Returning values from elixir functions inside modules - recursion

This is the method that processes an input string
def process(input) do
list=String.split(input, "\n")
f3=fn(a) ->
String.split(a," ")
end
list=Enum.map(list, f3)
func3=fn(n) ->
length(n)==3
end
func2=fn(n) ->
length(n)<=2
end
system=for x <-list, func3.(x), do: x
input=for y <- list, func2.(y), do: y
input=Enum.slice(input,0..length(input)-2)
output=""
output(input,output, system)
end
This is the output function that uses recursion to edit a string and eventually return its value
def output(input, output, system) do
cond do
length(input)==0 ->
output
true ->
[thing|tail]=input
if length(thing)==2 do
output=output<>"From "<>Enum.at(thing, 0)<>" to "<>Enum.at(thing,1)<>" is "<>Integer.to_string(calculate(thing, system))<>"km\n"
output(tail, output, system)
end
if length(thing)==1 do
if Enum.at(thing,0)=="Sun" do
output=output<>"Sun orbits"
output(tail, output, system)
else
output=output<>orbits(thing, system)<>" Sun"
output(tail, output, system)
end
end
output(tail, output, system)
end
end
As you can see when the input is an empty list it should return the output string. Using inspect shows that the output string does indeed have the correct value. Yet when the function is called in process(), it only returns the empty string, or nil.
Any help is appreciated, I am new to elixir so apologies if my code is a bit messy.

This could be a case where using pattern matching in the function head will let you avoid essentially all of the conditionals. You could break this down as:
def output([], message, _) do
message
end
def output([[from, to] | tail], message, system) do
distance = Integer.to_string(calculate(thing, system))
new_message = "#{message}From #{from} to #{to} is #{distance} km\n"
output(tail, new_message, system)
end
def output([["Sun"] | tail], message, system) do
output(tail, "Sun orbits #{message}", system)
end
def output([[thing] | tail], message, system) do
new_message = "#{message}#{orbits([thing], system)} Sun"
output(tail, new_message, system)
end
This gets around some of the difficulties highlighted in the comments: reassigning output inside a block doesn't have an effect, and there aren't non-local returns so after an if ... end block completes and goes on to the next conditional, its result is lost. This will also trap some incorrect inputs, and your process will exit with a pattern-match error if an empty or 3-element list winds up in the input list.
I've renamed the output parameter to the output function to message. This isn't required – the code will work fine whether or not you change it – but I found it a little confusing reading through the function whether output is a function call or a variable.

Related

F# Console.ReadLine not waiting for input

I'm new to F#, apologies if I'm missing something obvious here.
I have the following code, with the intent to get user input and convert it to a uint:
let println ln =
printfn "%s" ln
let rec getUserKeyInput =
let x = System.Console.ReadKey()
string x
let getInputWithPrompt prompt =
println prompt
getUserKeyInput
let rec getUserUIntFromStr str =
try
let i = str |> uint
i
with
| :? System.FormatException -> println "Please enter a positive integer";
(getUserUIntFromStr (getUserKeyInput))
When getUserUIntFromStr is called with let i = getUserUIntFromStr str "Please enter a positive integer" is printed infinitely. I've also tried Console.ReadLine() and stdin.ReadLine(), both in interactive and from main, with the same results. It looks to me like none of the "Read" functions are waiting for input, but that doesn't seem right and I'm guessing I've done something wrong. Any suggestions?
getUserKeyInput is a value, not a function. It's evaluated only once at init time, not every time you reference it.
To make it a function, you need to give it a parameter. What type of parameter? Well, technically any type will do, but F# has you covered: for situations where you need to have some value, but there isn't a sensible value to use (which happens surprisingly often), there is a special type unit with a single value denoted as parentheses ():
let getUserKeyInput () =
let x = System.Console.ReadKey()
string x
(also note that rec is unnecessary, because the function isn't actually recursive)
(also note that ReadKey takes such parameter as well - it's the same deal there)
And then pass the parameter to call the function:
println "Please enter a positive integer"
getUserUIntFromStr (getUserKeyInput ())

Understanding side effects with monadic traversal

I am trying to properly understand how side effects work when traversing a list in F# using monadic style, following Scott's guide here
I have an AsyncSeq of items, and a side-effecting function that can return a Result<'a,'b> (it is saving the items to disk).
I get the general idea - split the head and tail, apply the func to the head. If it returns Ok then recurse through the tail, doing the same thing. If an Error is returned at any point then short circuit and return it.
I also get why Scott's ultimate solution uses foldBack rather than fold - it keeps the output list in the same order as the input as each processed item is prepended to the previous.
I can also follow the logic:
The result from the list's last item (processed first as we are using foldback) will be passed as the accumulator to the next item.
If it is an Error and the next item is Ok, the next item is discarded.
If the next item is an Error, it replaces any previous results and becomes the accumulator.
That means by the time you have recursed over the entire list from right to left and ended up at the start, you either have an Ok of all of the results in the correct order or the most recent Error (which would have been the first to occur if we had gone left to right).
The thing that confuses me is that surely, since we are starting at the end of the list, all side effects of processing every item will take place, even if we only get back the last Error that was created?
This seems to be confirmed here as the print output starts with [5], then [4,5], then [3,4,5] etc.
The thing that confuses me is that this isn't what I see happening when I use AsyncSeq.traverseChoiceAsync from the FSharpx lib (which I wrapped to process Result instead of Choice). I see side effects happening from left to right, stopping on the first error, which is what I want to happen.
It also looks like Scott's non-tail recursive version (which doesn't use foldBack and just recurses over the list) goes from left to right? The same goes for the AsyncSeq version. That would explain why I see it short circuit on the first error but surely if it completes Ok then the output items would be reversed, which is why we normally use foldback?
I feel I am misunderstanding or misreading something obvious! Could someone please explain it to me? :)
Edit:
rmunn has given a really great comprehensive explanation of the AsyncSeq traversal below. The TLDR was that
Scott's initial implementation and the AsyncSeq traverse both do go from left to right as I thought and so only process until they hit an error
they keep their contents in order by prepending the head to the processed tail rather than prepending each processed result to the previous (which is what the built in F# fold does).
foldback would keep things in order but would indeed execute every case (which could take forever with an async seq)
It's pretty simple: traverseChoiceAsync isn't using foldBack. Yes, with foldBack the last item would be processed first, so that by the time you get to the first item and discover that its result is Error you'd have triggered the side effects of every item. Which is, I think, precisely why whoever wrote traverseChoiceAsync in FSharpx chose not to use foldBack, because they wanted to ensure that side effects would be triggered in order, and stop at the first Error (or, in the case of the Choice version of the function, the first Choice2Of2 — but I'll pretend from this point on that that function was written to use the Result type.)
Let's look at the traverseChoieAsync function in the code you linked to, and read through it step-by-step. I'll also rewrite it to use Result instead of Choice, because the two types are basically identical in function but with different names in the DU, and it'll be a little easier to tell what's going on if the DU cases are called Ok and Error instead of Choice1Of2 and Choice2Of2. Here's the original code:
let rec traverseChoiceAsync (f:'a -> Async<Choice<'b, 'e>>) (s:AsyncSeq<'a>) : Async<Choice<AsyncSeq<'b>, 'e>> = async {
let! s = s
match s with
| Nil -> return Choice1Of2 (Nil |> async.Return)
| Cons(a,tl) ->
let! b = f a
match b with
| Choice1Of2 b ->
return! traverseChoiceAsync f tl |> Async.map (Choice.mapl (fun tl -> Cons(b, tl) |> async.Return))
| Choice2Of2 e ->
return Choice2Of2 e }
And here's the original code rewritten to use Result. Note that it's a simple rename, and none of the logic needs to be changed:
let rec traverseResultAsync (f:'a -> Async<Result<'b, 'e>>) (s:AsyncSeq<'a>) : Async<Result<AsyncSeq<'b>, 'e>> = async {
let! s = s
match s with
| Nil -> return Ok (Nil |> async.Return)
| Cons(a,tl) ->
let! b = f a
match b with
| Ok b ->
return! traverseChoiceAsync f tl |> Async.map (Result.map (fun tl -> Cons(b, tl) |> async.Return))
| Error e ->
return Error e }
Now let's step through it. The whole function is wrapped inside an async { } block, so let! inside this function means "unwrap" in an async context (essentially, "await").
let! s = s
This takes the s parameter (of type AsyncSeq<'a>) and unwraps it, binding the result to a local name s that henceforth will shadow the original parameter. When you await the result of an AsyncSeq, what you get is the first element only, while the rest is still wrapped in an async that needs to be further awaited. You can see this by looking at the result of the match expression, or by looking at the definition of the AsyncSeq type:
type AsyncSeq<'T> = Async<AsyncSeqInner<'T>>
and AsyncSeqInner<'T> =
| Nil
| Cons of 'T * AsyncSeq<'T>
So when you do let! x = s when s is of type AsyncSeq<'T>, the value of x will either be Nil (when the sequence has run to its end) or it will be Cons(head, tail) where head is of type 'T and tail is of type AsyncSeq<'T>.
So after this let! s = s line, our local name s now refers to an AsyncSeqInner type, which contains the head item of the sequence (or Nil if the sequence was empty), and the rest of the sequence is still wrapped in an AsyncSeq so it has yet to be evaluated (and, crucially, its side effects have not yet happened).
match s with
| Nil -> return Ok (Nil |> async.Return)
There's a lot happening in this line, so it'll take a bit of unpacking, but the gist is that if the input sequence s had Nil as its head, i.e. had reached its end, then that's not an error, and we return an empty sequence.
Now to unpack. The outer return is in an async keyword, so it takes the Result (whose value is Ok something) and turns it into an Async<Result<something>>. Remembering that the return type of the function is declared as Async<Result<AsyncSeq>>, the inner something is clearly an AsyncSeq type. So what's going on with that Nil |> async.Return? Well, async isn't an F# keyword, it's the name of an instance of AsyncBuilder. Inside a computation expression foo { ... }, return x is translated into foo.Return(x). So calling async.Return x is just the same as writing async { return x }, except that it avoids nesting a computation expression inside another computation expression, which would be a little nasty to try and parse mentally (and I'm not 100% sure the F# compiler allows it syntactically). So Nil |> async.Return is async.Return Nil which means it produces a value of Async<x> where x is the type of the value Nil. And as we just saw, this Nil is a value of type AsyncSeqInner, so Nil |> async.Return produces an Async<AsyncSeqInner>. And another name for Async<AsyncSeqInner> is AsyncSeq. So this whole expression produces an Async<Result<AsyncSeq>> that has the meaning of "We're done here, there are no more items in the sequence, and there was no error".
Phew. Now for the next line:
| Cons(a,tl) ->
Simple: if the next item in the AsyncSeq named s was a Cons, we deconstruct it so that the actual item is now called a, and the tail (another AsyncSeq) is called tl.
let! b = f a
This calls f on the value we just got out of s, and then unwraps the Async part of f's return value, so that b is now a Result<'b, 'e>.
match b with
| Ok b ->
More shadowed names. Inside this branch of the match, b now names a value of type 'b rather than a Result<'b, 'e>.
return! traverseResultAsync f tl |> Async.map (Result.map (fun tl -> Cons(b, tl) |> async.Return))
Hoo boy. That's too much to tackle at once. Let's write this as if the |> operators were lined up on separate lines, and then we'll go through each step one at a time. (Note that I've wrapped an extra pair of parentheses around this, just to clarify that it's the final result of this whole expression that will be passed to the return! keyword).
return! (
traverseResultAsync f tl
|> Async.map (
Result.map (
fun tl -> Cons(b, tl) |> async.Return)))
I'm going to tackle this expression from the inside out. The inner line is:
fun tl -> Cons(b, tl) |> async.Return
The async.Return thing we've already seen. This is a function that takes a tail (we don't currently know, or care, what's inside that tail, except that by the necessity of the type signature of Cons it must be an AsyncSeq) and turns it into an AsyncSeq that is b followed by the tail. I.e., this is like b :: tl in a list: it sticks b onto the front of the AsyncSeq.
One step out from that innermost expression is:
Result.map
Remember that the function map can be thought of in two ways: one is "take a function and run it against whatever is "inside" this wrapper". The other is "take a function that operates on 'T and make it into a function that operates on Wrapper<'T>". (If you don't have both of those clear in your mind yet, https://sidburn.github.io/blog/2016/03/27/understanding-map is a pretty good article to help grok that concept). So what this is doing is taking a function of type AsyncSeq -> AsyncSeq and turning it into a function of type Result<AsyncSeq> -> Result<AsyncSeq>. Alternately, you could think of it as taking a Result<tail> and calling fun tail -> ... against that tail result, then re-wrapping the result of that function in a new Result. Important: Because this is using Result.map (Choice.mapl in the original) we know that if tail is an Error value (or if the Choice was a Choice2Of2 in the original), the function will not be called. So if traverseResultAsync produces a result that starts with an Error value, it's going to produce an <Async<Result<foo>>> where the value of Result<foo> is an Error, and so the value of the tail will be discarded. Keep that in mind for later.
Okay, next step out.
Async.map
Here, we have a Result<AsyncSeq> -> Result<AsyncSeq> function produced by the inner expression, and this converts it to an Async<Result<AsyncSeq>> -> Async<Result<AsyncSeq>> function. We've just talked about this, so we don't need to go over how map works again. Just remember that the effect of this Async<Result<AsyncSeq>> -> Async<Result<AsyncSeq>> function that we've built up will be the following:
Await the outer async.
If the result is Error, return that Error.
If the result is Ok tail, produce an Ok (Cons (b, tail)).
Next line:
traverseResultAsync f tl
I probably should have started with this, because this will actually run first, and then its value will be passed into the Async<Result<AsyncSeq>> -> Async<Result<AsyncSeq>> function that we've just analysed.
So what this whole thing will do is to say "Okay, we took the first part of the AsyncSeq we were handed, and passed it to f, and f produced an Ok result with a value we're calling b. So now we need to process the rest of the sequence similarly, and then, if the rest of the sequence produces an Ok result, we'll stick b on the front of it and return an Ok sequence with contents b :: tail. BUT if the rest of the sequence produces an Error, we'll throw away the value of b and just return that Error unchanged."
return!
This just takes the result we just got (either an Error or an Ok (b :: tail), already wrapped in an Async) and returns it unchanged. But note that the call to traverseResultAsync is NOT tail-recursive, because its value had to be passed into the Async.map (...) expression first.
And now we still have one more bit of traverseResultAsync to look at. Remember when I said "Keep that in mind for later"? Well, that time has arrived.
| Error e ->
return Error e }
Here we're back in the match b with expression. If b was an Error result, then no further recursive calls are made, and the whole traverseResultAsync returns an Async<Result> where the Result value is Error. And if we were currently nested deep inside a recursion (i.e., we're in the return! traverseResultAsync ... expression), then our return value will be Error, which means the result of the "outer" call, as we've kept in mind, will also be Error, discarding any other Ok results that might have happened "before".
Conclusion
And so the effect of all of that is:
Step through the AsyncSeq, calling f on each item in turn.
The first time f returns Error, stop stepping through, throw away any previous Ok results, and return that Error as the result of the whole thing.
If f never returns Error and instead returns Ok b every time, return an Ok result that contains an AsyncSeq of all those b values, in their original order.
Why are they in their original order? Because the logic in the Ok case is:
If sequence was empty, return an empty sequence.
Split into head and tail.
Get value b from f head.
Process the tail.
Stick value b in front of the result of processing the tail.
So if we started with (conceptually) [a1; a2; a3], which actually looks like Cons (a1, Cons (a2, Cons (a3, Nil))) we'll end up with Cons (b1, Cons (b2, Cons (b3, Nil))) which translates to the conceptual sequence [b1; b2; b3].
See #rmunn's great answer above for the explanation. I just wanted to post a little helper for anyone that reads this in the future, it allows you to use the AsyncSeq traverse with Results instead of the old Choice type it was written with:
let traverseResultAsyncM (mapping : 'a -> Async<Result<'b,'c>>) source =
let mapping' =
mapping
>> Async.map (function
| Ok x -> Choice1Of2 x
| Error e -> Choice2Of2 e)
AsyncSeq.traverseChoiceAsync mapping' source
|> Async.map (function
| Choice1Of2 x -> Ok x
| Choice2Of2 e -> Error e)
Also here is a version for non-async mappings:
let traverseResultM (mapping : 'a -> Result<'b,'c>) source =
let mapping' x = async {
return
mapping x
|> function
| Ok x -> Choice1Of2 x
| Error e -> Choice2Of2 e
}
AsyncSeq.traverseChoiceAsync mapping' source
|> Async.map (function
| Choice1Of2 x -> Ok x
| Choice2Of2 e -> Error e)

How to simulate Ruby's until loop in Elixir?

I'm converting a Ruby project to Elixir. How does Ruby's until loop translate to Elixir?
until scanner.eos? do
tokens << scan(line + 1)
end
Here's the full Ruby method:
def tokenize
#tokens = []
#lines.each_with_index do |text, line|
#scanner = StringScanner.new(text)
until #scanner.eos? do
#tokens << scan(line + 1)
end
end
#tokens
end
#lines is just a text file split by new lines. #lines = text.split("\n")
In Elixir, I've already converted the string scanner which looks like this: StringScanner.eos?(scanner):
#spec eos?(pid) :: boolean
def eos?(pid) when is_pid(pid) do
Also, in Elixir, tokens are tuples: #type token :: {:atom, any, {integer, integer}}. Where the {integer, integer} tuple is the line and position of the token.
This is the Elixir psuedo-code which doesn't quite work.
#spec scan(String.t, integer) :: token
def scan(text, line) when is_binary(text) and is_integer(line) do
string_scanner = StringScanner.new(text)
until StringScanner.eos?(string_scanner) do
result = Enum.find_value(#scanner_tokenizers, fn {scanner, tokenizer} ->
match = scanner.(string_scanner)
if match do
tokenizer.(string_scanner, match, line)
end
end)
IO.inspect result
end
StringScanner.stop(string_scanner)
result
end
Someone on the slack channel suggested using recursion, however they didn't elaborate with an example. I've seen recursion examples for summing / reducing which use accumulators etc. However, I don't see how that applies when evaluating a boolean.
Can anyone provide a working example which uses StringScanner.eos?(scanner)? Thanks.
It may be something like
def tokens(scanner) do
tokens(scanner, [])
end
defp tokens(scanner, acc) do
if StringScanner.eos?(scanner) do
acc
else
tokens(scanner, add_to_acc(scan_stuff(), acc))
end
end
At least this can be the general idea. As you'll see I kept a couple of functions very generic (scan_stuff/0 and add_to_acc/2) as I don't know how you mean to implement those; the first one is meant to do what scan(line + 1) does in the Ruby code, while the second one is meant to do what << does in the Ruby code (e.g., it could add the scanned stuff to the list of tokens or something similar).

How to show caller in a Julia backtrace?

Is there a way to get the file/name/line info for the caller of a Julia function?
I found this way to get some stacktrace info, and if the caller is another function (but not the main context) I get the file:line info:
module pd
global g_bTraceOn = true
export callerOfTraceIt
function callerOfTraceIt()
traceit( "hi" ) ;
end
function traceit( msg )
global g_bTraceOn
if ( g_bTraceOn )
bt = backtrace() ;
s = sprint(io->Base.show_backtrace(io, bt))
println( "debug: $s: $msg" )
end
end
end
using pd
callerOfTraceIt( )
This shows:
$ julia bt.jl
debug:
in traceit at C:\cygwin64\home\Peeter\julia\HarmonicBalance\bt.jl:15
in callerOfTraceIt at C:\cygwin64\home\Peeter\julia\HarmonicBalance\bt.jl:8
in include at boot.jl:245
in include_from_node1 at loading.jl:128
in process_options at client.jl:285
in _start at client.jl:354: hi
I'd really like just the second frame (caller of traceit()), and would also like the function name if it's available.
If you do #show bt inside traceit, you'll discover it's just a list of pointers, each corresponding to a single stack frame. Those stack frames that come from julia code (rather than C) are displayed by show_backtrace.
You can call Profile.lookup(uint(bt[1])) to extract file/function/line information from each element:
julia> Profile.lookup(uint(bt[1]))
LineInfo("rec_backtrace","/home/tim/src/julia-old/usr/bin/../lib/libjulia.so",-1,true,140293228378757)
julia> names(Profile.LineInfo)
5-element Array{Symbol,1}:
:func
:file
:line
:fromC
:ip
You likely want to ignore all elements with fromC == true.

Erlang sudoku solver - How to find the empty spots and try possible values recursively

I have been busy with a sudoku solver in Erlang yesterday and today. The working functionality I have now is that I can check if a sudoku in the form of a list, e.g.,
[6,7,1,8,2,3,4,9,5,5,4,9,1,7,6,3,2,8,3,2,8,5,4,9,1,6,7,1,3,2,6,5,7,8,4,9,9,8,6,4,1,2,5,7,3,4,5,7,3,9,8,6,1,2,8,9,3,2,6,4,7,5,1,7,1,4,9,3,5,2,8,6,2,6,5,7,8,1,9,3,4].
is valid or not by looking at the constraints (no duplicates in squares, rows, and columns).
This function is called valid(S) which takes a sudoku S and returns true if it is a valid sudoku and false if it is not. The function ignores 0's, which are used to represent empty values. This is an example of the same sudoku with some random empty values:
[0,7,1,8,2,3,4,0,5,5,4,9,0,7,6,3,2,8,3,0,8,5,0,9,1,6,7,1,3,2,6,5,7,8,4,9,0,8,6,4,1,2,5,7,0,4,5,7,3,9,8,6,1,0,8,9,3,2,6,4,7,5,1,7,1,4,9,3,0,2,8,6,2,6,5,7,8,1,9,3,4].
The next step is to find the first 0 in the list, and try a value from 1 to 9 and check if it produces a valid sudoku. If it does we can continue to the next 0 and try values there and see if it is valid or not. Once we cannot go further we go back to the previous 0 and try the next values et cetera until we end up with a solved sudoku.
The code I have so far looks like this (based on someone who got it almost working):
solve(First,Nom,[_|Last]) -> try_values({First,Nom,Last},pos()).
try_values(_,[]) -> {error, "No solution found"};
try_values({First,Nom,Last},[N|Pos]) ->
case valid(First++[N]++Last) of
true ->
case solve({First++[N]},Nom,Last) of
{ok,_} -> {ok, "Result"};
{error,_} -> try_values({First,N,Last},Pos)
end;
false -> try_values({First,N,Last},Pos)
end.
pos() is a list consisting of the values from 1 to 9. The idea is that we enter an empty list for First and a Sudoku list for [_|Last] in which we look for a 0 (Nom?). Then we try a value and if the list that results is valid according to our function we continue till we fail the position or have a result. When we fail we return a new try_values with remaining (Pos) values of our possibitilies.
Naturally, this does not work and returns:
5> sudoku:solve([],0,S).
** exception error: bad argument
in operator ++/2
called as {[6]}
++
[1,1,8,2,3,4,0,5,5,4,9,0,7,6,3,2,8,3,2,8,5,4,9,1,6,7,1,3,2|...]
in call from sudoku:try_values/2 (sudoku.erl, line 140)
in call from sudoku:try_values/2 (sudoku.erl, line 142)
With my inexperience I cannot grasp what I need to do to make the code logical and working. I would really appreciate it if someone with more experience could give me some pointers.
try_values([], []) -> error("No solution found");
try_values([Solution], []) -> Solution;
try_values(_, []) -> error("Bad sudoku: multiple solutions");
try_values(Heads, [0|Tail]) ->
NewHeads = case Heads of
[] -> [[P] || P <- pos()];
_ -> [Head++[P] || P <- pos(), Head <- Heads]
end,
ValidHeads = [Head || Head <- NewHeads, valid(Head++Tail)],
try_values(ValidHeads, Tail);
try_values([], [H|Tail]) -> try_values([[H]], Tail);
try_values(Heads, [H|Tail]) -> try_values([Head++[H] || Head <- Heads], Tail).
solve(Board) ->
case valid(Board) of
true -> try_values([], Board);
false -> error("No solution found")
end.
try_values does what you described. It builds solution by going through Board, trying all possible solutions (from pos()) when it finds 0 and collecting valid solutions in ValidHeads to pass them further to continue. Thus, it goes all possible ways, if at some point there are multiple valid sudoku they all will be added to Heads and will be tested on validity on following steps. solve is just a wrapper to call try_values([], Board).
Basically, the way to iterate recursively over 0's is to skip all non-zeros (2 last try_values expression) and do the job on zeros (fourth try_values expression).
First three try_values expressions check if solution is exist and single and return it in that case.

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