GraphQL Protobuff generator

Addressed problematics

• Consistency Across Systems: Automation ensures that both your GraphQL schemas and protobuf definitions are always in sync. This consistency reduces the risk of data mismatches and communication errors between services and clients.
• Reduced Manual Work: Manually maintaining parallel schemas in GraphQL and protobuf can be time-consuming and error-prone. Automation eliminates repetitive tasks, allowing developers to focus on more critical aspects of the project.
• Faster Iterations: With automated translation, any changes made to the GraphQL schema can be quickly propagated to the protobuf definitions. This rapid update cycle accelerates development and deployment processes.
• Improved Maintainability: Automation tools can handle complex schema transformations and edge cases, making it easier to maintain and evolve your APIs over time.
• Enhanced Collaboration: A unified schema approach simplifies understanding for all team members, including front-end and back-end developers, leading to better collaboration and fewer misunderstandings.

How It Works

1. Custom Annotations in GraphQL:

• Define Directives: GraphQL allows you to define custom directives (annotations) that can be attached to fields, types, or other schema elements.
• Annotate Fields: You can use these directives to mark fields that require special handling. For example, you might have directives like @exclude, @internal, or @secure.

2. Translation Tooling:

• Parsing Annotations: Your translation tool or script reads the GraphQL schema and parses the annotations.
• Conditional Logic: Based on the annotations, the tool decides whether to include, exclude, or transform a field in the protobuf definition.
• Security Transformations: For fields that need to be transformed (e.g., encrypted, hashed), the tool applies the necessary transformations during translation.

3. Output Generation

• Protobuf Definitions: The tool generates protobuf definitions based on the translated schema.
• Type Mapping: GraphQL types are mapped to protobuf types, ensuring that the data structures are compatible across systems.
• Custom Logic: The tool can also include custom logic or transformations in the generated code, depending on the annotations.

4. Integration with Codebase

• Generated Code: The generated protobuf definitions can be integrated into your codebase, allowing you to use them in your services and clients.
• Compile and Build: You can compile the protobuf definitions to generate client libraries, server stubs, or other artifacts for your system.
• Runtime Behavior: The translated schema and generated code ensure that your services and clients communicate effectively and securely.

Benefits

1. Enhanced Security

• Data Protection: By excluding sensitive fields or transforming them appropriately, you reduce the risk of exposing confidential information.
• Compliance: Helps in meeting regulatory requirements by ensuring sensitive data is handled according to security policies.

2. Flexibility and Control

• Fine-Grained Control: Annotations provide a way to control the translation at the field level.
• Custom Behavior: Allows for custom translation behaviors without changing the underlying schema or writing extensive custom code.

3. Consistency and Maintainability

• Single Source of Truth: Keeping annotations within the schema ensures that all metadata about field handling is centralized.
• Ease of Updates: Changes to annotations automatically reflect in the translation process, making maintenance easier.