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# _A multiplexer for your data pipelines_

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/taber)](http://cran.r-project.org/package=taber)

[![total_downloads](http://cranlogs.r-pkg.org/badges/grand-total/taber)](http://cran.r-project.org/package=taber)

## taber

`taber` is for people who use `dplyr` and `magrittr`. If your workflow is heavy on pipes, sometimes you need to do different operations on different parts of the data, sometimes that's cleaning or transforming the data. In my own work I deal with flight data and I need to do one set of operations on arrival data and another on departure data but all of it has the same format so I'd like to keep it together as one dataset. 

## Installation

```{r, eval=FALSE}
# taber is available on CRAN
install.packages("taber")

# the development version is available from github and can be installed most easily with devtools
devtools::install_github("restonslacker/taber")
```

## Example: Quicksort
```{r, eval=FALSE}
qsrt_ <- function(.data){
  if(length(.data)==0 || nrow(.data)==0 || all(.data$zed==.data$zed[1])){
    return((.data))
  }

  .data %>% scion(zed<=zed[1], false_fun=qsrt_ ) %>%
    scion(zed!=zed[1]) %>%
    qsrt_ %>%
    graft %>%
    graft
}

data.frame(zed = sample(1:25, 25, FALSE)) %>% qsrt_
```

## About the name

Taber is named for George Lindley Taber, noted American horticulturist and the eponym for my mother's favorite azalea. 

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taber's Issues

Issue of lazy evaluation with dev magrittr

Hello, I'm seeing an issue with the development version of magrittr which switches to a lazy evaluation approach. It causes this error in your package:

> aframe <- data.frame(zed = runif(100))
> set_to_zero <- . %>% mutate(zed = 0)
> aframe %>% scion(zed >0.5, false_fun=set_to_zero) %>% mutate(zed=1) %>% graft
Error in .pop() : 
  No more scions on stack. Perhaps you meant to specify the "data2" argument to graft()?
Calls: %>% -> graft -> .pop

That's because the pipeline is now evaluated as if it were nested, instead of linearly:

graft(mutate(scion(aframe, zed > 0.5, false_fun = set_to_zero), zed = 1))

Because of lazy evaluation, the input to graft has not been evaluated yet when you check if data2 is missing. One way to fix this is to force() the input like this:

--- a/R/tabe.R
+++ b/R/tabe.R
@@ -62,6 +62,7 @@ scion <- function(.data, ..., false_fun, false_name, false_env){
 #' @importFrom dplyr intersect
 #' @importFrom dplyr full_join
 graft <- function(.data, combine_fun, data2){
+  force(.data)
   if(missing(data2))
     data2 <- .pop()

We're planning to release magrittr in one month. It'd be great if you could update your package :)

Note that the future native pipe in the next version of R will use this same approach, so by fixing your package for the new magrittr behaviour you'll make it usable with the native pipe as well.

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