Package: dataclass 1.0.0

Chris Walker

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.

Authors:Chris Walker [aut, cre, cph]

dataclass_1.0.0.tar.gz
dataclass_1.0.0.zip(r-4.5)dataclass_1.0.0.zip(r-4.4)dataclass_1.0.0.zip(r-4.3)
dataclass_1.0.0.tgz(r-4.5-any)dataclass_1.0.0.tgz(r-4.4-any)dataclass_1.0.0.tgz(r-4.3-any)
dataclass_1.0.0.tar.gz(r-4.5-noble)dataclass_1.0.0.tar.gz(r-4.4-noble)
dataclass_1.0.0.tgz(r-4.4-emscripten)dataclass_1.0.0.tgz(r-4.3-emscripten)
dataclass.pdf |dataclass.html
dataclass/json (API)

# Install 'dataclass' in R:
install.packages('dataclass', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

archivedpackagesr-universe

2.40 score 5 stars 1 scripts 337 downloads 10 exports 17 dependencies

Last updated 1 days agofrom:deb25ecd05 (on package/dataclass). Checks:5 OK, 3 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 20 2025
R-4.5-winNOTEFeb 20 2025
R-4.5-macNOTEFeb 20 2025
R-4.5-linuxNOTEFeb 20 2025
R-4.4-winOKFeb 20 2025
R-4.4-macOKFeb 20 2025
R-4.3-winOKFeb 20 2025
R-4.3-macOKFeb 20 2025

Exports:any_objatm_vecchr_vecdata_validatordataclassdf_likedte_vecenforce_typeslgl_vecnum_vec

Dependencies:clidplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangtibbletidyselectutf8vctrswithr