Privacy-Preserving Synthetic Data for 'LLM' Workflows
Overview
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.
- CRAN resubmission:
- Replaced arXiv URL with arXiv DOI (
doi:10.48550/arXiv.2108.07258). - Ensured software/API names are in single quotes (e.g., 'SQL', 'LLM').
- Expanded acronym in Title (“LLM = Large Language Model”).
- Documentation tidy-ups:
- Added
\value{}togenerate_fake_from_schema()and clarified return classes. - Minor wording/typo fixes across vignettes and Rd files.
- CI/docs:
- Fixed pkgdown workflow and GitHub Pages settings.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 13
- Examples that run
- 67%2 run in a plain check (1 of them under a condition) · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 23%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
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9 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/zobaer09/fakedatar on 2026-10-21.
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Dependencies
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.2.2Latest2025-10-06 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-06
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 62 KB
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