#' An S4 class to represent a document collection.
#'
#' \code{docList} returns a special \code{tei2r} object that contains
#' a list of information about your document collection.
#'
#' @slot directory A string that gives the filepath to the main directory (folder), which
#' holds all the files in the collection.
#' @slot filenames A vector containing all of the filenames for the documents in
#' the collection.
#' @slot paths A vector containing the full path to each file in the collection.
#' @slot indexFile A string that gives the filepath to the index file for the
#' corpus. This file should house the meta-data for each file
#' in the corpus.
#' @slot index A data frame that holds the meta-data for each document in
#' the corpus. This data frame is created by reading the file
#' found at \code{indexFile.}
#' @slot stopwordsFile A string that gives the filepath to the file that contains
#' a comma seperated list of words to be removed during text
#' cleanup.
#' @slot stopwords A vector derived from the \code{stopwordsFile} that is passed
#' to the text cleanup functions in order for them to be removed
#' from the text.
#'
#' @slot texts A list of character vectors, each drawn from documents in the collection, and
#' each placed in the order provided by the index.
#'
#' @section What it does:
#' The \code{docList} is the foundation of the \code{tei2r}
#' package and should be the first object created when working
#' with the package. The object is constructed by calling the
#' \code{buildDocList} function. This function builds the object by
#' storing the path to the collection's files (\code{directory}), the
#' file containing the collection's meta-data (\code{indexFile}), and
#' the stopwords file (\code{stopwordsFile}). From these pieces
#' of information, the function automatically determines the
#' \code{filenames} and \code{paths} for the collection's files.
#' @seealso buildDocList
#' @export
docList <- setClass("docList",
slots = c(directory = "character",
filenames = "character",
paths = "character",
indexFile = "character",
index = "data.frame",
stopwordsFile = "character",
stopwords = "character",
texts = "list"
))
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