Quick and essential 'R' tricks for better, cleaner, more reproducible scripts.

quickcode is a collection of small, dependable helpers for everyday R scripting: a full family of not.* validation functions, PHP-style array/data-frame operations (push, pop, shuffle, rep), nullish-coalescing and "not in" operators, outlier and distribution detection, super variables, function-usage tracking, RStudio snippet addins, and more. None of it is flashy — it just removes boilerplate you'd otherwise rewrite in every project.

Installation

Install the released version from CRAN:

install.packages("quickcode")

Or install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("oobianom/quickcode")

Load it like any other package:

library(quickcode)

Why quickcode

Consistent negations. is.null() has no built-in opposite. quickcode adds not.null(), not.na(), not.numeric(), not.integer(), not.logical(), not.vector(), not.data(), not.environment(), not.duplicated(), not.image(), not.inherits(), not.exists() and friends, so conditionals read the way you'd say them out loud.
PHP-style array ergonomics. vector_push(), vector_pop(), data_push(), data_pop(), list_push(), data_shuffle(), data_rep() bring the array functions many scripters miss from other languages, working across vectors, lists, and data frames.
Operators that save keystrokes. %nin% (not in), %or% (nullish coalescing), %eo% (error coalescing), and %match% (string similarity) shorten common conditional patterns.
One-call environment resets. refresh() / clean() clear the console, clear the environment, reset the working directory, and reload files/libraries in a single call.
Statistics and outlier helpers. Z-scores, IQR-based and grouped outlier detection, distribution fit-checking (is.normal, is.poisson, is.weibull, ...), geometric mean/SD/CV, and histogram comparisons.
Super variables. newSuperVar() creates a variable that is accessible and mutable from any scope, with optional locking, class enforcement, and a limited number of permitted edits.
RStudio addins. Insert header comments, section dividers, or environment-reset snippets straight from the RStudio Addins menu — no need to remember or retype boilerplate.
Function usage tracking. track_func() wraps functions to record call frequency, timing, and argument patterns, for lightweight profiling and usage analytics.

Quick examples

The not.* family

not.null(NULL)      # TRUE
not.na(NA)           # FALSE
not.integer(45L)     # FALSE
not.integer(45)      # TRUE

Nullish coalescing and "not in"

NULL %or% "default"        # "default"
NA %or% "default"          # "default"
5 %or% "default"           # 5
5 %nin% c(1:10)            # FALSE
5 %nin% c(11:20)           # TRUE

PHP-style vector and data frame helpers

p1 <- c(6, 7, 8)
p2 <- c(1, 2, 3)
vector_push(p1, p2)
p1
#> [1] 6 7 8 1 2 3
df1 <- data.frame(ID = 1:10, ID2 = 1:10)
df2 <- data.frame(ID = 11:20, ID2 = 21:30)
data_push(df1, df2, "rows")

One-line variable initialization

init(a, b, c)               # a, b, c set to NULL
init(x, y, z, value = 5)    # x, y, z set to 5

Environment reset

quickcode::refresh()
quickcode::clean(
  setwd  = "/path/to/project",
  source = c("file1.R", "file2.R"),
  load   = c("data.RData")
)

Super variables

newSuperVar(config, value = list(threshold = 10), lock = TRUE)
config                 # view current value
config.set(list(threshold = 20))  # blocked while locked

Outlier and distribution checks

x <- c(rnorm(100), 50)
detect_outlier2(x)
zscore(x)
is.normal(rnorm(100))

See vignette("quickcode_r_introduction") for a longer walkthrough.

Function reference

NOT / validation functions

Function	Description
`not.null`	Not NULL
`not.na`	Not NA
`not.empty` / `is.empty`	Not empty / is empty
`not.numeric`	Not numeric
`not.integer`	Not an integer
`not.logical`	Not logical
`not.vector`	Not a vector
`not.data`	Not a data object
`not.duplicated`	Not duplicated elements
`not.environment`	Not an environment
`not.image` / `is.image`	File extension is/isn't an image
`not.inherits`	Does not inherit from specified classes
`not.exists`	Object does not exist
`has.error`	Check if a call or expression produces an error

Operators

Operator	Description
`%nin%` (alias `%!in%`)	Not in vector or array
`%or%`	Nullish coalescing operator
`%eo%`	Error coalescing operator
`%match%`	Percentage string similarity match
`%.%`	Simple function chaining

PHP-style array / data operations

Function	Description
`vector_push` / `vector_pop`	Add / remove elements from a vector
`list_push`	Add elements to a list
`data_push` / `data_pop`	Add / remove rows or columns from a data frame
`data_pop_filter`	Remove elements from data matching a filter
`data_rep` / `rows.rep` / `cols.rep`	Duplicate rows or columns X times
`data_shuffle` / `list_shuffle` / `vector_shuffle`	Shuffle a data frame, list, or vector
`switch_rows` / `switch_cols`	Swap two rows or columns
`sample_by_column`	Re-sample a dataset by column
`mutate_filter`	Mutate only a subset of a dataset
`add_key` (alias `indexed`)	Add index keys to a vector, list, data frame, or matrix

Variables & environment

Function	Description
`init`	Initialize one or more variables/objects at once
`newSuperVar`	Create a variable accessible/mutable from any scope, with locking and edit limits
`setOnce`	Set a variable only once
`refresh` / `clean` / `libraryAll`	Clear environment/console, reset working directory, load files & libraries
`summarize.envobj`	Summarize environment objects and their sizes
`lastwd`	Return to the previous working directory

Statistics, outliers & distributions

Function	Description
`zscore` / `zscore_outlier` / `zscore_outlier2`	Z-score calculation and z-score-based outlier flagging
`detect_outlier` / `detect_outlier2` / `iqr_outlier`	Outlier detection (including grouped)
`is.normal`, `is.lognormal`, `is.uniform`, `is.poisson`, `is.gamma`, `is.weibull`, `is.cauchy`, `is.logistic`	Test whether data fits a given distribution
`getDistribution`	Fit-check data against a distribution
`geo.mean`, `geo.sd`, `geo.cv`	Geometric mean, standard deviation, coefficient of variation
`mode.calc`	Mode of a numeric or character vector
`na.cumsum`	Cumulative sum with NA removal
`normalize.vector`	Normalize a numeric vector to [0, 1]
`sub.range` / `in.range`	Range difference / range membership checks
`unique_len`	Combine `unique()` and `length()`
`pairDist`	Distance of points from a cluster center
`compHist`	Compare histograms of two distributions

Machine learning & modeling utilities

Function	Description
`cat_to_num` / `cat_to_num2`	Convert categorical values to numeric
`from_tensor_slices`	Create tensor-like slices from a data frame or matrix
`multihead_att`	Multi-head attention computation
`learn_rate_scheduler`	Learning rate scheduling utilities
`make_dosing_df`	Create subject-by-time dosing records with covariates

Strings & text

Function	Description
`bionic_txt`	Generate bionic-reading formatted text
`randString`	Generate a random string
`strsplit.bool` / `strsplit.num`	Split a string into a boolean / numeric vector
`percent_match`	Percentage match between two strings
`ndecimal`	Count decimal places in a number
`as.boolean` / `yesNoBool`	Convert between boolean representations
`extract_comment` / `remove_comment` / `remove_content_in_quotes`	Text/comment extraction and cleanup
`getDate`	Extract all dates from a string
`extract_IP`	Extract IP addresses from a string

Dates

Function	Description
`date1to3` / `date3to1`	Combine vectors into a Date, or split a Date into vectors
`getWeekSeq`	Convert dates into numeric week counts
`is.leap`	Check whether a year is a leap year
`fAddDate`	Append a date to a filename
`is.increasing` / `is.decreasing`	Check whether values in a vector are increasing/decreasing

Files & filesystem

Function	Description
`duplicate`	Duplicate a file with global text replacement
`ai.duplicate`	Prompt-guided duplication and editing of files
`trim.file`	Remove empty lines from a file
`sort_file_type` / `sort_length`	Sort a vector by file type or content length
`read.csv.print` / `read.table.print`	Read and preview the first X rows/columns of a file
`insertInText`	Insert a string into the current RStudio file (Shiny helper)

RStudio addins & snippets

Addin / function	Description
`add.header`	Add a header comment to the current R file
`header.rmd`	Add a header comment to the current Rmd file
`add.sect.comment`	Insert a custom section comment
`add.snippet.clear`	Insert a console-clear / set-directory snippet

Colors & shapes

Function	Description
`rcolorconst`	Named R color constants
`mix.color` / `mix.cols.btw`	Blend two or more colors
`setDisAlpha` / `unsetDisAlpha`	Set/unset color transparency
`create_shape`	Create geometric shapes with optional text

Package & repo utilities

Function	Description
`find_packages`	Search CRAN packages by keyword
`archivedPkg`	List all CRAN-archived R packages
`rDecomPkg`	Check whether a package has been decommissioned from CRAN
`getGitRepoStart` / `getGitRepoChange`	Fetch a GitHub repo's creation / last-updated date
`track_func`	Track function call frequency, timing, and usage patterns

Math & misc

Function	Description
`plus` / `minus` / `inc`	Increment or decrement a vector by a value
`number`	Generate random integers
`const`	Common mathematical constants
`math.mm` / `math.qt`	Miscellaneous math and confidence-interval computations
`error.out` (`%eo%`)	Return an alternative value if an expression errors
`or` (`%or%`)	Return an alternative value if an expression is empty/NA/NULL
`chain_sep` (`%.%`) / `chain_func`	Simple function chaining

This list covers the most commonly used functions; run library(help = "quickcode") or browse the man/ directory for the complete, authoritative reference with full argument details and runnable examples.

Vignettes

vignette("quickcode_r_introduction") — general tour of the package
vignette("add_today_date_to_filenames_quickcode") — appending dates to filenames with fAddDate()
vignette("nullish_coalescing_operator_r") — using %or% and %eo%
vignette("track_function_usage_r") — profiling function usage with track_func()