How to create a List of Wildcard elements Scala - scala

I'm trying to write a function that returns a list (for querying purposes) that has some wildcard elements:
def createPattern(query: List[(String,String)]) = {
val l = List[(_,_,_,_,_,_,_)]
var iter = query
while(iter != null) {
val x = iter.head._1 match {
case "userId" => 0
case "userName" => 1
case "email" => 2
case "userPassword" => 3
case "creationDate" => 4
case "lastLoginDate" => 5
case "removed" => 6
}
l(x) = iter.head._2
iter = iter.tail
}
l
}
So, the user enters some query terms as a list. The function parses through these terms and inserts them into val l. The fields that the user doesn't specify are entered as wildcards.
Val l is causing me troubles. Am I going the right route or are there better ways to do this?
Thanks!

Gosh, where to start. I'd begin by getting an IDE (IntelliJ / Eclipse) which will tell you when you're writing nonsense and why.
Read up on how List works. It's an immutable linked list so your attempts to update by index are very misguided.
Don't use tuples - use case classes.
You shouldn't ever need to use null and I guess here you mean Nil.
Don't use var and while - use for-expression, or the relevant higher-order functions foreach, map etc.
Your code doesn't make much sense as it is, but it seems you're trying to return a 7-element list with the second element of each tuple in the input list mapped via a lookup to position in the output list.
To improve it... don't do that. What you're doing (as programmers have done since arrays were invented) is to use the index as a crude proxy for a Map from Int to whatever. What you want is an actual Map. I don't know what you want to do with it, but wouldn't it be nicer if it were from these key strings themselves, rather than by a number? If so, you can simplify your whole method to
def createPattern(query: List[(String,String)]) = query.toMap
at which point you should realise you probably don't need the method at all, since you can just use toMap at the call site.
If you insist on using an Int index, you could write
def createPattern(query: List[(String,String)]) = {
def intVal(x: String) = x match {
case "userId" => 0
case "userName" => 1
case "email" => 2
case "userPassword" => 3
case "creationDate" => 4
case "lastLoginDate" => 5
case "removed" => 6
}
val tuples = for ((key, value) <- query) yield (intVal(key), value)
tuples.toMap
}

Not sure what you want to do with the resulting list, but you can't create a List of wildcards like that.
What do you want to do with the resulting list, and what type should it be?
Here's how you might build something if you wanted the result to be a List[String], and if you wanted wildcards to be "*":
def createPattern(query:List[(String,String)]) = {
val wildcard = "*"
def orElseWildcard(key:String) = query.find(_._1 == key).getOrElse("",wildcard)._2
orElseWildcard("userID") ::
orElseWildcard("userName") ::
orElseWildcard("email") ::
orElseWildcard("userPassword") ::
orElseWildcard("creationDate") ::
orElseWildcard("lastLoginDate") ::
orElseWildcard("removed") ::
Nil
}

You're not using List, Tuple, iterator, or wild-cards correctly.
I'd take a different approach - maybe something like this:
case class Pattern ( valueMap:Map[String,String] ) {
def this( valueList:List[(String,String)] ) = this( valueList.toMap )
val Seq(
userId,userName,email,userPassword,creationDate,
lastLoginDate,removed
):Seq[Option[String]] = Seq( "userId", "userName",
"email", "userPassword", "creationDate", "lastLoginDate",
"removed" ).map( valueMap.get(_) )
}
Then you can do something like this:
scala> val pattern = new Pattern( List( "userId" -> "Fred" ) )
pattern: Pattern = Pattern(Map(userId -> Fred))
scala> pattern.email
res2: Option[String] = None
scala> pattern.userId
res3: Option[String] = Some(Fred)
, or just use the map directly.

Related

Working scala code using a var in a pure function. Is this possible without a var?

Is it possible (or even worthwhile) to try to write the below code block without a var? It works with a var. This is not for an interview, it's my first attempt at scala (came from java).
The problem: Fit people as close to the front of a theatre as possible, while keeping each request (eg. Jones, 4 tickets) in a single theatre section. The theatre sections, starting at the front, are sized 6, 6, 3, 5, 5... and so on. I'm trying to accomplish this by putting together all of the potential groups of ticket requests, and then choosing the best fitting group per section.
Here are the classes. A SeatingCombination is one possible combination of SeatingRequest (just the IDs) and the sum of their ticketCount(s):
class SeatingCombination(val idList: List[Int], val seatCount: Int){}
class SeatingRequest(val id: Int, val partyName: String, val ticketCount: Int){}
class TheatreSection(val sectionSize: Int, rowNumber: Int, sectionNumber: Int) {
def id: String = rowNumber.toString + "_"+ sectionNumber.toString;
}
By the time we get to the below function...
1.) all of the possible combinations of SeatingRequest are in a list of SeatingCombination and ordered by descending size.
2.) all of the TheatreSection are listed in order.
def getSeatingMap(groups: List[SeatingCombination], sections: List[TheatreSection]): HashMap[Int, TheatreSection] = {
var seatedMap = new HashMap[Int, TheatreSection]
for (sect <- sections) {
val bestFitOpt = groups.find(g => { g.seatCount <= sect.sectionSize && !isAnyListIdInMap(seatedMap, g.idList) })
bestFitOpt.filter(_.idList.size > 0).foreach(_.idList.foreach(seatedMap.update(_, sect)))
}
seatedMap
}
def isAnyListIdInMap(map: HashMap[Int, TheatreSection], list: List[Int]): Boolean = {
(for (id <- list) yield !map.get(id).isEmpty).reduce(_ || _)
}
I wrote the rest of the program without a var, but in this iterative section it seems impossible. Maybe with my implementation strategy it's impossible. From what else I've read, a var in a pure function is still functional. But it's been bothering me I can't think of how to remove the var, because my textbook told me to try to avoid them, and I don't know what I don't know.
You can use foldLeft to iterate on sections with a running state (and again, inside, on your state to add iteratively all the ids in a section):
sections.foldLeft(Map.empty[Int, TheatreSection]){
case (seatedMap, sect) =>
val bestFitOpt = groups.find(g => g.seatCount <= sect.sectionSize && !isAnyListIdInMap(seatedMap, g.idList))
bestFitOpt.
filter(_.idList.size > 0).toList. //convert option to list
flatMap(_.idList). // flatten list from option and idList
foldLeft(seatedMap)(_ + (_ -> sect))) // add all ids to the map with sect as value
}
By the way, you can simplify the second method using exists and map.contains:
def isAnyListIdInMap(map: HashMap[Int, TheatreSection], list: List[Int]): Boolean = {
list.exists(id => map.contains(id))
}
list.exists(predicate: Int => Boolean) is a Boolean which is true if the predicate is true for any element in list.
map.contains(key) checks if map is defined at key.
If you want to be even more concise, you don't need to give a name to the argument of the predicate:
list.exists(map.contains)
Simply changing var to val should do it :)
I think, you may be asking about getting rid of the mutable map, not of the var (it doesn't need to be var in your code).
Things like this are usually written recursively in scala or using foldLeft, like other answers suggest. Here is a recursive version:
#tailrec
def getSeatingMap(
groups: List[SeatingCombination],
sections: List[TheatreSection],
result: Map[Int, TheatreSection] = Map.empty): Map[Int, TheatreSection] = sections match {
case Nil => result
case head :: tail =>
val seated = groups
.iterator
.filter(_.idList.nonEmpty)
.filterNot(_.idList.find(result.contains).isDefined)
.find(_.seatCount <= head.sectionSize)
.fold(Nil)(_.idList.map(id => id -> sect))
getSeatingMap(groups, tail, result ++ seated)
}
btw, I don't think you need to test every id in list for presence in the map - should suffice to just look at the first one. You could also make it a bit more efficient, probably, if instead of checking the map every time to see if the group is already seated, you'd just drop it from the input list as soon as the section is assigned.
#tailrec
def selectGroup(
sect: TheatreSection,
groups: List[SeatingCombination],
result: List[SeatingCombination] = Nil
): (List[(Int, TheatreSection)], List[SeatingCombination]) = groups match {
case Nil => (Nil, result)
case head :: tail
if(head.idList.nonEmpty && head.seatCount <= sect.sectionSize) => (head.idList.map(_ -> sect), result.reverse ++ tail)
case head :: tail => selectGroup(sect, tail, head :: result)
}
and then in getSeatingMap:
...
case head :: tail =>
val(seated, remaining) => selectGroup(sect, groups)
getSeatingMap(remaining, tail, result ++ seated)
Here is how I was able to achieve without using the mutable.HashMap, the suggestion by the comment to use foldLeft was used to do it:
class SeatingCombination(val idList: List[Int], val seatCount: Int){}
class SeatingRequest(val id: Int, val partyName: String, val ticketCount: Int){}
class TheatreSection(val sectionSize: Int, rowNumber: Int, sectionNumber: Int) {
def id: String = rowNumber.toString + "_"+ sectionNumber.toString;
}
def getSeatingMap(groups: List[SeatingCombination], sections: List[TheatreSection]): Map[Int, TheatreSection] = {
sections.foldLeft(Map.empty[Int, TheatreSection]) { (m, sect) =>
val bestFitOpt = groups.find(g => {
g.seatCount <= sect.sectionSize && !isAnyListIdInMap(m, g.idList)
}).filter(_.idList.nonEmpty)
val newEntries = bestFitOpt.map(_.idList.map(_ -> sect)).getOrElse(List.empty)
m ++ newEntries
}
}
def isAnyListIdInMap(map: Map[Int, TheatreSection], list: List[Int]): Boolean = {
(for (id <- list) yield map.get(id).isDefined).reduce(_ || _)
}

Does this specific exercise lend itself well to a 'functional style' design pattern?

Say we have an array of one dimensional javascript objects contained in a file Array.json for which the key schema isn't known, that is the keys aren't known until the file is read.
Then we wish to output a CSV file with a header or first entry which is a comma delimited set of keys from all of the objects.
Each next line of the file should contain the comma separated values which correspond to each key from the file.
Array.json
[
abc:123,
xy:"yz",
s12:13,
],
...
[
abc:1
s:133,
]
A valid output:
abc,xy,s12,s
123,yz,13,
1,,,133
I'm teaching myself 'functional style' programming but I'm thinking that this problem doesn't lend itself well to a functional solution.
I believe that this problem requires some state to be kept for the output header and that subsequently each line depends on that header.
I'm looking to solve the problem in a single pass. My goals are efficiency for a large data set, minimal traversals, and if possible, parallelizability. If this isn't possible then can you give a proof or reasoning to explain why?
EDIT: Is there a way to solve the problem like this functionally?:
Say you pass through the array once, in some particular order. Then
from the start the header set looks like abc,xy,s12 for the first
object. With CSV entry 123,yz,13 . Then on the next object we add an
additional key to the header set so abc,xy,s12,s would be the header
and the CSV entry would be 1,,,133 . In the end we wouldn't need to
pass through the data set a second time. We could just append extra
commas to the result set. This is one way we could approach a single
pass....
Are there functional tools ( functions ) designed to solve problems like this, and what should I be considering? [ By functional tools I mean Monads,FlatMap, Filters, etc. ] . Alternatively, should I be considering things like Futures ?
Currently I've been trying to approach this using Java8, but am open to solutions from Scala, etc. Ideally I would be able to determine if Java8s' functional approach can solve the problem since that's the language I'm currently working in.
Since the csv output will change with every new line of input, you must hold that in memory before writing it out. If you consider creating an output text format from an internal representation of a csv file another "pass" over the data (the internal representation of the csv is practically a Map[String,List[String]] which you must traverse to convert it to text) then it's not possible to do this in a single pass.
If, however, this is acceptable, then you can use a Stream to read a single item from your json file, merge that into the csv file, and do this until the stream is empty.
Assuming, that the internal representation of the csv file is
trait CsvFile {
def merge(line: Map[String, String]): CsvFile
}
And you can represent a single item as
trait Item {
def asMap: Map[String, String]
}
You can implement it using foldLeft:
def toCsv(items: Stream[Item]): CsvFile =
items.foldLeft(CsvFile(Map()))((csv, item) => csv.merge(item.asMap))
or use recursion to get the same result
#tailrec def toCsv(items: Stream[Item], prevCsv: CsvFile): CsvFile =
items match {
case Stream.Empty => prevCsv
case item #:: rest =>
val newCsv = prevCsv.merge(item.asMap)
toCsv(rest, newCsv)
}
Note: Of course you don't have to create types for CsvFile or Item, you can use Map[String,List[String]] and Map[String,String] respectively
UPDATE:
As more detail was requested for the CsvFile trait/class, here's an example implementation:
case class CsvFile(lines: Map[String, List[String]], rowCount: Int = 0) {
def merge(line: Map[String, String]): CsvFile = {
val orig = lines.withDefaultValue(List.fill(rowCount)(""))
val current = line.withDefaultValue("")
val newLines = (lines.keySet ++ line.keySet) map {
k => (k, orig(k) :+ current(k))
}
CsvFile(newLines.toMap, rowCount + 1)
}
}
This could be one approach:
val arr = Array(Map("abc" -> 123, "xy" -> "yz", "s12" -> 13), Map("abc" -> 1, "s" -> 133))
val keys = arr.flatMap(_.keys).distinct // get the distinct keys for header
arr.map(x => keys.map(y => x.getOrElse(y,""))) // get an array of rows
Its completely OK to have state in functional programming. But having mutable state or mutating state is not allowed in functional programming.
Functional programming advocates creating new changed state instead of mutating the state in place.
So, its Ok to read and access state created in the program until and unless you are mutating or side effecting.
Coming to the point.
val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list.map { inner => inner.map { case (k, v) => k}}.flatten
list.map { inner => inner.map { case (k, v) => v}}.flatten
REPL
scala> val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list: List[List[(String, String)]] = List(List((abc,123), (xy,yz)), List((abc,1)))
scala> list.map { inner => inner.map { case (k, v) => k}}.flatten
res1: List[String] = List(abc, xy, abc)
scala> list.map { inner => inner.map { case (k, v) => v}}.flatten
res2: List[String] = List(123, yz, 1)
or use flatMap instead of map and flatten
val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list.flatMap { inner => inner.map { case (k, v) => k}}
list.flatMap { inner => inner.map { case (k, v) => v}}
In functional programming, mutable state is not allowed. But immutable states/values are fine.
Assuming that you have read your json file in to a value input:List[Map[String,String]], the codes below will solve your problem:
val input = List(Map("abc"->"123", "xy"->"yz" , "s12"->"13"), Map("abc"->"1", "s"->"33"))
val keys = input.map(_.keys).flatten.toSet
val keyvalues = input.map(kvs => keys.map(k => (k->kvs.getOrElse(k,""))).toMap)
val values = keyvalues.map(_.values)
val result = keys.mkString(",") + "\n" + values.map(_.mkString(",")).mkString("\n")

Retrieve tuple from string

I have the following input string:
"0.3215,Some(0.5123)"
I would like to retrieve the tuple (0.3215,Some(0.5123)) with: (BigDecimal,Option[BigDecimal]).
Here is one of the thing I tried so far:
"\\d+\\.\\d+,Some\\(\\d+\\.\\d+".r findFirstIn iData match {
case None => Map[BigDecimal, Option[BigDecimal]]()
case Some(s) => {
val oO = s.split(",Some\\(")
BigDecimal.valueOf(oO(0).toDouble) -> Option[BigDecimal](BigDecimal.valueOf(lSTmp2(1).toDouble))
}
}
Using a Map and transforming it into a tuple.
When I try directly the tuple I get an Equals or an Object.
Must miss something here...
Your code has several issues, but the big one seems to be that the case None side of the match returns a Map but the Some(s) side returns a Tuple2. Map and Tuple2 unify to their lowest-common-supertype, Equals, which is what you're seeing.
I think this is what you're trying to achieve?
val Pattern = "(\\d+\\.\\d+),Some\\((\\d+\\.\\d+)\\)".r
val s = "0.3215,Some(0.5123)"
s match {
case Pattern(a,b) => Map(BigDecimal(a) -> Some(BigDecimal(b)))
case _ => Map[BigDecimal, Option[BigDecimal]]()
}
// Map[BigDecimal,Option[BigDecimal]] = Map(0.3215 -> Some(0.5123))

Scala/Play/Squeryl Retrieve multiple params

I have the following url : http://localhost/api/books/?bookId=21&bookId=62?authorId=2
I want to retrieve all the bookId values with Scala and then use Squeryl to do a fetch in a the database.
I'm using the PlayFrameWork as the WebServer, so here's my code :
val params = request.queryString.map { case (k, v) => k -> v(0) } // Retrieve only one the first occurence of a param
So params.get("bookId") will only get the last value in the bookId params. e-g : 62.
To retrieve all my bookId params i tried this :
val params = request.queryString.map { case (k, v) => k -> v } so i can get a Seq[String], but what about the authorId which is not a Seq[String]? .
At the end i want to fetch the bookIds and authorId in my DB using Squeryl :
(a.author_id === params.get("authorId").?) and
(params.get("bookId").map(bookIds: Seq[String] => b.bookId in bookIds))
In my controller i get the params and open the DB connection :
val params = request.queryString.map { case (k, v) => k -> v(0) }
DB.withTransaction() { where(Library.whereHelper(params)}
In my model i use the queries :
def whereHelper(params : Map[String,String]) = {
(a.author_id === params.get("authorId").?) and
(params.get("bookId").map{bookIds: Seq[String] => b.bookId in bookIds})
}
Since bookIds is a list, i need to use the Seq[String]. There's a way to use request.queryString.map { case (k, v) => k -> v } for both a string (authorId) and a list of strings (bookIds) ?
Thanks,
If I really understand what you are trying to do, you want to know how to get the parameters from queryString. This is pretty simple and you can do the following at your controller:
def myAction = Action { request =>
// get all the values from parameter named bookId and
// transforming it to Long. Maybe you don't want the map
// and then you can just remove it.
val bookIds: Seq[Long] = request.queryString("bookId").map(_.toLong)
// Notice that now I'm using getQueryString which is a helper
// method to access a queryString parameter. It returns an
// Option[String] which we are mapping to a Option[Long].
// Again, if you don't need the mapping, just remove it.
val authorId: Option[Long] = request.getQueryString("authorId").map(_.toLong)
DB.withTransaction() { where(Library.whereHelper(authorId, bookIds) }
// Do something with the result
}
At your model you will have:
def whereHelper(authorId: Option[Long], booksId: List[Long]) = authorId match {
case Some(author_id) =>
(a.author_id === author_id) and
(b.bookId in bookIds)
case None =>
(b.bookId in bookIds)
}
I've left explicit types to help you understand what is happen. Now, since you have both values, you can just use the values at your query.
Edit after chat:
But, since you want to receive a params: Map[String, Seq[String]] at your models and is just having problems about how to get the authorId, here is what you can do:
def whereHelper(params: Map[String, Seq[String]]) = {
// Here I'm being defensive to the fact that maybe there is no
// "booksIds" key at the map. So, if there is not, an Seq.empty
// will be returned. map method will run only if there is something
// at the Seq.
val booksIds = params.getOrElse("booksIds", Seq.empty).map(_.toLong)
// The same defensive approach is being used here, and also getting
// the head as an Option, so if the Seq is empty, a None will be
// returned. Again, the map will be executed only if the Option
// is a Some, returning another Some with the value as a Long.
val authorId = params.getOrElse("authorId", Seq.empty).headOption
authorId.map(_.toLong) match {
case Some(author_id) =>
(a.author_id === author_id) and
(b.bookId in booksIds)
case None =>
(b.bookId in booksIds)
}
}
Of course, more parameters you have, more complicated this method will be.

scala : case class & copy() returning Any

could you help me concerning a basic question?
I have a list of "Rdv" (meetings) where Rdv is a case class having 3 fields storing phone numbers as Strings: telBureau, telPortable & TelPrivé.
I get this list from slick, via a native SQL query; this query fills the 3 phone number fields with either a String or "null"(a null object, not the "null" string).
I would like to remove these null fields, so I wrote this:
var l2:List[Rdv] = liste.list()
l2=l2.map( (w:Rdv) =>{
if ( w.telPrivé==null ) w.copy( telPrivé = "" )
})
but I get this error:
found:List[Any], required:List[Rdv]
so after the map I added ".asInstanceOf[List[Rdv]]" but then I get this error:
java.lang.ClassCastException: scala.runtime.BoxedUnit cannot be cast to metier.Objets$Rdv
It seems to ba a basic question, but I can't do that.
olivier.
Try this:
var l2: List[Rdv] = liste.list()
l2 = l2 map ((w: Rdv => if (w.telPrivé == null) w.copy( telPrivé = "" ) else w)
Could you try doing something like this?
val l2: List[Rdv] = liste list ()
val l3 = ls map{
case x # Rdv(_, null, _) => x.copy(telPrive = "")
case x => x
}
Honestly, should should make that field, if it's nullable to be an Option and then have a member function which you call defined such that:
case class Rdv(a: String, b: Option[String], c: String){
def realC = b getOrElse ""
}