Tricks with Arrays and Hashes

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Today's Perl tip is about a simple programming concept, but one that's easy to get wrong: basic operations when dealing with lists of data. Let's pretend we wish to find the unique elements in an array. For example, if we had:

my @array = (1, 1, 1, 2, 1);

we'd want to get back:

my @unique = (1, 2);

Naive solution

This problem is naively solved using a nested loop. For example:

# This is an AWFUL solution my @array = (1, 1, 1, 2, 1); my @uniques; FIND: foreach my $element (@array) { foreach my $unique (@uniques) { if($element == $unique) { # This is already in our unique array # so skip to the next element next FIND; } } # If we're here, it's not yet in our unique array, so add # it. push @uniques, $element; } # Uniques now contains all the unique elements print "@uniques

";

While this solution looks correct, and may seem fast when dealing with small lists, it's extremely slow when working with large lists. In fact this algorithm has a complexity of O(n2) , which means the time taken increases in proportion to the square of the number of elements. (See our Perl tip on Big-O notation for more information.)

Hash slices

A better way to find the unique elements in a list is to use a hash, since it guarantees its keys are unique. To build a hash, we only need to walk through our list once, which gives us an algorithmic complexity of O(n) , meaning our time scales in linear proportion to the number of elements we're processing.

We could use a looping construct to build our hash, but Perl actually provides us with a short-cut, known as a hash slice. A hash slice allows us to reference multiple keys at once, and looks a little like this:

my %favourite_colour; # A hash slice still uses curly-braces around the keys, but # an '@' to access multiple keys at once. @favourite_colour{ qw(Paul Jacinta Sean) } = qw(Blue Green Red);

We can use the fact that hash keys are unique, as well as the short-cut of using a hash-slice, to very quickly find our unique set:

my @duplicates = (1, 1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 9, 2, 3, 3,); my %unique; # Our hash here has keys, but all its values will be undefined. # That's fine, since we're only interested in the keys. @unique{@duplicates} = (); my @unique_elements = sort keys %unique; print "@unique_elements

"; # 1 2 3 4 5 6 7 8 9

Retaining the original order

If we did not sort the results, in the previous example, we might get back the set:

6 3 7 9 2 8 1 4 5

which is not related to the original order of @duplicates . This is because hashes do not keep any internal ordering. If it is important that the original ordering is preserved we can use Tie::IxHash (covered in our tip about Ordered hashes. Tie::IxHash does not come standard with Perl, but can be downloaded from the CPAN.

use Tie::IxHash; tie my %unique => 'Tie::IxHash'; my @duplicates = (1, 1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 9, 2, 3, 3,); @unique{@duplicates} = (); my @unique_elements = keys %unique; print "@unique_elements

"; # 1 2 3 4 5 6 7 8 9

This works even if our @duplicates are words:

my @duplicates = qw(e d c b e e e b c a a d e e a b ); @unique{@duplicates} = (); my @unique_elements = keys %unique; print "@unique_elements

"; # e d c b a

There's more than one way to do it (List::MoreUtils)

Although hash slices provide us with a very useful way to gain unique values, there's another, even easier way to achieve the same purpose. The List::MoreUtils module (available from the CPAN) provides a uniq function which with the same results as our Tie::IxHash example above:

use List::MoreUtils qw(uniq); my @duplicates = (1, 1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 9, 2, 3, 3,); my @unique_elements = uniq( @duplicates ); print "@unique_elements

"; # 1 2 3 4 5 6 7 8 9

The List::MoreUtils subroutines are not only easier to understand than our hand-rolled code, but since they're implemented in pure C they should also outperform our home-grown code by a significant margin.

Resources

For more information about keeping insert order for hashes see our Perl tip on Ordered Hashes and Tie::IxHash .

For more on List::MoreUtils and the other excellent methods it provides see the documentation.

For more on algorithmic complexity and why the naive solution is a bad choice see our tip on Big-O notation.

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