How to merge two lists of tuples that simulates Chasles' Relation?
(a, b), (b, c) => (a, c)
Here is an example:
val l1 = List(("Dan", "b"), ("Dan","a"), ("Bart", "c"))
val l2 = List(("a", "1"), ("c", "1"), ("b", "3"), ("a", "2"))
Expected result would be:
val result = List(("Dan", "3"), ("Dan", "1"), ("Dan", "2"), ("Bart", "1"))
You basically want to consider all pairs of one element from the first list and one from the second and keep those where the "b" elements match.
In other words, we want to map over l1 and, inside that map, map over l2, meaning we consider all the pairs of an element from each list, so something like:
l1.map(x => l2.map(y => (x,y))
That's not quite right, though, since we now have a List[List[((String, String),(String,String))]]--we needed to flatmap:
l1.flatMap(x => l2.map(y => (x,y)))
Now we have to filter to keep just the pairs we want and tidy up:
l1.flatMap(x => l2.map(y => (x,y)))
.filter{ case ((_,y),(b,_)) => y == b }
.map {case ((x, _),(_,c)) => (x,c) }
which gives us
List((Dan,3), (Dan,1), (Dan,2), (Bart,1))
That was kind of an ugly mess, so and we can tidy it up a bit--let's filter l2 in our original flatmap and build the result there, so we don't have to juggle the tuple of tuples:
l1.map{ case (x,y) =>
l2.filter{ case (b, _) => y == b}
.map{ case (_, c) => (x, c)} }
This is one of those cases where it's easier to read a for comprehension:
for {
(x, y) <- l1
(b, c) <- l2
if y == b
} yield (x,c)
For each tuple in l1 you can filter l2 to select the tuples with the matching first element:
def join[A, B, C](l1: List[(A, B)], l2: List[(B, C)]): List[(A, C)] = {
for {
(key, subkey) <- l1
value <- l2.collect { case (`subkey`, value) => value }
} yield key -> value
}
You could also convert l2 into a Map beforehand for better selection performance:
def join[A, B, C](l1: List[(A, B)], l2: List[(B, C)]): List[(A, C)] = {
val valuesMap = l2.groupBy(_._1)
for {
(key, subkey) <- l1
(_, value) <- valuesMap.getOrElse(subkey, Nil)
} yield key -> value
}
Related
I am trying to reverse a map that has a String as the key and a set of numbers as its value
My goal is to create a list that contains a tuple of a number and a list of strings that had the same number in the value set
I have this so far:
def flipMap(toFlip: Map[String, Set[Int]]): List[(Int, List[String])] = {
toFlip.flatMap(_._2).map(x => (x, toFlip.keys.toList)).toList
}
but it is only assigning every String to every Int
val map = Map(
"A" -> Set(1,2),
"B" -> Set(2,3)
)
should produce:
List((1, List(A)), (2, List(A, B)), (3, List(B)))
but is producing:
List((1, List(A, B)), (2, List(A, B)), (3, List(A, B)))
This works to, but it's not exactly what you might need and you may need some conversions to get the exact data type you need:
toFlip.foldLeft(Map.empty[Int, Set[String]]) {
case (acc, (key, numbersSet)) =>
numbersSet.foldLeft(acc) {
(updatingMap, newNumber) =>
updatingMap.updatedWith(newNumber) {
case Some(existingSet) => Some(existingSet + key)
case None => Some(Set(key))
}
}
}
I used Set to avoid duplicate key insertions in the the inner List, and used Map for better look up instead of the outer List.
You can do something like this:
def flipMap(toFlip: Map[String, Set[Int]]): List[(Int, List[String])] =
toFlip
.toList
.flatMap {
case (key, values) =>
values.map(value => value -> key)
}.groupMap(_._1)(_._2)
.view
.mapValues(_.distinct)
.toList
Note, I personally would return a Map instead of a List
Or if you have cats in scope.
def flipMap(toFlip: Map[String, Set[Int]]): Map[Int, Set[String]] =
toFlip.view.flatMap {
case (key, values) =>
values.map(value => Map(value -> Set(key)))
}.toList.combineAll
// both scala2 & scala3
scala> map.flatten{ case(k, s) => s.map(v => (k, v)) }.groupMapReduce{ case(k, v) => v }{case(k, v) => List(k)}{ _ ++ _ }
val res0: Map[Int, List[String]] = Map(1 -> List(A), 2 -> List(A, B), 3 -> List(B))
// scala3 only
scala> map.flatten((k, s) => s.map(v => (k, v))).groupMapReduce((k, v) => v)((k, v) => List(k))( _ ++ _ )
val res1: Map[Int, List[String]] = Map(1 -> List(A), 2 -> List(A, B), 3 -> List(B))
Suppose I have val someMap = Map[String -> Map[String -> String]] defined as such:
val someMap =
Map(
("a1" -> Map( ("b1" -> "c1"), ("b2" -> "c2") ) ),
("a2" -> Map( ("b3" -> "c3"), ("b4" -> "c4") ) ),
("a3" -> Map( ("b5" -> "c5"), ("b6" -> "c6") ) )
)
and I would like to flatten it to something that looks like
List(
("a1","b1","c1"),("a1","b2","c2"),
("a2","b3","c3"),("a2","b4","c4"),
("a3","b5","c5"),("a3","b6","c6")
)
What is the most efficient way of doing this? I was thinking about creating some helper function that processes each (a_i -> Map(String,String)) key value pair and return
def helper(key: String, values: Map[String -> String]): (String,String,String)
= {val sublist = values.map(x => (key,x._1,x._2))
return sublist
}
then flatmap this function over someMap. But this seems somewhat unnecessary to my novice scala eyes, so I was wondering if there was a more efficient way to parse this Map.
No need to create helper function just write nested lambda:
val result = someMap.flatMap { case (k, v) => v.map { case (k1, v1) => (k, k1, v1) } }
Or
val y = someMap.flatMap(x => x._2.map(y => (x._1, y._1, y._2)))
Since you're asking about efficiency, the most efficient yet functional approach I can think of is using foldLeft and foldRight.
You need foldRight since :: constructs the immutable list in reverse.
someMap.foldRight(List.empty[(String, String, String)]) { case ((a, m), acc) =>
m.foldRight(acc) {
case ((b, c), acc) => (a, b, c) :: acc
}
}
Here, assuming Map.iterator.reverse is implemented efficiently, no intermediate collections are created.
Alternatively, you can use foldLeft and then reverse the result:
someMap.foldLeft(List.empty[(String, String, String)]) { case (acc, (a, m)) =>
m.foldLeft(acc) {
case (acc, (b, c)) => (a, b, c) :: acc
}
}.reverse
This way a single intermediate List is created, but you don't rely on the implementation of the reversed iterator (foldLeft uses forward iterator).
Note: one liners, such as someMap.flatMap(x => x._2.map(y => (x._1, y._1, y._2))) are less efficient, as, in addition to the temporary buffer to hold intermediate results of flatMap, they create and discard additional intermediate collections for each inner map.
UPD
Since there seems to be some confusion, I'll clarify what I mean. Here is an implementation of map, flatMap, foldLeft and foldRight from TraversibleLike:
def map[B, That](f: A => B)(implicit bf: CanBuildFrom[Repr, B, That]): That = {
def builder = { // extracted to keep method size under 35 bytes, so that it can be JIT-inlined
val b = bf(repr)
b.sizeHint(this)
b
}
val b = builder
for (x <- this) b += f(x)
b.result
}
def flatMap[B, That](f: A => GenTraversableOnce[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = {
def builder = bf(repr) // extracted to keep method size under 35 bytes, so that it can be JIT-inlined
val b = builder
for (x <- this) b ++= f(x).seq
b.result
}
def foldLeft[B](z: B)(op: (B, A) => B): B = {
var result = z
this foreach (x => result = op(result, x))
result
}
def foldRight[B](z: B)(op: (A, B) => B): B =
reversed.foldLeft(z)((x, y) => op(y, x))
It's clear that map and flatMap create intermediate buffer using corresponding builder, while foldLeft and foldRight reuse the same user-supplied accumulator object, and only use iterators.
I have a list of tuples, where the first element is a string and the second is a list of strings.
For example...(ignoring speech marks)
val p = List((a, List(x,y,z)), (b, List(x)), (c, List(y,z)))
My goal is to group this list into a map with the elements of the nested lists acting as keys.
val q = Map(x -> List(a,b), y -> List(a,c), z-> List(a,c))
My initial thought was to group by the second elements of p but this assigns the entire lists to the keys.
I'm a beginner to Scala so any advice is appreciated. Should I expect to be able to complete this with higher order functions or would for loops be useful here?
Thanks in advance :)
Here are two variants:
val p = List(("a", List("x","y","z")), ("b", List("x")), ("c", List("y","z")))
// 1. "Transducers"
p.flatMap{ case (k, v) => v.map { _ -> k } } // List((x,a), (y,a), (z,a), (x,b), (y,c), (z,c))
.groupBy(_._1) // Map(z -> List((z,a), (z,c)), y -> List((y,a), (y,c)), x -> List((x,a), (x,b)))
.mapValues(_.map(_._2)) // Map(z -> List(a, c), y -> List(a, c), x -> List(a, b))
// 2. For-loop
var res = Map[String, List[String]]()
for ( (k, vs) <- p; v <- vs) {
res += v -> k :: res.getOrElse(v, List())
}
res // Map(x -> List(b, a), y -> List(c, a), z -> List(c, a))
// Note, values of `res` are inverted,
// because the efficient "cons" operator (::) was used to add values to the lists
// you can revert the lists afterwards as this:
res.mapValues(_.reverse) // Map(x -> List(a, b), y -> List(a, c), z -> List(a, c))
Second variant is more performant, because no intermediate collections are created, but it also could be considered "less idiomatic", as mutable variable res is used. However, it's totally fine to use mutable approach inside a private method.
UPD. Per #LuisMiguelMejíaSuárez's suggestions:
In (1), since scala 2.13, groupBy followed by mapValues can be replaced by groupMap, so the whole chain becomes:
p.flatMap{ case (k, v) => v.map { _ -> k } }
.groupMap(_._1)(_._2)
Another functional variant without intermediate collections can be achieved using foldLeft:
p.foldLeft(Map[String, List[String]]()) {
case (acc, (k, vs)) =>
vs.foldLeft(acc) { (acc1, v) =>
acc1 + (v -> (k :: acc1.getOrElse(v, List())))
}
}
Or slightly more efficiently with updatedWith (scala 2.13):
p.foldLeft(Map[String, List[String]]()) {
case (acc, (k, vs)) =>
vs.foldLeft(acc) { (acc1, v) =>
acc1.updatedWith(v) {
case Some(list) => Some(k :: list)
case None => Some(List(k))
}
}
}
... or same thing slightly shorter:
p.foldLeft(Map[String, List[String]]()) {
case (acc, (k, vs)) =>
vs.foldLeft(acc) { (acc1, v) =>
acc1.updatedWith(v)(_.map(k :: _).orElse(Some(List(k))))
}
}
Overall, I'd suggest either using foldLeft variant (most performant and functional), or the first, groupMap variant (shorter, and arguably more readable, but less performant), depending on your goals.
Your input list p is one step away from being a Map. From there all you need is a general purpose Map inverter.
import scala.collection.generic.IsIterableOnce
import scala.collection.Factory
// from Map[K,C[V]] to Map[V,C[K]] (Scala 2.13.x)
implicit class MapInverter[K,V,C[_]](m: Map[K,C[V]]) {
def invert(implicit iio: IsIterableOnce[C[V]] {type A = V}
, fac: Factory[K,C[K]]): Map[V,C[K]] =
m.foldLeft(Map.empty[V, List[K]]) {
case (acc, (k, vs)) =>
iio(vs).iterator.foldLeft(acc) {
case (a, v) =>
a + (v -> (k::a.getOrElse(v,Nil)))
}
}.map{case (k,v) => k -> v.to(fac)}
}
usage:
val p = List(("a", List("x","y","z")), ("b", List("x")), ("c", List("y","z")))
val q = p.toMap.invert
//Map(x -> List(b, a), y -> List(c, a), z -> List(c, a))
Assume we have the following lists of different size:
val list1 = ("a", "b", "c")
val list2 = ("x", "y")
Now I want to merge these 2 lists and create a new list with the string elements being concatenated:
val desiredResult = ("ax", "by", "c")
I tried
val wrongResult = (list1, list2).zipped map (_ + _)
as proposed here, but this doesn't work as intended, because zip discards those elements of the longer list that can't be matched.
How can I solve this problem? Is there a way to zip the lists and give a "default element" (like the empty string in this case) if one list is longer?
The method you are looking for is .zipAll:
scala> val list1 = List("a", "b", "c")
list1: List[String] = List(a, b, c)
scala> val list2 = List("x", "y")
list2: List[String] = List(x, y)
scala> list1.zipAll(list2, "", "")
res0: List[(String, String)] = List((a,x), (b,y), (c,""))
.zipAll takes 3 arguments:
the iterable to zip with
the default value if this (the collection .zipAll is called on) is shorter
the default value if the other collection is shorter
The API-based zipAll is the way to go, yet you can implement it (as an exercise) for instance as follows,
implicit class OpsSeq[A,B](val xs: Seq[A]) extends AnyVal {
def zipAll2(ys: Seq[B], xDefault: A, yDefault: B) = {
val xs2 = xs ++ Seq.fill(ys.size-xs.size)(xDefault)
val ys2 = ys ++ Seq.fill(xs.size-ys.size)(yDefault)
xs2.zip(ys2)
}
}
Hence for instance
Seq(1,2).zipAll2(Seq(3,4,5),10,20)
List((1,3), (2,4), (10,5))
and
list1.zipAll2(list2, "", "")
List((a,x), (b,y), (c,""))
A recursive version,
def zipAll3[A,B](xs: Seq[A], ys: Seq[B], xd: A, yd: B): Seq[(A,B)] = {
(xs,ys) match {
case (Seq(), Seq()) => Seq()
case (x +: xss, Seq()) => (x,yd) +: zipAll3(xss, Seq(), xd, yd)
case (Seq(), y +: yss) => (xd,y) +: zipAll3(Seq(), yss, xd, yd)
case (x +: xss, y +: yss) => (x,y) +: zipAll3(xss, yss, xd, yd)
}
}
with default xd and default yd values.
What's the idiomatic way to call map over a collection producing 0 or 1 result per entry?
Suppose I have:
val data = Array("A", "x:y", "d:e")
What I'd like as a result is:
val target = Array(("x", "y"), ("d", "e"))
(drop anything without a colon, split on colon and return tuples)
So in theory I think I want to do something like:
val attempt1 = data.map( arg => {
arg.split(":", 2) match {
case Array(l,r) => (l, r)
case _ => (None, None)
}
}).filter( _._1 != None )
What I'd like to do is avoid the need for the any-case and get rid of the filter.
I could do this by pre-filtering (but then I have to test the regex twice):
val attempt2 = data.filter( arg.contains(":") ).map( arg => {
val Array(l,r) = arg.split(":", 2)
(l,r)
})
Last, I could use Some/None and flatMap...which does get rid of the need to filter, but is it what most scala programmers would expect?
val attempt3 = data.flatMap( arg => {
arg.split(":", 2) match {
case Array(l,r) => Some((l,r))
case _ => None
}
})
It seems to me like there'd be an idiomatic way to do this in Scala, is there?
With a Regex extractor and collect :-)
scala> val R = "(.+):(.+)".r
R: scala.util.matching.Regex = (.+):(.+)
scala> Array("A", "x:y", "d:e") collect {
| case R(a, b) => (a, b)
| }
res0: Array[(String, String)] = Array((x,y), (d,e))
Edit:
If you want a map, you can do:
scala> val x: Map[String, String] = Array("A", "x:y", "d:e").collect { case R(a, b) => (a, b) }.toMap
x: Map[String,String] = Map(x -> y, d -> e)
If performance is a concern, you can use collection.breakOut as shown below to avoid creation of an intermediate array:
scala> val x: Map[String, String] = Array("A", "x:y", "d:e").collect { case R(a, b) => (a, b) } (collection.breakOut)
x: Map[String,String] = Map(x -> y, d -> e)