In my application I have use some "data" ValueCell (something like 20) and I would like to create a ValueCell which would be used to detect if any of my "data" ValueCell was updated . So I would like this cell to change whenever one of the other cells are changed.
Here is a simple code example
class StringFilter {
val referenceList = "foo"::"bar"::"scala"::"lift"::Nil
val length = ValueCell[Int](3)
val content = ValueCell[String]("")
//Here I put some functions to update length or prefix on my webpage
def filter(s:String):Boolean = (s.length==length.get)&&(s.contains(content.get))
val changed =ValueCell[???](???)
val results= changed.lift(referenceList.filter)
}
What should I put instead of ???? I am also open to solutions which are not using ValueCells, even if I will in the end need some cells because I have to use WiringUI.
Edit: lengthand contentdon't need to be cells but they need to be settable
Edit: After some more research I came to an idea: implement a case class like SeqCellbut which would not take a type for the Cells in parameter, and for an arbitrary number of cells. Is it possible?
Here is the implementation of SeqCell:
final case class SeqCell[T](cells: Cell[T]*) extends Cell[Seq[T]] {
cells.foreach(_.addDependent(this))
/**
* The cell's value and most recent change time
*/
def currentValue: (Seq[T], Long) = {
val tcv = cells.map(_.currentValue)
tcv.map(_._1) -> tcv.foldLeft(0L)((max, c) => if (max > c._2) max else c._2)
}
/**
* If the predicate cell changes, the Dependent will be notified
*/
def predicateChanged(which: Cell[_]): Unit = notifyDependents()
}
Edit: In scala Cellis not covariant, so it seems like I won't be able to make a SeqCell out of my multiple typed cells. I would really appreciate a global solution for an arbitrary number of cells.
Check out FuncCell. It's just another cell that will determine its value as a function of one or more other cells. The link I gave is the companion object which has apply methods for 1-5 cells, corresponding to the existing FuncCell1 .. FuncCell5 implementations. When one of those cells changes value, the FuncCell will update its own value- you would then hook up the WiringUI with your FuncCell.
Please forgive any syntax errors, I don't have an IDE open to check myself...
val changed: Cell[List[String]] = FuncCell(length, content){(len,con) =>
def filter(s: String) = (s.length == len) && (s.contains(con))
referenceList.filter(filter _)
}
If that's right, then changed is now a Cell whose value will reflect the result of calling referenceList.filter
In response to your edit regarding the SeqCell, I can think of two solutions:
1) Use Any as the type parameter in the SeqCell
val cell1: ValueCell[Int] = ...
val cell2: ValueCell[String] = ...
val cell3: ValueCell[Stuff] = ...
...
val combined: SeqCell[Any] = SeqCell(cell1, cell2, cell3, ...)
val results = FuncCell(combined){ seq: Seq[Any] => ... }
2) Combine the intermediate cells into tuples so that you can use the existing FuncCell implementations.
val intermediate1: Cell[(Int,String)] =
FuncCell(cell1,cell2){(a:Int, b:String) => a -> b}
val results =
FuncCell(intermediate1, cell3){(i: (Int, String), s: Stuff) => ...}
Related
I'm new to Scala and attempting to do some data analysis.
I have a CSV files with a few headers - lets say item no., item type, month, items sold.
I have made an Item class with the fields of the headers.
I split the CSV into a list with each iteration of the list being a row of the CSV file being represented by the Item class.
I am attempting to make a method that will create maps based off of the parameter I send in. For example if I want to group the items sold by month, or by item type. However I am struggling to send the Item.field into a method.
F.e what I am attempting is something like:
makemaps(Item.month);
makemaps(Item.itemtype);
def makemaps(Item.field):
if (item.field==Item.month){}
else (if item.field==Item.itemType){}
However my logic for this appears to be wrong. Any ideas?
def makeMap[T](items: Iterable[Item])(extractKey: Item => T): Map[T, Iterable[Item]] =
items.groupBy(extractKey)
So given this example Item class:
case class Item(month: String, itemType: String, quantity: Int, description: String)
You could have (I believe the type ascriptions are mandatory):
val byMonth = makeMap[String](items)(_.month)
val byType = makeMap[String](items)(_.itemType)
val byQuantity = makeMap[Int](items)(_.quantity)
val byDescription = makeMap[String](items)(_.description)
Note that _.month, for instance, creates a function taking an Item which results in the String contained in the month field (simplifying a little).
You could, if so inclined, save the functions used for extracting keys in the companion object:
object Item {
val month: Item => String = _.month
val itemType: Item => String = _.itemType
val quantity: Item => Int = _.quantity
val description: Item => String = _.description
// Allows us to determine if using a predefined extractor or using an ad hoc one
val extractors: Set[Item => Any] = Set(month, itemType, quantity, description)
}
Then you can pass those around like so:
val byMonth = makeMap[String](items)(Item.month)
The only real change semantically is that you explicitly avoid possible extra construction of lambdas at runtime, at the cost of having the lambdas stick around in memory the whole time. A fringe benefit is that you might be able to cache the maps by extractor if you're sure that the source Items never change: for lambdas, equality is reference equality. This might be particularly useful if you have some class representing the collection of Items as opposed to just using a standard collection, like so:
object Items {
def makeMap[T](items: Iterable[Item])(extractKey: Item => T): Map[T,
Iterable[Item]] =
items.groupBy(extractKey)
}
class Items(val underlying: immutable.Seq[Item]) {
def makeMap[T](extractKey: Item => T): Map[T, Iterable[Item]] =
if (Item.extractors.contains(extractKey)) {
if (extractKey == Item.month) groupedByMonth.asInstanceOf[Map[T, Iterable[Item]]]
else if (extractKey == Item.itemType) groupedByItemType.asInstanceOf[Map[T, Iterable[Item]]]
else if (extractKey == Item.quantity) groupedByQuantity.asInstanceOf[Map[T, Iterable[Item]]]
else if (extractKey == Item.description) groupedByDescription.asInstanceOf[Map[T, Iterable[Item]]]
else throw new AssertionError("Shouldn't happen!")
} else {
Items.makeMap(underlying)(extractKey)
}
lazy val groupedByMonth = Items.makeMap[String](underlying)(Item.month)
lazy val groupedByItemType = Items.makeMap[String](underlying)(Item.itemType)
lazy val groupedByQuantity = Items.makeMap[Int](underlying)(Item.quantity)
lazy val groupedByDescription = Items.makeMap[String](underlying)(Item.description)
}
(that is almost certainly a personal record for asInstanceOfs in a small block of code... I'm not sure if I should be proud or ashamed of this snippet)
I want to build an instance of a class Something by calling the function foo on this calss for every element in a list. e.g.
val list = List(1,2,3)
should result in a call with the same effect as:
val something = somethingBuilder.foo(1).foo(2).foo(3)
Is there a way to perform this?
As I understand your question, you can do :
val list = List(1,2,3)
val something = somethingBuilder
list.foreach(something.foo)
I am assuming that you care for the returned value of your builder call. Then following code will print Builder(6):
val list = List(1,2,3)
case class Builder(val i: Int){
def build(j: Int) = Builder(i+j)
}
val finalBuilder = list.foldLeft(Builder(0))(_.build(_))
println(finalBuilder)
If you only care for the side effect, maybe Rafael's solution is more adequate (although using the foldLeft will of course also trigger the side-effect).
This can be one of the solution.
val lst = List(1,2,3,4,5)
class Builder(val i: Int){
def Foo() {
println("Value is initialized: " + i)
}
}
lst.map( a => new Builder(a).Foo())
But the disclaimer, it does generates the list of empty lists as a side effect
print(lst.map( a => new Builder(a).Foo()))
This question isn't programming language specific (the more general the better), but I'm working in Scala (not necessarily on the JVM). Is there a means to reference count by call location, not the number of total calls? In particular, it would be great to be able to detect if a given method is called from more than one call location.
I think I can fake it to some extent by doing a reference equality check with a function, but this could be abused easily by having a global-ish token, or even calling the function multiple times in the same scope:
sealed case class Token();
class MyClass[A] {
var tokenOpt: Option[Token] = None
def callMeFromOnePlace(x: A)(implicit tk: Token) = {
tokenOpt match {
case Some(priorTk) => if (priorTk ne tk) throw new IllegalStateException("")
case None => tokenOpt = Some(tk)
}
// Do some work ...
}
}
Then this should work fine:
val myObj = new MyClass[Int]
val myIntList = List(1,2,3)
implicit val token = Token()
myIntList.map(ii => myObj.callMeFromOnePlace(ii))
But unfortunately, so would this:
val myObj = new MyClass[Int]
implicit val token = Token()
myObj.callMeFromOnePlace(1)
myObj.callMeFromOnePlace(1) //oops, want this to fail
When you are talking about call location, it can be represented by a call stack trace. Here is a simple example:
// keep track of calls here (you can use immutable style if you want)
var callCounts = Map.empty[Int, Int]
def f(): Unit = {
// calculate call stack trace hashCode for more efficient storage
// .toSeq makes WrappedArray, that knows how to properly calculate .hashCode()
val hashCode = new RuntimeException().getStackTrace.toSeq.hashCode()
val callLocation = hashCode
callCounts += (callLocation -> (callCounts.getOrElse(callLocation, 0) + 1))
}
List(1,2,3).foreach(_ =>
f()
)
f()
f()
println(callCounts) // Map(75070239 -> 3, 900408638 -> 1, -1658734417 -> 1)
I am not completely clear what you want to do but for your //oops.. example to fail you need just check the PriorTk is not None. (do note that it is not a thread safe solution )
For completeness, enforcing these kind of constraints from a type system perspective requires linear types.
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?