strict

The goal of strict to make R behave a little more strictly, making base functions more likely to throw an error rather than returning potentially ambiguous results.

library(strict)

Installation

# install.packages("devtools")
devtools::install_github("hadley/strict")

Features

library(strict)

• An alternative conflict resolution mechanism. Instead of warning about conflicts on package load and letting the last loaded package win, strict throws an error when you access ambiguous functions:

  library(strict)
  library(plyr)
  library(Hmisc)
  #> Loading required package: lattice
  #> Loading required package: survival
  #> Loading required package: Formula
  #> Loading required package: ggplot2
  
  is.discrete
  #> Error: [strict]
  #> Multiple definitions found for is.discrete.
  #> Please pick one:
  #>  * Hmisc::is.discrete
  #>  * plyr::is.discrete
  

  (Thanks to @krlmlr for this neat idea!)

• Shims for functions with "risky" arguments, i.e. arguments that either rely on global options (like

  stringsAsFactors

  ) or have computed defaults that 90% evaluate to one thing (like

  drop

  ). strict forces you to supply values for these arguments.

  library(strict)
  mtcars[, 1]
  #> Error: [strict]
  #> Please explicitly specify `drop` when selecting a single column
  #> Please see ?strict_drop for more details
  
  data.frame(x = "a")
  #> Error: [strict]
  #> Please supply a value for stringsAsFactors argument.
  #> Please see ?strict_arg for more details
  

• Automatically sets options to warn when partial matching occurs.

  library(strict)
  
  df  Warning in $.data.frame(df, x): Partial match of 'x' to 'xyz' in data
  #> frame
  #> [1] 1
  

• T

  and

  F

  generate errors, forcing you to use

  TRUE

  and

  FALSE

  .

  library(strict)
  T
  #> Error: [strict]
  #> Please use TRUE, not T
  

• sapply()

  throws an error suggesting that you use the type-safe

  vapply()

  instead.

  apply()

  throws an error if you use it with a data frame.

  library(strict)
  sapply(1:10, sum)
  #> Error: [strict]
  #> Please use `vapply()` instead of `sapply()`.
  #> Please see ?strict_sapply for more details
  

• :

  will throw an error instead of creating a decreasing sequence that terminates in 0.

  library(strict)
  
  x  Error: [strict]
  #> Tried to create descending sequence 1:0. Do you want to seq_along() instead?
  #> 
  #> Please see ?shim_colon for more details
  

• diag()

  and

  sample()

  throw an error if given scalar

  x

  . This avoids an otherwise unpleasant surprise.

  library(strict)
  
  sample(5:3)
  #> [1] 5 4 3
  sample(5:4)
  #> [1] 5 4
  lax(sample(5:5))
  #> [1] 3 2 1 4 5
  sample(5:5)
  #> Error: [strict]
  #> sample() has surprising behaviour when x is a scalar.
  #> Use sample.int() instead.
  #> Please see ?strict_sample for more details
  

Once strict is loaded, you can continue to run code in a lax manner using

lax()