is some explanation of how functions become pipelines and components.

That is a good point! I'll make sure we mention it in the pipeline section of the docs

This whole experiment with random numbers started as my attempt at verifying that code in clearml.pipeline

Correct 🙂 BTW: this is why we added PipelineDecorator.run_locally() so it is easier to debug, you can also use PipelineDecorator.debug_pipeline() to run the entire pipeline in a single process as python functions