CLI for R Packages

When to Use What

task: Display error with context and formatting use: cli_abort() with inline markup and bullet lists

task: Show warning with formatting use: cli_warn() with inline markup

task: Display informative message use: cli_inform() with inline markup

task: Show progress for counted operations use: cli_progress_bar() with total count

task: Show simple progress steps use: cli_progress_step() with status messages

task: Format code or function names use: {.code ...} or {.fn package::function}

task: Format file paths use: {.file path/to/file}

task: Format package names use: {.pkg packagename}

task: Format variable names use: {.var variable_name}

task: Format values use: {.val value}

task: Handle singular/plural text use: {?s} or {?y/ies} with pluralization

task: Create headers use: cli_h1(), cli_h2(), cli_h3()

task: Create alerts use: cli_alert_success(), cli_alert_danger(), cli_alert_warning(), cli_alert_info()

task: Create lists use: cli_ul(), cli_ol(), cli_dl() with cli_li()

Inline Markup Essentials

Use inline markup with {.class content} syntax to format text:

# Basic formatting
cli_text("Function {.fn mean} calculates averages")
cli_text("Install package {.pkg dplyr}")
cli_text("See file {.file ~/.Rprofile}")
cli_text("{.var x} must be numeric, not {.obj_type_of {x}}")
cli_text("Got value {.val {x}}")

# Code formatting
cli_text("Use {.code sum(x, na.rm = TRUE)}")

# Paths and arguments
cli_text("Reading from {.path /data/file.csv}")
cli_text("Set {.arg na.rm} to TRUE")

# Types and classes
cli_text("Object is {.cls data.frame}")

# Emphasis
cli_text("This is {.emph important}")
cli_text("This is {.strong critical}")

# Fields
cli_text("The {.field name} field is required")

Vector Collapsing

Vectors are automatically collapsed with commas and "and":

pkgs <- c("dplyr", "tidyr", "ggplot2")
cli_text("Installing packages: {.pkg {pkgs}}")
#> Installing packages: dplyr, tidyr, and ggplot2

files <- c("data.csv", "script.R")
cli_text("Found {length(files)} file{?s}: {.file {files}}")
#> Found 2 files: data.csv and script.R

Escaping Braces

Use double braces {{ and }} to escape literal braces:

cli_text("Use {{variable}} syntax in glue")
#> Use {variable} syntax in glue

For complete markup reference: See references/inline-markup.md for all 50+ inline classes, edge cases, nesting rules, and advanced patterns.

Pluralization Basics

Use {?} for pluralization with three patterns:

Single Alternative

nfile <- 1
cli_text("Found {nfile} file{?s}")
#> Found 1 file

nfile <- 3
cli_text("Found {nfile} file{?s}")
#> Found 3 files

Two Alternatives

ndir <- 1
cli_text("Found {ndir} director{?y/ies}")
#> Found 1 directory

ndir <- 5
cli_text("Found {ndir} director{?y/ies}")
#> Found 5 directories

Three Alternatives (zero/one/many)

nfile <- 0
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 0 files: no files

nfile <- 1
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 1 file: the file

nfile <- 3
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 3 files: the files

Helpers: qty() and no()

Use no() to display "no" instead of zero:

nfile <- 0
cli_text("Found {no(nfile)} file{?s}")
#> Found no files

Use qty() to set quantity explicitly:

nupd <- 3
ntotal <- 10
cli_text("{nupd}/{ntotal} {qty(nupd)} file{?s} {?needs/need} updates")
#> 3/10 files need updates

For advanced pluralization: See references/inline-markup.md for edge cases and complex patterns.

CLI Conditions: Core Patterns

Use cli conditions instead of base R for better formatting:

cli_abort() - Formatted Errors

# Before (base R)
stop("File not found: ", path)

# After (cli)
cli_abort("File {.file {path}} not found")

# With bullets for context
check_file <- function(path) {
  if (!file.exists(path)) {
    cli_abort(c(
      "File not found",
      "x" = "Cannot read {.file {path}}",
      "i" = "Check that the file exists"
    ))
  }
}

cli_warn() - Formatted Warnings

# Before (base R)
warning("Column ", col, " has missing values")

# After (cli)
cli_warn("Column {.field {col}} has missing values")

# With context
cli_warn(c(
  "Data quality issues detected",
  "!" = "Column {.field {col}} has {n_missing} missing value{?s}",
  "i" = "Consider using {.fn tidyr::drop_na}"
))

cli_inform() - Formatted Messages

# Before (base R)
message("Processing ", n, " files")

# After (cli)
cli_inform("Processing {n} file{?s}")

# With structure
cli_inform(c(
  "v" = "Successfully loaded {.pkg dplyr}",
  "i" = "Version {packageVersion('dplyr')}"
))

Bullet Types

• "x" - Error/problem (red X)
• "!" - Warning (yellow !)
• "i" - Information (blue i)
• "v" - Success (green checkmark)
• "*" - Bullet point
• ">" - Arrow/pointer

For advanced error design: See references/conditions.md for error design principles, rlang integration, testing strategies, and real-world patterns.

Basic Progress Indicators

Simple Progress Steps

process_data <- function() {
  cli_progress_step("Loading data")
  data <- load_data()

  cli_progress_step("Cleaning data")
  clean <- clean_data(data)

  cli_progress_step("Analyzing data")
  analyze(clean)
}

Basic Progress Bar

process_files <- function(files) {
  cli_progress_bar("Processing files", total = length(files))

  for (file in files) {
    process_file(file)
    cli_progress_update()
  }
}

Auto-Cleanup

Progress bars auto-close when the function exits:

process <- function() {
  cli_progress_bar("Working", total = 100)
  for (i in 1:100) {
    Sys.sleep(0.01)
    cli_progress_update()
  }
  # No need to call cli_progress_done() - auto-closes
}

For advanced progress: See references/progress.md for nested progress, custom formats, parallel processing, all progress variables, and Shiny integration.

Semantic CLI Elements

Headers

cli_h1("Main Section")
cli_h2("Subsection")
cli_h3("Detail")

Alerts

cli_alert_success("Operation completed successfully")
cli_alert_danger("Critical error occurred")
cli_alert_warning("Potential issue detected")
cli_alert_info("Additional information available")

Text and Code

# Regular text with markup
cli_text("This is formatted text with {.emph emphasis}")

# Code blocks
cli_code(c(
  "library(dplyr)",
  "mtcars %>% filter(mpg > 20)"
))

# Verbatim text (no formatting)
cli_verbatim("This is displayed exactly as-is: {not interpolated}")

Lists

# Unordered list
cli_ul()
cli_li("First item")
cli_li("Second item")
cli_end()

# Ordered list
cli_ol()
cli_li("First step")
cli_li("Second step")
cli_end()

# Definition list
cli_dl()
cli_li(c(name = "The name field"))
cli_li(c(email = "The email address"))
cli_end()

Common Workflows

Base R to CLI Migration

# Before: Base R error handling
validate_input <- function(x, y) {
  if (!is.numeric(x)) {
    stop("x must be numeric")
  }
  if (length(y) == 0) {
    stop("y cannot be empty")
  }
  if (length(x) != length(y)) {
    stop("x and y must have the same length")
  }
}

# After: CLI error handling
validate_input <- function(x, y) {
  if (!is.numeric(x)) {
    cli_abort(c(
      "{.arg x} must be numeric",
      "x" = "You supplied a {.cls {class(x)}} vector",
      "i" = "Use {.fn as.numeric} to convert"
    ))
  }

  if (length(y) == 0) {
    cli_abort(c(
      "{.arg y} cannot be empty",
      "i" = "Provide at least one element"
    ))
  }

  if (length(x) != length(y)) {
    cli_abort(c(
      "{.arg x} and {.arg y} must have the same length",
      "x" = "{.arg x} has length {length(x)}",
      "x" = "{.arg y} has length {length(y)}"
    ))
  }