I would like to passing a parameter via String and construct a Set of class objects, like this:
def getTypes(value: String) : Set[Class[Base]] = {
var set = Set[Class[Base]]()
var input = value.split(",")
if(input.contains("XXX"))
set ++ Class[xxx]
if(input.contains("YYY"))
set ++ Class[yyy]
if(input.contains("ZZZ"))
set ++ Class[zzz]
set
}
Then looping the set and use class.newInstance() to create the actual object to do something later. The able code can compile, but when it run, it complaint that
Error:(32, 16) object java.lang.Class is not a value
set ++ Class[xxx]
Any clue about about that?
There are two problems in your snippet. One, as aravindKrishna pointed, is you're trying to get Class literals improperly.
The other one is, you're treating your immutable Set like you would a mutable one. Remember you can't mutate the object itself - every operation returns a new one - so you should either reassign the variable every time (and using vars is discouraged for functional code), or use recursion, or construct the entire set in one go.
Here's an example of how to construct the set in one go:
def getTypes(value: String): Set[Class[_ <: Base]] = {
val mapping = Map(
"XXX", classOf[xxx],
"YYY", classOf[yyy],
"ZZZ", classOf[zzz])
val input = value.split(",").toSet
mapping.collect {
case (k, v) if input contains k => v
}.toSet
}
Or, translating your original code snippet more literally,
def getTypes(value: String): Set[Class[_ <: Base]] = {
val input = value.split(",").toSet
Set[Class[_ <: Base]]() ++
input.find("XXX" ==).map(_ => classOf[xxx]) ++
input.find("YYY" ==).map(_ => classOf[yyy]) ++
input.find("ZZZ" ==).map(_ => classOf[zzz])
}
Related
Edit:
Suppose I have a Seq:
Seq(Some("Earth"),Some("Mars"))
I need to add few more elements at start of this sequence. Values to be added are generated based on an Option value.
So I try to do as:
val o = ....//Option calculated here
Seq(o.map(myFunction(_)),"Earth","Mars")
def myFunction(s: String) = s match {
case "x" => Seq(Some("Jupiter"), Some("Venus"))
case "y" => Seq(Some("PLuto"), Some("Mercury"))
}
But map would give me Some(Seq(.....)).
For this kind of problem I recommend checking the Scaladoc and following a technique called type-tetris.
You need this:
def prependIfDefined(data: Option[A], previousElements: Seq[Option[B]]): Seq[Option[B]] =
data.fold(ifEmpty = Seq.empty[Option[B]])(getNewData) ++ previousElements
def getNewData(a: A): Seq[Option[B]] = ???
I wish to find a match within a List and return values dependant on the match. The CollectFirst works well for matching on the elements of the collection but in this case I want to match on the member swEl of the element rather than on the element itself.
abstract class CanvNode (var swElI: Either[CSplit, VistaT])
{
private[this] var _swEl: Either[CSplit, VistaT] = swElI
def member = _swEl
def member_= (value: Either[CSplit, VistaT] ){ _swEl = value; attach}
def attach: Unit
attach
def findVista(origV: VistaIn): Option[Tuple2[CanvNode,VistaT]] = member match
{
case Right(v) if (v == origV) => Option(this, v)
case _ => None
}
}
def nodes(): List[CanvNode] = topNode :: splits.map(i => List(i.n1, i.n2)).flatten
//Is there a better way of implementing this?
val temp: Option[Tuple2[CanvNode, VistaT]] =
nodes.map(i => i.findVista(origV)).collectFirst{case Some (r) => r}
Do I need a View on that, or will the collectFirst method ensure the collection is only created as needed?
It strikes me that this must be a fairly general pattern. Another example could be if one had a List member of the main List's elements and wanted to return the fourth element if it had one. Is there a standard method I can call? Failing that I can create the following:
implicit class TraversableOnceRichClass[A](n: TraversableOnce[A])
{
def findSome[T](f: (A) => Option[T]) = n.map(f(_)).collectFirst{case Some (r) => r}
}
And then I can replace the above with:
val temp: Option[Tuple2[CanvNode, VistaT]] =
nodes.findSome(i => i.findVista(origV))
This uses implicit classes from 2.10, for pre 2.10 use:
class TraversableOnceRichClass[A](n: TraversableOnce[A])
{
def findSome[T](f: (A) => Option[T]) = n.map(f(_)).collectFirst{case Some (r) => r}
}
implicit final def TraversableOnceRichClass[A](n: List[A]):
TraversableOnceRichClass[A] = new TraversableOnceRichClass(n)
As an introductory side node: The operation you're describing (return the first Some if one exists, and None otherwise) is the sum of a collection of Options under the "first" monoid instance for Option. So for example, with Scalaz 6:
scala> Stream(None, None, Some("a"), None, Some("b")).map(_.fst).asMA.sum
res0: scalaz.FirstOption[java.lang.String] = Some(a)
Alternatively you could put something like this in scope:
implicit def optionFirstMonoid[A] = new Monoid[Option[A]] {
val zero = None
def append(a: Option[A], b: => Option[A]) = a orElse b
}
And skip the .map(_.fst) part. Unfortunately neither of these approaches is appropriately lazy in Scalaz, so the entire stream will be evaluated (unlike Haskell, where mconcat . map (First . Just) $ [1..] is just fine, for example).
Edit: As a side note to this side note: apparently Scalaz does provide a sumr that's appropriately lazy (for streams—none of these approaches will work on a view). So for example you can write this:
Stream.from(1).map(Some(_).fst).sumr
And not wait forever for your answer, just like in the Haskell version.
But assuming that we're sticking with the standard library, instead of this:
n.map(f(_)).collectFirst{ case Some(r) => r }
I'd write the following, which is more or less equivalent, and arguably more idiomatic:
n.flatMap(f(_)).headOption
For example, suppose we have a list of integers.
val xs = List(1, 2, 3, 4, 5)
We can make this lazy and map a function with a side effect over it to show us when its elements are accessed:
val ys = xs.view.map { i => println(i); i }
Now we can flatMap an Option-returning function over the resulting collection and use headOption to (safely) return the first element, if it exists:
scala> ys.flatMap(i => if (i > 2) Some(i.toString) else None).headOption
1
2
3
res0: Option[java.lang.String] = Some(3)
So clearly this stops when we hit a non-empty value, as desired. And yes, you'll definitely need a view if your original collection is strict, since otherwise headOption (or collectFirst) can't reach back and stop the flatMap (or map) that precedes it.
In your case you can skip findVista and get even more concise with something like this:
val temp = nodes.view.flatMap(
node => node.right.toOption.filter(_ == origV).map(node -> _)
).headOption
Whether you find this clearer or just a mess is a matter of taste, of course.
Suppose I have
import scala.collection.immutable.TreeMap
val tree = new TreeMap[String, List[String]]
Now after above declaration, I want to assign key "k1" to List("foo", "bar")
and then how do i get or read back the key "k1" and also read back non-existent key "k2"?
what happens if I try to read non-existent key "k2" ?
The best way to "mutate" the immutable map is by referring to it in a variable (var as opposed to val):
var tree = TreeMap.empty[String, List[String]]
tree += ("k1" -> List("foo", "bar")) //a += b is sugar for "c = a + b; a = c"
It can be accessed directly using the apply method, where scala syntactic sugar kicks in so you can just access using parens:
val l = tree("k1") //equivalent to tree.apply("k1")
However, I rarely access maps like this because the method will throw a MatchError is the key is not present. Use get instead, which returns an Option[V] where V is the value-type:
val l = tree.get("k1") //returns Option[List[String]] = Some(List("foo", "bar"))
val m = tree.get("k2") //returns Option[List[String]] = None
In this case, the value returned for an absent key is None. What can I do with an optional result? Well, you can make use of methods map, flatMap, filter, collect and getOrElse. Try and avoid pattern-matching on it, or using the Option.get method directly!
For example:
val wordLen : List[Int] = tree.get("k1").map(l => l.map(_.length)) getOrElse Nil
EDIT: one way of building a Map without declaring it as a var, and assuming you are doing this by transforming some separate collection, is to do it via a fold. For example:
//coll is some collection class CC[A]
//f : A => (K, V)
val m = (TreeMap.empty[K, V] /: coll) { (tree, c) => tree + f(c) }
This may not be possible for your use case
I have a SQL database table with the following structure:
create table category_value (
category varchar(25),
property varchar(25)
);
I want to read this into a Scala Map[String, Set[String]] where each entry in the map is a set of all of the property values that are in the same category.
I would like to do it in a "functional" style with no mutable data (other than the database result set).
Following on the Clojure loop construct, here is what I have come up with:
def fillMap(statement: java.sql.Statement): Map[String, Set[String]] = {
val resultSet = statement.executeQuery("select category, property from category_value")
#tailrec
def loop(m: Map[String, Set[String]]): Map[String, Set[String]] = {
if (resultSet.next) {
val category = resultSet.getString("category")
val property = resultSet.getString("property")
loop(m + (category -> m.getOrElse(category, Set.empty)))
} else m
}
loop(Map.empty)
}
Is there a better way to do this, without using mutable data structures?
If you like, you could try something around
def fillMap(statement: java.sql.Statement): Map[String, Set[String]] = {
val resultSet = statement.executeQuery("select category, property from category_value")
Iterator.continually((resultSet, resultSet.next)).takeWhile(_._2).map(_._1).map{ res =>
val category = res.getString("category")
val property = res.getString("property")
(category, property)
}.toIterable.groupBy(_._1).mapValues(_.map(_._2).toSet)
}
Untested, because I don’t have a proper sql.Statement. And the groupBy part might need some more love to look nice.
Edit: Added the requested changes.
There are two parts to this problem.
Getting the data out of the database and into a list of rows.
I would use a Spring SimpleJdbcOperations for the database access, so that things at least appear functional, even though the ResultSet is being changed behind the scenes.
First, some a simple conversion to let us use a closure to map each row:
implicit def rowMapper[T<:AnyRef](func: (ResultSet)=>T) =
new ParameterizedRowMapper[T]{
override def mapRow(rs:ResultSet, row:Int):T = func(rs)
}
Then let's define a data structure to store the results. (You could use a tuple, but defining my own case class has advantage of being just a little bit clearer regarding the names of things.)
case class CategoryValue(category:String, property:String)
Now select from the database
val db:SimpleJdbcOperations = //get this somehow
val resultList:java.util.List[CategoryValue] =
db.query("select category, property from category_value",
{ rs:ResultSet => CategoryValue(rs.getString(1),rs.getString(2)) } )
Converting the data from a list of rows into the format that you actually want
import scala.collection.JavaConversions._
val result:Map[String,Set[String]] =
resultList.groupBy(_.category).mapValues(_.map(_.property).toSet)
(You can omit the type annotations. I've included them to make it clear what's going on.)
Builders are built for this purpose. Get one via the desired collection type companion, e.g. HashMap.newBuilder[String, Set[String]].
This solution is basically the same as my other solution, but it doesn't use Spring, and the logic for converting a ResultSet to some sort of list is simpler than Debilski's solution.
def streamFromResultSet[T](rs:ResultSet)(func: ResultSet => T):Stream[T] = {
if (rs.next())
func(rs) #:: streamFromResultSet(rs)(func)
else
rs.close()
Stream.empty
}
def fillMap(statement:java.sql.Statement):Map[String,Set[String]] = {
case class CategoryValue(category:String, property:String)
val resultSet = statement.executeQuery("""
select category, property from category_value
""")
val queryResult = streamFromResultSet(resultSet){rs =>
CategoryValue(rs.getString(1),rs.getString(2))
}
queryResult.groupBy(_.category).mapValues(_.map(_.property).toSet)
}
There is only one approach I can think of that does not include either mutable state or extensive copying*. It is actually a very basic technique I learnt in my first term studying CS. Here goes, abstracting from the database stuff:
def empty[K,V](k : K) : Option[V] = None
def add[K,V](m : K => Option[V])(k : K, v : V) : K => Option[V] = q => {
if ( k == q ) {
Some(v)
}
else {
m(q)
}
}
def build[K,V](input : TraversableOnce[(K,V)]) : K => Option[V] = {
input.foldLeft(empty[K,V]_)((m,i) => add(m)(i._1, i._2))
}
Usage example:
val map = build(List(("a",1),("b",2)))
println("a " + map("a"))
println("b " + map("b"))
println("c " + map("c"))
> a Some(1)
> b Some(2)
> c None
Of course, the resulting function does not have type Map (nor any of its benefits) and has linear lookup costs. I guess you could implement something in a similar way that mimicks simple search trees.
(*) I am talking concepts here. In reality, things like value sharing might enable e.g. mutable list constructions without memory overhead.
I want to create a class that takes string array as a constructor argument and has command line option values as members vals. Something like below, but I don't understand how the Bistate works.
import scalax.data._
import scalax.io.CommandLineParser
class TestCLI(arguments: Array[String]) extends CommandLineParser {
private val opt1Option = new Flag("p", "print") with AllowAll
private val opt2Option = new Flag("o", "out") with AllowAll
private val strOption = new StringOption("v", "value") with AllowAll
private val result = parse(arguments)
// true or false
val opt1 = result(opt1Option)
val opt2 = result(opt2Option)
val str = result(strOption)
}
Here are shorter alternatives to that pattern matching to get a boolean:
val opt1 = result(opt1Option).isInstanceOf[Positive[_]]
val opt2 = result(opt2Option).posValue.isDefined
The second one is probably better. The field posValue is an Option (there's negValue as well). The method isDefined from Option tells you whether it is a Some(x) or None.
I'm not personally familiar with Scalax or Bistate in particular, but just looking at the scaladocs, it looks like a left-right disjunction. Scala's main library has a monad very much like this (Either), so I'm surprised that they didn't just use the standard one.
In essence, Bistate and Either are a bit like Option, except their "None-equivalent" can contain a value. For example, if I were writing code using Either, I might do something like this:
def div(a: Int, b: Int) = if (b != 0) Left(a / b) else Right("Divide by zero")
div(4, 2) match {
case Left(x) => println("Result: " + x)
case Right(e) => Println("Error: " + e)
}
This would print "Result: 2". In this case, we're using Either to simulate an exception. We return an instance of Left which contains the value we want, unless that value cannot be computed for some reason, in which case we return an error message wrapped up inside an instance of Right.
So if I want to assign to variable boolean value of whether flag is found I have to do like below?
val opt1 = result(opt1Option) match {
case Positive(_) => true
case Negative(_) => false
}
Isn't there a way to write this common case with less code than that?