usage of implicit parameters is to make the return type of a method depend on the type of some of the parameters passed to it. A good example, mentioned by Jens, is the collections framework, and methods like map, whose full signature usually is:
def map[B, That](f: (A) ⇒ B)(implicit bf: CanBuildFrom[GenSeq[A], B, That]): That
Note that the return type That is determined by the best fitting CanBuildFrom that the compiler can find.
For another example of this, see that answer. There, the return type of the method Arithmetic.apply is determined according to a certain implicit parameter type (BiConverter).
It's easy, just remember:
to declare the variable to be passed in as implicit too
to declare all the implicit params after the non-implicit params in a separate ()
e.g.
def myFunction(): Int = {
implicit val y: Int = 33
implicit val z: Double = 3.3
functionWithImplicit("foo") // calls functionWithImplicit("foo")(y, z)
}
def functionWithImplicit(foo: String)(implicit x: Int, d: Double) = // blar blar
Implicit parameters are heavily used in the collection API. Many functions get an implicit CanBuildFrom, which ensures that you get the 'best' result collection implementation.
Without implicits you would either pass such a thing all the time, which would make normal usage cumbersome. Or use less specialized collections which would be annoying because it would mean you loose performance/power.
I am commenting on this post a bit late, but I have started learning scala lately.
Daniel and others have given nice background about implicit keyword.
I would provide me two cents on implicit variable from practical usage perspective.
Scala is best suited if used for writing Apache Spark codes. In Spark, we do have spark context and most likely the configuration class that may fetch the configuration keys/values from a configuration file.
Now, If I have an abstract class and if I declare an object of configuration and spark context as follows :-
abstract class myImplicitClass {
implicit val config = new myConfigClass()
val conf = new SparkConf().setMaster().setAppName()
implicit val sc = new SparkContext(conf)
def overrideThisMethod(implicit sc: SparkContext, config: Config) : Unit
}
class MyClass extends myImplicitClass {
override def overrideThisMethod(implicit sc: SparkContext, config: Config){
/*I can provide here n number of methods where I can pass the sc and config
objects, what are implicit*/
def firstFn(firstParam: Int) (implicit sc: SparkContext, config: Config){
/*I can use "sc" and "config" as I wish: making rdd or getting data from cassandra, for e.g.*/
val myRdd = sc.parallelize(List("abc","123"))
}
def secondFn(firstParam: Int) (implicit sc: SparkContext, config: Config){
/*following are the ways we can use "sc" and "config" */
val keyspace = config.getString("keyspace")
val tableName = config.getString("table")
val hostName = config.getString("host")
val userName = config.getString("username")
val pswd = config.getString("password")
implicit val cassandraConnectorObj = CassandraConnector(....)
val cassandraRdd = sc.cassandraTable(keyspace, tableName)
}
}
}
As we can see the code above, I have two implicit objects in my abstract class, and I have passed those two implicit variables as function/method/definition implicit parameters.
I think this is the best use case that we can depict in terms of usage of implicit variables.