Demo and examples of targets pipelines

Let’s look at our demo {targets} pipeline and, afterwards, some examples to see what a real-world pipeline looks like including figures, model, output, tables and a manuscript object.

Demo

With our example {targets} pipeline (open /projects/example-targets-workflow/example-targets-workflow.Rproj), and go through the following steps:

1. Visualize the pipeline’s steps and interdependencies.

tar_visnetwork()

2. Run the workflow

tar_make()

3. Explore the results

4. Look at the rendered manuscript document

Open the rendered document in the paper/ directory.

6. Now to make some changes

   1. Edit the raw-data file, for example by adding new rows to mimic more data being collected. Note: please do not edit raw data, this is just to illustrate how {targets} tracks external files for changes. Rerun tar_make().
   2. Delete an output figure. Rerun tar_make().
   3. Add a filter step before the group counts target. Rerun tar_make().

Examples of real-world pipelines

Check out some examples of full {targets} pipelines that we’ve developed to get a sense for the various applications and approaches that can be used.

• data cleaning and preparation pipeline
• In this pipeline, we use the targets function tar_cue to define how often the target should become stale and re-run, and file.exists to check which of a large list of input files exist on the users computer for processing
• movement ecology method (iSSA)
• We use iteration = 'group' with a column named “tar_group” to run the analysis by defined chunks in the data e.g. individuals and years
• Bayesian models with {brms}
• We use a custom target factory to prepare the pieces (e.g. priors, summaries, model fitting, model checks) that make up a complete Bayesian modeling approach
• Remote sensing and spatial application with {rgee}
• We use a multiline statement to filter images before sampling