R Targets Package Tutorial: Build Reproducible Data Pipelines

Description:
How to build reproducible, scalable data pipelines in R with the {targets} package. This video walks through why manually sourcing a script fails at scale, then shows a compact _targets.R example that registers a data file, cleans data, fits a model, and generates a plot — all managed as dependency-aware targets so only what changed gets re-run.

⭐ NOTES: https://codewithsusan.com/notes/r-targets-to-manage-workflow?r=yd

Topics Covered:
• Why sourcing a whole script breaks at scale (large data, slow models)
• How {targets} tracks dependencies and avoids unnecessary work
• A step-by-step _targets.R example you can copy and run
• Commands to run and inspect your pipeline (tar_make, tar_read, tar_visnetwork)
• Practical notes about when to use {targets}

⏱️ CHAPTERS ⏱️
00:00 Why sourcing breaks at scale
02:11 Create _targets.R and register packages
03:06 Define pipeline
04:34 Running the pipeline
06:50 Dependency graph via tar_visnetwork
07:16 Inspect results with tar_read() / tar_load(
08:34 Outsource commands to functions
10:00 When to use {targets} (best practices)

#rprogramming #datascience