A GraphQL implementation for the Crystal programming language, inspired by graphql-ruby and go-graphql.
graphql-crystal is a GraphQL implementation for the Crystal programming language that allows developers to build GraphQL servers using Crystal's static typing and performance. It solves the problem of creating type-safe GraphQL APIs in Crystal by providing tools to define schemas, resolve queries and mutations, and integrate with existing Crystal classes. The library supports schema definition from strings, automatic input parsing, and custom context objects for advanced use cases.
Crystal developers who need to build GraphQL APIs for their applications, particularly those coming from Ruby or Go GraphQL implementations who want similar functionality in Crystal. It's also suitable for teams adopting Crystal for backend services requiring flexible data querying.
Developers choose graphql-crystal because it brings GraphQL's powerful querying capabilities to Crystal's ecosystem with an API inspired by mature implementations like graphql-ruby and go-graphql. Its automatic input parsing into Crystal structs and seamless class integration reduce boilerplate while maintaining type safety.
a graphql implementation for crystal
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Instantiate GraphQL schemas directly from SDL strings, providing a clear and visual way to define the API structure as shown in the example schema definition in the README.
Make existing Crystal classes GraphQL-ready by including GraphQL::ObjectType and using the field macro, minimizing code changes for domain models like User and Post in the example.
Register custom structs to automatically parse JSON query variables into typed Crystal objects, reducing boilerplate and enhancing type safety, as demonstrated with PostInput structs.
Support for custom context objects allows passing authentication, logging, or other request-specific data to resolvers, enabling advanced use cases without cluttering resolver logic.
The library is explicitly marked as beta in the README, meaning users should expect bugs and instability, making it risky for critical production deployments without extensive testing.
As part of the smaller Crystal ecosystem, it lacks the extensive community plugins, client libraries, and monitoring tools available in more established GraphQL environments like JavaScript or Ruby.
Requires developers to manually define and sync schemas using strings and class annotations, which can be error-prone and less maintainable for large or evolving schemas compared to automated approaches.