Recursive functions for sequences in F# - recursion

Rather trivial question, but a quick google search didn't give me the answer.
What is a standard way to write a recursive functions for sequences? For lists you would do pattern matching with empty list and head+tail pattern, what is the equivalent for sequences?

There is no standard way to do so since you rarely write recursive functions for sequences.
You should look at a variety of high-order functions in Seq module. They are often more than adequate, so you don't have to write recursive functions by yourself.
To generate sequences recursively, sequence expression is a simple and intuitive way to go:
let rec allFiles dir =
seq { yield! Directory.GetFiles dir
for d in Directory.GetDirectories dir do
yield! allFiles d }
If you have to break down a sequence and manipulate it recursively, you are doing it wrong. You should either manipulate List or LazyList from F# PowerPack, and convert results back to sequences.

There is no way to get the tail of a sequence because it has not been evaluated (and could in theory be infinite), so you cannot pass the tail into a function recursively. You would just use Seq.iter or yield! to go through the sequence.

Related

Recursive functions and pattern matching in ocaml

The following code snippet comes from the official OCaml website:
# let rec compress = function
| a :: (b :: _ as t) -> if a = b then compress t else a :: compress t
| smaller -> smaller;;
val compress : 'a list -> 'a list = <fun>
The above function 'compresses' a list with consecutive, duplicative elements, e.g. :
# compress ["a";"a";"a";"a";"b";"c";"c";"a";"a";"d";"e";"e";"e";"e"];;
- : string list = ["a"; "b"; "c"; "a"; "d"; "e"]
I'm having a devil of a time understanding the logic of the above code. I'm used to coding imperatively, so this recursive, functional approach, combined with OCamls laconic - but obscure - syntax is causing me to struggle.
For example, where is the base case? Is it smaller -> smaller? I know smaller is a variable, or an identifier, but what is it returning (is returning even the right term in OCaml for what's happening here)?
I know that lists in OCaml are singly linked, so I'm also wondering if a new list is being generated, or if elements of the existed list are being cut? Since OCaml is functional, I'm inclined to think that lists are not mutable - is that correct? If you want to change a list, you essentially need to generate a new list with the elements you're seeking to add (or with the elements you're seeking to excise absent). Is this a correct understanding?
Yes, the base case is this:
| smaller -> smaller
The first pattern of the match expression matches any list of length 2 or greater. (It would be good to make sure you see why this is the case.)
Since OCaml matches patterns in order, the base case matches lists of lengths 0 and 1. That's why the programmer chose the name smaller. They were thinking "this is some smaller list".
The parts of a match statement look like this in general:
| pattern -> result
Any names in the pattern are bound to parts of the value matched against the pattern (as you say). So smaller is bound to the whole list. So in sum, the second part of the match says that if the list is of length 0 or 1, the result should just be the list itself.
Lists in OCaml are immutable, so it's not possible for the result of the function to be a modified version of the list. The result is a new list, unless the list is already a short list (of length 0 or 1).
So, what you say about the immutability of OCaml lists is exactly correct.

Recursively run through a vector in Clojure

I'm just starting to play with Clojure.
How do I run through a vector of items?
My naive recursive function would have a form like the classic map eg.
(defn map [f xs] (
(if (= xs [])
[]
(cons (f (first xs)) (map f (rest xs))
)
))
The thing is I can't find any examples of this kind of code on the web. I find a lot of examples using built-in sequence traversing functions like for, map and loop. But no-one doing the raw recursive version.
Is that because you SHOULDN'T do this kind of thing in Clojure? (eg. because it uses lower-level Java primitives that don't have tail-call optimisation or something?)?
When you say "run through a vector" this is quite vague; as Clojure is a lisp and thus specializes in sequence analysis and manipulation, the beauty of using this language is that you don't think in terms "run through a vector and then do something with each element," instead you'd more idiomatically say "pull this out of a vector" or "transform this vector into X" or "I want this vector to give me X".
It is because of this type of perspective in lisp languages that you will see so many examples and production code that doesn't just loop/recur through a vector but rather specifically goes after what is wanted in a short, idiomatic way. Using simple functions like reduce map filter for into and others allow you to elegantly move over a sequence such as a vector while simultaneously doing what you want with the contents. In most other languages, this would be at least 2 different parts: the loop, and then the actual logic to do what you want.
You'll often find that if you think about sequences using the more imperative idea you get with languages like C, C++, Java, etc, that your code is about 4x longer (at least) than it would otherwise be if you first thought about your plan in a more functional approach.
Clojure re-uses stack frames only with tail-recurstion and only when you use the explicit recur call. Everything else will be stack consuming. The above map example is not tail recursive because the cons happens after the recursive call so it can't be TCO'd in any language. If you switch it to use the continuation passing style and use an explicit call to recur instead of map then you should be good to go.

FP language: removing empty lists from a list

Suppose I've got the sequence <1,<>,2,<>>.
How could I go about deleting the empty lists and get <1,2>?
Ideally, without using recursion or iteration.
Thanks.
PS: I'm using FP programming language
What you're probably looking for is filter. It takes a predicate and takes out elements not satisfying it.
Since the FP language has a weird syntax and I couldn't find any documentation , I can't provide an implementation of filter. But in general, it can be implemented using a fold -- which is just the inserts from the link you provided.
Here's what I mean (in Haskell):
filter p list = foldr (\x xs -> if p x then x:xs else xs) [] list¹
If you don't get this, look here. When you have written filter, you can call it like
newList = filter notEmpty theList
(where nonEmpty is a predicate or lambda). Oh, and of course this only hides recursion by using another function; at some point, you have to recurse.
¹The : operator in Haskell is list consing (appending an element to the head), not function application.

Choosing unique items from a list, using recursion

As follow up to yesterday's question Erlang: choosing unique items from a list, using recursion
In Erlang, say I wanted choose all unique items from a given list, e.g.
List = [foo, bar, buzz, foo].
and I had used your code examples resulting in
NewList = [bar, buzz].
How would I further manipulate NewList in Erlang?
For example, say I not only wanted to choose all unique items from List, but also count the total number of characters of all resulting items from NewList?
In functional programming we have patterns that occur so frequently they deserve their own names and support functions. Two of the most widely used ones are map and fold (sometimes reduce). These two form basic building blocks for list manipulation, often obviating the need to write dedicated recursive functions.
Map
The map function iterates over a list in order, generating a new list where each element is the result of applying a function to the corresponding element in the original list. Here's how a typical map might be implemented:
map(Fun, [H|T]) -> % recursive case
[Fun(H)|map(Fun, T)];
map(_Fun, []) -> % base case
[].
This is a perfect introductory example to recursive functions; roughly speaking, the function clauses are either recursive cases (result in a call to iself with a smaller problem instance) or base cases (no recursive calls made).
So how do you use map? Notice that the first argument, Fun, is supposed to be a function. In Erlang, it's possible to declare anonymous functions (sometimes called lambdas) inline. For example, to square each number in a list, generating a list of squares:
map(fun(X) -> X*X end, [1,2,3]). % => [1,4,9]
This is an example of Higher-order programming.
Note that map is part of the Erlang standard library as lists:map/2.
Fold
Whereas map creates a 1:1 element mapping between one list and another, the purpose of fold is to apply some function to each element of a list while accumulating a single result, such as a sum. The right fold (it helps to think of it as "going to the right") might look like so:
foldr(Fun, Acc, [H|T]) -> % recursive case
foldr(Fun, Fun(H, Acc), T);
foldr(_Fun, Acc, []) -> % base case
Acc.
Using this function, we can sum the elements of a list:
foldr(fun(X, Sum) -> Sum + X, 0, [1,2,3,4,5]). %% => 15
Note that foldr and foldl are both part of the Erlang standard library, in the lists module.
While it may not be immediately obvious, a very large class of common list-manipulation problems can be solved using map and fold alone.
Thinking recursively
Writing recursive algorithms might seem daunting at first, but as you get used to it, it turns out to be quite natural. When encountering a problem, you should identify two things:
How can I decompose the problem into smaller instances? In order for recursion to be useful, the recursive call must take a smaller problem as its argument, or the function will never terminate.
What's the base case, i.e. the termination criterion?
As for 1), consider the problem of counting the elements of a list. How could this possibly be decomposed into smaller subproblems? Well, think of it this way: Given a non-empty list whose first element (head) is X and whose remainder (tail) is Y, its length is 1 + the length of Y. Since Y is smaller than the list [X|Y], we've successfully reduced the problem.
Continuing the list example, when do we stop? Well, eventually, the tail will be empty. We fall back to the base case, which is the definition that the length of the empty list is zero. You'll find that writing function clauses for the various cases is very much like writing definitions for a dictionary:
%% Definition:
%% The length of a list whose head is H and whose tail is T is
%% 1 + the length of T.
length([H|T]) ->
1 + length(T);
%% Definition: The length of the empty list ([]) is zero.
length([]) ->
0.
You could use a fold to recurse over the resulting list. For simplicity I turned your atoms into strings (you could do this with list_to_atom/1):
1> NewList = ["bar", "buzz"].
["bar","buzz"]
2> L = lists:foldl(fun (W, Acc) -> [{W, length(W)}|Acc] end, [], NewList).
[{"buzz",4},{"bar",3}]
This returns a proplist you can access like so:
3> proplists:get_value("buzz", L).
4
If you want to build the recursion yourself for didactic purposes instead of using lists:
count_char_in_list([], Count) ->
Count;
count_char_in_list([Head | Tail], Count) ->
count_char_in_list(Tail, Count + length(Head)). % a string is just a list of numbers
And then:
1> test:count_char_in_list(["bar", "buzz"], 0).
7

Haskell "collections" language design

Why is the Haskell implementation so focused on linked lists?
For example, I know Data.Sequence is more efficient
with most of the list operations (except for the cons operation), and is used a lot;
syntactically, though, it is "hardly supported". Haskell has put a lot of effort into functional abstractions, such as the Functor and the Foldable class, but their syntax is not compatible with that of the default list.
If, in a project I want to optimize and replace my lists with sequences - or if I suddenly want support for infinite collections, and replace my sequences with lists - the resulting code changes are abhorrent.
So I guess my wondering can be made concrete in questions such as:
Why isn't the type of map equal to (Functor f) => (a -> b) -> f a -> f b?
Why can't the [] and (:) functions be used for, for example, the type in Data.Sequence?
I am really hoping there is some explanation for this, that doesn't include the words "backwards compatibility" or "it just grew that way", though if you think there isn't, please let me know. Any relevant language extensions are welcome as well.
Before getting into why, here's a summary of the problem and what you can do about it. The constructors [] and (:) are reserved for lists and cannot be redefined. If you plan to use the same code with multiple data types, then define or choose a type class representing the interface you want to support, and use methods from that class.
Here are some generalized functions that work on both lists and sequences. I don't know of a generalization of (:), but you could write your own.
fmap instead of map
mempty instead of []
mappend instead of (++)
If you plan to do a one-off data type replacement, then you can define your own names for things, and redefine them later.
-- For now, use lists
type List a = [a]
nil = []
cons x xs = x : xs
{- Switch to Seq in the future
-- type List a = Seq a
-- nil = empty
-- cons x xs = x <| xs
-}
Note that [] and (:) are constructors: you can also use them for pattern matching. Pattern matching is specific to one type constructor, so you can't extend a pattern to work on a new data type without rewriting the pattern-matchign code.
Why there's so much list-specific stuff in Haskell
Lists are commonly used to represent sequential computations, rather than data. In an imperative language, you might build a Set with a loop that creates elements and inserts them into the set one by one. In Haskell, you do the same thing by creating a list and then passing the list to Set.fromList. Since lists so closely match this abstraction of computation, they have a place that's unlikely to ever be superseded by another data structure.
The fact remains that some functions are list-specific when they could have been generic. Some common functions like map were made list-specific so that new users would have less to learn. In particular, they provide simpler and (it was decided) more understandable error messages. Since it's possible to use generic functions instead, the problem is really just a syntactic inconvenience. It's worth noting that Haskell language implementations have very little list-speficic code, so new data structures and methods can be just as efficient as the "built-in" ones.
There are several classes that are useful generalizations of lists:
Functor supplies fmap, a generalization of map.
Monoid supplies methods useful for collections with list-like structure. The empty list [] is generalized to other containers by mempty, and list concatenation (++) is generalized to other containers by mappend.
Applicative and Monad supply methods that are useful for interpreting collections as computations.
Traversable and Foldable supply useful methods for running computations over collections.
Of these, only Functor and Monad were in the influential Haskell 98 spec, so the others have been overlooked to varying degrees by library writers, depending on when the library was written and how actively it was maintained. The core libraries have been good about supporting new interfaces.
I remember reading somewhere that map is for lists by default since newcomers to Haskell would be put off if they made a mistake and saw a complex error about "Functors", which they have no idea about. Therefore, they have both map and fmap instead of just map.
EDIT: That "somewhere" is the Monad Reader Issue 13, page 20, footnote 3:
3You might ask why we need a separate map function. Why not just do away with the current
list-only map function, and rename fmap to map instead? Well, that’s a good question. The
usual argument is that someone just learning Haskell, when using map incorrectly, would much
rather see an error about lists than about Functors.
For (:), the (<|) function seems to be a replacement. I have no idea about [].
A nitpick, Data.Sequence isn't more efficient for "list operations", it is more efficient for sequence operations. That said, a lot of the functions in Data.List are really sequence operations. The finger tree inside Data.Sequence has to do quite a bit more work for a cons (<|) equivalent to list (:), and its memory representation is also somewhat larger than a list as it is made from two data types a FingerTree and a Deep.
The extra syntax for lists is fine, it hits the sweet spot at what lists are good at - cons (:) and pattern-matching from the left. Whether or not sequences should have extra syntax is further debate, but as you can get a very long way with lists, and lists are inherently simple, having good syntax is a must.
List isn't an ideal representation for Strings - the memory layout is inefficient as each Char is wrapped with a constructor. This is why ByteStrings were introduced. Although they are laid out as an array ByteStrings have to do a bit of administrative work - [Char] can still be competitive if you are using short strings. In GHC there are language extensions to give ByteStrings more String-like syntax.
The other major lazy functional Clean has always represented strings as byte arrays, but its type system made this more practical - I believe the ByteString library uses unsafePerfomIO under the hood.
With version 7.8, ghc supports overloading list literals, compare the manual. For example, given appropriate IsList instances, you can write
['0' .. '9'] :: Set Char
[1 .. 10] :: Vector Int
[("default",0), (k1,v1)] :: Map String Int
['a' .. 'z'] :: Text
(quoted from the documentation).
I am pretty sure this won't be an answer to your question, but still.
I wish Haskell had more liberal function names(mixfix!) a la Agda. Then, the syntax for list constructors (:,[]) wouldn't have been magic; allowing us to at least hide the list type and use the same tokens for our own types.
The amount of code change while migrating between list and custom sequence types would be minimal then.
About map, you are a bit luckier. You can always hide map, and set it equal to fmap yourself.
import Prelude hiding(map)
map :: (Functor f) => (a -> b) -> f a -> f b
map = fmap
Prelude is great, but it isn't the best part of Haskell.

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