# Simple Usage

{flow}’s two main functions are `flow_view()` and `flow_run()`, which require only one argument for the simplest use cases.

    library(flow)

## `flow_view()`

`flow_view()` is used to display the logic of a function, a one item named list containing a function, a script or a quoted expression.

    # display a function's body
    flow_view(ave)

    # if non standard evaluation is an issue, use a one element named list
    fun <- ave
    flow_view(list(ave = fun))

    # display script
    flow_view("../tests/testthat.R")

    # display quoted expression
    flow_view(quote(if(1 + 1 == 2) {"ok"} else {"oh no"}))

`if` statements always branch into two paths, whether an `else` clause is present or not. `for`, `while`, and `repeat` loops are also supported.

The colored circles are exit points, orange for errors (using `stop()`), green for returned values (using `return()`) or just reaching the end of the function.

If you installed {plantuml} you can set `engine` to `"plantuml"`, plantuml diagrams are a bit less flexible but they often look more polished and compact.

    # display a function's body
    flow_view(ave, engine = "plantuml")

## `flow_run()`

`flow_run` actually executes a call to a function, and displays the logical path. It takes as a first argument an unquoted call to the function we want to dive in.

    factorial <- function(x) {
      if(!is.integer(x)) stop("`x` must be integer!")
      res <- 1
      for(i in 2:x) {
        res <- res * i
        if(res > 1000) stop("too big!!!")
      }
      res
    }

    flow_run(factorial(5L))
    #> [1] 120

`flow_run()` counts how many times code blocks were entered and these numbers are displayed next to the edges between parenthesis.

It can also be used on calls that fail, which is convenient for debugging, for instance the following call fails :

    flow_run(factorial(10L))
    #> Error in if (!out %in% c("code", "data")) {: argument is of length zero

If you call `flow_run()` on a call to an S3 generic, the appropriate S3 method will be represented.

    vec <- c(1:3, NA)
    flow_run(median(vec, na.rm = TRUE))
    #> [1] 2

The `"plantuml"` engine is not supported by `flow_run()`.