Vectorised Pattern Matching with Keyboard Shortcut

Convenient wrapper around grepl() to match a pattern: x %like% pattern. It always returns a logical vector and is always case-insensitive (use x %like_case% pattern for case-sensitive matching). Also, pattern can be as long as x to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.

like(x, pattern, ignore.case = TRUE)

x %like% pattern

x %unlike% pattern

x %like_case% pattern

x %unlike_case% pattern

Source

Idea from the like function from the data.table package, although altered as explained in Details.

Arguments

x: a character vector where matches are sought, or an object which can be coerced by as.character() to a character vector.
pattern: a character vector containing regular expressions (or a character string for fixed = TRUE) to be matched in the given character vector. Coerced by as.character() to a character string if possible.
ignore.case: if FALSE, the pattern matching is case sensitive and if TRUE, case is ignored during matching.

Value

A logical vector

Details

These like() and %like%/%unlike% functions:

Are case-insensitive (use %like_case%/%unlike_case% for case-sensitive matching)
Support multiple patterns
Check if pattern is a valid regular expression and sets fixed = TRUE if not, to greatly improve speed (vectorised over pattern)
Always use compatibility with Perl unless fixed = TRUE, to greatly improve speed

Using RStudio? The %like%/%unlike% functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like Shift+Ctrl+L or Shift+Cmd+L (see menu Tools > Modify Keyboard Shortcuts...). If you keep pressing your shortcut, the inserted text will be iterated over %like% -> %unlike% -> %like_case% -> %unlike_case%.

Stable Lifecycle

The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.

If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.

Examples

a <- "This is a test"
b <- "TEST"
a %like% b
#> TRUE
b %like% a
#> FALSE

# also supports multiple patterns
a <- c("Test case", "Something different", "Yet another thing")
b <- c(     "case",           "diff",      "yet")
a %like% b
#> TRUE TRUE TRUE
a %unlike% b
#> FALSE FALSE FALSE

a[1] %like% b
#> TRUE FALSE FALSE
a %like% b[1]
#> TRUE FALSE FALSE

# get isolates whose name start with 'Ent' or 'ent'
example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
# \donttest{
# faster way, since mo_name() is context-aware:
example_isolates[which(mo_name() %like% "^ent"), ]

if (require("dplyr")) {
  example_isolates %>%
    filter(mo_name() %like% "^ent")
}
# }