Installation 🤖

Install the nestjs-grpc-helper package with:

npm install @hodfords/nestjs-grpc-helper --save

Next, automatically generate the proto file and include it in main.ts before starting the application:

import { generateProtoService } from '@hodfords/nestjs-grpc-helper';

generateProtoService(camelCase(env.APP_NAME), env.ROOT_PATH + '/../');

Usage 🚀

Creating microservices

Create microservices using the @GrpcMicroservice decorator, similar to how you would use a Controller. Ensure that the response adheres to the nestjs-response rules:

@GrpcMicroservice()
export class UserMicroservice {
    constructor(private userService: UserService) {}

    @GrpcAction('Get user by id')
    @ResponseModel(UserResponse)
    findUserById(@GrpcValue() dto: GetUserByIdDto): Promise<UserEntity> {
        return this.userService.findUserById(dto.userId);
    }
}

Any Type

You can use any type if fixed types are not an option. However, since it’s passed as JSON, the performance may not be as optimal as with binary. Consider using binary if performance is a concern.

@Property({ type: String, format: 'any', required: false })
@AnyType()
data: any;

Create SDK

To generate a TypeScript SDK for your gRPC services, you can use the make-sdk command. This command will automatically generate the necessary proto files and package them into a JavaScript SDK. You also need the following configuration in your sdk-config.json file:

{
  "name": "sdkName",
  "packageName": "@hodfords/package-name",
  "format": true,
  "build": true,
  "output": "sdk",
  "outputBuild": "sdkBuild",
  "removeOutput": true,
  "addAllowDecorator": true,
  "tsconfig": {
    "extends": "./tsconfig.json",
    "compilerOptions": {
      "outDir": "sdkBuild"
    },
    "include": ["sdk"]
  }
}

Details of the configuration:

| Field | Description | |-------------------|-------------------------------------------------------| | name | Name of the SDK | | packageName | Name of the package | | format | Format the generated code | | build | Build the generated code | | output | Output directory for the generated code | | outputBuild | Output directory for the built code | | removeOutput | Remove the output directory | | addAllowDecorator | Add the allow decorator, need class-validator package | | tsconfig | TypeScript configuration |

To generate the SDK, run the following command:

npm run wz-command make-sdk

What this command does

This command will:

1. Collect all request and response types: It gathers all @GrpcValue request and response types from your project.
2. Generate proto file: Automatically generates the necessary proto files based on the collected types.
3. Create JavaScript Package: Packages the generated code into a JavaScript SDK. The SDK will be published using the name and version specified in your package.json, making it available for other services to import and use. The arguments, response structure, and method names remain consistent with the definitions in your gRPC service, ensuring seamless integration and functionality across services.

SDK usage

After publishing the SDK, other services can easily integrate it. Here’s an example of how to use the generated SDK

1. Import the sdk package

2. Register the microservice module: Configure the microservice in AppModule with the appropriate gRPC URL and timeout settings.

   UserModule.register({
       url: env.GRPC_URL,
       timeout: 5000
   });

3. Use the SDK in another service: Import the SDK and use it to interact with your gRPC services.

   export class OtherService {
       constructor(private userMicroservice: UserMicroservice) {}
   
       async doTask(userId: string): Promise<void> {
           const user = await this.userMicroservice.findUserById({ id: userId });
           // Process user information as needed
       }
   }

In this example, OtherService uses the UserMicroservice class from the SDK to call the findUserById method.

Mock response

To effectively generate and handle mock data in your application, you can use the @MockMethod, @MockSample, and @MockNested decorators.

Generate dynamic data with @MockMethod

Use @MockMethod to apply Faker methods for generating random values.

For example, to create a random string of 10 characters

@Property({ type: String, required: false })
@MockMethod('faker.datatype.string', [10])
@IsString()
name: string;

Set fixed values with @MockSample

If you need to set a fixed value for a property, use the @MockSample decorator. This is useful for enumerations or other predefined values.

For example, to set a fixed user type

@Property({
    type: String,
    enum: UserTypeEnum,
    enumName: 'UserTypeEnum'
})
@MockSample(UserTypeEnum.STANDARD)
@IsEnum(UserTypeEnum)
type: UserTypeEnum;

Generate nested data

Use @MockNested to generate mock data for nested objects or arrays of nested objects.

For example, to create an array of 5 nested objects

@Property({ type: UserResponse, isArray: true })
@IsArray()
@ValidateNested()
@Type(() => UserResponse)
@MockNested(5)
users: UserResponse[];

Document for GRPC

You can go to http://xyz/microservice-documents to check and try to call the gRPC method

MicroserviceDocumentModule.register({
    isEnable: true,
    prefix: <app-prefix>,
    packageName: camelCase(<package-name>),
    clientOptions: { ...microserviceGrpcConfig, customClass: CustomGrpcClient, transport: undefined }
})

License 📝

This project is licensed under the MIT License