SynthCity

Summary

SynthCity is a free, self-hosted Python library for generating and evaluating synthetic data. It is available for Linux and can be installed from PyPI or source. Its plugins cover tabular data, time series, survival analysis, and images, with listed approaches including GANs, VAEs, normalizing flows, Bayesian networks, random forests, and LLM-based generators. Evaluation metrics address data correctness, quality, and privacy, and the Benchmarks API supports selected metrics and repeated runs. Privacy-oriented methods include DECAF, DP-GAN, AdsGAN, PATEGAN, and PrivBayes; DECAF can apply inference-time debiasing based on user-defined fairness requirements. SynthCity demonstrates use with scikit-learn and lifelines datasets and provides utilities to save and load models from files or buffers. It does not handle missing data, so that must be imputed first; HyperImpute is suggested for this purpose. The project identifies its license as Apache-2.0, tracks public bugs through GitHub Issues, and welcomes pull requests. Its listed image generator architectures are not state of the art, and the project suggests extending them for other architectures.

Who it is for

SynthCity suits Python users who need to generate and evaluate synthetic data across the listed modalities. It may also suit users exploring privacy methods or fairness debiasing, provided missing values are handled before use.

Compared on synthetic data generation software

Free plan

Yesgithub.com

Deployment

self_hostedgithub.com

Facts

Purpose

SynthCity is a library for generating and evaluating synthetic tabular data.github.com · 3 Oct 2026

Extensible architecture

The library has a plugin architecture designed to be extended.github.com · 3 Oct 2026

Evaluation

It includes evaluation metrics for data correctness, quality, and privacy.github.com · 3 Oct 2026

Generator types

The listed models include GANs, VAEs, normalizing flows, Bayesian networks, random forests, and LLM-based generators.github.com · 3 Oct 2026

Data modalities

The repository describes generators for tabular data, time series, survival analysis, and images.github.com · 3 Oct 2026

Fairness and privacy

Privacy-focused methods include DECAF, DP-GAN, AdsGAN, PATEGAN, and PrivBayes, and DECAF supports inference-time debiasing using user-defined fairness requirements.github.com · 3 Oct 2026

Benchmarking

The Benchmarks API can evaluate generators using selected metrics and repeated runs.github.com · 3 Oct 2026

Integration

The README demonstrates using SynthCity with scikit-learn datasets and lifelines survival datasets.github.com · 3 Oct 2026

Installation

The library can be installed with pip from PyPI or installed from source.github.com · 3 Oct 2026

Missing data limit

SynthCity does not handle missing data, which must be imputed first; the README points to HyperImpute for this purpose.github.com · 3 Oct 2026

Image model limit

The README says its image generator architectures are not state of the art and suggests extending the image generator/discriminator architecture method for other architectures.github.com · 3 Oct 2026

Model serialization

Models can be serialized and loaded from buffers or files using the library's serialization utilities.github.com · 3 Oct 2026

Support and contributions

The project tracks public bugs through GitHub Issues and welcomes pull requests.github.com · 3 Oct 2026

License

The repository identifies its license as Apache-2.0.github.com · 3 Oct 2026

Where it ranks on Everything Xiaomi

• Best Synthetic Data Generation Software in 2026#8 of 30
• Best AI Synthetic Data Generators in 2026#8 of 26

Sources

• github.com/vanderschaarlab/synthcity· checked 3 Oct 2026