django服务使用rpc传输数据

概述

gRPC（gRPC Remote Procedure Call）是一种高性能、跨语言的远程过程调用（RPC）框架，由Google开发并开源。它基于HTTP/2协议进行通信，使用Protocol Buffers（protobuf）作为默认的消息编码格式。gRPC的目标是提供简单的、高效的RPC服务，使不同应用程序、服务或组件能够跨网络进行通信，而不必担心底层通信细节。

gRPC 使用 Protocol Buffers 来定义消息和服务，这意味着在通信中使用了严格的消息类型，确保了数据的一致性和完整性。

如果使用的话，是否会对当前的随意扩展的服务带来一定的限制。

基础依赖

pip install grpcio
pip install grpcio-tools

 


定义服务和消息

Language Guide (proto 3)

eg： 

syntax = "proto3";

package job;

service JobService {
    rpc GetJob(GetJobRequest) returns (GetJobResponse) {}
}

message GetJobRequest {
    int32 id = 1;
}

// 1,2 tag
message Location {
    int32 id = 1;
    string value = 2;
    int32 region_id = 3;
    string region = 4;
    bool is_qualified = 5;
}

message Skill {
    string value = 1;
    bool is_qualified = 5;
}

message GetJobResponse {
    int32 id = 1;
    string job_title = 2;
    int32 job_type_id = 3;
    string job_type_value = 4;
    string job_location = 5;
    Location location = 6;
    repeated Skill skills = 7;
}

 

生成 gRPC 代码
python -m grpc_tools.protoc -I./protos --python_out=. --pyi_out=. --grpc_python_out=. ./protos/job.proto
/protos是根目录

 

 

或者在相关服务端和客户端导入模块

job_pb2, job_pb2_grpc = grpc.protos_and_services("job.proto")

 

protos_and_services 函数会动态地加载 .proto 文件，运行时生成相应的Python类和方法

在一些场景中，可能更倾向于提前生成这些文件，以便能够更清晰地查看和理解由 .proto 文件生成的代码，或者因为开发、构建或部署流程更适合使用静态生成的文件。

两者之间的选择取决于具体需求和开发流程。

如果觉得动态加载更方便，可以使用grpc.protos_and_services

如果希望能够直接查看和管理生成的Python代码，可以使用grpcio-tools生成对应的文件

创建服务和客户端服务

Server 

import os
from concurrent import futures
import logging

import grpc
from rest_framework.generics import get_object_or_404

from rpc_services import job_pb2, job_pb2_grpc
from jobs.models import Job
from jobs.serializers import JobDetailSerializer


class JobGRPCService(job_pb2_grpc.JobService):

    def GetJob(self, request, context):
        job_id = request.id
        print(job_id)
        # job = get_object_or_404(
        #     Job,
        #     pk=job_id,
        # )
        # print(job)
        # serializer = JobDetailSerializer(
        #     job, context={"jobseeker": None}
        # )
        # data = serializer.data

        data = {
            "id": 167267,
            "job_title": "Java Developer",
            "job_type_id": 1,
            "job_type_value": "Full-time",
            "job_location": "bishan",
            "location": {
                "id": 162,
                "value": "Bishan",
                "region_id": 21,
                "region": "Central",
                "is_qualified": False
            },
            "xp_lvl": {
                "id": 2,
                "key": "1_to_3_years",
                "value": "1 - 3 Yrs Exp",
                "is_qualified": False
            },
            "skills": [
                {
                    "value": "Python",
                    "is_qualified": False
                },
                {
                    "value": "Java",
                    "is_qualified": False
                }
            ]
        }
        print(data)
        # ValueError: Protocol message GetJobResponse has no "xp_lvl" field.
        """
        int32 id = 1;
        string job_title = 2;
        int32 job_type_id = 3;
        string job_type_value = 4;
        string job_location = 5;
        Location location = 6;
        repeated Skill skills = 7;
        """
        return job_pb2.GetJobResponse(
            id=data["id"],
            job_title=data["job_title"],
            job_type_id=data["job_type_id"],
            job_type_value=data["job_type_value"],
            job_location=data["job_location"],
            location=data["location"],
            skills=data["skills"],
        )


def serve():
    print("Starting serve")
    logging.basicConfig()
    port = "50051"
    server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
    job_pb2_grpc.add_JobServiceServicer_to_server(JobGRPCService(), server)
    server.add_insecure_port("[::]:" + port)
    server.start()
    print("Server started, listening on " + port)
    server.wait_for_termination()


if __name__ == "__main__":
    # logging.basicConfig()
    serve()

 

Client
  


from __future__ import print_function




import logging




import grpc
import job_pb2
import job_pb2_grpc




from google.protobuf.json_format import MessageToJson





def run():
    # NOTE(gRPC Python Team): .close() is possible on a channel and should be
    # used in circumstances in which the with statement does not fit the needs
    # of the code.
    print("Will try to get job ...")
    with grpc.insecure_channel("localhost:50051") as channel:
        stub = job_pb2_grpc.JobServiceStub(channel)
        response = stub.GetJob(job_pb2.GetJobRequest(id=167267))




print(f"Client received: {response}")




 d = MessageToJson(response)
    print(d)





if __name__ == "__main__":
    logging.basicConfig()
    run()


 




运行rpc文件.proto 生成相应的文件就可以通信了


如图：




 



启动服务端和客户端




 

python server.py python client.py


Django中集成gRPC


可以使用 django-grpc-framework


AWS Lambda部署存在一定困难 应该无法依赖WSGI运行


通过Django Command 部署运行


独立rpc服务，通过容器镜像封装


安全认证方面


 


https://grpc.io/docs/guides/auth/


 


基于 TLS/SSL 的证书认证


基于令牌的认证


HTTP 标头认证


eg:




 

token ="token"metadata =[('authorization','Bearer '+ token)]response = stub.GetJob(job_pb2.GetJobRequest(id=167267), metadata=metadata)


 


健康检测


 


https://github.com/grpc/grpc/blob/master/examples/python/health_checking/greeter_server.py


 


相关文档生成


 


https://github.com/pseudomuto/protoc-gen-doc


 









		

		
posted @ 
2023-10-12 20:10 
Οo白麒麟оΟ 
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