Python Generated Code Reference

Introduction

gRPC Python relies on the protocol buffers compiler (protoc) to generate code. It uses a plugin to supplement the generated code by plain protoc with gRPC-specific code. For a .proto service description containing gRPC services, the plain protoc generated code is synthesized in a _pb2.py file, and the gRPC-specifc code lands in a _grpc_pb2.py file. The latter python module imports the former. In this guide, we focus on the gRPC-specific subset of the generated code.

Illustrative Example

Let’s look at the following FortuneTeller proto service:

service FortuneTeller {
  // Returns the horoscope and zodiac sign for the given month and day.
  rpc TellFortune(HoroscopeRequest) returns (HoroscopeResponse) {
    // errors: invalid month or day, fortune unavailable
  }

  // Replaces the fortune for the given zodiac sign with the provided one.
  rpc SuggestFortune(SuggestionRequest) returns (SuggestionResponse) {
    // errors: invalid zodiac sign
  }
}

gRPC protoc plugin will synthesize code elements along the lines of what follows in the corresponding _pb2_grpc.py file:

import grpc

import fortune_pb2

class FortuneTellerStub(object):

  def __init__(self, channel):
    """Constructor.

    Args:
      channel: A grpc.Channel.
    """
    self.TellFortune = channel.unary_unary(
        '/example.FortuneTeller/TellFortune',
        request_serializer=fortune_pb2.HoroscopeRequest.SerializeToString,
        response_deserializer=fortune_pb2.HoroscopeResponse.FromString,
        )
    self.SuggestFortune = channel.unary_unary(
        '/example.FortuneTeller/SuggestFortune',
        request_serializer=fortune_pb2.SuggestionRequest.SerializeToString,
        response_deserializer=fortune_pb2.SuggestionResponse.FromString,
        )


class FortuneTellerServicer(object):

  def TellFortune(self, request, context):
    """Returns the horoscope and zodiac sign for the given month and day.
    errors: invalid month or day, fortune unavailable
    """
    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
    context.set_details('Method not implemented!')
    raise NotImplementedError('Method not implemented!')

  def SuggestFortune(self, request, context):
    """Replaces the fortune for the given zodiac sign with the provided
one.
    errors: invalid zodiac sign
    """
    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
    context.set_details('Method not implemented!')
    raise NotImplementedError('Method not implemented!')


def add_FortuneTellerServicer_to_server(servicer, server):
  rpc_method_handlers = {
      'TellFortune': grpc.unary_unary_rpc_method_handler(
          servicer.TellFortune,
          request_deserializer=fortune_pb2.HoroscopeRequest.FromString,
          response_serializer=fortune_pb2.HoroscopeResponse.SerializeToString,
      ),
      'SuggestFortune': grpc.unary_unary_rpc_method_handler(
          servicer.SuggestFortune,
          request_deserializer=fortune_pb2.SuggestionRequest.FromString,
          response_serializer=fortune_pb2.SuggestionResponse.SerializeToString,
      ),
  }
  generic_handler = grpc.method_handlers_generic_handler(
      'example.FortuneTeller', rpc_method_handlers)
  server.add_generic_rpc_handlers((generic_handler,))

Code Elements

The gRPC generated code starts by importing the grpc package and the plain _pb2 module, synthesized by protoc, which defines non-gRPC-specifc code elements, like the classes corresponding to protocol buffers messages and descriptors used by reflection.

For each service Foo in the .proto file, three primary elements are generated:

Stub

The generated Stub class is used by the gRPC clients. It will have a constructor that takes a grpc.Channel object and initializes the stub. For each method in the service, the initializer adds a corresponding attribute to the stub object with the same name. Depending on the RPC type (i.e. unary or streaming), the value of that attribute will be callable objects of type UnaryUnaryMultiCallable, UnaryStreamMultiCallable, StreamUnaryMultiCallable, or StreamStreamMultiCallable.

Servicer

For each service, a Servicer class is generated. This class is intended to serve as the superclass of a service implementation. For each method in the service, a corresponding function in the Servicer class will be synthesized which is intended to be overriden in the actual service implementation. Comments associated with code elements in the .proto file will be transferred over as docstrings in the generated python code.

Registration Function

For each service, a function will be generated that registers a Servicer object implementing it on a grpc.Server object, so that the server would be able to appropriately route the queries to the respective servicer. This function takes an object that implements the Servicer, typically an instance of a subclass of the generated Servicer code element described above, and a grpc.Server object.