In the penultimate lecture of his Coursera course, Prof. Odersky offered the following for comprehension as the final step in a lovely case study:
def solutions(target: Int): Stream[Path] =
for {
pathSet <- pathSets
path <- pathSet
if path.endState contains target
} yield path
In an earlier lecture he drew some analogies between for comprehensions and SQL.
What I'm looking for is a way to yield only those paths that have a DISTINCT endState.
Is there a way to refer back from within a filter clause of the same comprehension to the items that have already been yielded?
Another approach might be to convert pathSets to a Map from endState to path before the for statement, then convert it back to a Stream before returning it. However, this would seem to lose the lazy computation benefits of using a Stream.
An earlier method from the same case study accomplished similar goals, but it was already a recursive function, while this one doesn't (seem to) need to be recursive.
It looks like I could use a mutable Set to track the endStates that get yielded, but that feels unsatisfying, since the course has successfully avoided using mutability so far.
Is there a way to refer back from within a filter clause of the same comprehension to the items that have already been yielded?
Your for comprehension desugars to something more or less like
pathSets flatMap {
pathSet => pathSet filter {
path => path.endState contains target
}
} map {path => path}
The last map with an identity function is your yield. I can't remember if the spec allows that map to be elided when it's an identity function.
Anyway, I hope this shows more clearly why there's no "reaching back" with that structure.
You can write a lazy, recursive distinctBy function
implicit class DistinctStream[T](s: Stream[T]) {
def distinctBy[V](f: T => V): Stream[T] = {
def distinctBy(remainder: Stream[T], seen:Set[V]): Stream[T] =
remainder match {
case head #:: tail =>
val value = f(head)
if (seen contains value) distinctBy(tail, seen)
else Stream.cons(head, distinctBy(tail, seen + value))
case empty => empty
}
distinctBy(s, Set())
}
}
And use it like so
def solutions(target: Int): Stream[Path] =
(for {
pathSet <- pathSets
path <- pathSet
if path.endState contains target
} yield path) distinctBy (_.endState)
Yeah, now there's recursion. But there already was because Stream's map, flatMap, and filter functions are all lazy recursive functions already.
Related
Why I'm getting "java.lang.IndexOutOfBoundsException: Index 0 out of bounds for length 0" while running next code??? :
val totalList = mutableListOf<MutableList<Int>>()
fun main() {
for (i in 0..15) {
for (j in 0..10) {
*some operations and calculations with **var element of type Int***
totalList[i].add(element)
}
}
}
I was thinking that in such case while iterating through 'j' it should add elements to mutableList[i], after this it should start adding elements to mutableList[i + 1] etc.... But instead I am recieving IndexOutOfBoundsException....
val totalList = mutableListOf<MutableList<Int>>()
All this does is create one list which is going to contain MutableList<Int> items. Right now, there's nothing in it (you've supplied no initial elements in the parentheses).
Skip forward a bit, and you do this:
totalList[0].add(element)
You're trying to get the first element of that empty list and add to it. But there is no first element (index 0) because the list is empty (length 0). That's what the error is telling you.
There's lots of ways to handle this - one thing you could do is create your lists up-front:
// create the 16 list items you want to access in the loop
// (the number is the item count, the lambda generates each item)
val totalList = MutableList(16) { mutableListOf<Int>() }
// then refer to that list's properties in your loop (no hardcoded 0..15)
for (i in totalList.indices) {
...
// guaranteed to exist since i is generated from the list's indices
totalList[i].add(element)
}
Or you could do it the way you are now, only using getOrElse to generate the empty list on-demand, when you try to get it but it doesn't exist:
for (i in 0..15) {
for (j in 0..10) {
// if the element at i doesn't exist, create a list instead, but also
// add it to the main list (see below)
totalList.getOrElse(i) {
mutableListOf<Int>().also { totalList.add(it) }
}.add(element)
}
}
Personally I don't really like this, you're using explicit indices but you're adding new list items to the end of the main list. That implicity requires that you're iterating over the list items in order - which you are here, but there's nothing enforcing that. If the order ever changed, it would break.
I'd prefer the first approach - create your structure of lists in advance, then iterate over those and fill them as necessary. Or you might want to consider arrays instead, since you have a fixed collection size you're "completing" by adding items to specific indices
Another approach (that I mentioned in the comments) is to create each list as a whole, complete thing, and then add that to your main list. This is generally how you do things in Kotlin - the standard library contains a lot of functional tools to allow you to chain operations together, transform things, and create immutable collections (which are safer and more explicit about whether they're meant to be changed or they're a fixed set of data).
for (i in 0..15) {
// map transforms each element of the range (each number) to an item,
// resulting in a list of items
val items = (0..10).map { j ->
// do whatever you're doing
// the last expression in the lambda is its resulting value,
// i.e. the item that ends up in the list
element
}
// now you have a complete list of items, add them to totalList
totalList.add(items)
}
(Or you could create the list directly with List(11) { j -> ... } but this is a more general example of transforming a bunch of things to a bunch of other things)
That example there is kinda half and half - you still have the imperative for loop going on as well. Writing it all using the same approach, you can get:
val totalList = (0..15).map { i ->
(0..10).map { j ->
// do stuff
element
}
}
I'd probably prefer the List(count) { i -> ... } approach for this, it's a better fit (this is a general example). That would also be better since you could use MutableList instead of List, if you really need them to be mutable (with the maps you could just chain .toMutableList() after the mapping function, as another step in the chain). Generally in Kotlin, collections are immutable by default, and this kind of approach is how you build them up without having to create a mutable list etc. and add items to it yourself
I was trying to generate all permutations of a list in Kotlin. There are a zillion examples out there which return a List<List<T>>, but my input list breaks those as they try to fit all the results in the output list. So I thought I would try to make a version returning Sequence<List<T>>...
fun <T> List<T>.allPermutations(): Sequence<List<T>> {
println("Permutations of $this")
if (isEmpty()) return emptySequence()
val list = this
return indices
.asSequence()
.flatMap { i ->
val elem = list[i]
(list - elem).allPermutations().map { perm -> perm + elem }
}
}
// Then try to print the first permutation
println((0..15).toList().allPermutations().first())
Problem is, Kotlin just seems to give up and asks for the complete contents of one of the nested sequences - so it never (or at least not for a very long time) ends up getting to the first element. (It will probably run out of memory before it gets there.)
I tried the same using Flow<T>, with the same outcome.
As far as I can tell, at no point does my code ask it to convert the sequence into a list, but it seems like something internal is doing it to me anyway, so how do I stop that?
As mentioned in the comments, you have handled the empty base case incorrectly. You should return a sequence of one empty list.
// an empty list has a single permutation - "itself"
if (isEmpty()) return sequenceOf(emptyList())
If you return an empty sequence, first will never find anything - your sequence is always empty - so it will keep evaluating the sequence until it ends, and throw an exception. (Try this with a smaller input like 0..2!)
I am trying to write more idiomatic Kotlin code and I am stuck with the best way to refactor this if condition. Basically when the condition if true (fragment is GenericActionsBottomSheetDialog instance in a list of Fragments) I return the funcion itself.
Here is what I had and how I refactored it. Is there better way to achieve it? After my refactoring it get worse:
Before refactor:
supportFragmentManager.fragments.iterator().forEach {
if (it is GenericActionsBottomSheetDialog)
return
After refactor:
supportFragmentManager.fragments.iterator().forEach { it ->
it.apply {
takeIf { it is GenericActionsBottomSheetDialog }?.apply { return }}}
If this forEach is the only thing in your current function (which it should IMO), you could get rid of the non-local return by using takeWhile instead:
supportFragmentManager.fragments
.takeWhile { it !is GenericActionsBottomSheetDialog }
.forEach {
// do stuff
}
/!\ be careful that this changes semantics if there is other stuff after the forEach in the same function declared with fun.
If you expect many fragments in the list, you could also use asSequence() before takeWhile so you don't create an intermediate list.
Here's one possibility, which separates the decision from the action:
if (supportFragmentManager.fragments.any{ it is GenericActionsBottomSheetDialog })
return
I think this approach makes the intent clearest. (It's also about the most efficient.)
any() simply checks each item in turn, stopping when it finds a match (or when it reaches the end of the list). Kotlin has many functions like this (inspired by functional programming languages) that use lambdas to operate on lists and other structures. They tend to be named for what they do, rather than how they do it — which makes code using them both short and easy to read. (You should be writing code for people to read, as much as for computers to execute!)
For completeness, here's another approach, which uses filterIsInstance():
if (supportFragmentManager.fragments
.filterIsInstance<GenericActionsBottomSheetDialog>)
.isNotEmpty())
return
There are bound to be many other ways. But I agree with the commenter that your ‘refactored’ approach, while using many more Kotlin functions, has little else to recommend it!
This is an opinion based question, and answers cannot be any different.
That being said: there is nothing wrong with if clauses. From what I can see from your current question, I'd leave it with an if.
Now, if you really do not want to use it, filter elements that are not of type GenericActionsBottomSheetDialog and apply whatever function you want on them (the part that is in your else clause, which we do not see).
EDIT:
In case you only want to check if the object of the GenericActionsBottomSheetDialog exists in the collection, you can perhaps do it like this:
val dialogExists = supportFragmentManager.fragments
.firstOrNull { it is GenericActionsBottomSheetDialog} != null
if (dialogExists) {
return
}
#gidds solution is IMO the most idiomatic one:
if (supportFragmentManager.fragments
.any { it is GenericActionsBottomSheetDialog }) return
I would like to add this solution eliminating the if:
supportFragmentManager.fragments
.firstOrNull { it is GenericActionsBottomSheetDialog }
?.run { return }
It's a matter of taste which one you pick, I prefer the first one.
I was wondering why you use the iterator? You could simply do:
supportFragmentManager.fragments.forEach {
I need to iterate 100's of ids in parallel and collect the result in list. I am trying to do it in following way
val context = newFixedThreadPoolContext(5, "custom pool")
val list = mutableListOf<String>()
ids.map {
val result:Deferred<String> = async(context) {
getResult(it)
}
//list.add(result.await()
}.mapNotNull(result -> list.add(result.await())
I am getting error at
mapNotNull(result -> list.add(result.await())
as await method is not available. Why await is not applicable at this place? Instead commented line
//list.add(result.await()
is working fine.
What is the best way to run this block in parallel using coroutine with custom thread pool?
Generally, you go in the right direction: you need to create a list of Deferred and then await() on them.
If this is exactly the code you are using then you did not return anything from your first map { } block, so you don't get a List<Deferred> as you expect, but List<Unit> (list of nothing). Just remove val result:Deferred<String> = - this way you won't assign result to a variable, but return it from the lambda. Also, there are two syntactic errors in the last line: you used () instead of {} and there is a missing closing parenthesis.
After these changes I believe your code will work, but still, it is pretty weird. You seem to mix two distinct approaches to transform a collection into another. One is using higher-order functions like map() and another is using a loop and adding to a list. You use both of them at the same time. I think the following code should do exactly what you need (thanks #Joffrey for improving it):
val list = ids.map {
async(context) {
getResult(it)
}
}.awaitAll().filterNotNull()
var take = R.curry(function take(count, o) {
return R.pick(R.take(count, R.keys(o)), o);
});
This function takes count keys from an object, in the order, in which they appear. I use it to limit a dataset which was grouped.
I understand that there are placeholder arguments, like R.__, but I can't wrap my head around this particular case.
This is possible thanks to R.converge, but I don't recommend going point-free in this case.
// take :: Number -> Object -> Object
var take = R.curryN(2,
R.converge(R.pick,
R.converge(R.take,
R.nthArg(0),
R.pipe(R.nthArg(1),
R.keys)),
R.nthArg(1)));
One thing to note is that the behaviour of this function is undefined since the order of the list returned by R.keys is undefined.
I agree with #davidchambers that it is probably better not to do this points-free. This solution is a bit cleaner than that one, but is still not to my mind as nice as your original:
// take :: Number -> Object -> Object
var take = R.converge(
R.pick,
R.useWith(R.take, R.identity, R.keys),
R.nthArg(1)
);
useWith and converge are similar in that they accept a number of function parameters and pass the result of calling all but the first one into that first one. The difference is that converge passes all the parameters it receives to each one, and useWith splits them up, passing one to each function. This is the first time I've seen a use for combining them, but it seems to make sense here.
That property ordering issue is supposed to be resolved in ES6 (final draft now out!) but it's still controversial.
Update
You mention that it will take some time to figure this out. This should help at least show how it's equivalent to your original function, if not how to derive it:
var take = R.converge(
R.pick,
R.useWith(R.take, R.identity, R.keys),
R.nthArg(1)
);
// definition of `converge`
(count, obj) => R.pick(R.useWith(R.take, R.identity, R.keys)(count, obj),
R.nthArg(1)(count, obj));
// definition of `nthArg`
(count, obj) => R.pick(R.useWith(R.take, R.identity, R.keys)(count, obj), obj);
// definition of `useWith`
(count, obj) => R.pick(R.take(R.identity(count), R.keys(obj)), obj);
// definition of `identity`
(count, obj) => R.pick(R.take(count, R.keys(obj)), obj);
Update 2
As of version 18, both converge and useWith have changed to become binary. Each takes a target function and a list of helper functions. That would change the above slightly to this:
// take :: Number -> Object -> Object
var take = R.converge(R.pick, [
R.useWith(R.take, [R.identity, R.keys]),
R.nthArg(1)
]);