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gRPC Basics - Python

This tutorial provides a basic Python programmer’s introduction to working with gRPC.

By walking through this example you’ll learn how to:

It assumes that you have read the Overview and are familiar with protocol buffers. You can find out more in the proto3 language guide and Python generated code guide.

Why use gRPC?

This example is a simple route mapping application that lets clients get information about features on their route, create a summary of their route, and exchange route information such as traffic updates with the server and other clients.

With gRPC you can define your service once in a .proto file and implement clients and servers in any of gRPC’s supported languages, which in turn can be run in environments ranging from servers inside Google to your own tablet - all the complexity of communication between different languages and environments is handled for you by gRPC. You also get all the advantages of working with protocol buffers, including efficient serialization, a simple IDL, and easy interface updating.

Example code and setup

The example code for this tutorial is in grpc/grpc/examples/python/route_guide. To download the example, clone the grpc repository by running the following command:

$ git clone -b v1.27.0 https://github.com/grpc/grpc

Then change your current directory to examples/python/route_guide in the repository:

$ cd grpc/examples/python/route_guide

You also should have the relevant tools installed to generate the server and client interface code - if you don’t already, follow the setup instructions in the Python quick start guide.

Defining the service

Your first step (as you’ll know from the Overview) is to define the gRPC service and the method request and response types using protocol buffers. You can see the complete .proto file in examples/protos/route_guide.proto.

To define a service, you specify a named service in your .proto file:

service RouteGuide {
   // (Method definitions not shown)

Then you define rpc methods inside your service definition, specifying their request and response types. gRPC lets you define four kinds of service method, all of which are used in the RouteGuide service:

// Obtains the feature at a given position.
rpc GetFeature(Point) returns (Feature) {}
// Obtains the Features available within the given Rectangle.  Results are
// streamed rather than returned at once (e.g. in a response message with a
// repeated field), as the rectangle may cover a large area and contain a
// huge number of features.
rpc ListFeatures(Rectangle) returns (stream Feature) {}
// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}
// Accepts a stream of RouteNotes sent while a route is being traversed,
// while receiving other RouteNotes (e.g. from other users).
rpc RouteChat(stream RouteNote) returns (stream RouteNote) {}

Your .proto file also contains protocol buffer message type definitions for all the request and response types used in our service methods - for example, here’s the Point message type:

// Points are represented as latitude-longitude pairs in the E7 representation
// (degrees multiplied by 10**7 and rounded to the nearest integer).
// Latitudes should be in the range +/- 90 degrees and longitude should be in
// the range +/- 180 degrees (inclusive).
message Point {
  int32 latitude = 1;
  int32 longitude = 2;

Generating client and server code

Next you need to generate the gRPC client and server interfaces from your .proto service definition.

First, install the grpcio-tools package:

$ pip install grpcio-tools

Use the following command to generate the Python code:

$ python -m grpc_tools.protoc -I../../protos --python_out=. --grpc_python_out=. ../../protos/route_guide.proto

Note that as we’ve already provided a version of the generated code in the example directory, running this command regenerates the appropriate file rather than creates a new one. The generated code files are called route_guide_pb2.py and route_guide_pb2_grpc.py and contain:

Note: The 2 in pb2 indicates that the generated code is following Protocol Buffers Python API version 2. Version 1 is obsolete. It has no relation to the Protocol Buffers Language version, which is the one indicated by syntax = "proto3" or syntax = "proto2" in a .proto file.

Creating the server

First let’s look at how you create a RouteGuide server. If you’re only interested in creating gRPC clients, you can skip this section and go straight to Creating the client (though you might find it interesting anyway!).

Creating and running a RouteGuide server breaks down into two work items: - Implementing the servicer interface generated from our service definition with functions that perform the actual “work” of the service. - Running a gRPC server to listen for requests from clients and transmit responses.

You can find the example RouteGuide server in examples/python/route_guide/route_guide_server.py.

Implementing RouteGuide

route_guide_server.py has a RouteGuideServicer class that subclasses the generated class route_guide_pb2_grpc.RouteGuideServicer:

# RouteGuideServicer provides an implementation of the methods of the RouteGuide service.
class RouteGuideServicer(route_guide_pb2_grpc.RouteGuideServicer):

RouteGuideServicer implements all the RouteGuide service methods.

Simple RPC

Let’s look at the simplest type first, GetFeature, which just gets a Point from the client and returns the corresponding feature information from its database in a Feature.

def GetFeature(self, request, context):
  feature = get_feature(self.db, request)
  if feature is None:
    return route_guide_pb2.Feature(name="", location=request)
    return feature

The method is passed a route_guide_pb2.Point request for the RPC, and a grpc.ServicerContext object that provides RPC-specific information such as timeout limits. It returns a route_guide_pb2.Feature response.

Response-streaming RPC

Now let’s look at the next method. ListFeatures is a response-streaming RPC that sends multiple Features to the client.

def ListFeatures(self, request, context):
  left = min(request.lo.longitude, request.hi.longitude)
  right = max(request.lo.longitude, request.hi.longitude)
  top = max(request.lo.latitude, request.hi.latitude)
  bottom = min(request.lo.latitude, request.hi.latitude)
  for feature in self.db:
    if (feature.location.longitude >= left and
        feature.location.longitude <= right and
        feature.location.latitude >= bottom and
        feature.location.latitude <= top):
      yield feature

Here the request message is a route_guide_pb2.Rectangle within which the client wants to find Features. Instead of returning a single response the method yields zero or more responses.

Request-streaming RPC

The request-streaming method RecordRoute uses an iterator of request values and returns a single response value.

def RecordRoute(self, request_iterator, context):
  point_count = 0
  feature_count = 0
  distance = 0.0
  prev_point = None

  start_time = time.time()
  for point in request_iterator:
    point_count += 1
    if get_feature(self.db, point):
      feature_count += 1
    if prev_point:
      distance += get_distance(prev_point, point)
    prev_point = point

  elapsed_time = time.time() - start_time
  return route_guide_pb2.RouteSummary(point_count=point_count,
Bidirectional streaming RPC

Lastly let’s look at the bidirectionally-streaming method RouteChat.

def RouteChat(self, request_iterator, context):
  prev_notes = []
  for new_note in request_iterator:
    for prev_note in prev_notes:
      if prev_note.location == new_note.location:
        yield prev_note

This method’s semantics are a combination of those of the request-streaming method and the response-streaming method. It is passed an iterator of request values and is itself an iterator of response values.

Starting the server

Once you have implemented all the RouteGuide methods, the next step is to start up a gRPC server so that clients can actually use your service:

def serve():
  server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
      RouteGuideServicer(), server)

Because start() does not block you may need to sleep-loop if there is nothing else for your code to do while serving.

Creating the client

You can see the complete example client code in examples/python/route_guide/route_guide_client.py.

Creating a stub

To call service methods, we first need to create a stub.

We instantiate the RouteGuideStub class of the route_guide_pb2_grpc module, generated from our .proto.

channel = grpc.insecure_channel('localhost:50051')
stub = route_guide_pb2_grpc.RouteGuideStub(channel)

Calling service methods

For RPC methods that return a single response (“response-unary” methods), gRPC Python supports both synchronous (blocking) and asynchronous (non-blocking) control flow semantics. For response-streaming RPC methods, calls immediately return an iterator of response values. Calls to that iterator’s next() method block until the response to be yielded from the iterator becomes available.

Simple RPC

A synchronous call to the simple RPC GetFeature is nearly as straightforward as calling a local method. The RPC call waits for the server to respond, and will either return a response or raise an exception:

feature = stub.GetFeature(point)

An asynchronous call to GetFeature is similar, but like calling a local method asynchronously in a thread pool:

feature_future = stub.GetFeature.future(point)
feature = feature_future.result()
Response-streaming RPC

Calling the response-streaming ListFeatures is similar to working with sequence types:

for feature in stub.ListFeatures(rectangle):
Request-streaming RPC

Calling the request-streaming RecordRoute is similar to passing an iterator to a local method. Like the simple RPC above that also returns a single response, it can be called synchronously or asynchronously:

route_summary = stub.RecordRoute(point_iterator)
route_summary_future = stub.RecordRoute.future(point_iterator)
route_summary = route_summary_future.result()
Bidirectional streaming RPC

Calling the bidirectionally-streaming RouteChat has (as is the case on the service-side) a combination of the request-streaming and response-streaming semantics:

for received_route_note in stub.RouteChat(sent_route_note_iterator):

Try it out!

Run the server, which will listen on port 50051:

$ python route_guide_server.py

Run the client (in a different terminal):

$ python route_guide_client.py