Target Markdown with defaults
In targets: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

Try some code chunks interactively, then render this report. Render again to see if the targets correctly skip. Delete the HTML file, _targets.R, _targets_r/, and _targets/ after rendering.

Packages

The example requires several R packages, and targets must be version 0.5.0.9000 or above.

install.packages(c("biglm", "dplyr", "ggplot2", "readr", "targets", "tidyr"))

Setup

First, load targets to activate the specialized knitr engine for Target Markdown.

library(targets)

Near the top, you may also wish to remove the _targets_r directory previously written by non-interactive runs of the report.

tar_unscript()

Globals

We first define some global options/functions common to all targets. The function below plots a histogram of ozone concentrations, and our histogram target will need it.

```{targets example-globals, tar_globals = TRUE} options(tidyverse.quiet = TRUE) tar_option_set(packages = c("biglm", "dplyr", "ggplot2", "readr", "tidyr")) create_plot <- function(data) { ggplot(data) + geom_histogram(aes(x = Ozone), bins = 12) + theme_gray(24) }

# Targets

Our first target borrows the `airquality` dataset built into base R.

```{targets raw-data}
tar_target(raw_data, airquality)

Our next targets preprocess the data, make a histogram, and fit a model.

```{targets downstream-targets} list( tar_target(data, raw_data %>% filter(!is.na(Ozone))), tar_target(hist, create_plot(data)), tar_target(fit, biglm(Ozone ~ Wind + Temp, data)) )

# Pipeline

If you ran all the `{targets}` chunks in non-interactive mode, then your R scripts are set up to run the pipeline.

```r
tar_make()

Output

You can retrieve results from the _targets/ data store using tar_read() or tar_load().

library(biglm)
tar_read(fit)

tar_read(hist)

The targets dependency graph helps your readers understand the steps of your pipeline at a high level.

tar_visnetwork()

At this point, you can go back and run {targets} chunks in interactive mode without interfering with the code or data of the non-interactive pipeline.