Why DataForge exists
A synthetic data library built the way enterprise .NET teams actually work.
Vision
Make realistic test data a one-liner. DataForge should be the default first import a .NET team reaches for when a database, mock, or demo needs believable data — with zero services to run and zero privacy exposure.
Motivation
- Hand-written fixtures rot the moment the schema changes.
- Random data generators ignore locale rules — addresses and identifiers stop looking real.
- Most solutions either hit a network service or bring a database dependency.
- Tests that generate different data on every run cannot be reproduced or debugged.
Architecture
Feature-based structure with a fluent builder at the core: country providers supply localized datasets, generators map them onto your POCOs, and the seed engine keeps everything reproducible.
DataForge/
├── Builder/ # fluent API: ForCountry, WithSeed, Create
├── Countries/ # PT ES FR DE GB US BR providers
├── Generators/ # built-in entity generators
├── Extensibility/ # custom generator hooks
└── Seeding/ # deterministic seed engineRoadmap
Core fluent API, seven country providers, seeded generation
Collection generation, uniqueness guarantees, performance pass
Custom generator registry, more entity generators (IBAN, license plates)
Additional countries, EF Core seeding helpers, CLI
Contributing
Contributions are welcome: new country providers, generators, docs, or bug reports. Start by reading the contributing guide, then open an issue or pull request on GitHub.
Contribute on GitHub
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