Stubborn Generator

Stubborn Generator

Stubborn Generator is an open-source tool that generates stubs, mocks, and fake data for testing purposes. It allows developers to quickly create fake APIs, databases, and more to use when testing their applications.
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stub mock fake-data testing

Stubborn Generator: Open-Source Testing Tool

Generate stubs, mocks, and fake data for testing with Stubborn Generator, an open-source tool that simplifies testing of APIs, databases, and more.

What is Stubborn Generator?

Stubborn Generator is an open-source tool used by developers and testers to easily generate stubs, mocks, and fake test data. It can quickly create fake APIs, databases, and other dependencies you would commonly stub or mock when testing applications.

Some key features and benefits of Stubborn Generator:

  • Generates fake APIs based on a OpenAPI/Swagger specification. This allows you to mock external web services your application depends on.
  • Creates fake databases populated with auto-generated data. Useful for local development and testing without needing real databases.
  • Customizable data models and fakers for generating domain-specific test data.
  • CLI and programmatic APIs for easy automation and integration into CI/CD pipelines.
  • Open source with an MIT license, available on GitHub. Customizable and extendable to suit your testing needs.

Overall, Stubborn Generator simplifies and speeds up the process of generating stubs, mocks, and fake test data. If you find yourself manually coding stubs or mocks, Stubborn Generator can save you significant development time. Its flexibility makes it useful for testing microservices, distributed systems, and more.

Stubborn Generator Features

Features

  1. Generates stubs, mocks, and fake data for testing
  2. Supports creating fake APIs, databases, and more
  3. Allows quick setup of testing environments
  4. Customizable data generation
  5. Supports multiple data formats (JSON, XML, SQL, etc.)

Pricing

  • Open Source

Pros

Open-source and free to use

Saves time and effort in setting up testing environments

Allows for more thorough testing of applications

Customizable to fit specific testing needs

Cons

May require some setup and configuration to use effectively

Limited to generating fake data, not for end-to-end testing

May not be suitable for complex or large-scale testing scenarios


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