Match Regular Expressions with a Nicer 'API'
A small wrapper on regular expression matching functions regexpr
and gregexpr to return the results in tidy data frames.
source("https://install-github.me/MangoTheCat/rematch2")Note that rematch2 is not compatible with the original rematch package.
There are at least three major changes:
- The order of the arguments for the functions is different. In
rematch2thetextvector is first, andpatternis second. - In the result,
.matchis the last column instead of the first. rematch2returnstibbledata frames. See https://github.com/hadley/tibble.
library(rematch2)With capture groups:
dates <- c("2016-04-20", "1977-08-08", "not a date", "2016",
"76-03-02", "2012-06-30", "2015-01-21 19:58")
isodate <- "([0-9]{4})-([0-1][0-9])-([0-3][0-9])"
re_match(text = dates, pattern = isodate)#> # A tibble: 7 × 5
#> `` `` `` .text .match
#> <chr> <chr> <chr> <chr> <chr>
#> 1 2016 04 20 2016-04-20 2016-04-20
#> 2 1977 08 08 1977-08-08 1977-08-08
#> 3 <NA> <NA> <NA> not a date <NA>
#> 4 <NA> <NA> <NA> 2016 <NA>
#> 5 <NA> <NA> <NA> 76-03-02 <NA>
#> 6 2012 06 30 2012-06-30 2012-06-30
#> 7 2015 01 21 2015-01-21 19:58 2015-01-21
Named capture groups:
isodaten <- "(?<year>[0-9]{4})-(?<month>[0-1][0-9])-(?<day>[0-3][0-9])"
re_match(text = dates, pattern = isodaten)#> # A tibble: 7 × 5
#> year month day .text .match
#> <chr> <chr> <chr> <chr> <chr>
#> 1 2016 04 20 2016-04-20 2016-04-20
#> 2 1977 08 08 1977-08-08 1977-08-08
#> 3 <NA> <NA> <NA> not a date <NA>
#> 4 <NA> <NA> <NA> 2016 <NA>
#> 5 <NA> <NA> <NA> 76-03-02 <NA>
#> 6 2012 06 30 2012-06-30 2012-06-30
#> 7 2015 01 21 2015-01-21 19:58 2015-01-21
A slightly more complex example:
github_repos <- c(
"metacran/crandb",
"jeroenooms/curl@v0.9.3",
"jimhester/covr#47",
"hadley/dplyr@*release",
"mangothecat/remotes@550a3c7d3f9e1493a2ba",
"/$&@R64&3"
)
owner_rx <- "(?:(?<owner>[^/]+)/)?"
repo_rx <- "(?<repo>[^/@#]+)"
subdir_rx <- "(?:/(?<subdir>[^@#]*[^@#/]))?"
ref_rx <- "(?:@(?<ref>[^*].*))"
pull_rx <- "(?:#(?<pull>[0-9]+))"
release_rx <- "(?:@(?<release>[*]release))"
subtype_rx <- sprintf("(?:%s|%s|%s)?", ref_rx, pull_rx, release_rx)
github_rx <- sprintf(
"^(?:%s%s%s%s|(?<catchall>.*))$",
owner_rx, repo_rx, subdir_rx, subtype_rx
)
re_match(text = github_repos, pattern = github_rx)#> # A tibble: 6 × 9
#> owner repo subdir ref pull release catchall
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 metacran crandb
#> 2 jeroenooms curl v0.9.3
#> 3 jimhester covr 47
#> 4 hadley dplyr *release
#> 5 mangothecat remotes 550a3c7d3f9e1493a2ba
#> 6 /$&@R64&3
#> # ... with 2 more variables: .text <chr>, .match <chr>
Extract all names, and also first names and last names:
name_rex <- paste0(
"(?<first>[[:upper:]][[:lower:]]+) ",
"(?<last>[[:upper:]][[:lower:]]+)"
)
notables <- c(
" Ben Franklin and Jefferson Davis",
"\tMillard Fillmore"
)
not <- re_match_all(notables, name_rex)
not#> # A tibble: 2 × 4
#> first last .text .match
#> <list> <list> <chr> <list>
#> 1 <chr [2]> <chr [2]> Ben Franklin and Jefferson Davis <chr [2]>
#> 2 <chr [1]> <chr [1]> \tMillard Fillmore <chr [1]>
not$first#> [[1]]
#> [1] "Ben" "Jefferson"
#>
#> [[2]]
#> [1] "Millard"
not$last#> [[1]]
#> [1] "Franklin" "Davis"
#>
#> [[2]]
#> [1] "Fillmore"
not$.match#> [[1]]
#> [1] "Ben Franklin" "Jefferson Davis"
#>
#> [[2]]
#> [1] "Millard Fillmore"
re_exec and re_exec_all are similar to re_match and re_match_all,
but they also return match positions. These functions return match
records. A match record has three components: match, start, end, and
each component can be a vector. It is similar to a data frame in this
respect.
pos <- re_exec(notables, name_rex)
pos#> # A tibble: 2 × 4
#> first last .text .match
#> * <list> <list> <chr> <list>
#> 1 <list [3]> <list [3]> Ben Franklin and Jefferson Davis <list [3]>
#> 2 <list [3]> <list [3]> \tMillard Fillmore <list [3]>
Unfortunately R does not allow hierarchical data frames (i.e. a column of a
data frame cannot be another data frame), but rematch2 defines some
special classes and an $ operator, to make it easier to extract parts
of re_exec and re_exec_all matches. You simply query the match,
start or end part of a column:
pos$first$match#> [1] "Ben" "Millard"
pos$first$start#> [1] 3 2
pos$first$end#> [1] 5 8
re_exec_all is very similar, but these queries return lists, with
arbitrary number of matches:
allpos <- re_exec_all(notables, name_rex)
allpos#> # A tibble: 2 × 4
#> first last .text .match
#> <list> <list> <chr> <list>
#> 1 <list [3]> <list [3]> Ben Franklin and Jefferson Davis <list [3]>
#> 2 <list [3]> <list [3]> \tMillard Fillmore <list [3]>
allpos$first$match#> [[1]]
#> [1] "Ben" "Jefferson"
#>
#> [[2]]
#> [1] "Millard"
allpos$first$start#> [[1]]
#> [1] 3 20
#>
#> [[2]]
#> [1] 2
allpos$first$end#> [[1]]
#> [1] 5 28
#>
#> [[2]]
#> [1] 8
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