ts-proto transforms your .proto files into strongly-typed, idiomatic TypeScript files!

(Note, if you're a new user of ts-proto and using a modern TS setup with esModuleInterop, or want to use ts-proto in ESM / snowpack / vite, you need to also pass that as a ts_proto_opt.)

• ts-proto
  • Table of contents
• Overview
• QuickStart
  • Buf
• Goals
• Example Types
• Highlights
• Auto-Batching / N+1 Prevention
• Usage
  • Supported options
  • Only Types
  • NestJS Support
  • Watch Mode
  • Basic gRPC implementation
• Sponsors
• Development
• Assumptions
• Todo
• OneOf Handling
• Default values and unset fields
• Well-Known Types
  • Wrapper Types
  • JSON Types (Struct Types)
  • Timestamp
• Number Types
• Current Status of Optional Values

ts-proto generates TypeScript types from protobuf schemas.

I.e. given a person.proto schema like:

message Person {
  string name = 1;
}

ts-proto will generate a person.ts file like:

interface Person {
  name: string
}

const Person = {
  encode(person): Writer { ... }
  decode(reader): Person { ... }
  toJSON(person): unknown { ... }
  fromJSON(data): Person { ... }
}

It also knows about services and will generate types for them as well, i.e.:

export interface PingService {
  ping(request: PingRequest): Promise<PingResponse>;
}

It will also generate client implementations of PingService; currently Twirp, grpc-web, grpc-js and nestjs are supported.

• npm install ts-proto
• protoc --plugin=./node_modules/.bin/protoc-gen-ts_proto --ts_proto_out=. ./simple.proto
  • (Note that the output parameter name, ts_proto_out, is named based on the suffix of the plugin's name, i.e. "ts_proto" suffix in the --plugin=./node_modules/.bin/protoc-gen-ts_proto parameter becomes the _out prefix, per protoc's CLI conventions.)
  • On Windows, use protoc --plugin=protoc-gen-ts_proto=.\node_modules\.bin\protoc-gen-ts_proto.cmd --ts_proto_out=. ./simple.proto (see #93)
  • Ensure you're using a modern protoc, i.e. the original protoc 3.0.0 doesn't support the _opt flag

This will generate *.ts source files for the given *.proto types.

If you want to package these source files into an npm package to distribute to clients, just run tsc on them as usual to generate the .js/.d.ts files, and deploy the output as a regular npm package.

If you're using Buf, pass strategy: all in your buf.gen.yaml file (docs).

version: v1
plugins:
  - name: ts
    out: ../gen/ts
    strategy: all
    path: ../node_modules/ts-proto/protoc-gen-ts_proto

You can also use the official plugin published to the Buf Registry.

version: v1
plugins:
  - remote: buf.build/stephenh/plugins/ts-proto
    out: ../gen/ts

• Idiomatic TypeScript/ES6 types
  • ts-proto is a clean break from either the built-in Google/Java-esque JS code of protoc or the "make .d.ts files the *.js comments" approach of protobufjs
  • (Techically the protobufjs/minimal package is used for actually reading/writing bytes.)
• TypeScript-first output
• Interfaces over classes
  • As much as possible, types are just interfaces, so you can work with messages just like regular hashes/data structures.
• Only supports codegen *.proto-to-*.ts workflow, currently no runtime reflection/loading of dynamic .proto files

The generated types are "just data", i.e.:

export interface Simple {
  name: string;
  age: number;
  createdAt: Date | undefined;
  child: Child | undefined;
  state: StateEnum;
  grandChildren: Child[];
  coins: number[];
}

Along with encode/decode factory methods:

export const Simple = {
  encode(message: Simple, writer: Writer = Writer.create()): Writer {
    ...
  },

  decode(reader: Reader, length?: number): Simple {
    ...
  },

  fromJSON(object: any): Simple {
    ...
  },

  fromPartial(object: DeepPartial<Simple>): Simple {
    ...
  },

  toJSON(message: Simple): unknown {
    ...
  },
};

This allows idiomatic TS/JS usage like:

const bytes = Simple.encode({ name: ..., age: ..., ... }).finish();
const simple = Simple.decode(Reader.create(bytes));
const { name, age } = simple;

Which can dramatically ease integration when converting to/from other layers without creating a class and calling the right getters/setters.

• A poor man's attempt at "please give us back optional types"

  The canonical protobuf wrapper types, i.e. google.protobuf.StringValue, are mapped as optional values, i.e. string | undefined, which means for primitives we can kind of pretend the protobuf type system has optional types.

  (Update: ts-proto now also supports the proto3 optional keyword.)

• Timestamps are mapped as Date

  (Configurable with the useDate parameter.)

• fromJSON/toJSON use the proto3 canonical JSON encoding format (e.g. timestamps are ISO strings), unlike protobufjs.

• ObjectIds can be mapped as mongodb.ObjectId

  (Configurable with the useObjectId parameter.)

(Note: this is currently only supported by the Twirp clients.)

If you're using ts-proto's clients to call backend micro-services, similar to the N+1 problem in SQL applications, it is easy for micro-service clients to (when serving an individual request) inadvertantly trigger multiple separate RPC calls for "get book 1", "get book 2", "get book 3", that should really be batched into a single "get books [1, 2, 3]" (assuming the backend supports a batch-oriented RPC method).

ts-proto can help with this, and essentially auto-batch your individual "get book" calls into batched "get books" calls.

For ts-proto to do this, you need to implement your service's RPC methods with the batching convention of:

• A method name of Batch<OperationName>
• The Batch<OperationName> input type has a single repeated field (i.e. repeated string ids = 1)
• The Batch<OperationName> output type has either a:
  • A single repeated field (i.e. repeated Foo foos = 1) where the output order is the same as the input ids order, or
  • A map of the input to an output (i.e. map<string, Entity> entities = 1;)

When ts-proto recognizes methods of this pattern, it will automatically create a "non-batch" version of <OperationName> for the client, i.e. client.Get<OperationName>, that takes a single id and returns a single result.

This provides the client code with the illusion that it can make individual Get<OperationName> calls (which is generally preferrable/easier when implementing the client's business logic), but the actual implementation that ts-proto provides will end up making Batch<OperationName> calls to the backend service.

You also need to enable the useContext=true build-time parameter, which gives all client methods a Go-style ctx parameter, with a getDataLoaders method that lets ts-proto cache/resolve request-scoped DataLoaders, which provide the fundamental auto-batch detection/flushing behavior.

See the batching.proto file and related tests for examples/more details.

But the net effect is that ts-proto can provide SQL-/ORM-style N+1 prevention for clients calls, which can be critical especially in high-volume / highly-parallel implementations like GraphQL front-end gateways calling backend micro-services.

ts-proto is a protoc plugin, so you run it by (either directly in your project, or more likely in your mono-repo schema pipeline, i.e. like Ibotta or Namely):

• Add ts-proto to your package.json
• Run npm install to download it
• Invoke protoc with a plugin parameter like:

protoc --plugin=node_modules/ts-proto/protoc-gen-ts_proto ./batching.proto -I.

ts-proto can also be invoked with Gradle using the protobuf-gradle-plugin:

protobuf {
    plugins {
        // `ts` can be replaced by any unused plugin name, e.g. `tsproto`
        ts {
            path = 'path/to/plugin'
        }
    }

    // This section only needed if you provide plugin options
    generateProtoTasks {
        all().each { task ->
            task.plugins {
                // Must match plugin ID declared above
                ts {
                    option 'foo=bar'
                }
            }
        }
    }
}

Generated code will be placed in the Gradle build directory.

• With --ts_proto_opt=context=true, the services will have a Go-style ctx parameter, which is useful for tracing/logging/etc. if you're not using node's async_hooks api due to performance reasons.

• With --ts_proto_opt=forceLong=long, all 64-bit numbers will be parsed as instances of Long (using the long library).

  Alternatively, if you pass --ts_proto_opt=forceLong=string, all 64-bit numbers will be outputted as strings.

  The default behavior is forceLong=number, which will internally still use the long library to encode/decode values on the wire (so you will still see a util.Long = Long line in your output), but will convert the long values to number automatically for you. Note that a runtime error is thrown if, while doing this conversion, a 64-bit value is larger than can be correctly stored as a number.

• With --ts_proto_opt=esModuleInterop=true changes output to be esModuleInterop compliant.

  Specifically the Long imports will be generated as import Long from 'long' instead of import * as Long from 'long'.

• With --ts_proto_opt=env=node or browser or both, ts-proto will make environment-specific assumptions in your output. This defaults to both, which makes no environment-specific assumptions.

  Using node changes the types of bytes from Uint8Array to Buffer for easier integration with the node ecosystem which generally uses Buffer.

  Currently browser doesn't have any specific behavior other than being "not node". It probably will soon/at some point.

• With --ts_proto_opt=useOptionals=messages (for message fields) or --ts_proto_opt=useOptionals=all (for message and scalar fields), fields are declared as optional keys, e.g. field?: Message instead of the default field: Message | undefined.

  ts-proto defaults to useOptionals=none because it:

  1. Prevents typos when initializing messages, and
  2. Provides the most consistent API to readers
  3. Ensures production messages are properly initialized with all fields.

  For typo prevention, optional fields make it easy for extra fields to slip into a message (until we get Exact Types), i.e.:

  interface SomeMessage {
    firstName: string | undefined;
    lastName: string | undefined;
  }
  // Declared with a typo
  const data = { firstName: 'a', lastTypo: 'b' };
  // With useOptionals=none, this correctly fails to compile; if `lastName` was optional, it would not
  const message: SomeMessage = { ...data };

  For a consistent API, if SomeMessage.lastName is optional lastName?, then readers have to check two empty conditions: a) is lastName undefined (b/c it was created in-memory and left unset), or b) is lastName empty string (b/c we read SomeMessage off the wire and correctly set lastName to empty string)?

  For ensuring proper initialization, if later SomeMessage.middleInitial is added, but it's marked as optional middleInitial?, you may have many call sites in production code that should now be passing middleInitial to create a valid SomeMessage, but are not.

  So, between typo-prevention, reader inconsistency, and proper initialization, ts-proto recommends using useOptionals=none as the "most safe" option.

  All that said, this approach does require writers/creators to set every field (although fromPartial is meant to address this), so if you still want to have optional fields, you can set useOptionals=messages or useOptionals=all.

  (See this issue and this issue for discussions on useOptional.)

• With --ts_proto_opt=exportCommonSymbols=false, utility types like DeepPartial won't be exportd.

  This should make it possible to use create barrel imports of the generated output, i.e. import * from ./foo and import * from ./bar.

  Note that if you have the same message name used in multiple *.proto files, you will still get import conflicts.

• With --ts_proto_opt=oneof=unions, oneof fields will be generated as ADTs.

  See the "OneOf Handling" section.

• With --ts_proto_opt=unrecognizedEnum=false enums will not contain an UNRECOGNIZED key with value of -1.

• With --ts_proto_opt=lowerCaseServiceMethods=true, the method names of service methods will be lowered/camel-case, i.e. service.findFoo instead of service.FindFoo.

• With --ts_proto_opt=snakeToCamel=false, fields will be kept snake case. snakeToCamel can also be set as string with --ts_proto_opt=snakeToCamel=keys,json. keys will keep field names as camelCase and json will keep json field names as camelCase. Empty string will keep field names as snake_case.

• With --ts_proto_opt=outputEncodeMethods=false, the Message.encode and Message.decode methods for working with protobuf-encoded/binary data will not be output.

  This is useful if you want "only types".

• With --ts_proto_opt=outputJsonMethods=false, the Message.fromJSON and Message.toJSON methods for working with JSON-coded data will not be output.

  This is also useful if you want "only types".

• With --ts_proto_opt=outputPartialMethods=false, the Message.fromPartial methods for accepting partially-formed objects/object literals will not be output.

• With --ts_proto_opt=stringEnums=true, the generated enum types will be string-based instead of int-based.

  This is useful if you want "only types" and are using a gRPC REST Gateway configured to serialize enums as strings.

  (Requires outputEncodeMethods=false.)

• With --ts_proto_opt=outputClientImpl=false, the client implementations, i.e. FooServiceClientImpl, that implement the client-side (in Twirp, see next option for grpc-web) RPC interfaces will not be output.

• With --ts_proto_opt=outputClientImpl=grpc-web, the client implementations, i.e. FooServiceClientImpl, will use the @improbable-eng/grpc-web library at runtime to send grpc messages to a grpc-web backend.

  (Note that this only uses the grpc-web runtime, you don't need to use any of their generated code, i.e. the ts-proto output replaces their ts-protoc-gen output.)

  You'll need to add the @improbable-eng/grpc-web and a transport to your project's package.json; see the integration/grpc-web directory for a working example. Also see #504 for integrating with grpc-web-devtools.

• With --ts_proto_opt=returnObservable=true, the return type of service methods will be Observable<T> instead of Promise<T>.

• With--ts_proto_opt=addGrpcMetadata=true, the last argument of service methods will accept the grpc Metadata type, which contains additional information with the call (i.e. access tokens/etc.).

  (Requires nestJs=true.)

• With--ts_proto_opt=addNestjsRestParameter=true, the last argument of service methods will be an rest parameter with type any. This way you can use custom decorators you could normally use in nestjs.

  (Requires nestJs=true.)

• With --ts_proto_opt=nestJs=true, the defaults will change to generate NestJS protobuf friendly types & service interfaces that can be used in both the client-side and server-side of NestJS protobuf implementations. See the nestjs readme for more information and implementation examples.

  Specifically outputEncodeMethods, outputJsonMethods, and outputClientImpl will all be false, and lowerCaseServiceMethods will be true.

  Note that addGrpcMetadata, addNestjsRestParameter and returnObservable will still be false.

• With --ts_proto_opt=useDate=false, fields of type google.protobuf.Timestamp will not be mapped to type Date in the generated types. See Timestamp for more details.

• With --ts_proto_opt=useObjectId=true, fields of a type called ObjectId where the message is constructed to have on field called value that is a string will be mapped to type mongodb.ObjectId in the generated types. This will require your project to install the mongodb npm package. See ObjectId for more details.

• With --ts_proto_opt=outputSchema=true, meta typings will be generated that can later be used in other code generators.

• With --ts_proto_opt=outputTypeRegistry=true, the type registry will be generated that can be used to resolve message types by fully-qualified name. Also, each message will get extra $type field containing fully-qualified name.

• With --ts_proto_opt=outputServices=grpc-js, ts-proto will output service definitions and server / client stubs in grpc-js format.

• With --ts_proto_opt=outputServices=generic-definitions, ts-proto will output generic (framework-agnostic) service definitions. These definitions contain descriptors for each method with links to request and response types, which allows to generate server and client stubs at runtime, and also generate strong types for them at compile time. An example of a library that uses this approach is nice-grpc.

• With --ts_proto_opt=outputServices=nice-grpc, ts-proto will output server and client stubs for nice-grpc. This should be used together with generic definitions, i.e. you should specify two options: outputServices=nice-grpc,outputServices=generic-definitions.

• With --ts_proto_opt=metadataType=Foo@./some-file, ts-proto add a generic (framework-agnostic) metadata field to the generic service definition.

• With --ts_proto_opt=outputServices=generic-definitions,outputServices=default, ts-proto will output both generic definitions and interfaces. This is useful if you want to rely on the interfaces, but also have some reflection capabilities at runtime.

• With --ts_proto_opt=outputServices=false, or =none, ts-proto will output NO service definitions.

• With --ts_proto_opt=emitImportedFiles=false, ts-proto will not emit google/protobuf/* files unless you explicit add files to protoc like this protoc --plugin=./node_modules/.bin/protoc-gen-ts_proto my_message.proto google/protobuf/duration.proto

• With --ts_proto_opt=fileSuffix=<SUFFIX>, ts-proto will emit generated files using the specified suffix. A helloworld.proto file with fileSuffix=.pb would be generated as helloworld.pb.ts. This is common behavior in other protoc plugins and provides a way to quickly glob all the generated files.

• With --ts_proto_opt=enumsAsLiterals=true, the generated enum types will be enum-ish object with as const.

• With --ts_proto_opt=useExactTypes=false, the generated fromPartial method will not use Exact types.

  The default behavior is useExactTypes=true, which makes fromPartial use Exact type for its argument to make TypeScript reject any unknown properties.

• With --ts_proto_opt=unknownFields=true, all unknown fields will be parsed and output as arrays of buffers.

• With --ts_proto_opt=onlyTypes=true, only types will be emitted, and imports for long and protobufjs/minimal will be excluded.

  This is the same as setting outputJsonMethods=false,outputEncodeMethods=false,outputClientImpl=false,nestJs=false

• With --ts_proto_opt=usePrototypeForDefaults=true, the generated code will wrap new objects with Object.create.

  This allows code to do hazzer checks to detect when default values have been applied, which due to proto3's behavior of not putting default values on the wire, is typically only useful for interacting with proto2 messages.

  When enabled, default values are inherited from a prototype, and so code can use Object.keys().includes("someField") to detect if someField was actually decoded or not.

  Note that, as indicated, this means Object.keys will not include set-by-default fields, so if you have code that iterates over messages keys in a generic fashion, it will have to also iterate over keys inherited from the prototype.

• With --ts_proto_opt=useJsonWireFormat=true, the generated code will reflect the JSON representation of Protobuf messages.

  Requires onlyTypes=true. Implies useDate=string and stringEnums=true. This option is to generate types that can be directly used with marshalling/unmarshalling Protobuf messages serialized as JSON.
  You may also want to set useOptionals=all, as gRPC gateways are not required to send default value for scalar values.

We have a great way of working together with nestjs. ts-proto generates interfaces and decorators for you controller, client. For more information see the nestjs readme.

If you want to run ts-proto on every change of a proto file, you'll need to use a tool like chokidar-cli and use it as a script in package.json:

"proto:generate": "protoc --ts_proto_out=. ./<proto_path>/<proto_name>.proto --ts_proto_opt=esModuleInterop=true",
"proto:watch": "chokidar \"**/*.proto\" -c \"npm run proto:generate\""

ts-proto is RPC framework agnostic - how you transmit your data to and from your data source is up to you. The generated client implementations all expect a rpc parameter, which type is defined like this:

interface Rpc {
  request(service: string, method: string, data: Uint8Array): Promise<Uint8Array>;
}

If you're working with gRPC, a simple implementation could look like this:

type RpcImpl = (service: string, method: string, data: Uint8Array) => Promise<Uint8Array>;

const sendRequest: RpcImpl = (service, method, data) => {
  // Conventionally in gRPC, the request path looks like
  //   "package.names.ServiceName/MethodName",
  // we therefore construct such a string
  const path = `${service}/${method}`;

  return new Promise((resolve, reject) => {
    // makeUnaryRequest transmits the result (and error) with a callback
    // transform this into a promise!
    const resultCallback: UnaryCallback<any> = (err, res) => {
      if (err) {
        return reject(err);
      }
      resolve(res);
    };

    function passThrough(argument: any) {
      return argument;
    }

    // Using passThrough as the serialize and deserialize functions
    conn.makeUnaryRequest(path, passThrough, passThrough, data, resultCallback);
  });
};

const rpc: Rpc = { request: sendRequest };

Kudos to our sponsors:

• ngrok funded ts-proto's initial grpc-web support.

If you need ts-proto customizations or priority support for your company, you can ping me at via email.

Requirements

• Docker or protoc v3.19.1
• yarn — npm install -g yarn

Setup

The commands below assume you have Docker installed. To use a local copy of protoc without docker, use commands suffixed with :local. If you are using OS X, install coreutils, brew install coreutils.

• Check out the repository for the latest code.
• Run yarn install to install the dependencies.
• Run yarn build:test or yarn build:test:local to generate the test files.

  This runs the following commands:

  • proto2bin — Converts integration test .proto files to .bin.
  • bin2ts — Runs ts-proto on the .bin files to generate .ts files.
  • proto2pbjs — Generates a reference implementation using pbjs for testing compatibility.

• Run yarn test

Workflow

• Modifying the plugin implementation:
  • The most important logic is found in src/main.ts.
  • Run yarn bin2ts or yarn bin2ts:local.
    Since the proto files were not changed, you only need to regenerate the typescript files.
  • Run yarn test to verify the typescript files are compatible with the reference implementation, and pass other tests.
• Updating or adding .proto files in the integration directory:
  • Run yarn watch to automatically regenerate test files when proto files change.
    • Or run yarn build:test to regenerate all integration test files.
  • Run yarn test to retest.

Contributing

• Run yarn build:test and yarn test to make sure everything works.
• Run yarn prettier to format the typescript files.
• Commit the changes:
  • Also include the generated .bin files for the tests where you added or modified .proto files.

    These are checked into git so that the test suite can run without having to invoke the protoc build chain.

  • Also include the generated .ts files.
• Create a pull request

Dockerized Protoc

The repository includes a dockerized version of protoc, which is configured in docker-compose.yml.

It can be useful in case you want to manually invoke the plugin with a known version of protoc.

Usage:

# Include the protoc alias in your shell.
. aliases.sh

# Run protoc as usual. The ts-proto directory is available in /ts-proto.
protoc --plugin=/ts-proto/protoc-gen-ts_proto --ts_proto_out=./output -I=./protos ./protoc/*.proto

# Or use the ts-protoc alias which specifies the plugin path for you.
ts-protoc --ts_proto_out=./output -I=./protos ./protoc/*.proto

• All paths must be relative paths within the current working directory of the host. ../ is not allowed
• Within the docker container, the absolute path to the project root is /ts-proto
• The container mounts the current working directory in /host, and sets it as its working directory.
• Once aliases.sh is sourced, you can use the protoc command in any folder.

• TS/ES6 module name is the proto package

• Support the string-based encoding of duration in fromJSON/toJSON
• Make oneof=unions the default behavior in 2.0
• Probably change forceLong default in 2.0, should default to forceLong=long
• Make esModuleInterop=true the default in 2.0

By default, oneof fields are modeled "flatly" in the message, i.e. oneof either_field { string field_a; string field_b } means that the message will have field_a: string | undefined; field_b: string | undefined.

With this output, you'll have to check both if object.field_a and if object.field_b, and if you set one, you'll have to remember to unset the other.

We recommend using the oneof=unions option, which will change the output to be an Abstract Data Type/ADT like:

interface YourMessage {
  eitherField: { $case: 'field_a'; field_a: string } | { $case: 'field_b'; field_b: string };
}

As this will automatically enforce only one of field_a or field_b "being set" at a time, because the values are stored in the eitherField field that can only have a single value at a time.

In ts-proto's currently-unscheduled 2.x release, oneof=unions will become the default behavior.

In core Protobuf, values that are unset or equal to the default value are not sent over the wire. The default value of a message is undefined. Primitive types take their natural default value, i.e. string is '', number is 0, etc. This behavior enables forward compatibility, as primitive fields will always have a value, even when omitted by outdated agents, but it also means default and unset values cannot be distinguished.

If you need primitive fields where you can detect set/unset, see Wrapper Types.

Encode / Decode

ts-proto follows the Protobuf rules, and always returns default values for unsets fields when decoding, while omitting them from the output when serialized in binary format.

syntax = "proto3";
message Foo {
  string bar = 1;
}

protobufBytes; // assume this is an empty Foo object, in protobuf binary format
Foo.decode(protobufBytes); // => { bar: '' }

Foo.encode({ bar: '' }); // => { }, writes an empty Foo object, in protobuf binary format

fromJSON / toJSON

Reading JSON will also initialize the default values. Since senders may either omit unset fields, or set them to the default value, use fromJSON to normalize the input.

Foo.fromJSON({}); // => { bar: '' }
Foo.fromJSON({ bar: '' }); // => { bar: '' }
Foo.fromJSON({ bar: 'baz' }); // => { bar: 'baz' }

When writing JSON, ts-proto currently does not normalize message when converting to JSON, other than omitting unset fields, but it may do so in the future.

// Current ts-proto behavior
Foo.toJSON({}); // => { }
Foo.toJSON({ bar: undefined }); // => { }
Foo.toJSON({ bar: '' }); // => { bar: '' } - note: this is the default value, but it's not omitted
Foo.toJSON({ bar: 'baz' }); // => { bar: 'baz' }

// Possible future behavior, where ts-proto would normalize message
Foo.toJSON({}); // => { }
Foo.toJSON({ bar: undefined }); // => { }
Foo.toJSON({ bar: '' }); // => { } - note: omitting the default value, as expected
Foo.toJSON({ bar: 'baz' }); // => { bar: 'baz' }

• Please open an issue if you need this behavior.

Protobuf comes with several predefined message definitions, called "Well-Known Types". Their interpretation is defined by the Protobuf specification, and libraries are expected to convert these messages to corresponding native types in the target language.

ts-proto currently automatically converts these messages to their corresponding native types.

• google.protobuf.BoolValue ⇆ boolean
• google.protobuf.BytesValue ⇆ Uint8Array
• google.protobuf.DoubleValue ⇆ number
• google.protobuf.FieldMask ⇆ string[]
• google.protobuf.FloatValue ⇆ number
• google.protobuf.Int32Value ⇆ number
• google.protobuf.Int64Value ⇆ number
• google.protobuf.ListValue ⇆ any[]
• google.protobuf.UInt32Value ⇆ number
• google.protobuf.UInt64Value ⇆ number
• google.protobuf.StringValue ⇆ string
• google.protobuf.Value ⇆ any (i.e. number | string | boolean | null | array | object)
• google.protobuf.Struct ⇆ { [key: string]: any }

Wrapper Types are messages containing a single primitive field, and can be imported in .proto files with import "google/protobuf/wrappers.proto".

Since these are messages, their default value is undefined, allowing you to distinguish unset primitives from their default values, when using Wrapper Types. ts-proto generates these fields as <primitive> | undefined.

For example:

// Protobuf
syntax = "proto3";

import "google/protobuf/wrappers.proto";

message ExampleMessage {
  google.protobuf.StringValue name = 1;
}

// TypeScript
interface ExampleMessage {
  name: string | undefined;
}

When encoding a message the primitive value is converted back to its corresponding wrapper type:

ExampleMessage.encode({ name: 'foo' }); // => { name: { value: 'foo' } }, in binary

When calling toJSON, the value is not converted, because wrapper types are idiomatic in JSON.

ExampleMessage.toJSON({ name: 'foo' }); // => { name: 'foo' }

Protobuf's language and types are not sufficient to represent all possible JSON values, since JSON may contain values whose type is unknown in advance. For this reason, Protobuf offers several additional types to represent arbitrary JSON values.

These are called Struct Types, and can be imported in .proto files with import "google/protobuf/struct.proto".

• google.protobuf.Value ⇆ any
  • This is the most general type, and can represent any JSON value (i.e. number | string | boolean | null | array | object).
• google.protobuf.ListValue ⇆ any[]
  • To represent a JSON array
• google.protobuf.Struct ⇆ { [key: string]: any }
  • To represent a JSON object

ts-proto automatically converts back and forth between these Struct Types and their corresponding JSON types.

Example:

// Protobuf
syntax = "proto3";

import "google/protobuf/struct.proto";

message ExampleMessage {
  google.protobuf.Value anything = 1;
}

// TypeScript
interface ExampleMessage {
  anything: any | undefined;
}

Encoding a JSON value embedded in a message, converts it to a Struct Type:

ExampleMessage.encode({ anything: { name: 'hello' } });
/* Outputs the following structure, encoded in protobuf binary format:
{
  anything: Value {
    structValue = Struct {
      fields = [
        MapEntry {
          key = "name",
          value = Value {
            stringValue = "hello"
          }
        ]
      }
    }
 }
}*/

ExampleMessage.encode({ anything: true });
/* Outputs the following structure encoded in protobuf binary format:
{
  anything: Value {
    boolValue = true
  }
}*/

The representation of google.protobuf.Timestamp is configurable by the useDate flag.

Numbers are by default assumed to be plain JavaScript numbers.

This is fine for Protobuf types like int32 and float, but 64-bit types like int64 can't be 100% represented by JavaScript's number type, because int64 can have larger/smaller values than number.

ts-proto's default configuration (which is forceLong=number) is to still use number for 64-bit fields, and then throw an error if a value (at runtime) is larger than Number.MAX_SAFE_INTEGER.

If you expect to use 64-bit / higher-than-MAX_SAFE_INTEGER values, then you can use the ts-proto forceLong option, which uses the long npm package to support the entire range of 64-bit values.

The protobuf number types map to JavaScript types based on the forceLong config option:

Where (*) indicates they might throw an error at runtime.

• Required primitives: use as-is, i.e. string name = 1.
• Optional primitives: use wrapper types, i.e. StringValue name = 1.
• Required messages: not available
• Optional messages: use as-is, i.e. SubMessage message = 1.