{"library":"sdv","type":"library","category":null,"description":"SDV (Synthetic Data Vault) is a Python library that allows users to generate synthetic data for various data types, including single tables, multi-table relational datasets, and sequential data. It provides a range of models and tools to create high-quality synthetic data that preserves the statistical properties and privacy of the original data. As of version 1.36.0, it continues to be actively developed, with a regular release cadence to add new features and improve existing models.","language":"python","status":"active","version":"1.36.0","tags":["synthetic data","data generation","privacy","machine learning","tabular data","data science"],"install":[{"cmd":"pip install sdv","imports":["from sdv.single_table import GaussianCopulaSynthesizer","from sdv.single_table.preset import SingleTablePreset","from sdv.datasets.demo import load_dataset"]}],"homepage":"https://docs.sdv.dev","github":"https://github.com/sdv-dev/SDV","docs":null,"changelog":"https://github.com/sdv-dev/SDV/blob/main/HISTORY.md","pypi":"https://pypi.org/project/sdv/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":40,"avg_install_s":84.8,"avg_import_s":13.96,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/sdv/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}