dataclass: Easily Create Structured Lists or Data Frames with Input Validation

Easily define templates for lists and data frames that validate each element. Specify the expected type (i.e., character, numeric, etc), expected length, minimum and maximum values, allowable values, and more for each element in your data. Decide whether violations of these expectations should throw an error or a warning. This package is useful for validating data within R processes which pull from dynamic data sources such as databases and web APIs to provide an extra layer of validation around input and output data.

Version: 0.3.0
Imports: purrr, rlang, glue, magrittr, tibble, cli, dplyr
Suggests: testthat (≥ 3.0.0)
Published: 2023-08-07
Author: Chris Walker [aut, cre, cph]
Maintainer: Chris Walker <walkerjameschris at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: dataclass results

Documentation:

Reference manual: dataclass.pdf

Downloads:

Package source: dataclass_0.3.0.tar.gz
Windows binaries: r-devel: dataclass_0.3.0.zip, r-release: dataclass_0.3.0.zip, r-oldrel: dataclass_0.3.0.zip
macOS binaries: r-release (arm64): dataclass_0.3.0.tgz, r-oldrel (arm64): dataclass_0.3.0.tgz, r-release (x86_64): dataclass_0.3.0.tgz
Old sources: dataclass archive

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