Language Guide (proto 3)

Covers how to use the version 3 of Protocol Buffers in your project.

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. It covers the proto3 version of the protocol buffers language: for information on the proto2 syntax, see the Proto2 Language Guide.

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.

Defining A Message Type

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.

syntax = "proto3";

message SearchRequest {
  string query = 1;
  int32 page_number = 2;
  int32 results_per_page = 3;
  • The first line of the file specifies that you’re using proto3 syntax: if you don’t do this the protocol buffer compiler will assume you are using proto2. This must be the first non-empty, non-comment line of the file.
  • 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.

Specifying Field Types

In the earlier example, all the fields are scalar types: two integers (page_number and results_per_page) and a string (query). You can also specify enumerations and composite types like other message types for your field.

Assigning Field Numbers

You must give each field in your message definition a number between 1 and 536,870,911 with the following restrictions:

  • The given number must be unique among all fields for that message.
  • Field numbers 19,000 to 19,999 are reserved for the Protocol Buffers implementation. The protocol buffer compiler will complain if you use one of these reserved field numbers in your message.
  • You cannot use any previously reserved field numbers or any field numbers that have been allocated to extensions.

This number cannot be changed once your message type is in use because it identifies the field in the message wire format. “Changing” a field number is equivalent to deleting that field and creating a new field with the same type but a new number. See Deleting Fields for how to do this properly.

Field numbers should never be reused. Never take a field number out of the reserved list for reuse with a new field definition. See Consequences of Reusing Field Numbers.

You should use the field numbers 1 through 15 for the most-frequently-set fields. Lower field number values take less space in the wire format. For example, field numbers in the range 1 through 15 take one byte to encode. Field numbers in the range 16 through 2047 take two bytes. You can find out more about this in Protocol Buffer Encoding.

Consequences of Reusing Field Numbers

Reusing a field number makes decoding wire-format messages ambiguous.

The protobuf wire format is lean and doesn’t provide a way to detect fields encoded using one definition and decoded using another.

Encoding a field using one definition and then decoding that same field with a different definition can lead to:

  • Developer time lost to debugging
  • A parse/merge error (best case scenario)
  • Leaked PII/SPII
  • Data corruption

Common causes of field number reuse:

  • renumbering fields (sometimes done to achieve a more aesthetically pleasing number order for fields). Renumbering effectively deletes and re-adds all the fields involved in the renumbering, resulting in incompatible wire-format changes.
  • deleting a field and not reserving the number to prevent future reuse.

The max field is 29 bits instead of the more-typical 32 bits because three lower bits are used for the wire format. For more on this, see the Encoding topic.

Specifying Field Labels

Message fields can be one of the following:

  • optional: An optional field is in one of two possible states:

    • the field is set, and contains a value that was explicitly set or parsed from the wire. It will be serialized to the wire.
    • the field is unset, and will return the default value. It will not be serialized to the wire.

    You can check to see if the value was explicitly set.

  • repeated: this field type can be repeated zero or more times in a well-formed message. The order of the repeated values will be preserved.

  • map: this is a paired key/value field type. See Maps for more on this field type.

  • If no explicit field label is applied, the default field label, called “implicit field presence,” is assumed. (You cannot explicitly set a field to this state.) A well-formed message can have zero or one of this field (but not more than one). You also cannot determine whether a field of this type was parsed from the wire. An implicit presence field will be serialized to the wire unless it is the default value. For more on this subject, see Field Presence.

In proto3, repeated fields of scalar numeric types use packed encoding by default. You can find out more about packed encoding in Protocol Buffer Encoding.

Well-formed Messages

The term “well-formed,” when applied to protobuf messages, refers to the bytes serialized/deserialized. The protoc parser validates that a given proto definition file is parseable.

In the case of optional fields that have more than one value, the protoc parser will accept the input, but only uses the last field. So, the “bytes” may not be “well-formed” but the resulting message would have only one and would be “well-formed” (but would not roundtrip the same).

Message Type Fields Have Field Presence

In proto3, message-type fields already have field presence. Because of this, adding the optional modifier doesn’t change the field presence for the field.

The definitions for Message2 and Message3 in the following code sample generate the same code for all languages, and there is no difference in representation in binary, JSON, and TextFormat:



message Message1 {}

message Message2 {
  Message1 foo = 1;

message Message3 {
  optional Message1 bar = 1;

Adding More Message Types

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:

message SearchRequest {
  string query = 1;
  int32 page_number = 2;
  int32 results_per_page = 3;

message SearchResponse {

Combining Messages leads to bloat While multiple message types (such as message, enum, and service) can be defined in a single .proto file, it can also lead to dependency bloat when large numbers of messages with varying dependencies are defined in a single file. It’s recommended to include as few message types per .proto file as possible.

Adding Comments

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

/* SearchRequest represents a search query, with pagination options to
 * indicate which results to include in the response. */

message SearchRequest {
  string query = 1;
  int32 page_number = 2;  // Which page number do we want?
  int32 results_per_page = 3;  // Number of results to return per page.

Deleting Fields

Deleting fields can cause serious problems if not done properly.

When you no longer need a field and all references have been deleted from client code, you may delete the field definition from the message. However, you must reserve the deleted field number. If you do not reserve the field number, it is possible for a developer to reuse that number in the future.

You should also reserve the field name to allow JSON and TextFormat encodings of your message to continue to parse.

Reserved Field Numbers

If you update a message type by entirely deleting a field, or commenting it out, future developers can reuse the field number when making their own updates to the type. This can cause severe issues, as described in Consequences of Reusing Field Numbers. To make sure this doesn’t happen, add your deleted field number to the reserved list.

The protoc compiler will generate error messages if any future developers try to use these reserved field numbers.

message Foo {
  reserved 2, 15, 9 to 11;

Reserved field number ranges are inclusive (9 to 11 is the same as 9, 10, 11).

Reserved Field Names

Reusing an old field name later is generally safe, except when using TextProto or JSON encodings where the field name is serialized. To avoid this risk, you can add the deleted field name to the reserved list.

Reserved names affect only the protoc compiler behavior and not runtime behavior, with one exception: TextProto implementations may discard unknown fields (without raising an error like with other unknown fields) with reserved names at parse time (only the C++ and Go implementations do so today). Runtime JSON parsing is not affected by reserved names.

message Foo {
  reserved 2, 15, 9 to 11;
  reserved "foo", "bar";

Note that you can’t mix field names and field numbers in the same reserved statement.

What’s Generated from Your .proto?

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.

  • 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 class for creating message class instances.
  • For Kotlin, in addition to the Java generated code, the compiler generates a .kt file for each message type with an improved Kotlin API. This includes a DSL that simplifies creating message instances, a nullable field accessor, and a copy function.
  • 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.
  • For Go, the compiler generates a .pb.go file with a type for each message type in your file.
  • For Ruby, the compiler generates a .rb file with a Ruby module containing your message types.
  • For Objective-C, the compiler generates a pbobjc.h and pbobjc.m file from each .proto, with a class for each message type described in your file.
  • For C#, the compiler generates a .cs file from each .proto, with a class for each message type described in your file.
  • For PHP, the compiler generates a .php message file for each message type described in your file, and a .php metadata file for each .proto file you compile. The metadata file is used to load the valid message types into the descriptor pool.
  • For Dart, the compiler generates a .pb.dart file with a class for each message type in your file.

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.

Scalar Value Types

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:

.proto TypeNotesC++ TypeJava/Kotlin Type[1]Python Type[3]Go TypeRuby TypeC# TypePHP TypeDart TypeRust Type
int32Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint32 instead.int32intintint32Fixnum or Bignum (as required)intintegerinti32
int64Uses variable-length encoding. Inefficient for encoding negative numbers – if your field is likely to have negative values, use sint64 instead.int64longint/long[4]int64Bignumlonginteger/string[6]Int64i64
uint32Uses variable-length encoding.uint32int[2]int/long[4]uint32Fixnum or Bignum (as required)uintintegerintu32
uint64Uses variable-length encoding.uint64long[2]int/long[4]uint64Bignumulonginteger/string[6]Int64u64
sint32Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int32s.int32intintint32Fixnum or Bignum (as required)intintegerinti32
sint64Uses variable-length encoding. Signed int value. These more efficiently encode negative numbers than regular int64s.int64longint/long[4]int64Bignumlonginteger/string[6]Int64i64
fixed32Always four bytes. More efficient than uint32 if values are often greater than 228.uint32int[2]int/long[4]uint32Fixnum or Bignum (as required)uintintegerintu32
fixed64Always eight bytes. More efficient than uint64 if values are often greater than 256.uint64long[2]int/long[4]uint64Bignumulonginteger/string[6]Int64u64
sfixed32Always four bytes.int32intintint32Fixnum or Bignum (as required)intintegerinti32
sfixed64Always eight bytes.int64longint/long[4]int64Bignumlonginteger/string[6]Int64i64
stringA string must always contain UTF-8 encoded or 7-bit ASCII text, and cannot be longer than 232.stringStringstr/unicode[5]stringString (UTF-8)stringstringStringProtoString
bytesMay contain any arbitrary sequence of bytes no longer than 232.stringByteStringstr (Python 2)
bytes (Python 3)
[]byteString (ASCII-8BIT)ByteStringstringListProtoBytes

[1] Kotlin uses the corresponding types from Java, even for unsigned types, to ensure compatibility in mixed Java/Kotlin codebases.

[2] 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.

[3] In all cases, setting values to a field will perform type checking to make sure it is valid.

[4] 64-bit or unsigned 32-bit integers are always represented as long when decoded, but can be an int if an int is given when setting the field. In all cases, the value must fit in the type represented when set. See [2].

[5] Python strings are represented as unicode on decode but can be str if an ASCII string is given (this is subject to change).

[6] Integer is used on 64-bit machines and string is used on 32-bit machines.

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

Default Values

When a message is parsed, if the encoded message does not contain a particular implicit presence element, accessing the corresponding field in the parsed object returns the default value for that field. These defaults are type-specific:

  • For strings, the default value is the empty string.
  • For bytes, the default value is empty bytes.
  • For bools, the default value is false.
  • For numeric types, the default value is zero.
  • For enums, the default value is the first defined enum value, which must be 0.
  • For message fields, the field is not set. Its exact value is language-dependent. See the generated code guide for details.

The default value for repeated fields is empty (generally an empty list in the appropriate language).

Note that for scalar message fields, once a message is parsed there’s no way of telling whether a field was explicitly set to the default value (for example whether a boolean was set to false) or just not set at all: you should bear this in mind when defining your message types. For example, don’t have a boolean that switches on some behavior when set to false if you don’t want that behavior to also happen by default. Also note that if a scalar message field is set to its default, the value will not be serialized on the wire. If a float or double value is set to +0 it will not be serialized, but -0 is considered distinct and will be serialized.

See the generated code guide for your chosen language for more details about how defaults work in generated code.


When you’re defining a message type, you might want one of its fields to only have one of a predefined 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 with a constant for each possible value.

In the following example we’ve added an enum called Corpus with all the possible values, and a field of type Corpus:

enum Corpus {

message SearchRequest {
  string query = 1;
  int32 page_number = 2;
  int32 results_per_page = 3;
  Corpus corpus = 4;

As you can see, the Corpus enum’s first constant maps to zero: every enum definition must contain a constant that maps to zero as its first element. This is because:

  • There must be a zero value, so that we can use 0 as a numeric default value.
  • The zero value needs to be the first element, for compatibility with the proto2 semantics where the first enum value is the default unless a different value is explicitly specified.

You can define aliases by assigning the same value to different enum constants. To do this you need to set the allow_alias option to true. Otherwise, the protocol buffer compiler generates a warning message when aliases are found. Though all alias values are valid during deserialization, the first value is always used when serializing.

enum EnumAllowingAlias {
  option allow_alias = true;

enum EnumNotAllowingAlias {
  // ENAA_RUNNING = 1;  // Uncommenting this line will cause a warning message.

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 earlier 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, Kotlin, 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.

During deserialization, unrecognized enum values will be preserved in the message, though how this is represented when the message is deserialized is language-dependent. In languages that support open enum types with values outside the range of specified symbols, such as C++ and Go, the unknown enum value is simply stored as its underlying integer representation. In languages with closed enum types such as Java, a case in the enum is used to represent an unrecognized value, and the underlying integer can be accessed with special accessors. In either case, if the message is serialized the unrecognized value will still be serialized with the message.

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

Reserved Values

If you update an enum type by entirely removing an enum entry, or commenting it out, future users can reuse the numeric value when making their own updates to the type. This can cause severe issues if they later load old versions of the same .proto, including data corruption, privacy bugs, and so on. One way to make sure this doesn’t happen is to specify that the numeric values (and/or names, which can also cause issues for JSON serialization) of your deleted entries are reserved. The protocol buffer compiler will complain if any future users try to use these identifiers. You can specify that your reserved numeric value range goes up to the maximum possible value using the max keyword.

enum Foo {
  reserved 2, 15, 9 to 11, 40 to max;
  reserved "FOO", "BAR";

Note that you can’t mix field names and numeric values in the same reserved statement.

Using Other Message Types

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

message SearchResponse {
  repeated Result results = 1;

message Result {
  string url = 1;
  string title = 2;
  repeated string snippets = 3;

Importing Definitions

In the earlier 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?

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:

import "myproject/other_protos.proto";

By default, you can use definitions only from directly imported .proto files. However, sometimes you may need to move a .proto file to a new location. Instead of moving the .proto file directly and updating all the call sites in a single change, you can put a placeholder .proto file in the old location to forward all the imports to the new location using the import public notion.

Note that the public import functionality is not available in Java.

import public dependencies can be transitively relied upon by any code importing the proto containing the import public statement. For example:

// new.proto
// All definitions are moved here
// old.proto
// This is the proto that all clients are importing.
import public "new.proto";
import "other.proto";
// client.proto
import "old.proto";
// You use definitions from old.proto and new.proto, but not other.proto

The protocol compiler searches for imported files in a set of directories specified on the protocol compiler command line using the -I/--proto_path flag. If no flag was given, it looks in the directory in which the compiler was invoked. In general you should set the --proto_path flag to the root of your project and use fully qualified names for all imports.

Using proto2 Message Types

It’s possible to import proto2 message types and use them in your proto3 messages, and vice versa. However, proto2 enums cannot be used directly in proto3 syntax (it’s okay if an imported proto2 message uses them).

Nested Types

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:

message SearchResponse {
  message Result {
    string url = 1;
    string title = 2;
    repeated string snippets = 3;
  repeated Result results = 1;

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

message SomeOtherMessage {
  SearchResponse.Result result = 1;

You can nest messages as deeply as you like. In the example below, note that the two nested types named Inner are entirely independent, since they are defined within different messages:

message Outer {       // Level 0
  message MiddleAA {  // Level 1
    message Inner {   // Level 2
      int64 ival = 1;
      bool  booly = 2;
  message MiddleBB {  // Level 1
    message Inner {   // Level 2
      int32 ival = 1;
      bool  booly = 2;

Updating A Message Type

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 when you use the binary wire format.

Check Proto Best Practices and the following rules:

  • Don’t change the field numbers for any existing fields. “Changing” the field number is equivalent to deleting the field and adding a new field with the same type. If you want to renumber a field, see the instructions for deleting a field.
  • If you add new fields, any messages serialized by code using your “old” message format can still be parsed by your new generated code. You should keep in mind the 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. See the Unknown Fields section for details.
  • Fields can be removed, as long as the field number is not used again in your updated message type. You may want to rename the field instead, perhaps adding the prefix “OBSOLETE_”, or make the field number reserved, so that future users of your .proto can’t accidentally reuse the number.
  • 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++ (for example, 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.
  • For string, bytes, and message fields, optional is compatible with repeated. Given serialized data of a repeated field as input, clients that expect this field to be optional will take the last input value if it’s a primitive type field or merge all input elements if it’s a message type field. Note that this is not generally safe for numeric types, including bools and enums. Repeated fields of numeric types can be serialized in the packed format, which will not be parsed correctly when an optional field is expected.
  • enum is compatible with int32, uint32, int64, and uint64 in terms of wire format (note that values will be truncated if they don’t fit). However, be aware that client code may treat them differently when the message is deserialized: for example, unrecognized proto3 enum types will be preserved in the message, but how this is represented when the message is deserialized is language-dependent. Int fields always just preserve their value.
  • Changing a single optional field or extension into a member of a new oneof is binary compatible, however for some languages (notably, Go) the generated code’s API will change in incompatible ways. For this reason, Google does not make such changes in its public APIs, as documented in AIP-180. With the same caveat about source-compatibility, moving multiple fields into a new oneof may be safe if you are sure that no code sets more than one at a time. Moving fields into an existing oneof is not safe. Likewise, changing a single field oneof to an optional field or extension is safe.
  • Changing a field between a map<K, V> and the corresponding repeated message field is binary compatible (see Maps, below, for the message layout and other restrictions). However, the safety of the change is application-dependent: when deserializing and reserializing a message, clients using the repeated field definition will produce a semantically identical result; however, clients using the map field definition may reorder entries and drop entries with duplicate keys.

Unknown Fields

Unknown fields are well-formed protocol buffer serialized data representing fields that the parser does not recognize. For example, when an old binary parses data sent by a new binary with new fields, those new fields become unknown fields in the old binary.

Proto3 messages preserve unknown fields and includes them during parsing and in the serialized output, which matches proto2 behavior.

Retaining Unknown Fields

Some actions can cause unknown fields to be lost. For example, if you do one of the following, unknown fields are lost:

  • Serialize a proto to JSON.
  • Iterate over all of the fields in a message to populate a new message.

To avoid losing unknown fields, do the following:

  • Use binary; avoid using text formats for data exchange.
  • Use message-oriented APIs, such as CopyFrom() and MergeFrom(), to copy data rather than copying field-by-field

TextFormat is a bit of a special case. Serializing to TextFormat prints unknown fields using their field numbers. But parsing TextFormat data back into a binary proto fails if there are entries that use field numbers.


The Any message type lets you use messages as embedded types without having their .proto definition. An Any contains an arbitrary serialized message as bytes, along with a URL that acts as a globally unique identifier for and resolves to that message’s type. To use the Any type, you need to import google/protobuf/any.proto.

import "google/protobuf/any.proto";

message ErrorStatus {
  string message = 1;
  repeated google.protobuf.Any details = 2;

The default type URL for a given message type is

Different language implementations will support runtime library helpers to pack and unpack Any values in a typesafe manner – for example, in Java, the Any type will have special pack() and unpack() accessors, while in C++ there are PackFrom() and UnpackTo() methods:

// Storing an arbitrary message type in Any.
NetworkErrorDetails details = ...;
ErrorStatus status;

// Reading an arbitrary message from Any.
ErrorStatus status = ...;
for (const google::protobuf::Any& detail : status.details()) {
  if (detail.Is<NetworkErrorDetails>()) {
    NetworkErrorDetails network_error;
    ... processing network_error ...

Currently the runtime libraries for working with Any types are under development.

The Any message types can hold arbitrary proto3 messages, similar to proto2 messages which can allow extensions.


If you have a message with many fields and where at most one field will be set at the same time, you can enforce this behavior and save memory by using the oneof feature.

Oneof fields are like regular fields except all the fields in a oneof share memory, and at most one field can be set at the same time. Setting any member of the oneof automatically clears all the other members. You can check which value in a oneof is set (if any) using a special case() or WhichOneof() method, depending on your chosen language.

Note that if multiple values are set, the last set value as determined by the order in the proto will overwrite all previous ones.

Field numbers for oneof fields must be unique within the enclosing message.

Using Oneof

To define a oneof in your .proto you use the oneof keyword followed by your oneof name, in this case test_oneof:

message SampleMessage {
  oneof test_oneof {
    string name = 4;
    SubMessage sub_message = 9;

You then add your oneof fields to the oneof definition. You can add fields of any type, except map fields and repeated fields. If you need to add a repeated field to a oneof, you can use a message containing the repeated field.

In your generated code, oneof fields have the same getters and setters as regular fields. You also get a special method for checking which value (if any) in the oneof is set. You can find out more about the oneof API for your chosen language in the relevant API reference.

Oneof Features

  • Setting a oneof field will automatically clear all other members of the oneof. So if you set several oneof fields, only the last field you set will still have a value.

    SampleMessage message;
    CHECK_EQ(, "name");
    // Calling mutable_sub_message() will clear the name field and will set
    // sub_message to a new instance of SubMessage with none of its fields set.
  • If the parser encounters multiple members of the same oneof on the wire, only the last member seen is used in the parsed message.

  • A oneof cannot be repeated.

  • Reflection APIs work for oneof fields.

  • If you set a oneof field to the default value (such as setting an int32 oneof field to 0), the “case” of that oneof field will be set, and the value will be serialized on the wire.

  • If you’re using C++, make sure your code doesn’t cause memory crashes. The following sample code will crash because sub_message was already deleted by calling the set_name() method.

    SampleMessage message;
    SubMessage* sub_message = message.mutable_sub_message();
    message.set_name("name");      // Will delete sub_message
    sub_message->set_...            // Crashes here
  • Again in C++, if you Swap() two messages with oneofs, each message will end up with the other’s oneof case: in the example below, msg1 will have a sub_message and msg2 will have a name.

    SampleMessage msg1;
    SampleMessage msg2;
    CHECK_EQ(, "name");

Backwards-compatibility issues

Be careful when adding or removing oneof fields. If checking the value of a oneof returns None/NOT_SET, it could mean that the oneof has not been set or it has been set to a field in a different version of the oneof. There is no way to tell the difference, since there’s no way to know if an unknown field on the wire is a member of the oneof.

Tag Reuse Issues

  • Move fields into or out of a oneof: You may lose some of your information (some fields will be cleared) after the message is serialized and parsed. However, you can safely move a single field into a new oneof and may be able to move multiple fields if it is known that only one is ever set. See Updating A Message Type for further details.
  • Delete a oneof field and add it back: This may clear your currently set oneof field after the message is serialized and parsed.
  • Split or merge oneof: This has similar issues to moving regular fields.


If you want to create an associative map as part of your data definition, protocol buffers provides a handy shortcut syntax:

map<key_type, value_type> map_field = N;

…where the key_type can be any integral or string type (so, any scalar type except for floating point types and bytes). Note that neither enum nor proto messages are valid for key_type. The value_type can be any type except another map.

So, for example, if you wanted to create a map of projects where each Project message is associated with a string key, you could define it like this:

map<string, Project> projects = 3;

Maps Features

  • Map fields cannot be repeated.
  • Wire format ordering and map iteration ordering of map values are undefined, so you cannot rely on your map items being in a particular order.
  • When generating text format for a .proto, maps are sorted by key. Numeric keys are sorted numerically.
  • When parsing from the wire or when merging, if there are duplicate map keys the last key seen is used. When parsing a map from text format, parsing may fail if there are duplicate keys.
  • If you provide a key but no value for a map field, the behavior when the field is serialized is language-dependent. In C++, Java, Kotlin, and Python the default value for the type is serialized, while in other languages nothing is serialized.
  • No symbol FooEntry can exist in the same scope as a map foo, because FooEntry is already used by the implementation of the map.

The generated map API is currently available for all supported languages. You can find out more about the map API for your chosen language in the relevant API reference.

Backwards compatibility

The map syntax is equivalent to the following on the wire, so protocol buffers implementations that do not support maps can still handle your data:

message MapFieldEntry {
  key_type key = 1;
  value_type value = 2;

repeated MapFieldEntry map_field = N;

Any protocol buffers implementation that supports maps must both produce and accept data that can be accepted by the earlier definition.


You can add an optional package specifier to a .proto file to prevent name clashes between protocol message types.

message Open { ... }

You can then use the package specifier when defining fields of your message type:

message Foo {
  ... open = 1;

The way a package specifier affects the generated code depends on your chosen language:

  • In C++ the generated classes are wrapped inside a C++ namespace. For example, Open would be in the namespace foo::bar.
  • In Java and Kotlin, the package is used as the Java package, unless you explicitly provide an option java_package in your .proto file.
  • In Python, the package directive is ignored, since Python modules are organized according to their location in the file system.
  • In Go, the package directive is ignored, and the generated .pb.go file is in the package named after the corresponding go_proto_library Bazel rule. For open source projects, you must provide either a go_package option or set the Bazel -M flag.
  • In Ruby, the generated classes are wrapped inside nested Ruby namespaces, converted to the required Ruby capitalization style (first letter capitalized; if the first character is not a letter, PB_ is prepended). For example, Open would be in the namespace Foo::Bar.
  • In PHP the package is used as the namespace after converting to PascalCase, unless you explicitly provide an option php_namespace in your .proto file. For example, Open would be in the namespace Foo\Bar.
  • In C# the package is used as the namespace after converting to PascalCase, unless you explicitly provide an option csharp_namespace in your .proto file. For example, Open would be in the namespace Foo.Bar.

Note that even when the package directive does not directly affect the generated code, for example in Python, it is still strongly recommended to specify the package for the .proto file, as otherwise it may lead to naming conflicts in descriptors and make the proto not portable for other languages.

Packages and Name Resolution

Type name resolution in the protocol buffer language works like C++: first the innermost scope is searched, then the next-innermost, and so on, with each package considered to be “inner” to its parent package. A leading ‘.’ (for example, means to start from the outermost scope instead.

The protocol buffer compiler resolves all type names by parsing the imported .proto files. The code generator for each language knows how to refer to each type in that language, even if it has different scoping rules.

Defining Services

If you want to use your message types with an RPC (Remote Procedure Call) system, you can define an RPC service interface in a .proto file and the protocol buffer compiler will generate service interface code and stubs in your chosen language. So, for example, if you want to define an RPC service with a method that takes your SearchRequest and returns a SearchResponse, you can define it in your .proto file as follows:

service SearchService {
  rpc Search(SearchRequest) returns (SearchResponse);

The most straightforward RPC system to use with protocol buffers is gRPC: a language- and platform-neutral open source RPC system developed at Google. gRPC works particularly well with protocol buffers and lets you generate the relevant RPC code directly from your .proto files using a special protocol buffer compiler plugin.

If you don’t want to use gRPC, it’s also possible to use protocol buffers with your own RPC implementation. You can find out more about this in the Proto2 Language Guide.

There are also a number of ongoing third-party projects to develop RPC implementations for Protocol Buffers. For a list of links to projects we know about, see the third-party add-ons wiki page.

JSON Mapping

Proto3 supports a canonical encoding in JSON, making it easier to share data between systems. The encoding is described on a type-by-type basis in the table below.

When parsing JSON-encoded data into a protocol buffer, if a value is missing or if its value is null, it will be interpreted as the corresponding default value.

When generating JSON-encoded output from a protocol buffer, if a protobuf field has the default value and if the field doesn’t support field presence, it will be omitted from the output by default. An implementation may provide options to include fields with default values in the output.

A proto3 field that is defined with the optional keyword supports field presence. Fields that have a value set and that support field presence always include the field value in the JSON-encoded output, even if it is the default value.

proto3JSONJSON exampleNotes
messageobject{"fooBar": v, "g": null, ...}Generates JSON objects. Message field names are mapped to lowerCamelCase and become JSON object keys. If the json_name field option is specified, the specified value will be used as the key instead. Parsers accept both the lowerCamelCase name (or the one specified by the json_name option) and the original proto field name. null is an accepted value for all field types and treated as the default value of the corresponding field type. However, null cannot be used for the json_name value. For more on why, see Stricter validation for json_name.
enumstring"FOO_BAR"The name of the enum value as specified in proto is used. Parsers accept both enum names and integer values.
map<K,V>object{"k": v, ...}All keys are converted to strings.
repeated Varray[v, ...]null is accepted as the empty list [].
booltrue, falsetrue, false
stringstring"Hello World!"
bytesbase64 string"YWJjMTIzIT8kKiYoKSctPUB+"JSON value will be the data encoded as a string using standard base64 encoding with paddings. Either standard or URL-safe base64 encoding with/without paddings are accepted.
int32, fixed32, uint32number1, -10, 0JSON value will be a decimal number. Either numbers or strings are accepted.
int64, fixed64, uint64string"1", "-10"JSON value will be a decimal string. Either numbers or strings are accepted.
float, doublenumber1.1, -10.0, 0, "NaN", "Infinity"JSON value will be a number or one of the special string values "NaN", "Infinity", and "-Infinity". Either numbers or strings are accepted. Exponent notation is also accepted.
Anyobject{"@type": "url", "f": v, ... }If the Any contains a value that has a special JSON mapping, it will be converted as follows: {"@type": xxx, "value": yyy}. Otherwise, the value will be converted into a JSON object, and the "@type" field will be inserted to indicate the actual data type.
Timestampstring"1972-01-01T10:00:20.021Z"Uses RFC 3339, where generated output will always be Z-normalized and uses 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted.
Durationstring"1.000340012s", "1s"Generated output always contains 0, 3, 6, or 9 fractional digits, depending on required precision, followed by the suffix "s". Accepted are any fractional digits (also none) as long as they fit into nano-seconds precision and the suffix "s" is required.
Structobject{ ... }Any JSON object. See struct.proto.
Wrapper typesvarious types2, "2", "foo", true, "true", null, 0, ...Wrappers use the same representation in JSON as the wrapped primitive type, except that null is allowed and preserved during data conversion and transfer.
FieldMaskstring"f.fooBar,h"See field_mask.proto.
ListValuearray[foo, bar, ...]
ValuevalueAny JSON value. Check google.protobuf.Value for details.
NullValuenullJSON null
Emptyobject{}An empty JSON object

JSON Options

A proto3 JSON implementation may provide the following options:

  • Always emit fields without presence: Fields that don’t support presence and that have their default value are omitted by default in JSON output (for example, an implicit presence integer with a 0 value, implicit presence string fields that are empty strings, and empty repeated and map fields). An implementation may provide an option to override this behavior and output fields with their default values.
  • Ignore unknown fields: Proto3 JSON parser should reject unknown fields by default but may provide an option to ignore unknown fields in parsing.
  • Use proto field name instead of lowerCamelCase name: By default proto3 JSON printer should convert the field name to lowerCamelCase and use that as the JSON name. An implementation may provide an option to use proto field name as the JSON name instead. Proto3 JSON parsers are required to accept both the converted lowerCamelCase name and the proto field name.
  • Emit enum values as integers instead of strings: The name of an enum value is used by default in JSON output. An option may be provided to use the numeric value of the enum value instead.


Individual declarations in a .proto file can be annotated with a number of options. Options do not change the overall meaning of a declaration, but may affect the way it is handled in a particular context. The complete list of available options is defined in /google/protobuf/descriptor.proto.

Some options are file-level options, meaning they should be written at the top-level scope, not inside any message, enum, or service definition. Some options are message-level options, meaning they should be written inside message definitions. Some options are field-level options, meaning they should be written inside field definitions. Options can also be written on enum types, enum values, oneof fields, service types, and service methods; however, no useful options currently exist for any of these.

Here are a few of the most commonly used options:

  • java_package (file option): The package you want to use for your generated Java/Kotlin classes. If no explicit java_package option is given in the .proto file, then by default the proto package (specified using the “package” keyword in the .proto file) will be used. However, proto packages generally do not make good Java packages since proto packages are not expected to start with reverse domain names. If not generating Java or Kotlin code, this option has no effect.

    option java_package = "";
  • java_outer_classname (file option): The class name (and hence the file name) for the wrapper Java class you want to generate. If no explicit java_outer_classname is specified in the .proto file, the class name will be constructed by converting the .proto file name to camel-case (so foo_bar.proto becomes If the java_multiple_files option is disabled, then all other classes/enums/etc. generated for the .proto file will be generated within this outer wrapper Java class as nested classes/enums/etc. If not generating Java code, this option has no effect.

    option java_outer_classname = "Ponycopter";
  • java_multiple_files (file option): If false, only a single .java file will be generated for this .proto file, and all the Java classes/enums/etc. generated for the top-level messages, services, and enumerations will be nested inside of an outer class (see java_outer_classname). If true, separate .java files will be generated for each of the Java classes/enums/etc. generated for the top-level messages, services, and enumerations, and the wrapper Java class generated for this .proto file won’t contain any nested classes/enums/etc. This is a Boolean option which defaults to false. If not generating Java code, this option has no effect.

    option java_multiple_files = true;
  • optimize_for (file option): Can be set to SPEED, CODE_SIZE, or LITE_RUNTIME. This affects the C++ and Java code generators (and possibly third-party generators) in the following ways:

    • SPEED (default): The protocol buffer compiler will generate code for serializing, parsing, and performing other common operations on your message types. This code is highly optimized.
    • CODE_SIZE: The protocol buffer compiler will generate minimal classes and will rely on shared, reflection-based code to implement serialization, parsing, and various other operations. The generated code will thus be much smaller than with SPEED, but operations will be slower. Classes will still implement exactly the same public API as they do in SPEED mode. This mode is most useful in apps that contain a very large number of .proto files and do not need all of them to be blindingly fast.
    • LITE_RUNTIME: The protocol buffer compiler will generate classes that depend only on the “lite” runtime library (libprotobuf-lite instead of libprotobuf). The lite runtime is much smaller than the full library (around an order of magnitude smaller) but omits certain features like descriptors and reflection. This is particularly useful for apps running on constrained platforms like mobile phones. The compiler will still generate fast implementations of all methods as it does in SPEED mode. Generated classes will only implement the MessageLite interface in each language, which provides only a subset of the methods of the full Message interface.
    option optimize_for = CODE_SIZE;
  • cc_generic_services, java_generic_services, py_generic_services (file options): Generic services are deprecated. Whether or not the protocol buffer compiler should generate abstract service code based on services definitions in C++, Java, and Python, respectively. For legacy reasons, these default to true. However, as of version 2.3.0 (January 2010), it is considered preferable for RPC implementations to provide code generator plugins to generate code more specific to each system, rather than rely on the “abstract” services.

    // This file relies on plugins to generate service code.
    option cc_generic_services = false;
    option java_generic_services = false;
    option py_generic_services = false;
  • cc_enable_arenas (file option): Enables arena allocation for C++ generated code.

  • objc_class_prefix (file option): Sets the Objective-C class prefix which is prepended to all Objective-C generated classes and enums from this .proto. There is no default. You should use prefixes that are between 3-5 uppercase characters as recommended by Apple. Note that all 2 letter prefixes are reserved by Apple.

  • packed (field option): Defaults to true on a repeated field of a basic numeric type, causing a more compact encoding to be used. There is no downside to using this option, but it can be set to false. Note that prior to version 2.3.0, parsers that received packed data when not expected would ignore it. Therefore, it was not possible to change an existing field to packed format without breaking wire compatibility. In 2.3.0 and later, this change is safe, as parsers for packable fields will always accept both formats, but be careful if you have to deal with old programs using old protobuf versions.

    repeated int32 samples = 4 [packed = false];
  • deprecated (field option): If set to true, indicates that the field is deprecated and should not be used by new code. In most languages this has no actual effect. In Java, this becomes a @Deprecated annotation. For C++, clang-tidy will generate warnings whenever deprecated fields are used. In the future, other language-specific code generators may generate deprecation annotations on the field’s accessors, which will in turn cause a warning to be emitted when compiling code which attempts to use the field. If the field is not used by anyone and you want to prevent new users from using it, consider replacing the field declaration with a reserved statement.

    int32 old_field = 6 [deprecated = true];

Enum Value Options

Enum value options are supported. You can use the deprecated option to indicate that a value shouldn’t be used anymore. You can also create custom options using extensions.

The following example shows the syntax for adding these options:

import "google/protobuf/descriptor.proto";

extend google.protobuf.EnumValueOptions {
  optional string string_name = 123456789;

enum Data {
  DATA_SEARCH = 1 [deprecated = true];
    (string_name) = "display_value"

See Custom Options to see how to apply custom options to enum values and to fields.

Custom Options

Protocol Buffers also allows you to define and use your own options. Note that this is an advanced feature which most people don’t need. If you do think you need to create your own options, see the Proto2 Language Guide for details. Note that creating custom options uses extensions, which are permitted only for custom options in proto3.

Option Retention

Options have a notion of retention, which controls whether an option is retained in the generated code. Options have runtime retention by default, meaning that they are retained in the generated code and are thus visible at runtime in the generated descriptor pool. However, you can set retention = RETENTION_SOURCE to specify that an option (or field within an option) must not be retained at runtime. This is called source retention.

Option retention is an advanced feature that most users should not need to worry about, but it can be useful if you would like to use certain options without paying the code size cost of retaining them in your binaries. Options with source retention are still visible to protoc and protoc plugins, so code generators can use them to customize their behavior.

Retention can be set directly on an option, like this:

extend google.protobuf.FileOptions {
  optional int32 source_retention_option = 1234
      [retention = RETENTION_SOURCE];

It can also be set on a plain field, in which case it takes effect only when that field appears inside an option:

message OptionsMessage {
  int32 source_retention_field = 1 [retention = RETENTION_SOURCE];

You can set retention = RETENTION_RUNTIME if you like, but this has no effect since it is the default behavior. When a message field is marked RETENTION_SOURCE, its entire contents are dropped; fields inside it cannot override that by trying to set RETENTION_RUNTIME.

Option Targets

Fields have a targets option which controls the types of entities that the field may apply to when used as an option. For example, if a field has targets = TARGET_TYPE_MESSAGE then that field cannot be set in a custom option on an enum (or any other non-message entity). Protoc enforces this and will raise an error if there is a violation of the target constraints.

At first glance, this feature may seem unnecessary given that every custom option is an extension of the options message for a specific entity, which already constrains the option to that one entity. However, option targets are useful in the case where you have a shared options message applied to multiple entity types and you want to control the usage of individual fields in that message. For example:

message MyOptions {
  string file_only_option = 1 [targets = TARGET_TYPE_FILE];
  int32 message_and_enum_option = 2 [targets = TARGET_TYPE_MESSAGE,
                                     targets = TARGET_TYPE_ENUM];

extend google.protobuf.FileOptions {
  optional MyOptions file_options = 50000;

extend google.protobuf.MessageOptions {
  optional MyOptions message_options = 50000;

extend google.protobuf.EnumOptions {
  optional MyOptions enum_options = 50000;

// OK: this field is allowed on file options
option (file_options).file_only_option = "abc";

message MyMessage {
  // OK: this field is allowed on both message and enum options
  option (message_options).message_and_enum_option = 42;

enum MyEnum {
  // Error: file_only_option cannot be set on an enum.
  option (enum_options).file_only_option = "xyz";

Generating Your Classes

To generate the Java, Kotlin, Python, C++, Go, Ruby, Objective-C, or C# code that you need to work with the message types defined in a .proto file, you need to run the protocol buffer compiler protoc on the .proto file. If you haven’t installed the compiler, download the package and follow the instructions in the README. For Go, you also need to install a special code generator plugin for the compiler; you can find this and installation instructions in the golang/protobuf repository on GitHub.

The Protocol Compiler is invoked as follows:

protoc --proto_path=IMPORT_PATH --cpp_out=DST_DIR --java_out=DST_DIR --python_out=DST_DIR --go_out=DST_DIR --ruby_out=DST_DIR --objc_out=DST_DIR --csharp_out=DST_DIR path/to/file.proto
  • IMPORT_PATH specifies a directory in which to look for .proto files when resolving import directives. If omitted, the current directory is used. Multiple import directories can be specified by passing the --proto_path option multiple times; they will be searched in order. -I=_IMPORT_PATH_ can be used as a short form of --proto_path.

  • You can provide one or more output directives:

    As an extra convenience, if the DST_DIR ends in .zip or .jar, the compiler will write the output to a single ZIP-format archive file with the given name. .jar outputs will also be given a manifest file as required by the Java JAR specification. Note that if the output archive already exists, it will be overwritten.

  • You must provide one or more .proto files as input. Multiple .proto files can be specified at once. Although the files are named relative to the current directory, each file must reside in one of the IMPORT_PATHs so that the compiler can determine its canonical name.

File location

Prefer not to put .proto files in the same directory as other language sources. Consider creating a subpackage proto for .proto files, under the root package for your project.

Location Should be Language-agnostic

When working with Java code, it’s handy to put related .proto files in the same directory as the Java source. However, if any non-Java code ever uses the same protos, the path prefix will no longer make sense. So in general, put the protos in a related language-agnostic directory such as //myteam/mypackage.

The exception to this rule is when it’s clear that the protos will be used only in a Java context, such as for testing.

Supported Platforms

For information about: