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#' @title generateListing
#' @description Generate LaTeX code for job info
#' @details Given a subsetted dataset of just one job this generates LaTeX code. Given jobname and company name, print out the section.
#' @author Jared P. Lander
#' @export generateListing
#' @rdname generateListing
#' @importFrom dplyr "%>%"
#' @seealso \code{\link{generateMultipleListings}} \code{\link{generateSection}}
#' @param data data.frame holding the info for one job
#' @param bullets The BulletName's for the desired rows
#' @param type The type of subsection to build; defaults to 'Job', the other currently supported value is 'Research'
#' @param specialChars Vector of characters that need to be double-backslashed escaped
#' @return LaTeX code for a subsection in the resume
#' @examples
#' library(dplyr)
#'
#' jobs <- read.csv(system.file('examples/Jobs.csv', package='resumer'))
#' oneJob <- jobs %>% filter(Company=='Pied Piper', JobName=='Tech Startup')
#' generateListing(oneJob)
#' generateListing(oneJob, bullets=c(1, 3))
#'
#' oneResearch <- jobs %>% filter(JobName=='Oddie Research', Company=='Hudson University')
#' generateListing(oneResearch, bullets=4, type='Research')
#' generateListing(oneResearch, bullets=4:5, type='Research')
#'
generateListing <- function(data, bullets, type='Job', specialChars='&')
{
# select just the wanted bullets
if(!missing(bullets))
{
data <- data %>% dplyr::filter(BulletName %in% bullets)
}
# only get the type we are looking for
data <- data %>% dplyr::filter(Type==type)
# get the information that is only needed once
company <- data$Company[1]
location <- data$Location[1]
title <- data$Title[1]
## build date section
# the start and stop are identical so just grab the first row
jobStart <- data$Start[1]
jobStop <- data$End[1]
# if the end date is not there, just use the start date, otherwise build both with a hyphen in between
if(is.na(jobStop) || jobStop == '')
{
dates <- jobStart
}else
{
dates <- sprintf("%s--%s", jobStart, jobStop)
}
if(type == 'Job')
{
type <- 'rSubsection'
# build opening line for the job based on the company name, dates, title and location
opening <- sprintf("\\begin{%s}{%s}{%s}{%s}{%s}", type, company, dates, title, location)
# get all the bullets, prefixed with \item, sub out characters which cause trouble and unlist
#points <- data %$% sprintf('\\item %s', Bullet) %>% useful::subSpecials(specialChars=specialChars) %>% unlist
points <- sprintf('\\item %s', data$Bullet) %>% useful::subSpecials(specialChars=specialChars) %>% unlist
# build ending which is the same for all jobs
ending <- sprintf("\\end{%s}", 'rSubsection')
} else
{
# build opening line for the job based on the company name, dates, title and location
opening <- sprintf("\\begin{%s}{%s}{%s}{%s}", 'research', company, data$Description[1], dates)
# get all the bullets, prefixed with \item, sub out characters which cause trouble and unlist
#points <- data %$% sprintf('%s\n\n', Bullet) %>% useful::subSpecials(specialChars=specialChars) %>% unlist
points <- sprintf('%s\n\n', data$Bullet) %>% useful::subSpecials(specialChars=specialChars) %>% unlist
# build ending which is the same for all jobs
ending <- sprintf("\\end{%s}", 'research')
}
paste(opening, paste(points, collapse="\n"), ending, sep="\n")
}
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