This module is for generating documents in Rich Text Format.
This module is a class; an object belonging to this class
acts like an output filehandle, and calling methods on it
causes RTF text to be written.
Incidentally, this module also exports a few useful functions,
upon request.
The following documentation assumes some familiarity with
the RTF Specification. Users not already intimately
familiar with RTF should look at RTF::Cookbook.
Text::Autoformat provides intelligent formatting of plaintext without
the need for any kind of embedded mark-up. The module recognizes
Internet quoting conventions, a wide range of bulleting and number
schemes, centred text, and block quotations, and reformats each
appropriately. Other options allow the user to adjust inter-word and
inter-paragraph spacing, justify text, and impose various capitalization
schemes.
The module also supplies a re-entrant, highly configurable replacement
for the built-in Perl format() mechanism.
Text::CSV_XS provides facilities for the composition and decomposition of
comma-separated values. An instance of the Text::CSV_XS class can combine
fields into a CSV string and parse a CSV string into fields.
The module accepts either strings or files as input and can utilize any
user-specified characters as delimiters, separators, and escapes so it is
perhaps better called ASV (anything separated values) rather than just CSV.
Text::Delimited provides a programattical interface to data stored in delimited
text files. It is dependant upon the first row of the text file containing
header information for each corresponding "column" in the remainder of the file.
After instancing, for each call to Read the next row's data is returned as a
hash reference. The individual elements are keyed by their corresonding column
headings.
Text::NSP - The Ngram Statistic Package allows a user to count
sequences of Ngrams in large corpora of text, and measure their
association.
The module NSP.pm is a stub that doesn't have any real functionality.
The real work is done by five programs:
count.pl statistic.pl rank.pl combig.pl kocos.pl
These are not modules, and are run from the command line.
Text-Ngram
n-Gram analysis is a field in textual analysis which uses sliding
window character sequences in order to aid topic analysis, language
determination and so on. The n-gram spectrum of a document can be
used to compare and filter documents in multiple languages, prepare
word prediction networks, and perform spelling correction.
This module provides an efficient XS-based implementation of n-gram
spectrum analysis.
This module is a thin wrapper for John Gruber's SmartyPants plugin for
various CMSs.
SmartyPants is a web publishing utility that translates plain ASCII
punctuation characters into "smart" typographic punctuation HTML
entities. SmartyPants can perform the following transformations:
* Straight quotes ( " and ' ) into "curly" quote HTML entities
* Backticks-style quotes (``like this'') into "curly" quote HTML entities
* Dashes (-- and ---) into en- and em-dash entities
* Three consecutive dots (...) into an ellipsis entity
RTF::Tokenizer is an object-orientated low-level RTF reader. If
you're looking to render RTF, or want a higher-level RTF processor,
this is not the module for you - you want RTF::Reader. This is the
sixth release of RTF::Tokenizer - it's faster, higher quality, and
implements the RTF standard better than any previous release.
It's also philosophically a better module, and conforms more
strictly to Object Orientated guidelines - it can be sub-classed
and the interface is cleaner.
dbacl is a digramic Bayesian text classifier. Given some text,
it calculates the posterior probabilities that the input resembles
one of any number of previously learned document collections.
It can be used to sort incoming email into arbitrary categories
such as spam, work, and play, or simply to distinguish an English text
from a French text. It fully supports international character sets,
and uses sophisticated statistical models based on the
Maximum Entropy Principle.
This module is a variation on the lovely Text::Diff module. Rather
than generating traditional line-oriented diffs, however, it generates
word-oriented diffs. This can be useful for tracking changes in
narrative documents or documents with very long lines. To diff
source code, one is still best off using Text::Diff. But if you
want to see how a short story changed from one version to the next,
this module will do the job very nicely.