Introduction

The tinycodet R-package adds some functions to help in your coding etiquette. It primarily focuses on 4 aspects:

Safer decimal (in)equality testing, standard-evaluated alternatives to with() and aes(), and other functions for safer coding.
A new package import system, that attempts to combine the benefits of using a package without attaching, with the benefits of attaching a package.
Extending the string manipulation capabilities of the stringi R package.
Reducing repetitive code.

The tinycodet R-package has only one dependency, namely stringi. Most functions in this R-package are fully vectorized and optimized, and have been well documented.

Here I’ll give a quick glimpse of what is possible in this R package.

Safer functionality

‘tinycodet’ adds some functions to help in coding more safely:

with_pro() and aes_pro() are standard-evaluated alternatives to base::with() and ggplot2::aes(). These use formulas as input.
In base R, (0.1*3) == 0.3 gives FALSE, due to the way decimal numbers are stored in programming languages like R and Python. tinycodet adds safer truth testing operators, that give correct results.
One can re-assign the values T and F. One can even run T <- FALSE and F <- TRUE!. tinycodet adds the lock_TF() function that forces T to stay TRUE and F to stay FALSE.

One example of aes_pro():

requireNamespace("ggplot2")
d <- import_data("ggplot2", "mpg")

x <- ~ cty
y <- ~ sqrt(hwy)
color <- ~ drv

ggplot2::ggplot(d, aes_pro(x, y, color = color)) +
  ggplot2::geom_point()

New import system

One can use a package without attaching the package (for example using ::), or one can attach a package (for example using library() or require()). The advantages and disadvantages of using without attaching a package versus attaching a package - at least those relevant for now - can be compactly presented in the following table:

	aspect	::	attach
1	prevent masking functions from other packages	Yes (+)	No (-)
2	prevent masking core R functions	Yes (+)	No (-)
3	clarify which function came from which package	Yes (+)	No (-)
4	place/expose functions only in current environment instead of globally	Yes (+)	No (-)
5	prevent namespace pollution	Yes (+)	No (-)
6	minimize typing - especially for infix operators (i.e. typing package::`%op%`(x, y) instead of `x %op% y` is cumbersome)	No (-)	Yes (+)
7	use multiple related packages, without constantly switching between package prefixes	No (-)	Yes (+)
	NOTE: + = advantage, - = disadvantage

What tinycodet attempts to do with its import system, is to somewhat find the best of both worlds. It does this by introducing the following functions:

import_as(): Import a main package, and optionally its re-exports + its dependencies + its extensions, under a single alias. This essentially combines the attaching advantage of using multiple related packages (row 7 on the table above), whilst keeping most advantages of using without attaching a package.
import_inops(): Expose infix operators from a package or an alias object to the current environment. This gains the attaching advantage of less typing (row 6 in table above), whilst simultaneously avoiding the disadvantage of attaching functions from a package globally (row 4).
import_data(): Directly return a data set from a package, to allow straight-forward assignment.

Here is an example using tinycodet's new import system; note that the following code is run without attaching a single R package (besides tinycodet itself of course):

# importing "tidytable" + "data.table" under alias "tdt.":
import_as( 
  ~ tdt., "tidytable", dependencies = "data.table"
)

## Importing packages and registering methods...

## Done
## You can now access the functions using `tdt.$`
## For conflicts report, packages order, and other attributes, run `attr.import(tdt.)`

# exposing operators from `magrrittr` to current environment:
import_inops("magrittr")

## Checking for conflicting infix operators in the current environment...

## Placing infix operators in current environment...

## Done

# directly assigning the "starwars" dataset to object "d":
d <- import_data("dplyr", "starwars") 

# see it in action:
d %>% tdt.$filter(species == "Droid") %>%
  tdt.$select(name, tdt.$ends_with("color"))

## # A tidytable: 6 × 4
##   name   hair_color skin_color  eye_color
##   <chr>  <chr>      <chr>       <chr>    
## 1 C-3PO  <NA>       gold        yellow   
## 2 R2-D2  <NA>       white, blue red      
## 3 R5-D4  <NA>       white, red  red      
## 4 IG-88  none       metal       red      
## 5 R4-P17 none       silver, red red, blue
## 6 BB8    none       none        black

Extending the string manipulation capabilities of stringi

‘tinycodet’ adds some additional functionality to ‘stringi’ (the primary package for string manipulation):

stri_locate_ith(): ‘stringi’ has functions to locate the first and last pattern occurrences. ‘tinycodet’ adds stri_locate_ith(), which can locate the \(i^\textrm{th}\) pattern occurrence.
‘stringi’ has some limited string arithmetic operators: %s+% and %s*%. ‘tinycodet’ enlarges this set with additional string arithmetic operators.
‘stringi’ has several string search and relation operators (%s==%, s%!=%). ‘tinycodet’ also enlarges this set with pattern searching operators (%s{}%, %s!{}%, strfind()<-).
cutting strings into pieces, without removing the delimiter, lies at the core of (almost) all boundaries-operations in ‘stringi’. For the user’s convenience, ‘tinycodet’ adds the strcut_ functions to cut strings in a more concise way (with less keystrokes).

Reduce repetitive code

# in base R:
ifelse( # repetitive, and gives unnecessary warning
  is.na(object>0), -Inf,
  ifelse(
    object>0,  log(object), object^2
  )
)
mtcars$mpg[mtcars$cyl>6] <- (mtcars$mpg[mtcars$cyl>6])^2 # long

# with tinycodet:
object |> transform_if(\(x)x>0, log, \(x)x^2, \(x) -Inf) # compact & no warning
mtcars$mpg[mtcars$cyl>6] %:=% \(x)x^2 # short

The Articles

If you’re still interested, I invite you to read the articles on the website (https://tony-aw.github.io/tinycodet/), and perhaps try out the package yourself.

The following articles are currently present:

Safer functionality: Describes the functions for safer/stricter coding.
Import system - main functions: Description of the main functions of the package import system introduced by tinycodet.
Import system - additional details: Additional important details on the tinycodet import system.
String related functions: Describes the tinycodet functions that extend the string manipulation capabilities of stringi.
String related infix operators: Describes the tinycodet infix operators that extend the string manipulation capabilities of stringi.
Don’t Repeat Yourself: Describes the tinycodet functions that help reduce repetitions in your code.
Miscellaneous functionality: Various other functions and operators that tinycodet introduces.
Relations to other R packages: Describes how tinycodet relates to other R packages, mostly regarding compatibility.

For a complete list of functions introduced by tinycodet, please see the References page.