loopback-connector-grpc

The gRPC connector enables LoopBack applications to interact with gRPC services.

Installation

In your application root directory, enter:

$ npm install loopback-connector-grpc --save

This will install the module from npm and add it as a dependency to the application's package.json file.

Configuration

To interact with a gRPC API, configure a data source backed by the gRPC connector:

With code:

  var ds = loopback.createDataSource('grpc', {
    connector: 'loopback-connector-grpc',
    spec: 'note.proto',
  });

With JSON in datasources.json (for example, with basic authentication):

"gRPCDataSource": {
    "name": "gRPCDataSource",
    "connector": "grpc",
    "spec": "note.proto",
    "security": {
      "type" : "basic", 
      "username": "the user name",
      "password": "thepassword"
}    

Data source properties

Specify the options for the data source with the following properties.

| Property | Description | Default | |----------|-------------|-----------| | connector | Must be 'loopback-connector-grpc' to specify gRPC connector| None | |spec | HTTP URL or path to the gRPC specification file (with file name extension .yaml/.yml or .json). File path must be relative to current working directory (process.cwd()).| None | |validate | When true, validates provided spec against gRPC specification 2.0 before initializing a data source. | false| | security | Security configuration for making authenticated requests to the API. | None |

Authentication

Basic authentication:

security: {
  rootCerts: 'rootCerts.crt', // Path to root certs
  key: 'gprc.key', // Path to client SSL private key
  cert: 'grpc.crt' // Path to client SSL certificate
}

Creating a model from the gRPC data source

The gRPC connector loads the API specification document asynchronously. As a result, the data source won't be ready to create models until it is connected. For best results, use an event handler for the connected event of data source:

ds.once('connected', function(){
  var PetService = ds.createModel('PetService', {});
  ...
});

Once the model is created, all available gRPC API operations can be accessed as model methods, for example:

...
PetService.getPetById({petId: 1}, function (err, res){
  ...
});

The model methods can also be called as promises:

PetService.getPetById({petId: 1}).then(function(res) {
  ...
}, function(err) {
  ...
});
// in async/await flavor
const res = await PetService.getPetById({petId: 1});

Extend a model to wrap/mediate API Operations

Once you define the model, you can wrap or mediate it to define new methods. The following example simplifies the getPetById operation to a method that takes petID and returns a Pet instance.

PetService.searchPet = function(petID, cb){
  PetService.getPetById({petId: petID}, function(err, res){
    if(err) cb(err, null);
    var result = res.data;
    cb(null, result);
  });
};

This custom method on the PetService model can be exposed as REST API end-point. It uses loopback.remoteMethod to define the mappings:

PetService.remoteMethod(
  'searchPet', {
    accepts: [
      { arg: 'petID', type: 'string', required: true,
        http: { source: 'query' }
      }
    ],
    returns: {arg: 'result', type: 'object', root: true },
    http: {verb: 'get', path: '/searchPet'}
  }
);

Example

Coming soon...