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, and see the release notes for the new version in the protocol buffers GitHub repository.
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, with 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.
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 v1.17.1 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.
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) {}
stream
keyword before the response type.// 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) {}
stream
keyword before the request type.// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}
stream
keyword before both the request and the response.// 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;
}
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:
RouteGuideStub
, which can be used by clients to invoke RouteGuide RPCsRouteGuideServicer
, which defines the interface for implementations
of the RouteGuide serviceadd_RouteGuideServicer_to_server
, which adds a RouteGuideServicer to
a grpc.Server
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.
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:
You can find the example RouteGuide
server in
examples/python/route_guide/route_guide_server.py.
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.
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)
else:
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.
Now let’s look at the next method. ListFeatures
is a response-streaming RPC
that sends multiple Feature
s 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 Feature
s. Instead of returning a single response the
method yields zero or more responses.
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,
feature_count=feature_count,
distance=int(distance),
elapsed_time=int(elapsed_time))
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
prev_notes.append(new_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.
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))
route_guide_pb2_grpc.add_RouteGuideServicer_to_server(
RouteGuideServicer(), server)
server.add_insecure_port('[::]:50051')
server.start()
Because start()
does not block you may need to sleep-loop if there is nothing
else for your code to do while serving.
You can see the complete example client code in examples/python/route_guide/route_guide_client.py.
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)
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.
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()
Calling the response-streaming ListFeatures
is similar to working with
sequence types:
for feature in stub.ListFeatures(rectangle):
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()
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):
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