High-performance open-source synthetic data engine. Uses LLMs for schema design and vectorized NumPy for deterministic, scalable generation.
-
Updated
Feb 15, 2026 - Python
High-performance open-source synthetic data engine. Uses LLMs for schema design and vectorized NumPy for deterministic, scalable generation.
Python library to generate and validate credit card numbers. Features a fast, offline BIN lookup using a local database. Zero dependencies, no API keys needed. Perfect for generating test data.
A Python module that provides a unified interface to access mock galaxy catalogs and more for the LSST DESC
Generate random strings that make sense.
Generate synthetic observational datasets from quantum-geometry signatures for LIGO, EHT, and gravitational wave detectors with realistic noise models and instrument specifications
🎩 Generate JSON/YAML/XML... mock data with a structured template
Generate fake data
Creates bank mock data in a simple way
Generate, Load, Develop and Test with consistent relational datasets!
pseudo_big_data is a Python package that generates mock-up datasets for various data types and sizes for testing and development purposes.
Free Open Source Mock Data Generator - A powerful desktop application and REST API for generating realistic fake data, test data, and sample data for testing, development, and prototyping.
leblanc is a modular Python library designed for the rapid generation of large-scale synthetic datasets across various business sectors. It is primarily built using Pandas, NumPy, and Faker to create realistic, structured DataFrames suitable for Data Science training, testing, and exploratory data analysis (EDA).
A flexible web tool to generate synthetic CSV datasets using Regex patterns, Gaussian distributions, and Linear trends. Built with FastAPI and Alpine.js.
Add a description, image, and links to the mock-data topic page so that developers can more easily learn about it.
To associate your repository with the mock-data topic, visit your repo's landing page and select "manage topics."