Install with devtools::install_gh("moodymudskipper/mmpipe")
This package proposes new pipe operators, a function to define custom operators easily, 2 other pipe friendly functions for conditional steps or printing.
- %W>% : silence warnings
- %V>% : uses
View()on the output - %L>% : Logs the relevant call to the console
- %P>% : uses
print()on the output - %S>% : prints the
summary()of the output - %G>% : uses
tibble::glimpseon the output - %D>% : Debugs the pipe chain at the relevant step
- %C>% : Clocks the relevant step
- add_pipe : build custom pipe
- pif : conditional steps
- pprint : pipe friendly printing
magrittr's operators are also exported so they can be used without attaching alias functions.
When we attach mmpipe the functions magrittr:::is_pipe and magrittr:::wrap_function are modified to register our new pipes in the package, thus a couple warnings are displayed.
library(mmpipe)
#> Warning: S3 method '-.gg' was declared in NAMESPACE but not found
#> Warning: changing locked binding for 'is_pipe' in 'magrittr' whilst loading
#> 'mmpipe'
#> Warning: changing locked binding for 'wrap_function' in 'magrittr' whilst
#> loading 'mmpipe'silence a warning:
data.frame(a = c(1,-1)) %W>% transform(a = sqrt(a))
#> a
#> 1 1
#> 2 NaNlog steps in the console:
iris %L>% {Sys.sleep(1);head(.,2)} %L>% {Sys.sleep(2);.[4:5]}
#> {
#> Sys.sleep(1)
#> head(., 2)
#> }
#> {
#> Sys.sleep(2)
#> .[4:5]
#> }
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosause print, summary or glimpse on output:
iris %P>% head(2) %P>% `[`(4:5)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosa
#>
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosa
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosa
iris %S>% head(2) %S>% `[`(4:5)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> Min. :4.90 Min. :3.000 Min. :1.4 Min. :0.2 setosa :2
#> 1st Qu.:4.95 1st Qu.:3.125 1st Qu.:1.4 1st Qu.:0.2 versicolor:0
#> Median :5.00 Median :3.250 Median :1.4 Median :0.2 virginica :0
#> Mean :5.00 Mean :3.250 Mean :1.4 Mean :0.2
#> 3rd Qu.:5.05 3rd Qu.:3.375 3rd Qu.:1.4 3rd Qu.:0.2
#> Max. :5.10 Max. :3.500 Max. :1.4 Max. :0.2
#>
#> Petal.Width Species
#> Min. :0.2 setosa :2
#> 1st Qu.:0.2 versicolor:0
#> Median :0.2 virginica :0
#> Mean :0.2
#> 3rd Qu.:0.2
#> Max. :0.2
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosa
iris %G>% head(2) %G>% `[`(4:5)
#> Observations: 2
#> Variables: 5
#> $ Sepal.Length <dbl> 5.1, 4.9
#> $ Sepal.Width <dbl> 3.5, 3.0
#> $ Petal.Length <dbl> 1.4, 1.4
#> $ Petal.Width <dbl> 0.2, 0.2
#> $ Species <fct> setosa, setosa
#>
#> Observations: 2
#> Variables: 2
#> $ Petal.Width <dbl> 0.2, 0.2
#> $ Species <fct> setosa, setosa
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosaview steps of chain in the viewer:
iris %V>% head(2) %V>% `[`(4:5)debug the chain:
iris %>% head(2) %D>% `[`(4:5)
#> debugging in: pipe_browse()
#> debug: .[4:5]
#> exiting from: pipe_browse()
#> Petal.Width Species
#> 1 0.2 setosa
#> 2 0.2 setosatime operations:
iris %C>% head(2) %C>% {Sys.sleep(2);.}
#> user system elapsed
#> 0 0 0
#>
#> user system elapsed
#> 0 0 2
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosaWe create an operator by feeding to add_pipe its raw name and the modified body of the expression a regular pipe call would return.
the operator is created and magrittr's namespace is modified to make the new operator compatible.
This is not obvious so let's see some examples, if we wanted to recreate existing operators.
Redefining %P2>% as %P>% twin :
add_pipe(`%P2>%`, substitute({. <- print(b);cat("\n"); .}, list(b = body)))
iris %P2>% head(3) %>% head(2)
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosaRedefining %T2>% as %T>% twin :
add_pipe(`%T2>%`, call("{", body, quote(.)))
iris %T2>% {message("side effect")} %>% head(2)
#> side effect
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosaRedefining %W2>% as %W>% twin :
add_pipe(`%W2>%`, substitute(
{options(warn = -1); on.exit(options(warn = w)); b},
list(w = options()$warn, b = body)))
data.frame(a = c(1,-1)) %W2>% transform(a = sqrt(a))
#> a
#> 1 1
#> 2 NaNSee magrittr:::wrap_function's code for a better understanding.
See also functions rm_pipe and list_pipes.
Using functions:
iris %>% pif(is.data.frame, dim, nrow)
#> [1] 150 5Using formulas:
iris %>% pif(~is.numeric(Species), ~"numeric :)",~paste(class(Species)[1],":("))
#> [1] "factor :("Using raw expressions:
iris %>% pif(nrow(iris) > 2, head(iris,2))
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosaBe careful with expressions!
iris %>% pif(TRUE, dim, warning("this will be evaluated"))
#> Warning in pif(., TRUE, dim, warning("this will be evaluated")): this will
#> be evaluated
#> [1] 150 5
iris %>% pif(TRUE, dim, ~warning("this won't be evaluated"))
#> [1] 150 5library(ggplot2)
iris %>%
pprint(~"hello") %>%
head(2) %>%
transform(Species = NULL) %>%
pprint(rowSums,na.rm = TRUE) %>%
pprint(~setNames(.[1:2],toupper(names(.[1:2])))) %>%
pprint(dim)
#> [1] "hello"
#> 1 2
#> 10.2 9.5
#> SEPAL.LENGTH SEPAL.WIDTH
#> 1 5.1 3.5
#> 2 4.9 3.0
#> [1] 2 4