Split and recombine EPUB text sections based on regular expression pattern matching.
a data frame created by
character, a regular expression.
This function takes a regular expression and uses it to determine new break points for the full e-book text.
This is particularly useful when sections pulled from EPUB metadata have arbitrary breaks and the text contains meaningful breaks at random locations in various sections.
epub_recombine collapses the text and then creates a new nested data frame containing new chapter/section labels, word counts and character counts,
associated with the text based on the new break points.
Usefulness depends on the quality of the e-book. While this function exists to improve the data structure of e-book content parsed from e-books with poor metadata formatting, it still requires original formatting that will at least allow such an operation to be successful, specifically a consistent, non-ambiguous regular expression pattern. See examples below using the built in e-book dataset.
When used in conjunction with
epub_sift via the
sift argument, recombining and resifting is done recursively.
This is because it is possible that sifting can create a need to rerun the recombine step in order to regenerate proper chapter indexing for the section column.
However, recombining a second time does not lead to a need to resift, so recursion ends after one round regardless.
This is a convenient way to avoid the syntax:
epub_recombine([args]) %>% epub_sift([args]) %>% epub_recombine([args]).
a data frame
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file <- system.file("dracula.epub", package = "epubr") x <- epub(file) # parse entire e-book x$data[] # note arbitrary section breaks (not between chapters) pat <- "CHAPTER [IVX]+" # but a reliable pattern exists for new breaks epub_recombine(x, pat) # not as expected; pattern also in table of contents epub_recombine(x, pat, sift = list(n = 1000)) # sift low word-count sections
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