Dict is a R package which implements a key-value
dictionary data structure based on R6 class. It is designed to be
similar usages with other languages’ dictionary implementations
(e.g. Python).
R’s vector and list, of course can have
names, so you can get and set value by a name (key) like a dictionary.
Using regular data structure must be a recommended way in the most of
cases. But, if you are interested in the following characteristics, this
package is for you!
install.packages("Dict")
# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("five-dots/Dict")To instantiate a dict, you can pass any length of key-value pairs to the initialize method.
library(Dict)
ages <- Dict$new(
Charlie = 40L,
Alice = 30L,
Bob = 25L,
.class = "integer",
.overwrite = TRUE
)
ages# A tibble: 3 x 2
key value
<chr> <list>
1 Charlie <int [1]>
2 Alice <int [1]>
3 Bob <int [1]>
dict() can be used instead of Dict$new()
as some IDEs cloud not show R6’s function arguments hint..class specifies what kind of objects the dictionary
can contains. Default “any” means the dict cloud have any type of
value..overwrite controls the behavior when the same key is
added.tbl_df from tibble package
whose key is a character column and value is a list column. You can use
various existing tooling for data.frame or
tibble to manipulate dict items.A value can be access by both Dict$get() or
`[` with a character key or integer index of items
rows.
ages["Bob"]
ages$get("Bob")
ages$get(3L)[1] 25
[1] 25
[1] 25
If no key found, value of default is returned.
ages["Michael", default = 30][1] 30
Adding a item also can be done by R6 methods Dict$add()
or `[<-`.
ages["John"] <- 18L # or ages$add(John = 18L)
ages["John"][1] 18
Can be overridden if .overwrite = TRUE (default).
ages["Bob"] <- 26L
ages$get("Bob")[1] 26
Remove item:
ages$remove("Bob")Check if items contains a key:
ages$has("Bob")[1] FALSE
Sort by keys:
ages$sort()
ages# A tibble: 3 x 2
key value
<chr> <list>
1 Alice <int [1]>
2 Charlie <int [1]>
3 John <int [1]>
Clear items:
ages$clear()
ages# A tibble: 0 x 2
# … with 2 variables: key <chr>, value <list>
Fields:
ages$keys
ages$values
ages$items
ages$length