Package: FakeDataR
Title: Privacy-Preserving Synthetic Data for 'LLM' Workflows
Version: 0.2.2
Authors@R: 
    person(given = "Zobaer", family = "Ahmed",
           email = "zunnun09@gmail.com",
           role = c("aut","cre"))
Description: 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>.
License: MIT + file LICENSE
URL: https://zobaer09.github.io/FakeDataR/,
        https://github.com/zobaer09/FakeDataR
BugReports: https://github.com/zobaer09/FakeDataR/issues
Encoding: UTF-8
RoxygenNote: 7.3.2
Imports: dplyr, jsonlite, zip
Suggests: readr, testthat (>= 3.0.0), knitr, rmarkdown, DBI, RSQLite,
        tibble, nycflights13, palmerpenguins, gapminder, arrow, withr
VignetteBuilder: knitr, rmarkdown
Config/testthat/edition: 3
Language: en-US
NeedsCompilation: no
Packaged: 2025-09-30 03:48:13 UTC; Zobaer Ahmed
Author: Zobaer Ahmed [aut, cre]
Maintainer: Zobaer Ahmed <zunnun09@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-06 08:10:19 UTC
Built: R 4.6.0; ; 2026-04-25 20:14:16 UTC; unix
