FakeDataR: Privacy-Preserving Synthetic Data for 'LLM' Workflows

Generate privacy-preserving synthetic datasets that mirror structure, types, factor levels, and missingness; export bundles for 'LLM' workflows (data plus 'JSON' schema and guidance); and build fake data directly from 'SQL' database tables without reading real rows. Methods are related to approaches in Nowok, Raab and Dibben (2016) <doi:10.32614/RJ-2016-019> and the foundation-model overview by Bommasani et al. (2021) <doi:10.48550/arXiv.2108.07258>.

Version:	0.2.2
Imports:	dplyr, jsonlite, zip
Suggests:	readr, testthat (≥ 3.0.0), knitr, rmarkdown, DBI, RSQLite, tibble, nycflights13, palmerpenguins, gapminder, arrow, withr
Published:	2025-10-06
DOI:	10.32614/CRAN.package.FakeDataR
Author:	Zobaer Ahmed [aut, cre]
Maintainer:	Zobaer Ahmed <zunnun09 at gmail.com>
BugReports:	https://github.com/zobaer09/FakeDataR/issues
License:	MIT + file LICENSE
URL:	https://zobaer09.github.io/FakeDataR/, https://github.com/zobaer09/FakeDataR
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	FakeDataR results

Documentation:

Reference manual:	FakeDataR.html , FakeDataR.pdf
Vignettes:	Database schema workflow (no data read) (source, R code) FakeDataR: Getting started (source, R code) Privacy and validation (source, R code)

Downloads:

Package source:	FakeDataR_0.2.2.tar.gz
Windows binaries:	r-devel: FakeDataR_0.2.2.zip, r-release: FakeDataR_0.2.2.zip, r-oldrel: FakeDataR_0.2.2.zip
macOS binaries:	r-release (arm64): FakeDataR_0.2.2.tgz, r-oldrel (arm64): FakeDataR_0.2.2.tgz, r-release (x86_64): FakeDataR_0.2.2.tgz, r-oldrel (x86_64): FakeDataR_0.2.2.tgz

Linking:

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