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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: | 1.0.0 |
| Imports: | purrr, rlang, glue, magrittr, tibble, cli, dplyr, lifecycle |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2024-09-24 |
| DOI: | 10.32614/CRAN.package.dataclass |
| 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 |
| Reference manual: | dataclass.pdf |
| Package source: | dataclass_1.0.0.tar.gz |
| Windows binaries: | r-devel: dataclass_1.0.0.zip, r-release: dataclass_1.0.0.zip, r-oldrel: dataclass_1.0.0.zip |
| macOS binaries: | r-release (arm64): dataclass_1.0.0.tgz, r-oldrel (arm64): dataclass_1.0.0.tgz, r-release (x86_64): dataclass_1.0.0.tgz, r-oldrel (x86_64): dataclass_1.0.0.tgz |
| Old sources: | dataclass archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.