--- title: Basics tutorial description: A basic tutorial introduction to gRPC in Python. weight: 50 --- 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](/docs/what-is-grpc/introduction/) and are familiar with [protocol buffers](https://developers.google.com/protocol-buffers/docs/overview). You can find out more in the [proto3 language guide](https://developers.google.com/protocol-buffers/docs/proto3) and [Python generated code guide](https://developers.google.com/protocol-buffers/docs/reference/python-generated). ### Why use gRPC? {{< why-grpc >}} ### Example code and setup The example code for this tutorial is in [grpc/grpc/examples/python/route_guide](https://github.com/grpc/grpc/tree/{{< param grpc_vers.core >}}/examples/python/route_guide). To download the example, clone the `grpc` repository by running the following command: ```sh $ git clone -b {{< param grpc_vers.core >}} https://github.com/grpc/grpc ``` Then change your current directory to `examples/python/route_guide` in the repository: ```sh $ 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](../quickstart/). ### Defining the service Your first step (as you'll know from the [Introduction to gRPC](/docs/what-is-grpc/introduction/)) is to define the gRPC *service* and the method *request* and *response* types using [protocol buffers](https://developers.google.com/protocol-buffers/docs/overview). You can see the complete .proto file in [`examples/protos/route_guide.proto`](https://github.com/grpc/grpc/blob/{{< param grpc_vers.core >}}/examples/protos/route_guide.proto). To define a service, you specify a named `service` in your .proto file: ```protobuf 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. ```protobuf // 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. ```protobuf // 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. ```protobuf // 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. ```protobuf // 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: ```protobuf // 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: ```sh $ pip install grpcio-tools ``` Use the following command to generate the Python code: ```sh $ 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: - 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 RPCs - `RouteGuideServicer`, 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 a `grpc.Server` {{< alert title="Note" color="info" >}} 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. {{< /alert >}} ### Creating the server {#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](#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](https://github.com/grpc/grpc/blob/{{< param grpc_vers.core >}}/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`: ```python # 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`. ```python 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. ```python 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](https://docs.python.org/2/library/stdtypes.html#iterator-types) of request values and returns a single response value. ```python 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`. ```python 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: ```python 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 {#client} You can see the complete example client code in [examples/python/route_guide/route_guide_client.py](https://github.com/grpc/grpc/blob/{{< param grpc_vers.core >}}/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. ```python 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: ```python feature = stub.GetFeature(point) ``` An asynchronous call to `GetFeature` is similar, but like calling a local method asynchronously in a thread pool: ```python 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: ```python 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: ```python route_summary = stub.RecordRoute(point_iterator) ``` ```python 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: ```python for received_route_note in stub.RouteChat(sent_route_note_iterator): ``` ### Try it out! Run the server: ```sh $ python route_guide_server.py ``` From a different terminal, run the client: ```sh $ python route_guide_client.py ```