I need to generate strings with the same length. I can't realize how. Many thanks
val s = for {
x <- Gen.alphaStr
} yield ...
example code:
import org.scalacheck.Gen
import org.scalacheck.Prop.forAll
// strGen generates a fixed length random string
val strGen = (n: Int) => Gen.listOfN(n, Gen.alphaChar).map(_.mkString)
val fixedLengthStr = forAll(strGen(10)){ s =>
s.length == 10
}
fixedLengthStr.check
to inspect a generated string use:
strGen(5).sample
There is a suchThat(f: T => Boolean): Gen[T] = new Gen[T] on Gen, so could be used like
val stringShorterThan = (n: Int) => Gen.alphaStr.suchThat(s => s.length <= n)
val string64 = stringShorterThan(64)
Related
I want to generate a List of some class which contains several fields. One of them is Int type and it doesn’t have to repeat. Could you help me to write the code?
I tried next:
case class Person(name: String, age: Int)
implicit val genPerson: Gen[Person] =
for {
name <- arbitrary[String]
age <- Gen.posNum[Int]
} yield Person(name, age)
implicit val genListOfPerson: Gen[scala.List[Person]] = Gen.listOfN(3, genPerson)
The problem is that I got an instance of a person with equal age.
If you're requiring that no two Persons in the generated list have the same age, you can
implicit def IntsArb: Arbitrary[Int] = Arbitrary(Gen.choose[Int](0, Int.MaxValue))
implicit val StringArb: Arbitrary[String] = Arbitrary(Gen.listOfN(5, Gen.alphaChar).map(_.mkString))
implicit val PersonGen = Arbitrary(Gen.resultOf(Person.apply _))
implicit val PersonsGen: Arbitrary[List[Person]] =
Arbitrary(Gen.listOfN(3, PersonGen.arbitrary).map { persons =>
val grouped: Map[Int, List[Person]] = persons.groupBy(_.age)
grouped.values.map(_.head) // safe because groupBy
})
Note that this will return a List with no duplicate ages but there's no guarantee that the list will have size 3 (it is guaranteed that the list will be nonempty, with size at most 3).
If having a list of size 3 is important, at the risk of generation failing if the "dice are against you", you can have something like:
def uniqueAges(persons: List[Person], target: Int): Gen[List[Person]] = {
val grouped: Map[Int, List[Person]] = persons.groupBy(_.age)
val uniquelyAged = grouped.values.map(_.head)
val n = uniquelyAged.size
if (n == target) Gen.const(uniquelyAged)
else {
val existingAges = grouped.keySet
val genPerson = PersonGen.arbitrary.retryUntil { p => !existingAges(p.age) }
Gen.listOf(target - n, genPerson)
.flatMap(l => uniqueAges(l, target - n))
.map(_ ++ uniquelyAged)
}
}
implicit val PersonsGen: Arbitrary[List[Person]] =
Arbitrary(Gen.listOfN(3, PersonGen.arbitrary).flatMap(l => uniqueAges(l, 3)))
You can do it as follows:
implicit def IntsArb: Arbitrary[Int] = Arbitrary(Gen.choose[Int](0, Int.MaxValue))
implicit val StringArb: Arbitrary[String] = Arbitrary(Gen.listOfN(5, Gen.alphaChar).map(_.mkString))
implicit val PersonGen = Arbitrary(Gen.resultOf(Person.apply _))
implicit val PersonsGen: Arbitrary[List[Person]] = Arbitrary(Gen.listOfN(3, PersonGen.arbitrary))
I have the following issue
Given this list in input , I want to concateneate integers for each line having the same title,
val listIn= List("TitleB,Int,11,0",
"TitleB,Int,1,0",
"TitleB,Int,1,0",
"TitleB,Int,3,0",
"TitleA,STR,3,0",
"TitleC,STR,4,5")
I wrote the following function
def sumB(list: List[String]): List[String] = {
val itemPattern = raw"(.*)(\d+),(\d+)\s*".r
list.foldLeft(ListMap.empty[String, (Int,Int)].withDefaultValue((0,0))) {
case (line, stri) =>
val itemPattern(k,i,j) = stri
val (a, b) = line(k)
line.updated(k, (i.toInt + a, j.toInt + b))
}.toList.map { case (k, (i, j)) => s"$k$i,$j" }
}
Expected output would be:
List("TitleB,Int,16,0",
"TitleA,STR,3,0",
"TitleC,STR,4,5")
Since you are looking to preserve the order of the titles as they appear in the input data, I would suggest you to use LinkedHashMap with foldLeft as below
val finalResult = listIn.foldLeft(new mutable.LinkedHashMap[String, (String, String, Int, Int)]){ (x, y) => {
val splitted = y.split(",")
if(x.keySet.contains(Try(splitted(0)).getOrElse(""))){
val oldTuple = x(Try(splitted(0)).getOrElse(""))
x.update(Try(splitted(0)).getOrElse(""), (Try(splitted(0)).getOrElse(""), Try(splitted(1)).getOrElse(""), oldTuple._3+Try(splitted(2).toInt).getOrElse(0), oldTuple._4+Try(splitted(3).toInt).getOrElse(0)))
x
}
else {
x.put(Try(splitted(0)).getOrElse(""), (Try(splitted(0)).getOrElse(""), Try(splitted(1)).getOrElse(""), Try(splitted(2).toInt).getOrElse(0), Try(splitted(3).toInt).getOrElse(0)))
x
}
}}.mapValues(iter => iter._1+","+iter._2+","+iter._3+","+iter._4).values.toList
finalResult should be your desired output
List("TitleB,Int,16,0", "TitleA,STR,3,0", "TitleC,STR,4,5")
I'm trying to write some code to make it easy to chain functions that return Scalaz Validation types. One method I am trying to write is analogous to Validation.flatMap (Short circuit that validation) which I will call andPipe. The other is analogous to |#| on ApplicativeBuilder (accumulating errors) except it only returns the final Success type, which I will call andPass
Suppose I have functions:
def allDigits: (String) => ValidationNEL[String, String]
def maxSizeOfTen: (String) => ValidationNEL[String, String]
def toInt: (String) => ValidationNEL[String, Int]
As an example, I would like to first pass the input String to both allDigits and maxSizeOf10. If there are failures, it should short circuit by not calling the toInt function and return either or both failures that occurred. If Successful, I would like to pass the Success value to the toInt function. From there, it would either Succeed with the output value being an Int, or it would fail returning only the validation failure from toInt.
def intInput: (String) => ValidationNEL[String,Int] = (allDigits andPass maxSizeOfTen) andPipe toInt
Is there a way to do this without my add-on implementation below?
Here is my Implementation:
trait ValidationFuncPimp[E,A,B] {
val f: (A) => Validation[E, B]
/** If this validation passes, pass to f2, otherwise fail without accumulating. */
def andPipe[C](f2: (B) => Validation[E,C]): (A) => Validation[E,C] = (a: A) => {
f(a) match {
case Success(x) => f2(x)
case Failure(x) => Failure(x)
}
}
/** Run this validation and the other validation, Success only if both are successful. Fail accumulating errors. */
def andPass[D](f2: (A) => Validation[E,D])(implicit S: Semigroup[E]): (A) => Validation[E,D] = (a:A) => {
(f(a), f2(a)) match {
case (Success(x), Success(y)) => Success(y)
case (Failure(x), Success(y)) => Failure(x)
case (Success(x), Failure(y)) => Failure(y)
case (Failure(x), Failure(y)) => Failure(S.append(x, y))
}
}
}
implicit def toValidationFuncPimp[E,A,B](valFunc : (A) => Validation[E,B]): ValidationFuncPimp[E,A,B] = {
new ValidationFuncPimp[E,A,B] {
val f = valFunc
}
}
I'm not claiming that this answer is necessarily any better than drstevens's, but it takes a slightly different approach and wouldn't fit in a comment there.
First for our validation methods (note that I've changed the type of toInt a bit, for reasons I'll explain below):
import scalaz._, Scalaz._
def allDigits: (String) => ValidationNEL[String, String] =
s => if (s.forall(_.isDigit)) s.successNel else "Not all digits".failNel
def maxSizeOfTen: (String) => ValidationNEL[String, String] =
s => if (s.size <= 10) s.successNel else "Too big".failNel
def toInt(s: String) = try(s.toInt.right) catch {
case _: NumberFormatException => NonEmptyList("Still not an integer").left
}
I'll define a type alias for the sake of convenience:
type ErrorsOr[+A] = NonEmptyList[String] \/ A
Now we've just got a couple of Kleisli arrows:
val validator = Kleisli[ErrorsOr, String, String](
allDigits.flatMap(x => maxSizeOfTen.map(x *> _)) andThen (_.disjunction)
)
val integerizer = Kleisli[ErrorsOr, String, Int](toInt)
Which we can compose:
val together = validator >>> integerizer
And use like this:
scala> together("aaa")
res0: ErrorsOr[Int] = -\/(NonEmptyList(Not all digits))
scala> together("12345678900")
res1: ErrorsOr[Int] = -\/(NonEmptyList(Too big))
scala> together("12345678900a")
res2: ErrorsOr[Int] = -\/(NonEmptyList(Not all digits, Too big))
scala> together("123456789")
res3: ErrorsOr[Int] = \/-(123456789)
Using flatMap on something that isn't monadic makes me a little uncomfortable, and combining our two ValidationNEL methods into a Kleisli arrow in the \/ monad—which also serves as an appropriate model for our string-to-integer conversion—feels a little cleaner to me.
This is relatively concise with little "added code". It is still sort of wonky though because it ignores the successful result of applying allDigits.
scala> val validated = for {
| x <- allDigits
| y <- maxSizeOfTen
| } yield x *> y
validated: String => scalaz.Validation[scalaz.NonEmptyList[String],String] = <function1>
scala> val validatedToInt = (str: String) => validated(str) flatMap(toInt)
validatedToInt: String => scalaz.Validation[scalaz.NonEmptyList[String],Int] = <function1>
scala> validatedToInt("10")
res25: scalaz.Validation[scalaz.NonEmptyList[String],Int] = Success(10)
Alternatively you could keep both of the outputs of allDigits and maxSizeOfTen.
val validated2 = for {
x <- allDigits
y <- maxSizeOfTen
} yield x <|*|> y
I'm curious if someone else could come up with a better way to combine these. It's not really composition...
val validatedToInt = (str: String) => validated2(str) flatMap(_ => toInt(str))
Both validated and validated2 accumulate failures as shown below:
scala> def allDigits: (String) => ValidationNEL[String, String] = _ => failure(NonEmptyList("All Digits Fail"))
allDigits: String => scalaz.Scalaz.ValidationNEL[String,String]
scala> def maxSizeOfTen: (String) => ValidationNEL[String, String] = _ => failure(NonEmptyList("max > 10"))
maxSizeOfTen: String => scalaz.Scalaz.ValidationNEL[String,String]
scala> val validated = for {
| x <- allDigits
| y <- maxSizeOfTen
| } yield x *> y
validated: String => scalaz.Validation[scalaz.NonEmptyList[String],String] = <function1>
scala> val validated2 = for {
| x <- allDigits
| y <- maxSizeOfTen
| } yield x <|*|> y
validated2: String => scalaz.Validation[scalaz.NonEmptyList[String],(String, String)] = <function1>
scala> validated("ten")
res1: scalaz.Validation[scalaz.NonEmptyList[String],String] = Failure(NonEmptyList(All Digits Fail, max > 10))
scala> validated2("ten")
res3: scalaz.Validation[scalaz.NonEmptyList[String],(String, String)] = Failure(NonEmptyList(All Digits Fail, max > 10))
Use ApplicativeBuilder with the first two, so that the errors accumulate,
then flatMap toInt, so toInt only gets called if the first two succeed.
val validInt: String => ValidationNEL[String, Int] =
for {
validStr <- (allDigits |#| maxSizeOfTen)((x,_) => x);
i <- toInt
} yield(i)
Is there any difference between this code:
for(term <- term_array) {
val list = hashmap.get(term)
...
}
and:
for(term <- term_array; val list = hashmap.get(term)) {
...
}
Inside the loop I'm changing the hashmap with something like this
hashmap.put(term, string :: list)
While checking for the head of list it seems to be outdated somehow when using the second code snippet.
The difference between the two is, that the first one is a definition which is created by pattern matching and the second one is a value inside a function literal. See Programming in Scala, Section 23.1 For Expressions:
for {
p <- persons // a generator
n = p.name // a definition
if (n startsWith "To") // a filter
} yield n
You see the real difference when you compile sources with scalac -Xprint:typer <filename>.scala:
object X {
val x1 = for (i <- (1 to 5); x = i*2) yield x
val x2 = for (i <- (1 to 5)) yield { val x = i*2; x }
}
After code transforming by the compiler you will get something like this:
private[this] val x1: scala.collection.immutable.IndexedSeq[Int] =
scala.this.Predef.intWrapper(1).to(5).map[(Int, Int), scala.collection.immutable.IndexedSeq[(Int, Int)]](((i: Int) => {
val x: Int = i.*(2);
scala.Tuple2.apply[Int, Int](i, x)
}))(immutable.this.IndexedSeq.canBuildFrom[(Int, Int)]).map[Int, scala.collection.immutable.IndexedSeq[Int]]((
(x$1: (Int, Int)) => (x$1: (Int, Int) #unchecked) match {
case (_1: Int, _2: Int)(Int, Int)((i # _), (x # _)) => x
}))(immutable.this.IndexedSeq.canBuildFrom[Int]);
private[this] val x2: scala.collection.immutable.IndexedSeq[Int] =
scala.this.Predef.intWrapper(1).to(5).map[Int, scala.collection.immutable.IndexedSeq[Int]](((i: Int) => {
val x: Int = i.*(2);
x
}))(immutable.this.IndexedSeq.canBuildFrom[Int]);
This can be simplified to:
val x1 = (1 to 5).map {i =>
val x: Int = i * 2
(i, x)
}.map {
case (i, x) => x
}
val x2 = (1 to 5).map {i =>
val x = i * 2
x
}
Instantiating variables inside for loops makes sense if you want to use that variable the for statement, like:
for (i <- is; a = something; if (a)) {
...
}
And the reason why your list is outdated, is that this translates to a foreach call, such as:
term_array.foreach {
term => val list= hashmap.get(term)
} foreach {
...
}
So when you reach ..., your hashmap has already been changed. The other example translates to:
term_array.foreach {
term => val list= hashmap.get(term)
...
}
What is wrong is the following method?
def someMethod(funcs: => Option[String]*) = {
...
}
That actually "works" under 2.7.7 if you add parens:
scala> def someMethod(funcs: => (Option[String]*)) = funcs
someMethod: (=> Option[String]*)Option[String]*
except it doesn't actually work at runtime:
scala> someMethod(Some("Fish"),None)
scala.MatchError: Some(Fish)
at scala.runtime.ScalaRunTime$.boxArray(ScalaRunTime.scala:136)
at .someMethod(<console>:4)
at .<init>(<console>:6)
at .<clinit>(<console>) ...
In 2.8 it refuses to let you specify X* as the output of any function or by-name parameter, even though you can specify it as an input (this is r21230, post-Beta 1):
scala> var f: (Option[Int]*) => Int = _
f: (Option[Int]*) => Int = null
scala> var f: (Option[Int]*) => (Option[Int]*) = _
<console>:1: error: no * parameter type allowed here
var f: (Option[Int]*) => (Option[Int]*) = _
But if you try to convert from a method, it works:
scala> def m(oi: Option[Int]*) = oi
m: (oi: Option[Int]*)Option[Int]*
scala> var f = (m _)
f: (Option[Int]*) => Option[Int]* = <function1>
scala> f(Some(1),None)
res0: Option[Int]* = WrappedArray(Some(1), None)
So it's not entirely consistent.
In any case, you can possibly achieve what you want by passing in an Array and then sending that array to something that takes repeated arguments:
scala> def aMethod(os: Option[String]*) { os.foreach(println) }
aMethod: (os: Option[String]*)Unit
scala> def someMethod(funcs: => Array[Option[String]]) { aMethod(funcs:_*) }
someMethod: (funcs: => Array[Option[String]])Unit
scala> someMethod(Array(Some("Hello"),Some("there"),None))
Some(Hello)
Some(there)
None
If you really want to (easily) pass a bunch of lazily evaluated arguments, then you need a little bit of infrastructure that as far as I know doesn't nicely exist in the library (this is code for 2.8; view it as inspiration for a similar strategy in 2.7):
class Lazy[+T](t: () => T, lt: Lazy[T]) {
val params: List[() => T] = (if (lt eq null) Nil else t :: lt.params)
def ~[S >: T](s: => S) = new Lazy[S](s _,this)
}
object Lz extends Lazy[Nothing](null,null) {
implicit def lazy2params[T : Manifest](lz: Lazy[T]) = lz.params.reverse.toArray
}
Now you can easily create a bunch of parameters that are lazily evaluated:
scala> import Lz._ // To get implicit def
import Lz._
scala> def lazyAdder(ff: Array[()=>Int]) = {
| println("I'm adding now!");
| (0 /: ff){(n,f) => n+f()}
| }
lazyAdder: (ff: Array[() => Int])Int
scala> def yelp = { println("You evaluated me!"); 5 }
yelp: Int
scala> val a = 3
a: Int = 3
scala> var b = 7
b: Int = 7
scala> lazyAdder( Lz ~ yelp ~ (a+b) )
I'm adding now!
You evaluated me!
res0: Int = 15
scala> val plist = Lz ~ yelp ~ (a+b)
plist: Lazy[Int] = Lazy#1ee1775
scala> b = 1
b: Int = 1
scala> lazyAdder(plist)
I'm adding now!
You evaluated me!
res1: Int = 9
Evidently repeated arguments are not available for by-name parameters.