r2r
provides a flexible implementation of hash tables in R, allowing
for:
You can install the released version of r2r
from CRAN with:
install.packages("r2r")
and the development version from my R-universe repository, with:
install.packages("r2r", repos = "https://vgherard.r-universe.dev")
library(r2r)
<- hashmap()
m
# Insert and query a single key-value pair
"user" ]] <- "vgherard"
m[[ "user" ]]
m[[ #> [1] "vgherard"
# Insert and query multiple key-value pairs
c(1, 2, 3) ] <- c("one", "two", "three")
m[ c(1, 3) ]
m[ #> [[1]]
#> [1] "one"
#>
#> [[2]]
#> [1] "three"
# Keys and values can be arbitrary R objects
lm(mpg ~ wt, mtcars) ]] <- c(TRUE, FALSE, TRUE)
m[[ lm(mpg ~ wt, mtcars) ]]
m[[ #> [1] TRUE FALSE TRUE
For further details, including an introductory vignette illustrating
the features of r2r
hash maps, you can consult the
r2r
website.
If you encounter a bug, want to suggest a feature or need further help,
you can open a GitHub
issue.
hash
CRAN package {hash}
also offers an implementation of hash tables based on R environments.
The two tables below offer a comparison between {r2r}
and
{hash}
(for more details, see the benchmarks
Vignette)
Feature | r2r | hash |
---|---|---|
Basic data structure | R environment | R environment |
Arbitrary type keys | X | |
Arbitrary type values | X | X |
Arbitrary hash function | X | |
Arbitrary key comparison function | X | |
Throw or return default on missing keys | X | |
Hash table inversion | X |
Features supported by {r2r} and {hash}.
Task | Comparison |
---|---|
Key insertion | {r2r} ~ {hash} |
Key query | {r2r} < {hash} |
Key deletion | {r2r} << {hash} |
Performances of {r2r} and {hash} for basic hash table operations.