应答流式RPC 请求流式RPC 向流式RPC 流式RPC的三种具体形式

https://mp.weixin.qq.com/s/pWwSfXl71GQZ3KPmAHE_dA

用Python进行gRPC接口测试（二）

大帆船 搜狗测试 2020-02-07

 

上期回顾：用Python进行gRPC接口测试

一、流式RPC的三种具体形式

流式RPC不同于简单RPC只有“单发单收“一种形式，而是可以分为三种不同的形式——“应答流式RPC”，“请求流式RPC”，“双向流式RPC”。对于这三种不同的形式，python有不同的请求及接收方式，下面就让我们来具体了解一下。（对于下面操作有疑问的同学可以去看上一期的内容）

首先接口协议是有区别的，我们来看三种形式的接口定义：

应答流式RPC：

rpc ListFeatures(Rectangle) returns (stream Feature) {}

请求流式RPC：

rpc RecordRoute(stream Point) returns (RouteSummary) {}

双向流式RPC：

rpc RouteChat(stream RouteNote) returns (stream RouteNote) {}

可以看到，请求和响应参数中流式内容的前面会有一个stream标识，代表这是一个流式的内容。应答流式RPC只有返回是流式的，请求流式RPC只有请求是流式的，而双向流式RPC请求和返回都是流式的。

一个包含接口的完整proto协议文件（route_guide.proto）内容如下：

syntax = "proto3";
option java_multiple_files = true;option java_package = "io.grpc.examples.routeguide";option java_outer_classname = "RouteGuideProto";option objc_class_prefix = "RTG";
package routeguide;
service RouteGuide {  rpc ListFeatures(Rectangle) returns (stream Feature) {}  rpc RecordRoute(stream Point) returns (RouteSummary) {}  rpc RouteChat(stream RouteNote) returns (stream RouteNote) {}}
message Point {  int32 latitude = 1;  int32 longitude = 2;}
message Rectangle {  Point lo = 1;  Point hi = 2;}message Feature {  string name = 1;  Point location = 2;}
message RouteNote {  Point location = 1;  string message = 2;}
message RouteSummary {  int32 point_count = 1;  int32 feature_count = 2;  int32 distance = 3;  int32 elapsed_time = 4;}

根据协议文件生成route_guide_pb2.py、route_guide_pb2_grpc.py两个必要的模块文件，然后就可以根据他们来创建客户端了。

二、客户端实现

1、应答流式RPC

应答流式RPC返回的内容为流式，一次请求，n次返回。我们可以用for循环来接收返回的内容：

def guide_list_features(stub):    rectangle = route_guide_pb2.Rectangle(        lo=route_guide_pb2.Point(latitude=400000000, longitude=-750000000),        hi=route_guide_pb2.Point(latitude=420000000, longitude=-730000000))    print("Looking for features between 40, -75 and 42, -73")
    features = stub.ListFeatures(rectangle)
    for feature in features:        print("Feature called %s at %s" % (feature.name, feature.location))

2、请求流式RPC

请求流式RPC请求的内容为流式，n次请求，一次返回。我们可以用迭代器来发送若干份请求数据：

def generate_route(feature_list):    for _ in range(0, 10):        random_feature = feature_list[random.randint(0, len(feature_list) - 1)]        print("Visiting point %s" % random_feature.location)        yield random_feature.location

def guide_record_route(stub):    feature_list = route_guide_resources.read_route_guide_database()
    route_iterator = generate_route(feature_list)    route_summary = stub.RecordRoute(route_iterator)    print("Finished trip with %s points " % route_summary.point_count)    print("Passed %s features " % route_summary.feature_count)    print("Travelled %s meters " % route_summary.distance)    print("It took %s seconds " % route_summary.elapsed_time)

其中route_iterator为一个迭代器。

3、双向流式RPC

双向流式RPC请求的内容为流式，返回内容也为流式，n次请求，n次返回。我们可以用迭代器来发送若干份请求数据，通过for循环来接收返回结果：

def generate_messages():    messages = [        make_route_note("First message", 0, 0),        make_route_note("Second message", 0, 1),        make_route_note("Third message", 1, 0),        make_route_note("Fourth message", 0, 0),        make_route_note("Fifth message", 1, 0),    ]    for msg in messages:        print("Sending %s at %s" % (msg.message, msg.location))        yield msg

def guide_route_chat(stub):    responses = stub.RouteChat(generate_messages())    for response in responses:        print("Received message %s at %s" %              (response.message, response.location))

三、实际应用

在录音笔项目中，需要对转写后的文本进行分段语义整理，由于文本内容可能较多，服务端需要采用流式的方式进行接收，并通过流式的方式将结果返给客户端，于是这里采用了双向流式RPC形式的接口。

接口协议如下（仅为演示需要，只展示部分内容）：

syntax = "proto3";
package sogou.parrot.inner.semantic.v1;import "google/protobuf/duration.proto";import "record.proto";option go_package = "git.speech.sogou/semantic/v1;semantic";
service discourse_understand{    rpc UnderstandFullText(stream UnderstandFullTextRequest) returns(stream UnderstandFullTextResponse);        }message UnderstandFullTextRequest{    repeated SubSentence sub_sentences = 1;    repeated sogou.parrot.record.v1.NonSpeechSoundInfo sound_infos = 2;    repeated sogou.parrot.record.v1.AIMark ai_marks = 3;}
message UnderstandFullTextResponse{        UnderstandFullTextResult result = 2;}

实现客户端的关键代码如下：

def gen_iterator(request):    for r in [request]:        yield r
def get_understand_full_textresponse(stub, ai_marks, sound_infos, sub_sentences):    request = UnderstandFullTextRequest()    request.sub_sentences.extend(sub_sentences)    request.sound_infos.extend(sound_infos)    request.ai_marks.extend(ai_marks)    request_iter = gen_iterator(request)    try:        resps = stub.UnderstandFullText(request_iter)        for resp in resps:            resp_str = json.dumps(json.loads(MessageToJson(resp)),indent=4, ensure_ascii=False)            print(resp_str)    except Exception as e:        print (e)
def run():    ai_marks, sound_infos, sub_sentences = extract_data()    with grpc.insecure_channel(sys.argv[2]) as channel:        stub = discourse_understandStub(channel)        print("-------------- UnderstandFullText --------------")        get_understand_full_textresponse(stub, ai_marks, sound_infos, sub_sentences)
if __name__ == '__main__':    run()

https://mp.weixin.qq.com/s/Y2sHs_Sq4lB3hBhKGSvaNg

程序员如何用gRPC谈一场恋爱

原创 neil 腾讯技术工程 2019-06-12

 

语： 本文以幽默诙谐的方式，介绍gRPC的4种client-server服务模式的开发实践及应用场景

前言：为什么要写这篇文章？

• The best way to learn is to teach. gRPC的examples里的例子是一个简易的router，琐碎的业务代码很多，看起来比较绕。于是就自己写一个例子，看看自己是否都将这些知识点掌握了。

• 谈恋爱的过程，其实跟client-server服务模式非常像。单独讲这4种模式有些无聊，所以就尝试用一种尽量有趣的方式去介绍，顺便也可以作为某些男生的一份简单的恋爱指南。

gRPC client-server服务模式

这里先将重要的结论写出来，方便以后查阅，具体介绍见下文。找不到准确的中文来翻译这几种模式，就保留了英文。

•  0x1: A simple RPC

  最简单的一发一收的client-server模型。这就是我们用得最多的模式

•  0x2: A client-to-server streaming RPC

  client先建立长连接，然后发送多个request给server，server最后统一回一个rsp

应用场景：

1. agent上报CPU，内存等数据到server

2. 客户端心跳

3. 客户端并发调用细小粒度的接口。比如有5个后台接口A B C D E，客户端在不同页面，可以调用不同的接口组合。比如在个人页，就调用ABC；在动态页面，就调用CDE，后台都只会有一个rsp。这种模式的好处就是让后台可以将接口的粒度细化，客户端调用灵活，减少重复代码，提高复用率

• 0x3: A server-to-client streaming RPC

  client先发一个请求到server，然后server不停的回包

应用场景：

1. 股票app。客户端向服务端发送一个股票代码，服务端就把该股票的实时数据源源不断的返回给客户端

2. app的在线push。client先发请求到server注册，然后server就可以发在线push了

• 0x4: A Bidirectional streaming RPC

  建立一个长连接，然后client和server可以随意收发数据

应用场景：

1. 聊天机器人

2. 有状态的游戏服务器进行数据交换。比如LOL，王者荣耀等竞技游戏，client和server之间需要非常频繁地交换数据

• 总结：除了一发一收的模式，client-to-server与server-to-client这两种模式，其实用双向RPC都可以做到。但是双向RPC的编码难度更高(后面例子中可以看到)，异常处理也需要更仔细，所以具体使用哪种模式需要根据具体需求来分析

接下来就让我用一个男女生之间的交往故事来说明这4种服务模式。内容纯属虚构，并故意写得比较搞笑。如果有不恰当的描述，请告诉我。

男女生交往之gRPC的4种模式

一些说明

• Selina：女生名字，client

• John：男生名字，server

• 等等，女生是client，男生是server。那么，女生给男生提要求，是不是就是client向server请求数据一样自然！！！！噢噢噢，这应该是我学编程以来，领悟到的最重要的道理吧！！！

基础代码说明

• client

// 建立跟server的连接  conn, err := grpc.Dial(love_const.Address, grpc.WithInsecure())

（左滑可查看完整代码，下同）

• server

// 设置监听协议与端口lis, err := net.Listen("tcp", love_const.Address)
 // 初始化gRPC server实例 grpcServer := grpc.NewServer() // 注册命令字与处理函数 love_proto.RegisterBehaviorServer(grpcServer, newServer())
 // 启动服务 grpcServer.Serve(lis)

0x1: A simple RPC

 

• Selina职场工作不顺，刚被leader说了一顿，又恰好来大姨妈了，心情十分不好，问John:在哪

• John正在打游戏，非常忙，未察觉出Selina的语气有异样，说：刚起床，在打游戏呢

Selina: "在哪"Jhon: "刚起床，在打游戏呢"

这种模式就是我们用得最多的模式，一发一收

• client代码

response, err := client.WhereAreYou(ctx, message)

• server代码

func (s *loveServer) WhereAreYou(ctx context.Context, message *love_proto.Message) (*love_proto.Response, error) { rsp := new(love_proto.Response) rsp.Words = "刚起床，在打游戏呢" return rsp, nil}

0x2: A client-to-server streaming RPC

 

• Selina开始向John诉苦，说了很多话

• John忙着打游戏，只看清“我来大姨妈了”，就只回了一句：哦，多喝热水

Selina: "你在干嘛"Selina: "我不开心"Selina: "我要和你说话"Selina: "你怎么还不打电话过来"Selina: "我来大姨妈了"Jhon: "哦，多喝热水"

这种模式是client先建立长连接，然后发送多个request给server，server最后统一回一个rsp。

应用场景

1. agent收集CPU，内存等数据到server

2. 客户端心跳

3. 客户端并发调用细小粒度的接口。比如有5个后台接口A B C D E，客户端在不同页面，可以调用不同的接口组合，比如在个人页，就调用ABC；在动态页面，就调用CDE，后台都只会有一个rsp。这种模式的好处就是让后台可以将接口的粒度细化，客户端调用灵活，减少重复代码，提高复用率

• client代码

// 获取一个stream对象 stream, err := client.ContinuousCall(ctx) if err != nil {     log.Fatalf("%v.ContinuousCall(_) = _, %v", client, err) } // 通过stream来发送多个message for _, message := range messages {   fmt.Printf("message words: %s\n", message.Words)     if err := stream.Send(message); err != nil {        log.Fatalf("%v.Send(%v) = %v", stream, message, err)    } } // 发送EOF给server，然后收取server的回包 reply, err := stream.CloseAndRecv() if err != nil {  log.Fatalf("%v.CloseAndRecv() got error %v, want %v", stream, err, nil) }

• server代码

 for {     // 不断收取client的发包     message, err := stream.Recv()     // 当客户端发送EOF时说明要给回包了     if err == io.EOF {        rsp := new(love_proto.Response)       rsp.Words = "哦，多喝热水"         return stream.SendAndClose(rsp)     }    if err != nil {        return err    }    printGirlWords(message.Words) }

0x3: A server-to-client streaming RPC

 

• Selina生气了

• John先一直想解决方案，然后发现没有回应，就要买礼物，安慰等措施：包治百病

Selina: "这么久不给我打电话，你是不是不爱我了？"Jhon: "啊，宝贝你怎么了？"Jhon: "我刚刚在玩游戏，那一局刚开，我走不开啊"Jhon: "你不能不讲道理啊"Jhon: "你都20分钟不回我了"Jhon: "好了，宝贝，我错了，都是我的错"Jhon: "你在家等我，我过去接你，带你去买包包"

这种模式是client先发一个请求到server，然后server不停的回包

应用场景

1. 股票app。客户端向服务端发送一个股票代码，服务端就把该股票的实时数据源源不断的返回给客户端

2. app的在线push。client先发请求到server注册，然后server就可以发在线push了

• client代码

// 获取stream对象，并发送一个消息 stream, err := client.LoveOrNot(ctx, message) if err != nil {    log.Fatalf("%v.LoveOrNot(_) = _, %v", client, err) } for {    // 不断收取server回包    response, err := stream.Recv()    // EOF表示server发包结束    if err == io.EOF {        break   }     if err != nil {         log.Fatalf("%v.LoveOrNot(_) = _, %v", client, err)    }     log.Printf("rsp: %s", response.Words) }

• server代码

for _, response := range responses {   // 不停向client发消息     if err := stream.Send(response); err != nil {         return err     } }

0x4: A Bidirectional streaming RPC

 

• John道歉，买礼物，Selina不再生气，于是开始聊天

Selina: "好呀好呀"Jhon: "宝贝我很快就到啦"Selina: "等我化妆"Jhon: "宝贝我很快就到啦"Selina: "亲爱的你最好啦"Jhon: "宝贝我很快就到啦"Selina: "么么哒"Jhon: "宝贝我很快就到啦"

这种模式就是建立一个长连接，然后client和server可以随意收发数据

应用场景

1. 聊天机器人

2. 有状态的游戏服务器进行数据交换。比如LOL，王者荣耀等竞技游戏，client和server之间需要非常频繁地交换数据

• client代码

 // 获取stream对象 stream, err := client.LoveChat(ctx)if err != nil {   log.Fatalf("%v.LoveChat(_) = _, %v", client, err) } // 这个管道没有太多实际意义，只是为了让client将rsp都收完整 waitc := make(chan struct{}) go func() {     for {         // 不停地收server的包         response, err := stream.Recv()        // server回包EOF，然后关闭管道        if err == io.EOF {             // read done.            close(waitc)             log.Printf("EOF return")            return        }         if err != nil {           log.Fatalf("Failed to receive a note : %v", err)        }         log.Printf("rsp: %s", response.Words)    } }() // 每隔一秒向server发一个消息，模拟聊天场景 for _, message := range messages {     time.Sleep(1 * time.Second)    if err := stream.Send(message); err != nil {        log.Fatalf("Failed to send a message: %v", err)    } } // 这里告诉server: client已经将数据发完了(其实就是给server发一个EOF)，server会返回一个io.EOF stream.CloseSend() <-waitc

• server代码

 for {    // 不断收取client发包    message, err := stream.Recv()    if err == io.EOF {        return nil    }    if err != nil {        return err     }
     for _, response := range responses {         // 给client发包        if err := stream.Send(response); err != nil {            return err       }     } }

男生们看过来，看过来

• 既然标题写了“用gRPC教程序员谈恋爱”，那么肯定就得给点干货。女生可能天生比男生更感性一些，所以当女生在倾诉问题的时候，千万不要只去想解决方案，而是要尽快地安慰女生，倾听她的吐槽，顺着她的思路去稍微吐槽下。可以换位思考，如果你自己心情不好的时候，肯定也想有人来安慰，而不是想听到”你要看开一点，这样工作效率才会高”之类的解决方案的话

• 在倾听和安慰之后，然后把问题解决，或者帮助女生把问题解决。做和说同样重要。

https://github.com/grpc/grpc/blob/master/src/python/grpcio/grpc/framework/interfaces/face/face.py

Attributes:
	cardinality: A cardinality.Cardinality value.
	style: A style.Service value.
	unary_unary_inline: The implementation of the method as a callable value
	that takes a request value and a ServicerContext object and returns a
	response value. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_UNARY and style is style.Service.INLINE.
	unary_stream_inline: The implementation of the method as a callable value
	that takes a request value and a ServicerContext object and returns an
	iterator of response values. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_STREAM and style is style.Service.INLINE.
	stream_unary_inline: The implementation of the method as a callable value
	that takes an iterator of request values and a ServicerContext object and
	returns a response value. Only non-None if cardinality is
	cardinality.Cardinality.STREAM_UNARY and style is style.Service.INLINE.
	stream_stream_inline: The implementation of the method as a callable value
	that takes an iterator of request values and a ServicerContext object and
	returns an iterator of response values. Only non-None if cardinality is
	cardinality.Cardinality.STREAM_STREAM and style is style.Service.INLINE.
	unary_unary_event: The implementation of the method as a callable value that
	takes a request value, a response callback to which to pass the response
	value of the RPC, and a ServicerContext. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_UNARY and style is style.Service.EVENT.
	unary_stream_event: The implementation of the method as a callable value
	that takes a request value, a stream.Consumer to which to pass the
	response values of the RPC, and a ServicerContext. Only non-None if
	cardinality is cardinality.Cardinality.UNARY_STREAM and style is
	style.Service.EVENT.
	stream_unary_event: The implementation of the method as a callable value
	that takes a response callback to which to pass the response value of the
	RPC and a ServicerContext and returns a stream.Consumer to which the
	request values of the RPC should be passed. Only non-None if cardinality
	is cardinality.Cardinality.STREAM_UNARY and style is style.Service.EVENT.
	stream_stream_event: The implementation of the method as a callable value
	that takes a stream.Consumer to which to pass the response values of the
	RPC and a ServicerContext and returns a stream.Consumer to which the
	request values of the RPC should be passed. Only non-None if cardinality
	is cardinality.Cardinality.STREAM_STREAM and style is
	style.Service.EVENT.

 

 

 

 

Attributes:
	cardinality: A cardinality.Cardinality value.
	style: A style.Service value.
	unary_unary_inline: The implementation of the method as a callable value
	that takes a request value and a ServicerContext object and returns a
	response value. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_UNARY and style is style.Service.INLINE.
	unary_stream_inline: The implementation of the method as a callable value
	that takes a request value and a ServicerContext object and returns an
	iterator of response values. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_STREAM and style is style.Service.INLINE.
	stream_unary_inline: The implementation of the method as a callable value
	that takes an iterator of request values and a ServicerContext object and
	returns a response value. Only non-None if cardinality is
	cardinality.Cardinality.STREAM_UNARY and style is style.Service.INLINE.
	stream_stream_inline: The implementation of the method as a callable value
	that takes an iterator of request values and a ServicerContext object and
	returns an iterator of response values. Only non-None if cardinality is
	cardinality.Cardinality.STREAM_STREAM and style is style.Service.INLINE.
	unary_unary_event: The implementation of the method as a callable value that
	takes a request value, a response callback to which to pass the response
	value of the RPC, and a ServicerContext. Only non-None if cardinality is
	cardinality.Cardinality.UNARY_UNARY and style is style.Service.EVENT.
	unary_stream_event: The implementation of the method as a callable value
	that takes a request value, a stream.Consumer to which to pass the
	response values of the RPC, and a ServicerContext. Only non-None if
	cardinality is cardinality.Cardinality.UNARY_STREAM and style is
	style.Service.EVENT.
	stream_unary_event: The implementation of the method as a callable value
	that takes a response callback to which to pass the response value of the
	RPC and a ServicerContext and returns a stream.Consumer to which the
	request values of the RPC should be passed. Only non-None if cardinality
	is cardinality.Cardinality.STREAM_UNARY and style is style.Service.EVENT.
	stream_stream_event: The implementation of the method as a callable value
	that takes a stream.Consumer to which to pass the response values of the
	RPC and a ServicerContext and returns a stream.Consumer to which the
	request values of the RPC should be passed. Only non-None if cardinality
	is cardinality.Cardinality.STREAM_STREAM and style is
	style.Service.EVENT.