checks: Evaluate checks on the blueprint build output

In nyuglobalties/blueprintr: Automagically Document and Test Datasets Using Targets Or Drake

Evaluate checks on the blueprint build output

Description

After building a dataset, it's beneficial (if not a requirement) to run tests on that dataset to ensure that it behaves as expected. blueprintr gives authors a framework to run these tests automatically, both for individual variables and general dataset checks. blueprintr provides three functions as models for developing these kinds of functions: one to check that all expected variables are present, one to check the variable types, and a generic function that checks if variable values are contained within a known set.

Usage

all_variables_present(df, meta, blueprint)

all_types_match(df, meta)

Arguments

df	The built dataset
meta	The dataset's metadata
blueprint	The dataset's blueprint

nyuglobalties/blueprintr documentation built on July 16, 2024, 10:27 a.m.