TL;DR

Here we are with TASK #1 from the Perl Weekly Challenge #087. Enjoy!

# The update(s)

As correctly pointed out by Abigail in Perl Weekly Challenge 87, Part 1, forgetting to remove duplicates in the sequence dooms any solution based on pre-sorting of the input data. So… consider this as an easy task on the reader!

# The challenge

You are given an unsorted array of integers @N. Write a script to find the longest consecutive sequence. Print 0 if none sequence found.

# The questions

Some questions would be ritual - what about invalid inputs? Is the empty list allowed as input? Are those integers bounded in some way?

A meta question though is… why print 0 if none sequence found? Why not print… an empty sequence, or a sequence with only one item (which is, admittedly, hardly a sequence, but whatever). This print 0 is really an itch!

Update Oh, by the way… one last question: can we have duplicate items in the input? No? Sure? Very well! Because, you know… the solutions below will break if there are duplicate items! 🙄

# The solution

We will be looking at three solutions. Three!

(Well, the Three! is an exclamation, not the factorial of three, otherwise we would have six solutions. Six! 🙄)

Jokes apart, none of them is particularly clever, and all rely on sorting the input array because… well, spotting sequences on a sorted array is so easier, and I do like my comfort zone.

Additionally, all solutions focus on returning a list - the print 0 madness will be addressed elsewhere 😄. In particular, we will be using the following wrapper:

sub longest_consecutive_sequence ($sub, @N) { my @sequence =$sub->(@N);
local $" = ', '; say((@sequence > 1) ? "(@sequence)" : '0'); }  It receives a pointer to the specific solution function, and the input array, taking care to call the sub and… print out what needs to be printed out. ## Basic solution The basic solution is pretty… basic:  1 sub lcs_basic (@N) { 2 return unless @N; 3 @N = sort {$a <=> $b} @N; 4 my ($ls, $ll,$cs, $cl) = (0, 0, 0, 1); 5 for my$i (1 .. $#N, -1) { 6 if ($i >= 0 && $N[$i] == $N[$i - 1] + 1) { # consecutive
7          $cl++; 8 } 9 else { # end or not consecutive 10 ($ls, $ll) = ($cs, $cl) if$cl > $ll; 11 ($cs, $cl) = ($i, 1);
12       }
13    }
14    return @N[$ls .. ($ls + $ll - 1)]; 15 }  The empty list case is easily dismissed at the beginning (line 2). We keep two pairs of integer variables: • $ls and $ll are, respectively, the start index of the longest sequence found so far, and the length of the sequence; • $cs and $cl are, respectively, the start index of the sequence we are currently analyzing, and its length. These variables start with the values in line 4 because… well, for what we know at the beginning, the best list starts at the first integer is one item long, and it is also what we want to investigate more in the beginning. The loop goes through all the rest of the indices (remember? The item in the first position has already been considered by our initializations in line 4) plus a fake index (the -1) that is useful to keep all checks tight inside the loop and avoid dealing with a special condition where the last sequence in the list is also the longest. Inside the loop, there are three cases: • we have a valid index $i, and the associated value inside the array is indeed the consecutive of the previous one;
• we have a valid index, but the value is not the consecutive of the previous one;
• we have a fake index.

The first case is easily addressed: the current sequence is… still a sequence, and we can just record the fact that it is one item longer (line 7) before moving on to the following item.

The last two cases mark a condition where the current sequence has been interrupted, either by a new sequence, or by the end of the whole input list. Whatever the case, anyway, we compare the current list with the best we had so far, and keep the longer one (line 10); then reset the values for the current list, starting from the current position ($i) and resetting the length to 1 (i.e. the new current list includes the element at the $i-th position).

After all elements have been analyzed… we can return the best we found (line 14).

## A slightly less basic solution

Why not optimize something that probably does not need to be optimized? Let’s have fun!

(Yes, this Covid-19 stuff radically shifted some definitions for me, including that of having fun 😅).

One objection that we might move to the basic solution is that it makes no sense to look for other sequences if we can be sure that what we have so far is already the best.

How can we be sure of it?!? Well… if the remaining items are less than the longest sequence we have, there’s no way they can contain a longer sequence, right? For good measure, we will also include the case where they are equal, because in this case we can just keep the one we have, right?

 1 sub lcs_less_basic (@N) {
2    return unless @N;
3    @N = sort {$a <=>$b} @N;
4    my ($ls,$ll, $cs,$cl) = (0, 0, 0, 1);
5    for my $i (1 ..$#N, -1) {
6       if ($i >= 0 &&$N[$i] ==$N[$i - 1] + 1) { # consecutive 7$cl++;
8       }
9       else { # end or not consecutive
10          ($ls,$ll) = ($cs,$cl) if $cl >$ll;
11          last if $ll >=$#N - $i + 1; # compare with max residual length 12 ($cs, $cl) = ($i, 1);
13       }
14    }
15    return @N[$ls .. ($ls + $ll - 1)]; 16 }  It’s the same as before, with the addiiton of line 11 where we do the test and stop looking for a solution if the conditions apply. This test is done in the check and reset branch of the test in line 6, because it’s where we can be sure of the best length so far and have an estimate of the longest possible sequence after this. ## A conceptually simpler solution I have to admit that the two solutions above were not the ones I coded first. I actually started with a conceptually simpler solution, i.e. one where I addressed the problem like this: • sort the input list (as before) • build sub-lists of consecutive items • find the longest sub-list This allows me to think at a higher level of abstraction - instead of fiddling with indexes and lengths and stuff. It also proved very useful to spot bugs in the other solutions 😎 I said conceptually… but the actual implementation might be somehow not totally basic, because it’s based on iterators:  1 sub lcs_with_iterators (@N) { 2 my$iterator = lcs_iterator(@N);
3    my $longest = []; 4 while (my$sequence = $iterator->()) { 5$longest = $sequence if$sequence->@* > $longest->@*; 6 } 7 return$longest->@*;
8 }
9
10 sub lcs_iterator (@N) {
11    @N = sort {$a <=>$b} @N;
12    return sub {
13       return unless @N;
14       my @sequence = shift @N;
15       push @sequence, shift @N while @N && $N ==$sequence[-1] + 1;
16       return \@sequence;
17    };
18 }


The first function lcs_with_iterators is the outer one; it grabs an iterator (from the other function, line 2), i.e. a reference to a sub that can be repeatedly called (line 4) to get the next sequence to compare.

We start with an empty longest sequence (line 3) - at the beginning it’s the best we have, isn’t it?

At each iteration, we compare the length and keep the longest (line 5). At the end, we return it. Isn’t it very, very readable?!?

The iterator factory function lcs_iterator is where the rest happens. The array is sorted as before (line 11), then a reference to an anonymous sub is returned, where this sorted array will be sliced into consecutive sub-lists, returned as reference to arrays (lines 14 through 16) or as… nothing, if there is nothing left in @N.

Each sub-sequence is initialized with the first (remaining) item in @N (line 14), then items are added if they comply with the rules (line 15).

## A comparison

The three solutions have their merits:

• the iterator-based is the most high-level and readable of the three. It’s totally not optimized - it does a lot of copies around, etc. - but it has the merit of being somehow too simple to do wrong. As such, it’s an excellent sanity checker for more optimized solutions - let’s consider that a trusted baseline;
• the basic solution is a first attempt at avoiding unnecessary copies, by keeping indexes instead of making copies around;
• the less basic solution tries to chip off some additional time… when that make sense. Does it make sense?

# So long…

As always, here’s the full code:

#!/usr/bin/env perl
use 5.024;
use warnings;
use experimental qw< postderef signatures >;
no warnings qw< experimental::postderef experimental::signatures >;

my @N = @ARGV ? @ARGV : (100, 4, 50, 3, 2);
local $" = ', '; my @lcs; longest_consecutive_sequence(\&lcs_basic, @N); longest_consecutive_sequence(\&lcs_less_basic, @N); longest_consecutive_sequence(\&lcs_with_iterators, @N); sub longest_consecutive_sequence ($sub, @N) {
my @sequence = $sub->(@N); local$" = ', ';
say((@sequence > 1) ? "(@sequence)" : '0');
}

sub lcs_basic (@N) {
return unless @N;
@N = sort {$a <=>$b} @N;
my ($ls,$ll, $cs,$cl) = (0, 0, 0, 1);
for my $i (1 ..$#N, -1) {
if ($i >= 0 &&$N[$i] ==$N[$i - 1] + 1) { # consecutive$cl++;
}
else { # end or not consecutive
($ls,$ll) = ($cs,$cl) if $cl >$ll;
($cs,$cl) = ($i, 1); } } return @N[$ls .. ($ls +$ll - 1)];
}

sub lcs_less_basic (@N) {
return unless @N;
@N = sort {$a <=>$b} @N;
my ($ls,$ll, $cs,$cl) = (0, 0, 0, 1);
for my $i (1 ..$#N, -1) {
if ($i >= 0 &&$N[$i] ==$N[$i - 1] + 1) { # consecutive$cl++;
}
else { # end or not consecutive
($ls,$ll) = ($cs,$cl) if $cl >$ll;
last if $ll >=$#N - $i + 1; # compare with max residual length ($cs, $cl) = ($i, 1);
}
}
return @N[$ls .. ($ls + $ll - 1)]; } sub lcs_with_iterators (@N) { my$iterator = lcs_iterator(@N);
my $longest = []; while (my$sequence = $iterator->()) {$longest = $sequence if$sequence->@* > $longest->@*; } return$longest->@*;
}

sub lcs_iterator (@N) {
@N = sort {$a <=>$b} @N;
return sub {
return unless @N;
my @sequence = shift @N;
push @sequence, shift @N while @N && $N ==$sequence[-1] + 1;
return \@sequence;
};
}


Have a good one!

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