Protocol Buffers

Protocol Buffers#

To facilitate communication between components and enable seamless integration of outputs from one component as inputs to another, we will utilize Protocol Buffers (Protobuf) in conjunction with gRPC.

Protocol Buffers is a language-agnostic, platform-neutral framework designed by Google for serializing structured data. It is widely employed for data interchange, particularly in remote procedure calls (RPCs), configuration files, and data storage systems. Protobuf allows for the efficient serialization of data into a compact binary format, which can later be deserialized back into structured data.

The process begins with defining your data structures in a .proto file, which serves as the schema for your messages by specifying the fields and their respective types. Each field is assigned a unique number used for identification in the binary format. Protocol Buffers not only facilitate the definition of data structures but also support the definition of services. A service in Protobuf outlines a set of remote procedure calls (RPCs) that a client application can execute remotely. This feature is particularly beneficial for building distributed systems and APIs using gRPC. To define a service, you include a service block in your .proto file, specifying the service name and the RPC methods it offers, along with their request and response message types.

Creating the Proto File#

When creating the proto file, it is essential to consider which methods or services should be exposed to the client, as well as the data that needs to be exchanged between the client and server to facilitate these methods. The data to be transmitted is defined through message structures within the proto file. Each message contains a list of fields, each assigned a unique number. Below is an example of a data structure named Person which includes the fields name, id, and email.

message Person {
  string name = 1; // Field 1: A string called 'name'
  int32 id = 2;    // Field 2: An integer called 'id'
  string email = 3; // Field 3: A string called 'email'
}

As illustrated, each field is assigned a unique number for binary encoding, and the type of data expected is specified for each field. In this example, name and email expect string values, while id expects an integer. Other available data types include int64 and bool.

If a field is intended to hold multiple values, such as a list of numbers, it should be defined with the repeated keyword:

message AddressBook {
  repeated Person people = 1; // A list of 'Person' messages
}

In this example, the people field holds a list of Person messages, indicated by the use of the repeated keyword.

To define the methods available to the client, service definitions are used. These services define the RPC methods that can be invoked remotely. Each RPC method specifies the request and response message types. Below is an example of a service named PersonService, which provides the RPC method SummarizePerson. This method accepts a Person message as input and returns a Summary message, which is also defined in the example:

syntax = "proto3";

package example;

// Define the Person message
message Person {
  string name = 1;
  int32 id = 2;
  string email = 3;
}

// Define the Summary message
message Summary {
  string info = 1; // Summary information about the person
}

// Define the PersonService with a single RPC method
service PersonService {
  rpc SummarizePerson (Person) returns (Summary);
}

With a fundamental understanding of Protocol Buffers and the process of writing proto files, we can explore how these concepts integrate with gRPC to enable robust communication between components.

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