synthyverse 0.1.5

Synthetic data generation and evaluation library

Welcome to the synthyverse! An extensive ecosystem for synthetic data generation and evaluation in Python. Read the docs for in-depth usage. The synthyverse is a work in progress. Please provide any suggestions through a GitHub Issue.

Features

• 🔧 Highly modular installation. Install only those modules which you require to keep your installation lightweight.
• 📚 Extensive library for synthetic data. Any generator or metric can be quickly added without dependency conflicts due to synthyverse's modular installation. This allows the synthyverse to host a great amount of generators and evaluation metrics. It also allows the synthyverse to wrap around any existing synthetic data library.
• ⚙️ Benchmarking module for simplified synthetic data pipelines. The benchmarking module executes a modular pipeline of synthetic data generation and evaluation. Choose a generator, set of evaluation metrics, and pipeline parameters, and obtain results on synthetic data quality.
• 👷 Minimal preprocessing required. All preprocessing is handled by the synthyverse, so no need for scaling, one-hot encoding, or handling missing values. Different preprocessing schemes can be used by setting simple parameters.
• 👍 Set constraints for your synthetic data. You can specify inter-column constraints which you want your synthetic data to follow. Constraints are modelled explicitly by the synthyverse, not through oversampling. This ensures efficient and reliable constraint setting.

Installation

The synthyverse is unique in its modular installation set-up. To avoid conflicting dependencies, we provide various installation templates. Each template installs only those dependencies which are required to access certain modules.

Templates provide installation for specific generators, the evaluation module, and more. Install multiple templates to get access to multiple modules of the synthyverse, e.g., multiple generators and evaluation.

We strongly advise to only install templates which you require during a specific run. Installing multiple templates gives rise to potential dependency conflicts. Use separate virtual environments across installations.

Note that the core installation without any template doesn't install any modules.

Available Installation Templates

The following installation templates are available:

Template Name	Category	Installation Command
arf	Generator	pip install synthyverse[arf]
bn	Generator	pip install synthyverse[bn]
cdtd	Generator	pip install synthyverse[cdtd]
ctabgan	Generator	pip install synthyverse[ctabgan]
ctgan	Generator	pip install synthyverse[ctgan]
forestdiffusion	Generator	pip install synthyverse[forestdiffusion]
nrgboost	Generator	pip install synthyverse[nrgboost]
permutation	Generator	pip install synthyverse[permutation]
realtabformer	Generator	pip install synthyverse[realtabformer]
smote	Generator	pip install synthyverse[smote]
synthpop	Generator	pip install synthyverse[synthpop]
tabargn	Generator	pip install synthyverse[tabargn]
tabddpm	Generator	pip install synthyverse[tabddpm]
tabsyn	Generator	pip install synthyverse[tabsyn]
tvae	Generator	pip install synthyverse[tvae]
unmaskingtrees	Generator	pip install synthyverse[unmaskingtrees]
xgenboost	Generator	pip install synthyverse[xgenboost]
base	Generator	pip install synthyverse[base]
eval	Evaluation	pip install synthyverse[eval]
full	All	pip install synthyverse[full]

Note: You can install multiple templates by separating them with commas, e.g., pip install synthyverse[ctgan,eval]

General Installation Template

pip install synthyverse[template]

Installation Examples

pip install synthyverse[ctgan]

pip install synthyverse[arf,bn,ctgan,tvae]

pip install synthyverse[ctgan,eval]

Usage

We refer to the docs to learn how to use the synthyverse!

Tutorials

• Tabular Synthetic Data with the synthyverse: Introduction