Datafaker

With over 150 built-in providers spanning names, addresses, pop culture, and domain-specific fields like finance and healthcare, it eliminates the need to manually source or code test data. The README lists providers from Address to Zelda, demonstrating breadth.

Supports generating data directly into CSV, JSON, XML, and YAML using a declarative schema, making it easy to create structured mock APIs or database dumps. Examples in the README show how to define fields and transformers for formats.

Leverages standard Java Locales to produce region-specific data like US zip codes or Japanese names, which is crucial for testing internationalization. The README provides code snippets for locale-based initialization and lists supported locales.

The unique value guarantee ensures no repeats within a session, essential for generating distinct test datasets without collisions. The documentation highlights methods like `faker.unique().fetchFromYaml()` for this purpose.