Basics tutorial
A basic tutorial introduction to gRPC in Python.
Basics tutorial
This tutorial provides a basic Python programmer’s introduction to working with gRPC.
By walking through this example you’ll learn how to:
- Define a service in a
.proto
file. - Generate server and client code using the protocol buffer compiler.
- Use the Python gRPC API to write a simple client and server for your service.
It assumes that you have read the Introduction to gRPC and are familiar with protocol buffers. You can find out more in the proto3 language guide and Python generated code guide.
Why use gRPC?
Our 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 we can define our service once in a .proto
file and generate clients
and servers in any of gRPC’s supported languages, which in turn can be run in
environments ranging from servers inside a large data center to your own tablet —
all the complexity of communication between different languages and environments is
handled for you by gRPC. We 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 v1.66.0 --depth 1 --shallow-submodules 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 Quick start.
Defining the service
Your first step (as you’ll know from the Introduction to gRPC) 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:
A simple RPC where the client sends a request to the server using the stub and waits for a response to come back, just like a normal function call.
// Obtains the feature at a given position. rpc GetFeature(Point) returns (Feature) {}
A response-streaming RPC where the client sends a request to the server and gets a stream to read a sequence of messages back. The client reads from the returned stream until there are no more messages. As you can see in the example, you specify a response-streaming method by placing the
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) {}
A request-streaming RPC where the client writes a sequence of messages and sends them to the server, again using a provided stream. Once the client has finished writing the messages, it waits for the server to read them all and return its response. You specify a request-streaming method by placing the
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) {}
A bidirectionally-streaming RPC where both sides send a sequence of messages using a read-write stream. The two streams operate independently, so clients and servers can read and write in whatever order they like: for example, the server could wait to receive all the client messages before writing its responses, or it could alternately read a message then write a message, or some other combination of reads and writes. The order of messages in each stream is preserved. You specify this type of method by placing the
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;
}
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=. --pyi_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:
- classes for the messages defined in
route_guide.proto
- classes for the service defined in
route_guide.proto
RouteGuideStub
, which can be used by clients to invoke RouteGuide RPCsRouteGuideServicer
, which defines the interface for implementations of the RouteGuide service
- a function for the service defined in
route_guide.proto
add_RouteGuideServicer_to_server
, which adds a RouteGuideServicer to agrpc.Server
Note
The2
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.Generating gRPC interfaces with custom package path
To generate gRPC client interfaces with a custom package path, you can use the -I
parameter along with the grpc_tools.protoc
command. This approach allows you to specify a custom package name for the generated files.
Here’s an example command to generate the gRPC client interfaces with a custom package path:
python -m grpc_tools.protoc -Igrpc/example/custom/path=../../protos \
--python_out=. --grpc_python_out=. \
../../protos/route_guide.proto
The generated files will be placed in the ./grpc/example/custom/path/
directory:
./grpc/example/custom/path/route_guide_pb2.py
./grpc/example/custom/path/route_guide_pb2_grpc.py
With this setup, the generated route_guide_pb2_grpc.py
file will correctly import the protobuf definitions using the custom package structure, as shown below:
import grpc.example.custom.path.route_guide_pb2 as route_guide_pb2
By following this approach, you can ensure that the files will call each other correctly with respect to the specified package path. This method allows you to maintain a custom package structure for your gRPC client interfaces.
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)
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.
Response-streaming RPC
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.
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,
feature_count=feature_count,
distance=int(distance),
elapsed_time=int(elapsed_time),
)
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
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.
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))
route_guide_pb2_grpc.add_RouteGuideServicer_to_server(RouteGuideServicer(), server)
server.add_insecure_port("[::]:50051")
server.start()
server.wait_for_termination()
The server start()
method is non-blocking. A new thread will be instantiated
to handle requests. The thread calling server.start()
will often
not have any other work to do in the meantime. In this case, you can call
server.wait_for_termination()
to cleanly block the calling thread until the
server terminates.
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:
python route_guide_server.py
From a different terminal, run the client:
python route_guide_client.py