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Lucy::Analysis::RegexTokenizer – Apache Lucy Documentation
Apache Lucy™

NAME

Lucy::Analysis::RegexTokenizer - Split a string into tokens.

SYNOPSIS

my $whitespace_tokenizer
    = Lucy::Analysis::RegexTokenizer->new( pattern => '\S+' );

# or...
my $word_char_tokenizer
    = Lucy::Analysis::RegexTokenizer->new( pattern => '\w+' );

# or...
my $apostrophising_tokenizer = Lucy::Analysis::RegexTokenizer->new;

# Then... once you have a tokenizer, put it into a PolyAnalyzer:
my $polyanalyzer = Lucy::Analysis::PolyAnalyzer->new(
    analyzers => [ $word_char_tokenizer, $normalizer, $stemmer ], );

DESCRIPTION

Generically, “tokenizing” is a process of breaking up a string into an array of “tokens”. For instance, the string “three blind mice” might be tokenized into “three”, “blind”, “mice”.

Lucy::Analysis::RegexTokenizer decides where it should break up the text based on a regular expression compiled from a supplied pattern matching one token. If our source string is…

"Eats, Shoots and Leaves."

… then a “whitespace tokenizer” with a pattern of "\\S+" produces…

Eats,
Shoots
and
Leaves.

… while a “word character tokenizer” with a pattern of "\\w+" produces…

Eats
Shoots
and
Leaves

… the difference being that the word character tokenizer skips over punctuation as well as whitespace when determining token boundaries.

CONSTRUCTORS

new

my $word_char_tokenizer = Lucy::Analysis::RegexTokenizer->new(
    pattern => '\w+',    # required
);

Create a new RegexTokenizer.

  • pattern - A string specifying a Perl-syntax regular expression which should match one token. The default value is \w+(?:[\x{2019}']\w+)*, which matches “it’s” as well as “it” and “O’Henry’s” as well as “Henry”.

METHODS

transform

my $inversion = $regex_tokenizer->transform($inversion);

Take a single Inversion as input and returns an Inversion, either the same one (presumably transformed in some way), or a new one.

  • inversion - An inversion.

INHERITANCE

Lucy::Analysis::RegexTokenizer isa Lucy::Analysis::Analyzer isa Clownfish::Obj.