Protocol Buffer Basics: C#

This tutorial provides a basic C# programmer's introduction to working with protocol buffers, using the proto3 version of the protocol buffers language. By walking through creating a simple example application, it shows you how to

• Define message formats in a .proto file.
• Use the protocol buffer compiler.
• Use the C# protocol buffer API to write and read messages.

This isn't a comprehensive guide to using protocol buffers in C#. For more detailed reference information, see the Protocol Buffer Language Guide, the C# API Reference, the C# Generated Code Guide, and the Encoding Reference.  

Why use protocol buffers?

The example we're going to use is a very simple "address book" application that can read and write people's contact details to and from a file. Each person in the address book has a name, an ID, an email address, and a contact phone number.

How do you serialize and retrieve structured data like this? There are a few ways to solve this problem:

• Use .NET binary serialization with System.Runtime.Serialization.Formatters.Binary.BinaryFormatter and associated classes. This ends up being very fragile in the face of changes, expensive in terms of data size in some cases. It also doesn't work very well if you need to share data with applications written for other platforms.
• You can invent an ad-hoc way to encode the data items into a single string – such as encoding 4 ints as "12:3:-23:67". This is a simple and flexible approach, although it does require writing one-off encoding and parsing code, and the parsing imposes a small run-time cost. This works best for encoding very simple data.
• Serialize the data to XML. This approach can be very attractive since XML is (sort of) human readable and there are binding libraries for lots of languages. This can be a good choice if you want to share data with other applications/projects. However, XML is notoriously space intensive, and encoding/decoding it can impose a huge performance penalty on applications. Also, navigating an XML DOM tree is considerably more complicated than navigating simple fields in a class normally would be. 

Protocol buffers are the flexible, efficient, automated solution to solve exactly this problem. With protocol buffers, you write a .proto description of the data structure you wish to store. From that, the protocol buffer compiler creates a class that implements automatic encoding and parsing of the protocol buffer data with an efficient binary format. The generated class provides getters and setters for the fields that make up a protocol buffer and takes care of the details of reading and writing the protocol buffer as a unit. Importantly, the protocol buffer format supports the idea of extending the format over time in such a way that the code can still read data encoded with the old format.

Where to find the example code

Our example is a command-line application for managing an address book data file, encoded using protocol buffers. The command AddressBook (see: Program.cs) can add a new entry to the data file or parse the data file and print the data to the console.

You can find the complete example in the examples directory and csharp/src/AddressBook directory of the GitHub repository.  

Defining your protocol format

To create your address book application, you'll need to start with a .proto file. The definitions in a .proto file are simple: you add a message for each data structure you want to serialize, then specify a name and a type for each field in the message. In our example, the .proto file that defines the messages is addressbook.proto.

The .proto file starts with a package declaration, which helps to prevent naming conflicts between different projects.

syntax = "proto3";
package tutorial;

import "google/protobuf/timestamp.proto";

 

In C#, your generated classes will be placed in a namespace matching the package name if csharp_namespace is not specified. In our example, the csharp_namespace option has been specified to override the default, so the generated code uses a namespace of Google.Protobuf.Examples.AddressBook instead of Tutorial.

option csharp_namespace = "Google.Protobuf.Examples.AddressBook";

 

Next, you have your message definitions. A message is just an aggregate containing a set of typed fields. Many standard simple data types are available as field types, including bool, int32, float, double, and string. You can also add further structure to your messages by using other message types as field types.

message Person {
  string name = 1;
  int32 id = 2;  // Unique ID number for this person.
  string email = 3;

  enum PhoneType {
    MOBILE = 0;
    HOME = 1;
    WORK = 2;
  }

  message PhoneNumber {
    string number = 1;
    PhoneType type = 2;
  }

  repeated PhoneNumber phones = 4;

  google.protobuf.Timestamp last_updated = 5;
}

// Our address book file is just one of these.
message AddressBook {
  repeated Person people = 1;
}

 

In the above example, the Person message contains PhoneNumber messages, while the AddressBook message contains Person messages. You can even define message types nested inside other messages – as you can see, the PhoneNumber type is defined inside Person. You can also define enum types if you want one of your fields to have one of a predefined list of values – here you want to specify that a phone number can be one of MOBILE, HOME, or WORK.

The " = 1", " = 2" markers on each element identify the unique "tag" that field uses in the binary encoding. Tag numbers 1-15 require one less byte to encode than higher numbers, so as an optimization you can decide to use those tags for the commonly used or repeated elements, leaving tags 16 and higher for less-commonly used optional elements. Each element in a repeated field requires re-encoding the tag number, so repeated fields are particularly good candidates for this optimization.

If a field value isn't set, a default value is used: zero for numeric types, the empty string for strings, false for bools. For embedded messages, the default value is always the "default instance" or "prototype" of the message, which has none of its fields set. Calling the accessor to get the value of a field which has not been explicitly set always returns that field's default value.

If a field is repeated, the field may be repeated any number of times (including zero). The order of the repeated values will be preserved in the protocol buffer. Think of repeated fields as dynamically sized arrays.

You'll find a complete guide to writing .proto files – including all the possible field types – in the Protocol Buffer Language Guide. Don't go looking for facilities similar to class inheritance, though – protocol buffers don't do that.  

Compiling your protocol buffers

Now that you have a .proto, the next thing you need to do is generate the classes you'll need to read and write AddressBook (and hence Person and PhoneNumber) messages. To do this, you need to run the protocol buffer compiler protoc on your .proto:

1. If you haven't installed the compiler, download the package and follow the instructions in the README.
2. Now run the compiler, specifying the source directory (where your application's source code lives – the current directory is used if you don't provide a value), the destination directory (where you want the generated code to go; often the same as $SRC_DIR), and the path to your .proto. In this case, you would invoke:

   protoc -I=$SRC_DIR --csharp_out=$DST_DIR $SRC_DIR/addressbook.proto

    

2.  
   Because you want C# code, you use the --csharp_out option – similar options are provided for other supported languages.

This generates Addressbook.cs in your specified destination directory. To compile this code, you'll need a project with a reference to the Google.Protobuf assembly.     

The addressbook classes

Generating Addressbook.cs gives you five useful types:

• A static Addressbook class that contains metadata about the protocol buffer messages.
• An AddressBook class with a read-only People property.
• A Person class with properties for Name, Id, Email and Phones.
• A PhoneNumber class, nested in a static Person.Types class.
• A PhoneType enum, also nested in Person.Types.

You can read more about the details of exactly what's generated in the C# Generated Code guide, but for the most part you can treat these as perfectly ordinary C# types. One point to highlight is that any properties corresponding to repeated fields are read-only. You can add items to the collection or remove items from it, but you can't replace it with an entirely separate collection. The collection type for repeated fields is always RepeatedField<T>. This type is like List<T> but with a few extra convenience methods, such as an Add overload accepting a collection of items, for use in colleciton initializers.

Here's an example of how you might create an instance of Person:

Person john = new Person
{
    Id = 1234,
    Name = "John Doe",
    Email = "jdoe@example.com",
    Phones = { new Person.Types.PhoneNumber { Number = "555-4321", Type = Person.Types.PhoneType.Home } }
};

 

Note that with C# 6, you can use using static to remove the Person.Types ugliness:

// Add this to the other using directives
using static Google.Protobuf.Examples.AddressBook.Person.Types;
...
// The earlier Phones assignment can now be simplified to:
Phones = { new PhoneNumber { Number = "555-4321", Type = PhoneType.HOME } }

 

Parsing and serialization

The whole purpose of using protocol buffers is to serialize your data so that it can be parsed elsewhere. Every generated class has a WriteTo(CodedOutputStream) method, where CodedOutputStream is a class in the protocol buffer runtime library. However, usually you'll use one of the extension methods to write to a regular System.IO.Stream or convert the message to a byte array or ByteString. These extension messages are in the Google.Protobuf.MessageExtensions class, so when you want to serialize you'll usually want a using directive for the Google.Protobuf namespace. For example:

using Google.Protobuf;
...
Person john = ...; // Code as before
using (var output = File.Create("john.dat"))
{
    john.WriteTo(output);
}

 

Parsing is also simple. Each generated class has a static Parser property which returns a MessageParser<T> for that type. That in turn has methods to parse streams, byte arrays and ByteStrings. So to parse the file we've just created, we can use:

Person john;
using (var input = File.OpenRead("john.dat"))
{
    john = Person.Parser.ParseFrom(input);
}

 

A full example program to maintain an addressbook (adding new entries and listing existing ones) using these messages is available in the Github repository.  

Extending a Protocol Buffer

Sooner or later after you release the code that uses your protocol buffer, you will undoubtedly want to "improve" the protocol buffer's definition. If you want your new buffers to be backwards-compatible, and your old buffers to be forward-compatible – and you almost certainly do want this – then there are some rules you need to follow. In the new version of the protocol buffer:

• you must not change the tag numbers of any existing fields.
• you may delete fields.
• you may add new fields but you must use fresh tag numbers (i.e. tag numbers that were never used in this protocol buffer, not even by deleted fields).

(There are some exceptions to these rules, but they are rarely used.)

If you follow these rules, old code will happily read new messages and simply ignore any new fields. To the old code, singular fields that were deleted will simply have their default value, and deleted repeated fields will be empty. New code will also transparently read old messages.

However, keep in mind that new fields will not be present in old messages, so you will need to do something reasonable with the default value. A type-specific default value is used: for strings, the default value is the empty string. For booleans, the default value is false. For numeric types, the default value is zero. 

Reflection

Message descriptors (the information in the .proto file) and instances of messages can be examined programmatically using the reflection API. This can be useful when writing generic code such as a different text format or a smart diff tool. Each generated class has a static Descriptor property, and the descriptor for any instance can be retrieved using the IMessage.Descriptor property. As a quick example of how these can be used, here is a short method to print the top-level fields of any message.

public void PrintMessage(IMessage message)
{
    var descriptor = message.Descriptor;
    foreach (var field in descriptor.Fields.InDeclarationOrder())
    {
        Console.WriteLine(
            "Field {0} ({1}): {2}",
            field.FieldNumber,
            field.Name,
            field.Accessor.GetValue(message);
    }
}