# This file contains all the code needed to parse and print various sections of your CV
# from data. Feel free to tweak it as you desire!
#' Create a CV_Printer object.
#'
#' @param data_location Path of the spreadsheets holding all your data. This can be
#' either a URL to a google sheet with multiple sheets containing the four
#' data types or a path to a folder containing four `.csv`s with the neccesary
#' data.
#' @param source_location Where is the code to build your CV hosted?
#' @param pdf_mode Is the output being rendered into a pdf? Aka do links need
#' to be stripped?
#' @param sheet_is_publicly_readable If you're using google sheets for data,
#' is the sheet publicly available? (Makes authorization easier.)
#' @return A new `CV_Printer` object.
create_CV_object <- function(data_location,
pdf_mode = FALSE,
resume_mode = FALSE,
sheet_is_publicly_readable = TRUE) {
cv <- list(
pdf_mode = pdf_mode,
links = c()
)
is_google_sheets_location <- stringr::str_detect(data_location, "docs\\.google\\.com")
if (is_google_sheets_location) {
if (sheet_is_publicly_readable) {
# This tells google sheets to not try and authenticate. Note that this will only
# work if your sheet has sharing set to "anyone with link can view"
googlesheets4::gs4_deauth()
} else {
# My info is in a public sheet so there's no need to do authentication but if you want
# to use a private sheet, then this is the way you need to do it.
# designate project-specific cache so we can render Rmd without problems
options(gargle_oauth_cache = ".secrets")
}
read_gsheet <- function(sheet_id) {
googlesheets4::read_sheet(data_location, sheet = sheet_id, skip = 1, col_types = "c")
}
cv$entries_data <- read_gsheet(sheet_id = "entries")
cv$skills <- read_gsheet(sheet_id = "language_skills")
cv$text_blocks <- read_gsheet(sheet_id = "text_blocks")
cv$contact_info <- read_gsheet(sheet_id = "contact_info")
} else {
# Want to go old-school with csvs?
cv$entries_data <- readr::read_csv(paste0(data_location, "entries.csv"), skip = 1)
cv$skills <- readr::read_csv(paste0(data_location, "language_skills.csv"), skip = 1)
cv$text_blocks <- readr::read_csv(paste0(data_location, "text_blocks.csv"), skip = 1)
cv$contact_info <- readr::read_csv(paste0(data_location, "contact_info.csv"), skip = 1)
}
extract_year <- function(dates) {
date_year <- stringr::str_extract(dates, "(20|19)[0-9]{2}")
date_year[is.na(date_year)] <- lubridate::year(lubridate::ymd(Sys.Date())) + 10
date_year
}
parse_dates <- function(dates) {
date_month <- stringr::str_extract(dates, "(\\w+|\\d+)(?=(\\s|\\/|-)(20|19)[0-9]{2})")
date_month[is.na(date_month)] <- "1"
paste("1", date_month, extract_year(dates), sep = "-") |>
lubridate::dmy()
}
cv$entries_data <- cv$entries_data |>
dplyr::filter(
!resume_mode | in_resume == "TRUE"
)
# Check if the column "description_md" exists in the entries_data dataframe
if ("description_md" %in% colnames(cv$entries_data)) {
cv$entries_data <- cv$entries_data |>
dplyr::rename(description_bullets = description_md)
} else {
# Assume we're using old bullet_1, bullet_2, etc. columns
cv$entries_data <- cv$entries_data |>
tidyr::unite(
tidyr::starts_with("description"),
col = "description_bullets",
sep = "\n- ",
na.rm = TRUE
) |>
dplyr::mutate(
description_bullets = ifelse(description_bullets != "", paste0("- ", description_bullets), "")
)
}
# Clean up entries dataframe to format we need it for printing
cv$entries_data <- cv$entries_data |>
dplyr::mutate(
start = ifelse(start == "NULL", NA, start),
end = ifelse(end == "NULL", NA, end),
start_year = extract_year(start),
end_year = extract_year(end),
no_start = is.na(start),
has_start = !no_start,
no_end = is.na(end),
has_end = !no_end,
start_end_are_same = start == end,
timeline = dplyr::case_when(
no_start & no_end ~ "N/A",
no_start & has_end ~ as.character(end),
start_end_are_same ~ as.character(end),
has_start & no_end ~ paste("Current", "-", start),
TRUE ~ paste(end, "-", start)
)
) |>
dplyr::arrange(desc(parse_dates(end))) |>
dplyr::mutate_all(~ ifelse(is.na(.), "N/A", .))
cv
}
# Remove links from a text block and add to internal list
sanitize_links <- function(cv, text) {
if (cv$pdf_mode) {
link_titles <- stringr::str_extract_all(text, "(?<=\\[).+?(?=\\])")[[1]]
link_destinations <- stringr::str_extract_all(text, "(?<=\\().+?(?=\\))")[[1]]
n_links <- length(cv$links)
n_new_links <- length(link_titles)
if (n_new_links > 0) {
# add links to links array
cv$links <- c(cv$links, link_destinations)
# Build map of link destination to superscript
link_superscript_mappings <- purrr::set_names(
paste0("<sup>", (1:n_new_links) + n_links, "</sup>"),
paste0("(", link_destinations, ")")
)
# Replace the link destination and remove square brackets for title
text <- text |>
stringr::str_replace_all(stringr::fixed(link_superscript_mappings)) |>
stringr::str_replace_all("\\[(.+?)\\]", "\\1")
}
}
list(cv = cv, text = text)
}
#' @description Take a position data frame and the section id desired and prints the section to markdown.
#' @param section_id ID of the entries section to be printed as encoded by the `section` column of the `entries` table
print_section <- function(cv, section_id, glue_template = "default") {
if (glue_template == "default") {
glue_template <- "
### {title}
{loc}
{institution}
{timeline}
{description_bullets}
\n\n\n"
}
section_data <- dplyr::filter(cv$entries_data, section == section_id)
if (length(section_data) == 0) {
stop(glue::glue("Tried to print section {section_id} with no entries. Make sure everything is spelled correctly or remove this section."))
}
# Take entire entries data frame and removes the links in descending order
# so links for the same position are right next to each other in number.
for (i in 1:nrow(section_data)) {
for (col in c("title", "description_bullets")) {
strip_res <- sanitize_links(cv, section_data[i, col])
section_data[i, col] <- strip_res$text
cv <- strip_res$cv
}
}
print(glue::glue_data(section_data, glue_template))
invisible(strip_res$cv)
}
#' @description Prints out text block identified by a given label.
#' @param label ID of the text block to print as encoded in `label` column of `text_blocks` table.
print_text_block <- function(cv, label) {
text_block <- dplyr::filter(cv$text_blocks, loc == label) |>
dplyr::pull(text)
strip_res <- sanitize_links(cv, text_block)
cat(strip_res$text)
invisible(strip_res$cv)
}
#' @description Construct a bar chart of skills
#' @param out_of The relative maximum for skills. Used to set what a fully filled in skill bar is.
print_skill_bars <- function(cv, out_of = 5, bar_color = "#969696", bar_background = "#d9d9d9", glue_template = "default") {
if (glue_template == "default") {
glue_template <- "
<div
class = 'skill-bar'
style = \"background:linear-gradient(to right,
{bar_color} {width_percent}%,
{bar_background} {width_percent}% 100%)\"
>{skill}</div>"
}
cv$skills |>
dplyr::mutate(width_percent = round(100 * as.numeric(level) / out_of)) |>
glue::glue_data(glue_template) |>
print()
invisible(cv)
}
#' @description List of all links in document labeled by their superscript integer.
print_links <- function(cv) {
n_links <- length(cv$links)
if (n_links > 0) {
cat("
Links {data-icon=link}
--------------------------------------------------------------------------------
<br>
")
purrr::walk2(cv$links, 1:n_links, function(link, index) {
print(glue::glue("{index}. {link}"))
})
}
invisible(cv)
}
#' @description Contact information section with icons
print_contact_info <- function(cv) {
glue::glue_data(
cv$contact_info,
"- <i class='fa fa-{icon}'></i> {contact}"
) |> print()
invisible(cv)
}
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