Autocurator-Synthetic-Data-Benchmark AmirhosseinHonardoust · PARTIAL
Autocurator is a comprehensive benchmarking toolkit for evaluating synthetic tabular data. It measures fidelity, coverage, privacy, and utility through quantitative metrics, visual reports, and PCA/correlation diagnostics. Ideal for validating VAE, GAN, Copula, or Diffusion-generated datasets.
github.com/AmirhosseinHonardoust/Autocurator-Synthetic-Data-Benchmark · ★ 20 · Forks 1 · Size 729 KB
SUMMARY
Technologies 14
Scored 11
Observed 11
Practices 6
Evidence 16
Skips 3
COVERAGE
Analyzed 37 files · 183 commits · 0 API calls
TECHNOLOGIES & DEPTH
JSON LANGUAGE Depth 70
1 files · PRODUCTION
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
2 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
22 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
Black QUALITY Depth —
0 files · config only
Jinja2 LIBRARY Depth 44
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NumPy LIBRARY Depth 81
13 files · PRODUCTION, TEST
Ruff QUALITY Depth —
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mypy QUALITY Depth —
0 files · config only
pandas LIBRARY Depth 81
14 files · PRODUCTION, TEST
pytest TESTING Depth 74
6 files · PRODUCTION, TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-11-11
Last commit 2026-07-26
Active months 2
Commits 183