Protocol – 编码无悔 / Intent & Focused

[原创] Techniques 中文翻译（Google Protocol Buffers中文教程）

learnhard — Tue, 14 Sep 2010 05:37:00 +0000

Techniques 技巧

注：这是本人的翻译，可能不准确，可能有错误，但是基本上可以理解，希望能对大家有所帮助！（转载须注明出处：本文来自learnhard的博客：http://www.codelast.com/& http://blog.csdn.net/learnhard/）

This page describes some commonly-used design patterns for dealing with Protocol Buffers. You can also send design and usage questions to the Protocol Buffers discussion group.
文章来源：http://www.codelast.com/

l 将多个消息转化为流

l 大数据集

l 联合类型

l 自描述的消息

本文描述了处理Protocol Buffers的时候一些常用的设计模式。你也可以向Protocol Buffers讨论组（Protocol Buffers discussion group）发送设计和使用方面的问题寻求解答。

Streaming Multiple Messages 将多个消息转化为流

If you want to write multiple messages to a single file or stream, it is up to you to keep track of where one message ends and the next begins. The Protocol Buffer wire format is not self-delimiting, so protocol buffer parsers cannot determine where a message ends on their own. The easiest way to solve this problem is to write the size of each message before you write the message itself. When you read the messages back in, you read the size, then read the bytes into a separate buffer, then parse from that buffer. (If you want to avoid copying bytes to a separate buffer, check out the CodedInputStream class (in both C++ and Java) which can be told to limit reads to a certain number of bytes.)

如果你想将多个消息写入一个文件或流（stream）中，那么是由你来记录一个消息的终点以及另一个消息的起点的。Protocol Buffer数据传输格式不是自我限定的（self-delimiting），所以protocol buffer解析器无法自己决定一个消息结束于何处。解决这个问题的最简单的方法就是：在写入每一个消息之前，先写入消息的大小。当你读取消息的时候，先读取消息大小，然后将指定的字节数读入一个独立的缓冲区中，然后再解析缓冲区里的东西。如果你不想将数据拷贝到一个独立的缓冲区中，请查看CodedInputStream类（C++和Java都可用）的使用方法——你可以用它来限制只读取指定字节的数据。

文章来源：http://www.codelast.com/

Large Data Sets 大数据集

Protocol Buffers are not designed to handle large messages. As a general rule of thumb, if you are dealing in messages larger than a megabyte each, it may be time to consider an alternate strategy.

Protocol Buffers不是设计来处理大消息的。根据一般经验，如果你要处理的单条消息大于1M，那就是采取其他策略的时候了。

That said, Protocol Buffers are great for handling individual messages within a large data set. Usually, large data sets are really just a collection of small pieces, where each small piece may be a structured piece of data. Even though Protocol Buffers cannot handle the entire set at once, using Protocol Buffers to encode each piece greatly simplifies your problem: now all you need is to handle a set of byte strings rather than a set of structures.

也就是说，Protocol Buffers非常适合于处理一个大数据集内有多个单独的消息。通常，大数据集只是许多小块数据的集合，每一小块都是一块结构化的数据。即使是这样，Protocol Buffers也不能马上处理整个数据集，使用Protocol Buffers来编码每一块数据可以极大地简化你的问题：现在你所需要的只是处理一组字符串，而不是一组结构体了。

Protocol Buffers do not include any built-in support for large data sets because different situations call for different solutions. Sometimes a simple list of records will do while other times you may want something more like a database. Each solution should be developed as a separate library, so that only those who need it need to pay the costs.

Protocol Buffers没有内置任何对大数据集的支持，因为不同的情况需要不同的解决方案。

有时，一个简单的记录列表就解决问题了，而在某些情况下，你可能更想要的是类似于数据库的东西。每个解决方案都应该作为一个独立的库来开发，所以只有需要它的人才需要付出代价。

Union Types 联合类型

You may sometimes want to send a message that could be one of several different types. However, protocol buffer parsers cannot necessarily determine the type of a message based on the contents alone. So how do you make sure that the recipient application knows how to decode your message? One solution is to create a wrapper message that has one optional field for each possible message type.

有时，你可能想发送一个消息，它的类型可以是几种不同的类型之一。然而，protocol buffer解析器无法仅凭消息内容来决定消息的类型。所以，你如何确保接收方应用程序能知道怎么解析消息呢？有一个解决方案是：创建一个封装的消息，其含有N个optional的字段，每一个字段对应一种可能的消息类型。

文章来源：http://www.codelast.com/

For example, if you have message types Foo, Bar, and Baz, you can combine them with a type like:

例如，如果你有消息类型Foo，Bar和Baz，那么你可以将它们与类型结合起来，像这样：

message OneMessage {

// One of the following will be filled in.

optional Foo foo = 1;

optional Bar bar = 2;

optional Baz baz = 3;

}

You may also want to have an enum field that identifies which message is filled in, so that you can switch on it:

你也可能想这样做：添加一个枚举字段来标识是哪个消息被填充了，这样的话你就可以对它使用switch（来进行不同的处理）：

message OneMessage {

enum Type { FOO = 1; BAR = 2; BAZ = 3; }

// Identifies which field is filled in.

required Type type = 1;

// One of the following will be filled in.

optional Foo foo = 2;

optional Bar bar = 3;

optional Baz baz = 4;

}

If you have a very large number of possible types, listing every one of them in your container type may be unwieldy. Instead, you should consider using extensions:

如果你有大量“可能的类型”，那么在你的容器类型中将它们一一列举出来可能非常困难。在这种情况下，你应该考虑使用扩展（extensions）：

message OneMessage {

extensions 100 to max;

}

// Elsewhere...

extend OneMessage {

optional Foo foo_ext = 100;

optional Bar bar_ext = 101;

optional Baz baz_ext = 102;

}

Note that you can use the ListFields reflection method (in C++, Java, and Python) to get a list of all fields present in the message, including extensions. You might use this as part of a scheme for registering handlers for diverse message types.

注意：你可以使用反射函数ListFields（C++，Java和Python都可用）来获取一个消息中的所有字段的列表（包括扩展）。在实现一个为不同消息类型分别注册句柄的技术方案的时候，你可能用得上这个功能。

Self-describing Messages 自描述的消息

Protocol Buffers do not contain descriptions of their own types. Thus, given only a raw message without the corresponding .proto file defining its type, it is difficult to extract any useful data.

However, note that the contents of a .proto file can itself be represented using protocol buffers. The file src/google/protobuf/descriptor.protoin the source code package defines the message types involved. protoc can output a FileDescriptorSet – which represents a set of .proto files – using the --descriptor_set_out option. With this, you could define a self-describing protocol message like so:

Protocol Buffers不包含自我类型描述的信息。因此，如果只提供原始消息，而不提供对应的.proto文件，你将很难从中提取出任何有用的数据。

然而，请注意：一个.proto文件的内容可以使用protocol buffers来描述。通过使用--descriptor_set_out选项，源代码包中的src/google/protobuf/descriptor.proto文件定义了相关的消息类型。protoc编译器可以输出一个FileDescriptorSet——这个集合表示一系列的.proto文件。利用它，你可以像这样定义一个自描述的协议消息：

message SelfDescribingMessage {

// Set of .proto files which define the type.

required FileDescriptorSet proto_files = 1;

// Name of the message type. Must be defined by one of the files in

// proto_files.

required string type_name = 2;

// The message data.

required bytes message_data = 3;

}

By using classes like DynamicMessage (available in C++ and Java), you can then write tools which can manipulate SelfDescribingMessages.

All that said, the reason that this functionality is not included in the Protocol Buffer library is because we have never had a use for it inside Google.

通过使用像DynamicMessage这样的类（C++和Java都可用），你可以编写出操作SelfDescribingMessage的工具。

总之，Protocol Buffer库之所以没有包含这个特性，是因为我们在Google还从没有需要用它的机会。

文章来源：https://www.codelast.com/
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[原创] Style Guide中文翻译（Google Protocol Buffers中文教程）

learnhard — Tue, 14 Sep 2010 05:30:16 +0000

Style Guide 风格指南

注：这是本人的翻译，可能不准确，可能有错误，但是基本上可以理解，希望能对大家有所帮助！（转载须注明出处：本文来自learnhard的博客：http://www.codelast.com/& http://blog.csdn.net/learnhard/）

This document provides a style guide for .proto files. By following these conventions, you'll make your protocol buffer message definitions and their corresponding classes consistent and easy to read.

本文档提供了.proto文件的书写风格指南。通过遵守这些约定，你的protocol buffer消息定义和它们的对应类将会风格一致且易于阅读。

Message And Field Names 消息和字段名

Use CamelCase (with an initial capital) for message names – for example, SongServerRequest. Use underscore_separated_names for field names – for example, song_name.

消息名使用驼峰格式（每个单词首字母大写）来书写——例如SongServerRequest。字段名使用小写的下划线分隔式（underscore_separated_names）来书写——例如song_name。

文章来源：http://www.codelast.com/

message SongServerRequest {

required string song_name = 1;

}

Using this naming convention for field names gives you accessors like the following:

字段名使用这种形式的命名约定的话，生成的访问类中的函数就有如下形式：

C++:
conststring& song_name(){...}
void set_song_name(conststring& x){...}

Java:
public String getSongName(){...}
public Builder setSongName(String v){...}

Enums 枚举

Use CamelCase (with an initial capital) for enum type names and CAPITALS_WITH_UNDERSCORES for value names:

枚举名使用驼峰格式（每个单词首字母大写）来书写，值名使用大写的下划线分隔式（CAPITALS_WITH_UNDERSCORES）来书写：

enum Foo {
FIRST_VALUE =1;
SECOND_VALUE =2;
}

Each enum value should end with a semicolon, not a comma.

每一个枚举值都应该以分号结尾，而不是逗号。

文章来源：http://www.codelast.com/

Services 服务

If your .proto defines an RPC service, you should use CamelCase (with an initial capital) for both the service name and any RPC method names:

如果你的.proto文件定义了一个RPC服务，那么服务名和任何RPC函数名都应该使用驼峰格式（每个单词首字母大写）来书写：

service FooService {

rpc GetSomething(FooRequest) returns (FooResponse);

}

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[原创] Language Guide中文翻译（Google Protocol Buffers中文教程）

learnhard — Tue, 14 Sep 2010 05:22:37 +0000

Language Guide 语言指南

· Defining A Message Type

· Scalar Value Types

· Optional And Default Values

· Enumerations

· Using Other Message Types

· Nested Types

· Updating A Message Type

· Extensions

· Packages

· Defining Services

· Options

· Generating Your Classes

This guide describes how to use the protocol buffer language to structure your protocol buffer data, including .proto file syntax and how to generate data access classes from your .proto files.

This is a reference guide – for a step by step example that uses many of the features described in this document, see the tutorial for your chosen language.

l 定义一个消息（message）类型

l 标量值类型

l 可选的（optional）字段以及默认值

l 枚举

l 使用其他消息类型

l 嵌套类型

l 更新一个消息类型

l 扩展

l 包（package）

l 定义服务（service）

l 选项（option）

l 生成访问类

本指南描述了怎样使用protocol buffer语言来构造你的protocol buffer数据，包括.proto文件语法以及怎样生成.proto文件的数据访问类。

本文是一个参考指南——如果要查看如何使用本文中描述的多个特性的循序渐进的例子，请在tutorial中查找你需要的语言的教程。

Defining A Message Type 定义一个消息类型

First let's look at a very simple example. Let's say you want to define a search request message format, where each search request has a query string, the particular page of results you are interested in, and a number of results per page. Here's the .proto file you use to define the message type.

首先看一个非常简单的例子。假设你想定义一个“搜索请求”（search request）的消息格式，每一个搜索请求含有一个查询字符串、你感兴趣的查询结果所在的页数，以及每一页多少条查询结果。那么下面这个就是用来定义消息类型的.proto文件了：

message SearchRequest {

required string query = 1;

optional int32 page_number = 2;

optional int32 result_per_page = 3;

}

The SearchRequest message definition specifies three fields (name/value pairs), one for each piece of data that you want to include in this type of message. Each field has a name and a type.

SearchRequest消息类型指定了3个字段（名/值 对），你想在消息中承载的数据分别对应于每一个字段。每个字段都有一个名字（name）和一个类型（type）。

文章来源：http://www.codelast.com/

Specifying Field Types 指定字段类型

In the above example, all the fields are scalar types: two integers (page_number and result_per_page) and a string (query). However, you can also specify composite types for your fields, including enumerations and other message types.

在上面的例子中，所有字段都是标量类型（scalar types）:两个整型（page_number和result_per_page），一个string（query）。然而，你也可以为字段指定合成的类型，包括枚举（enumerations）以及其他消息类型。

Assigning Tags 分配标识号

As you can see, each field in the message definition has a unique numbered tag. These tags are used to identify your fields in the message binary format, and should not be changed once your message type is in use. Note that tags with values in the range 1 through 15 take one byte to encode. Tags in the range 16 through 2047 take two bytes. So you should reserve the tags 1 through 15 for very frequently occurring message elements. Remember to leave some room for frequently occurring elements that might be added in the future.

The smallest tag number you can specify is 1, and the largest is 2²⁹ - 1, or 536,870,911. You also cannot use the numbers 19000 though 19999 (FieldDescriptor::kFirstReservedNumber through FieldDescriptor::kLastReservedNumber), as they are reserved for the Protocol Buffers implementation - the protocol buffer compiler will complain if you use one of these reserved numbers in your .proto.

如你所见，在消息定义中，每一个字段都有一个独一无二的标识号（unique numbered tag）。这些标识号是用来在消息二进制格式（message binary format）中识别你的字段的。注意：[1,15]之内的标识号在编码的时候会占用一个字节。[16,2047]之内的标识号则占用2个字节。所以你应该为那些频繁出现的消息元素保留[1,15]之内的标识号。切记：要为将来有可能添加的、频繁出现的标识号预留一些标识号。

Specifying Field Rules 指定字段规则

You specify that message fields are one of the following:

· required: a well-formed message must have exactly one of this field.

· optional: a well-formed message can have zero or one of this field (but not more than one).

· repeated: this field can be repeated any number of times (including zero) in a well-formed message. The order of the repeated values will be preserved.

你所指定的消息字段必须是如下之一：

l required：一个格式良好的消息一定要含有1个这种字段。

l optional：一个格式良好的消息可以有0个或1个这种字段（但不超过1个）。

l repeated：在一个格式良好的消息中，这种字段可以重复任意多次（包括0次）。重复的值的顺序会被保留。

（译者注：这一段内容我不太理解，因为Google提供的.proto示例文件并没有按这个说法来编写…）

For historical reasons, repeated fields of basic numeric types aren't encoded as efficiently as they could be. New code should use the special option [packed=true] to get a more efficient encoding. For example:

由于历史原因，基本数值类型的repeated的字段并没有被尽可能地高效编码。在新的代码（译者注：这里是指.proto文件的内容）中，用户应该使用特殊选项[packed=true]来保证更高效的编码。例如：

repeated int32 samples = 4 [packed=true];

Required Is Forever You should be very careful about marking fields as required. If at some point you wish to stop writing or sending a required field, it will be problematic to change the field to an optional field – old readers will consider messages without this field to be incomplete and may reject or drop them unintentionally. You should consider writing application-specific custom validation routines for your buffers instead. Some engineers at Google have come to the conclusion that using required does more harm than good; they prefer to use onlyoptional and repeated. However, this view is not universal.

required是永久性的：在把一个字段标识为required的时候，你应该特别小心。如果在某些情况下你不想写入或者发送一个required的字段，那么将该字段更改为optional可能会遇到问题——旧版本的读者（译者注：即读取、解析消息的一方）会认为不含该字段的消息（message）是不完整的，从而有可能会拒绝解析。在这种情况下，你应该考虑编写特别针对于应用程序的、自定义的消息校验函数。Google的一些工程师得出了一个结论：使用required弊多于利；他们更愿意使用optional和repeated而不是required。当然，这个观点并不具有普遍性。

文章来源：http://www.codelast.com/

Adding More Message Types 添加更多消息类型

Multiple message types can be defined in a single .proto file. This is useful if you are defining multiple related messages – so, for example, if you wanted to define the reply message format that corresponds to your SearchResponse message type, you could add it to the same .proto:

在一个.proto文件中可以定义多个消息类型。在定义多个相关的消息的时候，这一点特别有用——例如，如果你想定义与你的SearchResponse消息类型对应的回复消息格式的话，你可以将它添加到相同的.proto文件中：

message SearchRequest {

required string query = 1;

optional int32 page_number = 2;

optional int32 result_per_page = 3;

}

message SearchResponse {

...

}

Adding Comments 添加注释

To add comments to your .proto files, use C/C++-style // syntax.

向.proto文件添加注释，可以使用C/C++风格的双斜杠（//） 语法格式。

message SearchRequest {

required string query = 1;

optional int32 page_number = 2;// Which page number do we want?

optional int32 result_per_page = 3;// Number of results to return per page.

}

What's Generated From Your .proto? 从你的.proto文件生成了什么？

When you run the protocol buffer compiler on a .proto, the compiler generates the code in your chosen language you'll need to work with the message types you've described in the file, including getting and setting field values, serializing your messages to an output stream, and parsing your messages from an input stream.

当你对.proto文件运行protocol buffer编译器（protocol buffer compiler）的时候，编译器生成你所选择的语言的代码，这些代码可以操作你在.proto文件中定义的消息类型，包括获取、设置字段值，将你的消息序列化到一个输出流中，以及从一个输入流中解析你的消息。

For C++, the compiler generates a .h and .cc file from each .proto, with a class for each message type described in your file.

For Java, the compiler generates a .java file with a class for each message type, as well as a special Builder classes for creating message class instances.

对C++来说，编译器为每一个.proto文件生成了一个.h文件和一个.cc文件，.proto文件中的每一个消息有一个对应的类。

对Java来说，编译器为每一个消息类型生成了一个.java文件，以及一个特殊的Builder类（这个类是用来创建消息类接口的）。

Python is a little different – the Python compiler generates a module with a static descriptor of each message type in your .proto, which is then used with a metaclass to create the necessary Python data access class at runtime.

You can find out more about using the APIs for each language by following the tutorial for your chosen language. For even more API details, see the relevant API reference.

对Python来说，有点不一样——Python编译器为.proto文件中的每个消息类型生成一个模型，其含有一个静态描述符（static descriptor，译者注：没用过Python，不清楚这样翻译正确与否），该模型与一个元类（metaclass）在运行时（runtime）被用来创建必需的Python数据访问类。

你可以从每种语言的教程中找到更多使用使用API的方法。如欲查看更详细的API信息，请阅相关的文章API reference。

Scalar Value Types 标量数值类型

A scalar message field can have one of the following types – the table shows the type specified in the .proto file, and the corresponding type in the automatically generated class:

一个标量消息字段可以含有一个如下的类型——该表格展示了定义于.proto文件中的类型，以及与之对应的、在自动生成的访问类中定义的类型：

.proto Type

Notes

C++ Type

Java Type

double

float

int32

Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint32 instead.

使用可变长编码方式。编码负数时不够高效——如果你的字段可能含有负数，那么请使用sint32。

int32

int

int64

Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint64 instead.

使用可变长编码方式。编码负数时不够高效——如果你的字段可能含有负数，那么请使用sint64。

int64

long

uint32

Uses variable-length encoding.

使用可变长编码方式。

uint32

int^[1]

uint64

Uses variable-length encoding.

使用可变长编码方式。

uint64

long^[1]

sint32

Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int32s.

使用可变长编码方式。有符号的整型值。编码时比通常的int32高效。

int32

int

sint64

Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int64s.

使用可变长编码方式。有符号的整型值。编码时比通常的int64高效。

int64

long

fixed32

Always four bytes. More efficient than uint32 if values are often greater than 2²⁸.

总是4个字节。如果数值总是比总是比2²⁸大的话，这个类型会比uint32高效。

uint32

int^[1]

fixed64

Always eight bytes. More efficient than uint64 if values are often greater than 2⁵⁶.

总是8个字节。如果数值总是比总是比2⁵⁶大的话，这个类型会比uint64高效。

uint64

long^[1]

sfixed32

Always four bytes.

总是4个字节。

int32

int

sfixed64

Always eight bytes.

总是8个字节。

int64

long

bool

boolean

string

A string must always contain UTF-8 encoded or 7-bit ASCII text.

一个字符串必须是UTF-8编码或者7-bit ASCII编码的文本。

string

String

bytes

May contain any arbitrary sequence of bytes.

可能包含任意顺序的字节数据。

string

ByteString

You can find out more about how these types are encoded when you serialize your message in Protocol Buffer Encoding.

^[1] In Java, unsigned 32-bit and 64-bit integers are represented using their signed counterparts, with the top bit simply being stored in the sign bit.

你可以在文章Protocol Buffer Encoding中，找到更多“序列化消息时各种类型如何编码”的信息。

^[1]在Java中，无符号32位和64位整型以它们对应的有符号类型来表示。

Optional Fields And Default Values Optional的字段和默认值

As mentioned above, elements in a message description can be labeled optional. A well-formed message may or may not contain an optional element. When a message is parsed, if it does not contain an optional element, the corresponding field in the parsed object is set to the default value for that field. The default value can be specified as part of the message description. For example, let's say you want to provide a default value of 10 for a SearchRequest's result_per_page value.

如上所述，消息描述中的一个元素可以被标记为“可选的”（optional）。一个格式良好的消息可以包含一个optional的元素，也可以不包含。当解析一个消息的时候，如果它不包含optional的元素，那么解析出来的对象中的对应字段就被置为默认值。默认值可以在消息描述文件中指定。例如，要为SearchRequest消息的result_per_page字段指定默认值10，可以这样做：

optional int32 result_per_page = 3 [default = 10];

If the default value is not specified for an optional element, a type-specific default value is used instead: for strings, the default value is the empty string. For bools, the default value is false. For numeric types, the default value is zero. For enums, the default value is the first value listed in the enum's type definition.

如果没有为optional的元素指定默认值，那么就会使用与特定类型相关的默认值：对string来说，默认值是空字符串。对bool来说，默认值是false。对数值类型来说，默认值是0。对枚举来说，默认值是枚举类型定义中的第一个值。

文章来源：http://www.codelast.com/

Enumerations 枚举

When you're defining a message type, you might want one of its fields to only have one of a pre-defined list of values. For example, let's say you want to add a corpus field for each SearchRequest, where the corpus can be UNIVERSAL, WEB, IMAGES, LOCAL, NEWS, PRODUCTS or VIDEO. You can do this very simply by adding an enum to your message definition - a field with an enum type can only have one of a specified set of constants as its value (if you try to provide a different value, the parser will treat it like an unknown field). In the following example we've added an enum called Corpuswith all the possible values, and a field of type Corpus:

当你定义一个消息类型的时候，你可能想为一个字段指定某“预定义值序列”（pre-defined list of values）中的一个值。例如，假设你想为每一个SearchRequest消息添加一个corpus字段，而corpus的值可能是UNIVERSAL，WEB，IMAGES，LOCAL，NEWS，PRODUCTS或VIDEO中的一个。你可以很容易地实现这一点：通过向你的消息定义中添加一个枚举（enum）就可以了。一个enum类型的字段只能用指定的常量集（specified set of constants）中的一个值作为其值（如果你尝试指定不同的值，解析器就会把它当作一个未知的字段来对待）。在下面的例子中，我们已经添加了一个叫做Corpus的枚举（enum）——它含有所有可能的值——以及一个类型为Corpus的字段：

message SearchRequest {

required string query = 1;

optional int32 page_number = 2;

optional int32 result_per_page = 3 [default = 10];

enum Corpus {

UNIVERSAL = 0;

WEB = 1;

IMAGES = 2;

LOCAL = 3;

NEWS = 4;

PRODUCTS = 5;

VIDEO = 6;

}

optional Corpus corpus = 4 [default = UNIVERSAL];

}

Enumerator constants must be in the range of a 32-bit integer. Since enum values use varint encoding on the wire, negative values are inefficient and thus not recommended. You can define enums within a message definition, as in the above example, or outside – these enums can be reused in any message definition in your .proto file. You can also use an enum type declared in one message as the type of a field in a different message, using the syntax MessageType.EnumType.

When you run the protocol buffer compiler on a .proto that uses an enum, the generated code will have a corresponding enum for Java or C++, or a special EnumDescriptor class for Python that's used to create a set of symbolic constants with integer values in the runtime-generated class.

For more information about how to work with message enums in your applications, see the generated code guide for your chosen language.

枚举常量必须在32位整型值的范围内。因为enum值是使用可变编码方式的，对负数不够高效，因此不推荐在enum中使用负数。如上例所示，你可以在一个消息定义的内部或外部定义枚举——这些枚举可以在你的.proto文件中的任何消息定义里重用。你也可以在一个消息中声明一个枚举类型，而在另一个不同的消息中使用它——采用MessageType.EnumType的语法格式。

当你对一个使用了枚举的.proto文件运行protocol buffer编译器的时候，生成的代码中将有一个对应的enum（对Java或C++来说），或者一个特殊的EnumDescriptor类（对Python来说），它被用来在运行时生成的类中创建一系列的整型值符号常量（symbolic constants）。

关于如何在你的应用程序的消息中使用枚举的更多信息，请查看你所选择的语言的generated code guide。

Using Other Message Types 使用其他消息类型

You can use other message types as field types. For example, let's say you wanted to include Result messages in each SearchResponsemessage – to do this, you can define a Result message type in the same .proto and then specify a field of type Result in SearchResponse:

你可以将其他消息类型用作字段类型。例如，假设你想在每一个SearchResponse消息中包含Result消息，你可以这样做——在相同的.proto文件中定义一个Result消息类型，然后在SearchResponse消息中指定一个Result类型的字段：

message SearchResponse {

repeated Result result = 1;

}

message Result {

required string url = 1;

optional string title = 2;

repeated string snippets = 3;

}

Importing Definitions 导入定义

In the above example, the Result message type is defined in the same file as SearchResponse – what if the message type you want to use as a field type is already defined in another .proto file?

在上面的例子中，Result消息类型与SearchResponse是定义在同一文件中的——如果你要使用的消息类型已经在其他.proto文件中已经定义过了呢？

You can use definitions from other .proto files by importing them. To import another .proto's definitions, you add an import statement to the top of your file:

你可以通过导入（importing）其他.proto文件中的定义来使用它们。要导入其他.proto文件的定义，你需要在你的文件中添加一个导入声明：

import "myproject/other_protos.proto";

The protocol compiler searches for imported files in a set of directories specified on the protocol compiler command line using the -I/--import_path flag. If no flag was given, it looks in the directory in which the compiler was invoked.

然后，protocol编译器就会在一系列目录中查找需要被导入的文件，这些目录通过protocol编译器的命令行参数-I/--import_path指定。如果不提供参数，编译器就在其调用目录下查找。

文章来源：http://www.codelast.com/

Nested Types 嵌套类型

You can define and use message types inside other message types, as in the following example – here the Result message is defined inside the SearchResponse message:

你可以在其他消息类型中定义、使用消息类型，在下面的例子中，Result消息就定义在SearchResponse消息内：

message SearchResponse {

message Result {

required string url = 1;

optional string title = 2;

repeated string snippets = 3;

}

repeated Result result = 1;

}

If you want to reuse this message type outside its parent message type, you refer to it as Parent.Type:

如果你想在它的父消息类型的外部重用这个消息类型，你需要以Parent.Type的形式使用它：

message SomeOtherMessage {

optional SearchResponse.Result result = 1;

}

You can nest messages as deeply as you like:

你可以将消息嵌套任意多层：

message Outer { // Level 0

message MiddleAA { // Level 1

message Inner { // Level 2

required int64 ival = 1;

optional bool booly = 2;

}

message MiddleBB { // Level 1

message Inner { // Level 2

required int32 ival = 1;

optional bool booly = 2;

}

Groups 组

Note that this feature is deprecated and should not be used when creating new message types – use nested message types instead.

注意：这个特性已经被弃用了，在创建新的消息类型的时候，不应该再使用它——你应该使用嵌套消息类型来代替它。

Groups are another way to nest information in your message definitions. For example, another way to specify a SearchResponse containing a number of Results is as follows:

“组”是在你的消息定义中嵌套信息的另一种方法。例如，在SearchResponse中包含若干Result的另一种方法是：

message SearchResponse {

repeated group Result = 1 {

required string url = 2;

optional string title = 3;

repeated string snippets = 4;

}

A group simply combines a nested message type and a field into a single declaration. In your code, you can treat this message just as if it had aResult type field called result (the latter name is converted to lower-case so that it does not conflict with the former). Therefore, this example is exactly equivalent to the SearchResponse above, except that the message has a different wire format.

一个“组”只是简单地将一个嵌套消息类型和一个字段捆绑到一个单独的声明中。在你的代码中，你可以把它看成是含有一个Result类型、名叫result的字段的消息（后面的名字被转换成了小写，所以它不会与前面的冲突）。

因此，除了数据传输格式（wire format）不同之外，这个例子与上面的SearchResponse例子是完全等价的。

Updating A Message Type 更新一个消息类型

If an existing message type no longer meets all your needs – for example, you'd like the message format to have an extra field – but you'd still like to use code created with the old format, don't worry! It's very simple to update message types without breaking any of your existing code. Just remember the following rules:

如果一个已有的消息无法再满足你的需求——例如，你想在消息中添加一个额外的字段——但是你同时还想让为旧版本写的代码仍然可用，不用怕！更新消息而不破坏已有代码是非常简单的。只要你记住下面的规则：

· Don't change the numeric tags for any existing fields.

· Any new fields that you add should be optional or repeated. This means that any messages serialized by code using your "old" message format can be parsed by your new generated code, as they won't be missing any required elements. You should set up sensible default values for these elements so that new code can properly interact with messages generated by old code. Similarly, messages created by your new code can be parsed by your old code: old binaries simply ignore the new field when parsing. However, the unknown fields are not discarded, and if the message is later serialized, the unknown fields are serialized along with it – so if the message is passed on to new code, the new fields are still available. Note that preservation of unknown fields is currently not available for Python.

· Non-required fields can be removed, as long as the tag number is not used again in your updated message type (it may be better to rename the field instead, perhaps adding the prefix "OBSOLETE_", so that future users of your .proto can't accidentally reuse the number).

· A non-required field can be converted to an extension and vice versa, as long as the type and number stay the same.

· int32, uint32, int64, uint64, and bool are all compatible – this means you can change a field from one of these types to another without breaking forwards- or backwards-compatibility. If a number is parsed from the wire which doesn't fit in the corresponding type, you will get the same effect as if you had cast the number to that type in C++ (e.g. if a 64-bit number is read as an int32, it will be truncated to 32 bits).

· sint32 and sint64 are compatible with each other but are not compatible with the other integer types.

· string and bytes are compatible as long as the bytes are valid UTF-8.

· Embedded messages are compatible with bytes if the bytes contain an encoded version of the message.

· fixed32 is compatible with sfixed32, and fixed64 with sfixed64.

l 不要更改任何已有的字段的数值标识（tag）。

l 你添加的任何字段都必须是optional或repeated的。这就意味着任何使用你的“旧”消息格式的代码序列化的消息可以被你的新代码所解析，因为它们不会丢掉任何required的元素。你应该为这些元素设置合理的默认值（default values），这样新的代码就能够正确地与老代码生成的消息交互了。类似地，你的新代码创建的消息也能被你的老代码解析：老的二进制程序在解析的时候只是简单地将新字段忽略。然而，未知的字段是没有被抛弃的，此后，如果消息被序列化，未知的字段会随之一起被序列化——所以，如果消息传到了新代码那里，则新的字段仍然可用。注意：对Python来说，对未知字段的保留策略是无效的。

l 非required的字段可以移除——只要它们的标识号（tag number）在你的新消息类型中不再使用（更好的做法可能是重命名那个字段，例如在字段前添加“OBSOLETE_”前缀，那样的话，你的.proto文件的用户将来就不会无意中重新使用了那些不该使用的标识号）。

l 一个非required的字段可以转换为一个扩展（extension），反之亦然——只要它的类型和标识号保持不变。

l int32, uint32, int64, uint64,和bool是全部兼容的，这意味着你可以将这些类型中的一个转换为另外一个，而不会破坏前向、后向的兼容性。如果解析出来的数字与对应的类型不相符，那么结果就像在C++中对它进行了强制类型转换一样（例如，如果把一个64位数字当作int32来读取，那么它就会被截断为32位的数字）。

l sint32和sint64是互相兼容的，但是它们与其他整数类型不兼容。

l string和bytes是兼容的——只要bytes是有效的UTF-8编码。

l 嵌套消息与bytes是兼容的——只要bytes包含该消息的一个编码过的版本。

l fixed32与sfixed32是兼容的，fixed64与sfixed64是兼容的。

Extensions 扩展

Extensions let you declare that a range of field numbers in a message are available for third-party extensions. Other people can then declare new fields for your message type with those numeric tags in their own .proto files without having to edit the original file. Let's look at an example:

通过扩展，你可以将一个范围内的字段标识号声明为可被第三方扩展所用。然后，其他人就可以在他们自己的.proto文件中为你的消息类型声明新的字段，而不必去编辑原始文件了。让我们看个例子：

message Foo {

// ...

extensions 100 to 199;

}

This says that the range of field numbers [100, 199] in Foo is reserved for extensions. Other users can now add new fields to Foo in their own.proto files that import your .proto, using tags within your specified range – for example:

这个例子表明：在消息Foo中，范围[100,199]之内的字段标识号被保留为扩展用。现在，其他人就可以在他们自己的.proto文件中添加新字段到Foo里了，但是添加的字段标识号要在指定的范围内——例如：

extend Foo {

optional int32 bar = 126;

}

This says that Foo now has an optional int32 field called bar.

When your user's Foo messages are encoded, the wire format is exactly the same as if the user defined the new field inside Foo. However, the way you access extension fields in your application code is slightly different to accessing regular fields – your generated data access code has special accessors for working with extensions. So, for example, here's how you set the value of bar in C++:

这个例子表明：消息Foo现在有一个名为bar的optional int32字段。

当用户的Foo消息被编码的时候，数据的传输格式与用户在Foo里定义新字段的效果是完全一样的。

然而，你在程序代码中访问扩展字段的方法与访问普通的字段稍有不同——你生成的数据访问代码为扩展准备了特殊的访问函数来访问它。例如，下面是你如何在C++中设置bar的值：

Foo foo;
foo.SetExtension(bar, 15);

Similarly, the Foo class defines templated accessors HasExtension(), ClearExtension(), GetExtension(), MutableExtension(), andAddExtension(). All have semantics matching the corresponding generated accessors for a normal field. For more information about working with extensions, see the generated code reference for your chosen language.

Note that extensions can be of any field type, including message types.

类似地，Foo类也定义了模板函数HasExtension()，ClearExtension()，GetExtension()，MutableExtension()，以及AddExtension()。这些函数的语义都与对应的普通字段的访问函数相符。要查看更多使用扩展的信息，请参考相应语言的代码生成指南。

注意：扩展可以是任何字段类型，包括消息类型。

文章来源：http://www.codelast.com/

Nested Extensions 嵌套的扩展

You can declare extensions in the scope of another type:

你可以在另一个类型的范围内声明扩展：

message Baz {

extend Foo {

optional int32 bar = 126;

}

...

}

In this case, the C++ code to access this extension is:

在此例中，访问此扩展的C++代码是：

Foo foo;

foo.SetExtension(Baz::bar, 15);

In other words, the only effect is that bar is defined within the scope of Baz.

换句话说，唯一的效果就是bar被定义在Baz的范围内。

This is a common source of confusion: Declaring an extend block nested inside a message type does not imply any relationship between the outer type and the extended type. In particular, the above example does not mean that Baz is any sort of subclass of Foo. All it means is that the symbol bar is declared inside the scope of Baz; it's simply a static member.

这是个引起混淆的来源：在一个消息类型中嵌套声明一个extend块并没有暗示外部类型（outer type）与扩展类型（extended type）之间有任何联系。特别地，上面的例子没有表明Baz是Foo的任何类型的子类。它所表明的仅仅是：符号bar是在Baz的内部声明的；它只是一个静态成员罢了。

A common pattern is to define extensions inside the scope of the extension's field type – for example, here's an extension to Foo of type Baz, where the extension is defined as part of Baz:

一个通常的设计模式就是：在扩展的字段类型的范围内定义该扩展——例如，下面是一个Foo的扩展（该扩展是Baz类型的），其中，扩展被定义为了Baz的一部分：

（译者注：这样的定义形式确很容易引起混淆，请继续往下看，以帮助你消除这种混淆）

message Baz {

extend Foo {

optional Baz foo_ext = 127;

}

...

}

However, there is no requirement that an extension with a message type be defined inside that type. You can also do this:

然而，并没有强制要求一个消息类型的扩展一定要定义在那个消息中。你也可以这样做：

message Baz {

...

}

// This can even be in a different file.

extend Foo {

optional Baz foo_baz_ext = 127;

}

In fact, this syntax may be preferred to avoid confusion. As mentioned above, the nested syntax is often mistaken for subclassing by users who are not already familiar with extensions.

事实上，这种语法格式更能防止引起混淆。正如上面所提到的，嵌套的语法通常被错误地认为有子类化的关系——尤其是对那些还不熟悉扩展的用户来说。

文章来源：https://www.codelast.com/
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[原创] Protocol Buffer Basics: C++中文翻译（Google Protocol Buffers中文教程）

learnhard — Tue, 14 Sep 2010 05:04:12 +0000

Protocol Buffer Basics: C++（Protocol Buffer基础：C++篇）

注：这是本人的翻译，可能不准确，可能有错误，但是基本上可以理解，希望能对大家有所帮助！（转载需注明出处：本文来自learnhard的博客：http://www.codelast.com/ & http://blog.csdn.net/learnhard/）

This tutorial provides a basic C++ programmer's introduction to working with protocol buffers. 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.

本教程提供了面向C++程序员的protocol buffers的基本介绍。通过创建一个简单的示例程序，它教你如何：

l 定义.proto文件的消息格式。

l 使用protocol buffer的编译器。

l 使用protoco buffer的C++ API来读写消息。

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.

本文并不是关于protocol buffers的C++使用的全面教程。要查看更详细的参考资料，请阅如下文章：Protocol Buffer Language Guide，C++ API Reference，C++ Generated Code Guide，以及 Encoding Reference。

Why Use Protocol Buffers? 为什么要使用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:

· The raw in-memory data structures can be sent/saved in binary form. Over time, this is a fragile approach, as the receiving/reading code must be compiled with exactly the same memory layout, endianness, etc. Also, as files accumulate data in the raw format and copies of software that are wired for that format are spread around, it's very hard to extend the format.

· 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.

（这一段不翻译了，没意思）

Where to Find the Example Code 在哪可以找到示例代码

The example code is included in the source code package, under the "examples" directory. Download it here.

示例代码包含在源代码包中的“examples”目录下。点击此处下载。

Defining Your Protocol Format 定义你自己的协议格式

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. Here is the .proto file that defines your messages, addressbook.proto.

要创建你的地址薄应用程序，你需要从编写一个.proto文件开始。.proto文件的定义是比较简单的：为每一个你需要序列化的数据结构添加一个消息（message），然后为消息（message）中的每一个字段（field）指定一个名字和一个类型。下面就是一个定义你的多个消息（messages）的文件addressbook.proto：

package tutorial;

message Person {

required string name = 1;

required int32 id = 2;

optional string email = 3;

enum PhoneType {

MOBILE = 0;

HOME = 1;

WORK = 2;

}

message PhoneNumber {

required string number = 1;

optional PhoneType type = 2 [default = HOME];

}

repeated PhoneNumber phone = 4;

}

message AddressBook {

repeated Person person = 1;

}

As you can see, the syntax is similar to C++ or Java. Let's go through each part of the file and see what it does.

正如你所看到的一样，该语法类似于C++或Java的语法。让我们依次来看看文件的每一部分的作用。

The .proto file starts with a package declaration, which helps to prevent naming conflicts between different projects. In C++, your generated classes will be placed in a namespace matching the package name.

.proto文件以一个package声明开始。这个声明是为了防止不同项目之间的命名冲突。对应到C++中去，你用这个.proto文件生成的类将被放置在一个与package名相同的命名空间中。

文章来源：http://www.codelast.com/

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 – 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.

再往下看，就是若干消息（message）定义了。一个消息就是某些类型的字段的集合。许多标准的、简单的数据类型都可以用作字段类型，包括bool，int32，float，double，以及string。你也可以使用其他的消息（message）类型来作为你的字段类型——在上面的例子中，消息Person就是一个被用作字段类型的例子。

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.

在每一项后面的、类似于“= 1”，“= 2”的标志指出了该字段在二进制编码中使用的唯一“标识（tag）”。标识号1~15编码所需的字节数比更大的标识号使用的字节数要少1个，所以，如果你想寻求优化，可以为经常使用或者重复的项采用1~15的标识（tag），其他经常使用的optional项采用≥16的标识（tag）。在重复的字段中，每一项都要求重编码标识号（tag number），所以重复的字段特别适用于这种优化情况。

Each field must be annotated with one of the following modifiers:

· required: a value for the field must be provided, otherwise the message will be considered "uninitialized". If libprotobuf is compiled in debug mode, serializing an uninitialized message will cause an assertion failure. In optimized builds, the check is skipped and the message will be written anyway. However, parsing an uninitialized message will always fail (by returning false from the parse method). Other than this, a required field behaves exactly like an optional field.

· optional: the field may or may not be set. If an optional field value isn't set, a default value is used. For simple types, you can specify your own default value, as we've done for the phone number type in the example. Otherwise, a system default 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 an optional (or required) field which has not been explicitly set always returns that field's default value.

· 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.

每一个字段都必须用以下之一的修饰符来修饰：

l required：必须提供字段值，否则对应的消息就会被认为是“未初始化的”。如果libprotobuf是以debug模式编译的，序列化一个未初始化的消息（message）将会导致一个断言错误。在优化过的编译情况下（译者注：例如release），该检查会被跳过，消息会被写入。然而，解析一个未初始化的消息仍然会失败（解析函数会返回false）。除此之外，一个required的字段与一个optional的字段就没有区别了。

l optional：字段值指定与否都可以。如果没有指定一个optional的字段值，它就会使用默认值。对简单类型来说，你可以指定你自己的默认值，就像我们在上面的例子中对phone number的type字段所做的一样。如果你不指定默认值，就会使用系统默认值：数据类型的默认值为0，string的默认值为空字符串，bool的默认值为false。对嵌套消息（message）来说，其默认值总是消息的“默认实例”或“原型”，即：没有任何一个字段是指定了值的。调用访问类来取一个未显式指定其值的optional（或者required）的字段的值，总是会返回字段的默认值。

l repeated：字段会重复N次（N可以为0）。重复的值的顺序将被保存在protocol buffer中。你只要将重复的字段视为动态大小的数组就可以了。

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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.

你可以在Protocol Buffer Language Guide一文中找到编写.proto文件的完整指南（包括所有可能的字段类型）。但是，不要想在里面找到与类继承相似的特性，因为protocol buffers不是拿来做这个的。

Compiling Your Protocol Buffers 编译你的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 Personand 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...:

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

Because you want C++ classes, you use the --cpp_out option – similar options are provided for other supported languages.

This generates the following files in your specified destination directory:

· addressbook.pb.h, the header which declares your generated classes.

· addressbook.pb.cc, which contains the implementation of your classes.

在得到了一个.proto文件之后，下一步你就要生成可以读写AddressBook消息（当然也就包括了Person以及PhoneNumber消息）的类了。此时你需要运行protocol buffer编译器来编译你的.proto文件：

1. 如果你还没有安装该编译器，下载安装包 并参照README文件中的说明来安装。

2. 安装了之后，就可以运行编译器了。指定源目录（即你的应用程序源代码所在的目录——如果不指定的话，就使用当前目录）、目标目录（即生成的代码放置的目录，通常与$SRC_DIR是一样的），以及你的.proto文件所在的目录。在我们这里，可以这样用：

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

因为需要生成的是C++类，所以使用了--cpp_out选项参数——protocol buffers也为其他支持的语言提供了类似的选项参数。这样就可以在你指定的目标目录下生成如下文件：

l addressbook.pb.h：声明你生成的类的头文件。

l addressbook.pb.cc：你生成的类的实现文件。

The Protocol Buffer API

Let's look at some of the generated code and see what classes and functions the compiler has created for you. If you look in tutorial.pb.h, you can see that you have a class for each message you specified in tutorial.proto. Looking closer at the Person class, you can see that the complier has generated accessors for each field. For example, for the name, id, email, and phone fields, you have these methods:

让我们看一下生成的代码，了解一下编译器为你创建了什么样的类和函数。如果你看了tutorial.pb.h文件，就会发现你得到了一个类，它对应于tutorial.proto文件中写的每一个消息（message）。更深入一步，看看Person 类：编译器为每一个字段生成了读写函数。例如，对name，id，email以及phone字段，分别有如下函数：

// name
inline bool has_name() const;
inline void clear_name();
inline const ::std::string& name() const;
inline void set_name(const ::std::string& value);
inline void set_name(const char* value);
inline ::std::string* mutable_name();

// id
inline bool has_id() const;
inline void clear_id();
inline int32_t id() const;
inline void set_id(int32_t value);

// email
inline bool has_email() const;
inline void clear_email();
inline const ::std::string& email() const;
inline void set_email(const ::std::string& value);
inline void set_email(const char* value);
inline ::std::string* mutable_email();

// phone
inline int phone_size() const;
inline void clear_phone();
inline const ::google::protobuf::RepeatedPtrField< ::tutorial::Person_PhoneNumber >& phone() const;
inline ::google::protobuf::RepeatedPtrField< ::tutorial::Person_PhoneNumber >* mutable_phone();
inline const ::tutorial::Person_PhoneNumber& phone(int index) const;
inline ::tutorial::Person_PhoneNumber* mutable_phone(int index);
inline ::tutorial::Person_PhoneNumber* add_phone();

As you can see, the getters have exactly the name as the field in lowercase, and the setter methods begin with set_. There are also has_ methods for each singular (required or optional) field which return true if that field has been set. Finally, each field has a clear_ method that un-sets the field back to its empty state.

正如你所看到的，getter函数具有与字段名一模一样的名字，并且是小写的，而setter函数都是以set_前缀开头。此外，还有has_前缀的函数，对每一个单一的（required或optional的）字段（译者注：此处估计是“非repeated字段”的意思）来说，如果字段被置（set）了值，该函数会返回true。最后，每一个字段还有一个clear_前缀的函数，用来将字段重置（un-set）到空状态（empty state）。

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While the numeric id field just has the basic accessor set described above, the name and email fields have a couple of extra methods because they're strings – a mutable_ getter that lets you get a direct pointer to the string, and an extra setter. Note that you can call mutable_email() even ifemail is not already set; it will be initialized to an empty string automatically. If you had a singular message field in this example, it would also have a mutable_ method but not a set_ method.

然而，数值类型的字段id就只有如上所述的基本读写函数，name和email字段则有一些额外的函数，因为它们是string——前缀为mutable_的函数返回string的直接指针（direct pointer）。除此之外，还有一个额外的setter函数。注意：你甚至可以在email还没有被置（set）值的时候就调用mutable_email()，它会被自动初始化为一个空字符串。在此例中，如果有一个单一消息字段，那么它也会有一个mutable_ 前缀的函数，但是没有一个set_ 前缀的函数。

Repeated fields also have some special methods – if you look at the methods for the repeated phone field, you'll see that you can

· check the repeated field's _size (in other words, how many phone numbers are associated with this Person).

· get a specified phone number using its index.

· update an existing phone number at the specified index.

· add another phone number to the message which you can then edit (repeated scalar types have an add_ that just lets you pass in the new value).

重复的字段也有一些特殊的函数——如果你看一下重复字段phone 的那些函数，就会发现你可以：

l 得到重复字段的_size（换句话说，这个Person关联了多少个电话号码）。

l 通过索引（index）来获取一个指定的电话号码。

l 通过指定的索引（index）来更新一个已经存在的电话号码。

l 向消息（message）中添加另一个电话号码，然后你可以编辑它（重复的标量类型有一个add_前缀的函数，允许你传新值进去）。

For more information on exactly what members the protocol compiler generates for any particular field definition, see the C++ generated code reference.

关于编译器如何生成特殊字段的更多信息，请查看文章C++ generated code reference。

Enums and Nested Classes 枚举和嵌套类

The generated code includes a PhoneType enum that corresponds to your .proto enum. You can refer to this type as Person::PhoneType and its values as Person::MOBILE, Person::HOME, and Person::WORK (the implementation details are a little more complicated, but you don't need to understand them to use the enum).

生成的代码中包含了一个PhoneType 枚举，它对应于.proto文件中的那个枚举。你可以把这个类型当作Person::PhoneType，其值为Person::MOBILE，Person::HOME和Person::WORK（实现的细节稍微复杂了点，但是没关系，不理解它也不会影响你使用该枚举）。

The compiler has also generated a nested class for you called Person::PhoneNumber. If you look at the code, you can see that the "real" class is actually called Person_PhoneNumber, but a typedef defined inside Person allows you to treat it as if it were a nested class. The only case where this makes a difference is if you want to forward-declare the class in another file – you cannot forward-declare nested types in C++, but you can forward-declare Person_PhoneNumber.

编译器还生成了一个名为Person::PhoneNumber的嵌套类。如果你看看代码，就会发现“真实的”类实际上是叫做Person_PhoneNumber，只不过Person 内部的一个typedef允许你像一个嵌套类一样来对待它。这一点所造成的唯一一个区别就是：如果你想在另一个文件中对类进行前向声明（forward-declare）的话，你就不能在C++中对嵌套类型进行前向声明了，但是你可以对Person_PhoneNumber进行前向声明。

Standard Message Methods 标准消息函数

Each message class also contains a number of other methods that let you check or manipulate the entire message, including:

· bool IsInitialized() const;: checks if all the required fields have been set.

· string DebugString() const;: returns a human-readable representation of the message, particularly useful for debugging.

· void CopyFrom(const Person& from);: overwrites the message with the given message's values.

· void Clear();: clears all the elements back to the empty state.

These and the I/O methods described in the following section implement the Message interface shared by all C++ protocol buffer classes. For more info, see the complete API documentation for Message.

每一个消息（message）还包含了其他一系列函数，用来检查或管理整个消息，包括：

l bool IsInitialized() const;：检查是否全部的required字段都被置（set）了值。

l string DebugString() const;：返回一个易读的消息表示形式，对调试特别有用。

l void CopyFrom(const Person& from);：用外部消息的值，覆写调用者消息内部的值。

l void Clear();：将所有项复位到空状态（empty state）。

这些函数以及后面章节将要提到的I/O函数实现了Message 的接口，它们被所有C++ protocol buffer类共享。更多信息，请查看文章 complete API documentation for Message。

Parsing and Serialization 解析&序列化

Finally, each protocol buffer class has methods for writing and reading messages of your chosen type using the protocol buffer binary format. These include:

· bool SerializeToString(string* output) const;: serializes the message and stores the bytes in the given string. Note that the bytes are binary, not text; we only use the string class as a convenient container.

· bool ParseFromString(const string& data);: parses a message from the given string.

· bool SerializeToOstream(ostream* output) const;: writes the message to the given C++ ostream.

· bool ParseFromIstream(istream* input);: parses a message from the given C++ istream.

These are just a couple of the options provided for parsing and serialization. Again, see the Message API reference for a complete list.

最后，每一个protocol buffer类都有读写你所选择的消息类型的函数。它们包括：

l bool SerializeToString(string* output) const;：将消息序列化并储存在指定的string中。注意里面的内容是二进制的，而不是文本；我们只是使用string作为一个很方便的容器。

l bool ParseFromString(const string& data);：从给定的string解析消息。

l bool SerializeToOstream(ostream* output) const;：将消息写入到给定的C++ ostream中。

l bool ParseFromIstream(istream* input);：从给定的C++ istream解析消息。

这些函数只是用于解析和序列化的几个函数罢了。请再次参考Message API reference以查看完整的函数列表。

Protocol Buffers and O-O Design Protocol buffer classes are basically dumb data holders (like structs in C++); they don't make good first class citizens in an object model. If you want to add richer behaviour to a generated class, the best way to do this is to wrap the generated protocol buffer class in an application-specific class. Wrapping protocol buffers is also a good idea if you don't have control over the design of the .proto file (if, say, you're reusing one from another project). In that case, you can use the wrapper class to craft an interface better suited to the unique environment of your application: hiding some data and methods, exposing convenience functions, etc. You should never add behaviour to the generated classes by inheriting from them. This will break internal mechanisms and is not good object-oriented practice anyway.

protocol buffers和面向对象的设计 protocol buffer类通常只是纯粹的数据存储器（就像C++中的结构体一样）；它们在对象模型中并不是一等公民。如果你想向生成的类中添加更丰富的行为，最好的方法就是在应用程序中对它进行封装。如果你无权控制.proto文件的设计的话，封装protocol buffers也是一个好主意（例如，你从另一个项目中重用一个.proto文件）。在那种情况下，你可以用封装类来设计接口，以更好地适应你的应用程序的特定环境：隐藏一些数据和方法，暴露一些便于使用的函数，等等。但是你绝对不要通过继承生成的类来添加行为。这样做的话，会破坏其内部机制，并且不是一个好的面向对象的实践。

Writing A Message 写消息

Now let's try using your protocol buffer classes. The first thing you want your address book application to be able to do is write personal details to your address book file. To do this, you need to create and populate instances of your protocol buffer classes and then write them to an output stream.

Here is a program which reads an AddressBook from a file, adds one new Person to it based on user input, and writes the new AddressBook back out to the file again. The parts which directly call or reference code generated by the protocol compiler are highlighted.

现在让我们尝试使用你的protocol buffer类。你想让你的address book程序完成的第一件事情就是向你的address book文件写入详细的个人信息。要实现这一点，你需要创建protocol buffer类的实例并将它们写入到一个输出流（output stream）中。

下面的这个程序从一个文件中读取AddressBook ，然后根据用户的输入向其中添加一个新的Person ，然后再将新的AddressBook 写回文件中。由protocol buffer编译器生成的代码或者直接调用的代码都被突出显示了。

#include
#include
#include
#include "addressbook.pb.h"
using namespace std;

// This function fills in a Person message based on user input.
void PromptForAddress(tutorial::Person* person) {
cout << "Enter person ID number: ";
int id;
cin >> id;
person->set_id(id);
cin.ignore(256, '\n'); // cin.ignore(a,ch)方法是从输入流（cin）中提取字符，提取的字符被忽略（ignore），不被使用。每抛弃一个字符，它都要计数和比较字符：如果计数值达到a或者被抛弃的字符是ch，则cin.ignore()函数执行终止；否则，它继续等待。它的一个常用功能就是用来清除以回车结束的输入缓冲区的内容，消除上一次输入对下一次输入的影响。比如可以这么用：cin.ignore(1024,'\n')，通常把第一个参数设置得足够大，这样实际上总是只有第二个参数'\n'起作用，所以这一句就是把回车（包括回车）之前的所以字符从输入缓冲（流）中清除出去。

cout << "Enter name: ";
getline(cin, *person->mutable_name());

cout << "Enter email address (blank for none): ";
string email;
getline(cin, email);
if (!email.empty()) {
person->set_email(email);
}

while (true) {
cout << "Enter a phone number (or leave blank to finish): ";
string number;
getline(cin, number);
if (number.empty()) {
break;
}

tutorial::Person::PhoneNumber* phone_number = person->add_phone();
phone_number->set_number(number);

cout << "Is this a mobile, home, or work phone? ";
string type;
getline(cin, type);
if (type == "mobile") {
phone_number->set_type(tutorial::Person::MOBILE);
} else if (type == "home") {
phone_number->set_type(tutorial::Person::HOME);
} else if (type == "work") {
phone_number->set_type(tutorial::Person::WORK);
} else {
cout << "Unknown phone type. Using default." << endl;
}
}
}

// Main function: Reads the entire address book from a file,
// adds one person based on user input, then writes it back out to the same
// file.
int main(int argc, char* argv[]) {
// Verify that the version of the library that we linked against is
// compatible with the version of the headers we compiled against.
GOOGLE_PROTOBUF_VERIFY_VERSION;

if (argc != 2) {
cerr << "Usage: " << argv[0] << " ADDRESS_BOOK_FILE" << endl;
return -1;
}

tutorial::AddressBook address_book;

{
// Read the existing address book.
fstream input(argv[1], ios::in | ios::binary);
if (!input) {
cout << argv[1] << ": File not found. Creating a new file." << endl;
} else if (!address_book.ParseFromIstream(&input)) {
cerr << "Failed to parse address book." << endl;
return -1;
}
}

// Add an address.
PromptForAddress(address_book.add_person());

{
// Write the new address book back to disk.
fstream output(argv[1], ios::out | ios::trunc | ios::binary);
if (!address_book.SerializeToOstream(&output)) {
cerr << "Failed to write address book." << endl;
return -1;
}
}

// Optional: Delete all global objects allocated by libprotobuf.
google::protobuf::ShutdownProtobufLibrary();

return 0;
}

Notice the GOOGLE_PROTOBUF_VERIFY_VERSION macro. It is good practice – though not strictly necessary – to execute this macro before using the C++ Protocol Buffer library. It verifies that you have not accidentally linked against a version of the library which is incompatible with the version of the headers you compiled with. If a version mismatch is detected, the program will abort. Note that every .pb.cc file automatically invokes this macro on startup.

注意GOOGLE_PROTOBUF_VERIFY_VERSION宏。你最好像这样——尽管这不是严格要求的——在使用C++ Protocol Buffer库之前执行该宏。它会检查你是不是在无意中链接到了与你使用的头文件不兼容的protocol buffer库。如果检测到了不匹配情况，程序会中止运行下去。注意：每一个.pb.cc文件在开始的时候都会自动调用该宏。

文章来源：http://www.codelast.com/

Also notice the call to ShutdownProtobufLibrary() at the end of the program. All this does is delete any global objects that were allocated by the Protocol Buffer library. This is unnecessary for most programs, since the process is just going to exit anyway and the OS will take care of reclaiming all of its memory. However, if you use a memory leak checker that requires that every last object be freed, or if you are writing a library which may be loaded and unloaded multiple times by a single process, then you may want to force Protocol Buffers to clean up everything.

另外还需要注意的是程序结尾处调用的ShutdownProtobufLibrary()函数。该函数所做的所有工作就是删除由Protocol Buffer库分配的全局对象。在大多数程序中，这都是没有必要的，因为进程一退出，操作系统就回收了它的内存。然而，如果你使用了内存检查工具（译者注：例如valgrind）来检查你的程序的话（内存检查工具要求每一个对象最后都要被释放），或者你写了一个可能会在一个进程中多次被加载、卸载的库，那么你可能就需要强制Protocol Buffer来清理一切了。

Reading A Message 读消息

Of course, an address book wouldn't be much use if you couldn't get any information out of it! This example reads the file created by the above example and prints all the information in it.

当然，如果你不能从一个address book中取出信息的话，那么它也就没什么用了！下面的例子展示了如何读取上面的程序创建的文件，并将读到的所有信息打印出来。

#include
#include
#include
#include "addressbook.pb.h"
using namespace std;

// Iterates though all people in the AddressBook and prints info about them.
void ListPeople(const tutorial::AddressBook& address_book) {
for (int i = 0; i < address_book.person_size(); i++) {
const tutorial::Person& person = address_book.person(i);

cout << "Person ID: " << person.id() << endl;
cout << " Name: " << person.name() << endl;
if (person.has_email()) {
cout << " E-mail address: " << person.email() << endl;
}

for (int j = 0; j < person.phone_size(); j++) {
const tutorial::Person::PhoneNumber& phone_number = person.phone(j);

switch (phone_number.type()) {
case tutorial::Person::MOBILE:
cout << " Mobile phone #: ";
break;
case tutorial::Person::HOME:
cout << " Home phone #: ";
break;
case tutorial::Person::WORK:
cout << " Work phone #: ";
break;
}
cout << phone_number.number() << endl;
}
}
}

// Main function: Reads the entire address book from a file and prints all
// the information inside.
int main(int argc, char* argv[]) {
// Verify that the version of the library that we linked against is
// compatible with the version of the headers we compiled against.
GOOGLE_PROTOBUF_VERIFY_VERSION;

if (argc != 2) {
cerr << "Usage: " << argv[0] << " ADDRESS_BOOK_FILE" << endl;
return -1;
}

tutorial::AddressBook address_book;

{
// Read the existing address book.
fstream input(argv[1], ios::in | ios::binary);
if (!address_book.ParseFromIstream(&input)) {
cerr << "Failed to parse address book." << endl;
return -1;
}
}

ListPeople(address_book);

// Optional: Delete all global objects allocated by libprotobuf.
google::protobuf::ShutdownProtobufLibrary();

return 0;
}

Extending a Protocol Buffer 扩展一个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 must not add or delete any required fields.

· you may delete optional or repeated fields.

· you may add new optional or repeated 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, optional 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 optional fields will not be present in old messages, so you will need to either check explicitly whether they're set with has_, or provide a reasonable default value in your .proto file with [default = value] after the tag number. If the default value is not specified for an optional element, a type-specific default value is used instead: for strings, the default value is the empty string. For booleans, the default value is false. For numeric types, the default value is zero. Note also that if you added a new repeated field, your new code will not be able to tell whether it was left empty (by new code) or never set at all (by old code) since there is no has_ flag for it.

无论或早或晚，在你放出你那使用protocol buffer的代码之后，你必定会想“改进”protocol buffer的定义。如果你想让你的新buffer向后兼容（backwards-compatible），并且旧的buffer能够向前兼容（forward-compatible）——你一定希望如此——那么你在新的protocol buffer中就要遵守其他的一些规则了：

l 对已存在的任何字段，你都不能更改其标识（tag）号。

l 你绝对不能添加或删除任何required的字段。

l 你可以添加新的optional或repeated的字段，但是你必须使用新的标识（tag）号（例如，在这个protocol buffer中从未使用过的标识号——甚至于已经被删除过的字段使用过的标识号也不行）。

（有一些例外情况，但是它们很少使用。）

如果你遵守这些规则，老的代码将能很好地解析新的消息（message），并忽略掉任何新的字段。对老代码来说，已经被删除的optional字段将被赋予默认值，已被删除的repeated字段将是空的。新的代码也能够透明地读取旧的消息。但是，请牢记心中：新的optional字段将不会出现在旧的消息中，所以你要么需要显式地检查它们是否由has_前缀的函数置（set）了值，要么在你的.proto文件中，在标识（tag）号的后面用[default = value]提供一个合理的默认值。如果没有为一个optional项指定默认值，那么就会使用与特定类型相关的默认值：对string来说，默认值是空字符串。对boolean来说，默认值是false。对数值类型来说，默认值是0。还要注意：如果你添加了一个新的repeated字段，你的新代码将无法告诉你它是否被留空了（被新代码），或者是否从未被置（set）值（被旧代码），这是因为它没有has_标志。

Optimization Tips 优化小技巧

The C++ Protocol Buffers library is extremely heavily optimized. However, proper usage can improve performance even more. Here are some tips for squeezing every last drop of speed out of the library:

· Reuse message objects when possible. Messages try to keep around any memory they allocate for reuse, even when they are cleared. Thus, if you are handling many messages with the same type and similar structure in succession, it is a good idea to reuse the same message object each time to take load off the memory allocator. However, objects can become bloated over time, especially if your messages vary in "shape" or if you occasionally construct a message that is much larger than usual. You should monitor the sizes of your message objects by calling the SpaceUsed method and delete them once they get too big.

· Your system's memory allocator may not be well-optimized for allocating lots of small objects from multiple threads. Try using Google's tcmalloc instead.

Protocol Buffer 的C++库已经做了极度优化。但是，正确的使用方法仍然会提高很多性能。下面是一些小技巧，用来提升protocol buffer库的最后一丝速度能力：

l 如果有可能，重复利用消息（message）对象。即使被清除掉，消息（message）对象也会尽量保存所有被分配来重用的内存。这样的话，如果你正在处理很多类型相同的消息以及一系列相似的结构，有一个好办法就是重复使用同一个消息（message）对象，从而使内存分配的压力减小一些。然而，随着时间的流逝，对象占用的内存也有可能变得越来越大，尤其是当你的消息尺寸（译者注：各消息内容不同，有些消息内容多一些，有些消息内容少一些）不同的时候，或者你偶尔创建了一个比平常大很多的消息（message）的时候。你应该自己监测消息（message）对象的大小——通过调用SpaceUsed函数——并在它太大的时候删除它。

l 在多线程中分配大量小对象的内存的时候，你的操作系统的内存分配器可能优化得不够好。在这种情况下，你可以尝试用一下Google's tcmalloc。

Advanced Usage 高级使用

Protocol buffers have uses that go beyond simple accessors and serialization. Be sure to explore the C++ API reference to see what else you can do with them.

One key feature provided by protocol message classes is reflection. You can iterate over the fields of a message and manipulate their values without writing your code against any specific message type. One very useful way to use reflection is for converting protocol messages to and from other encodings, such as XML or JSON. A more advanced use of reflection might be to find differences between two messages of the same type, or to develop a sort of "regular expressions for protocol messages" in which you can write expressions that match certain message contents. If you use your imagination, it's possible to apply Protocol Buffers to a much wider range of problems than you might initially expect!

Reflection is provided by the Message::Reflection interface.

Protocol Buffers的作用绝不仅仅是简单的数据存取以及序列化。请阅读C++ API reference全文来看看你还能用它来做什么。

protocol消息类所提供的一个关键特性就是反射。你不需要编写针对一个特殊的消息（message）类型的代码，就可以遍历一个消息的字段，并操纵它们的值，就像XML和JSON一样。“反射”的一个更高级的用法可能就是可以找出两个相同类型的消息之间的区别，或者开发某种“协议消息的正则表达式”，利用正则表达式，你可以对某种消息内容进行匹配。只要你发挥你的想像力，就有可能将Protocol Buffers应用到一个更广泛的、你可能一开始就期望解决的问题范围上。

“反射”是由Message::Reflection interface提供的。

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