ts-proto
ts-proto
transforms your .proto
files into strongly-typed, idiomatic TypeScript files!
Table of contents
Overview
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.
QuickStart
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
(see installation instructions for your platform, i.e. protoc
v3.0.0
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.
Buf
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
To prevent buf push
from reading irrelevent .proto
files, configure buf.yaml
like so:
build:
excludes: [node_modules]
You can also use the official plugin published to the Buf Registry.
version: v1
plugins:
- plugin: buf.build/community/stephenh-ts-proto
out: ../gen/ts
opt:
- outputServices=...
- useExactTypes=...
ESM
If you're using a modern TS setup with either esModuleInterop
or running in an ESM environment, you'll need to pass ts_proto_opt
s of:
esModuleInterop=true
if using esModuleInterop
in your tsconfig.json
, andimportSuffix=.js
if executing the generated ts-proto code in an ESM environment
Goals
In terms of the code that ts-proto
generates, the general goals are:
- 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
Non-Goals
Note that ts-proto is not an out-of-the-box RPC framework; instead it's more of a swiss-army knife (as witnessed by its many config options), that lets you build exactly the RPC framework you'd like on top of it (i.e. that best integrates with your company's protobuf ecosystem; for better or worse, protobuf RPC is still a somewhat fragmented ecosystem).
If you'd like an out-of-the-box RPC framework built on top of ts-proto, there are a few examples:
(Note for potential contributors, if you develop other frameworks/mini-frameworks, or even blog posts/tutorials, on using ts-proto
, we're happy to link to them.)
We also don't support clients for google.api.http
-based Google Cloud APIs, see #948 if you'd like to submit a PR.
Example Types
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 = {
create(baseObject?: DeepPartial<Simple>): 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.
Highlights
-
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 useMongoObjectId
parameter.)
Auto-Batching / N+1 Prevention
(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.
Usage
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.
Supported options
-
With --ts_proto_opt=globalThisPolyfill=true
, ts-proto will include a polyfill for globalThis.
Defaults to false
, i.e. we assume globalThis
is available.
-
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).
With --ts_proto_opt=forceLong=string
, all 64-bit numbers will be output as strings.
With --ts_proto_opt=forceLong=bigint
, all 64-bit numbers will be output as BigInt
s. This option still uses the long
library to encode/decode internally within protobuf.js
, but then converts to/from BigInt
s in the ts-proto-generated code.
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:
- Prevents typos when initializing messages, and
- Provides the most consistent API to readers
- 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;
lastName: string;
}
const data = { firstName: "a", lastTypo: "b" };
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, per the proto3 spec, initialized 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
and create
are meant to address this), so if you still want to have optional keys, 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
and protobufPackage
won't be export
d.
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=unrecognizedEnumName=<NAME>
enums will contain a key <NAME>
with value of the unrecognizedEnumValue
option.
Defaults to UNRECOGNIZED
.
-
With --ts_proto_opt=unrecognizedEnumValue=<NUMBER>
enums will contain a key provided by the unrecognizedEnumName
option with value of <NUMBER>
.
Defaults to -1
.
-
With --ts_proto_opt=unrecognizedEnum=false
enums will not contain an unrecognized enum key and value as provided by the unrecognizedEnumName
and unrecognizedEnumValue
options.
-
With --ts_proto_opt=removeEnumPrefix=true
generated enums will have the enum name removed from members.
FooBar.FOO_BAR_BAZ = "FOO_BAR_BAZ"
will generate FooBar.BAZ = "FOO_BAR_BAZ"
-
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 in both the message keys and the toJSON
/ fromJSON
methods.
snakeToCamel
can also be set as a _
-delimited list of strings (comma is reserved as the flag delimited), i.e. --ts_proto_opt=snakeToCamel=keys_json
, where including keys
will make message keys be camel case and including json
will make JSON keys be camel case.
Empty string, i.e. snakeToCamel=
, will keep both messages keys and JSON
keys as snake case (it is the same as snakeToCamel=false
).
Note that to use the json_name
attribute, you'll have to use the json
.
The default behavior is keys_json
, i.e. both will be camel cased, and json_name
will be used if set.
-
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=outputJsonMethods=to-only
and --ts_proto_opt=outputJsonMethods=from-only
you will be able to export only one between the Message.toJSON
and Message.fromJSON
methods.
This is useful if you're using ts-proto just to encode
or decode
and not for both.
-
With --ts_proto_opt=outputPartialMethods=false
, the Message.fromPartial
and Message.create
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, lowerCaseServiceMethods
will be true and outputServices
will be ignored.
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=useMongoObjectId=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=outputTypeAnnotations=true
, each message will be given a $type
field containing its fully-qualified name. You can use --ts_proto_opt=outputTypeAnnotations=static-only
to omit it from the interface
declaration.
-
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 be given a $type
field containing its 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=rpcBeforeRequest=true
, ts-proto will add a function definition to the Rpc interface definition with the signature: beforeRequest(service: string, message: string, request: <RequestType>)
. It will will also automatically set outputServices=default
. Each of the Service's methods will call beforeRequest
before performing it's request.
-
With --ts_proto_opt=rpcAfterResponse=true
, ts-proto will add a function definition to the Rpc interface definition with the signature: afterResponse(service: string, message: string, response: <ResponseType>)
. It will will also automatically set outputServices=default
. Each of the Service's methods will call afterResponse
before returning the response.
-
With --ts_proto_opt=rpcErrorHandler=true
, ts-proto will add a function definition to the Rpc interface definition with the signature: handleError(service: string, message: string, error: Error)
. It will will also automatically set outputServices=default
.
-
With --ts_proto_opt=useAbortSignal=true
, the generated services will accept an AbortSignal
to cancel RPC calls.
-
With --ts_proto_opt=useAsyncIterable=true
, the generated services will use AsyncIterable
instead of Observable
.
-
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=importSuffix=<SUFFIX>
, ts-proto will emit file imports using the specified suffix. An import of helloworld.ts
with fileSuffix=.js
would generate import "helloworld.js"
. The default is to import without a file extension. Supported by TypeScript 4.7.x and up.
-
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
and create
methods will not use Exact types.
The default behavior is useExactTypes=true
, which makes fromPartial
and create
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=useJsonName=true
, json_name
defined in protofiles will be used instead of message field names.
-
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.
-
With --ts_proto_opt=useNumericEnumForJson=true
, the JSON converter (toJSON
) will encode enum values as int, rather than a string literal.
-
With --ts_proto_opt=initializeFieldsAsUndefined=false
, all optional field initializers will be omited from the generated base instances.
-
With --ts_proto_opt=Mgoogle/protobuf/empty.proto=./google3/protobuf/empty
, ('M' means 'importMapping', similar to protoc-gen-go), the generated code import path for ./google/protobuf/empty.ts
will reflect the overridden value:
Mfoo/bar.proto=@myorg/some-lib
will map foo/bar.proto
imports into import ... from '@myorg/some-lib'
.Mfoo/bar.proto=./some/local/lib
will map foo/bar.proto
imports into import ... from './some/local/lib'
.Mfoo/bar.proto=some-modules/some-lib
will map foo/bar.proto
imports into import ... from 'some-module/some-lib'
.- Note: Uses are accummulated, so multiple values are expected in the form of
--ts_proto_opt=M... --ts_proto_opt=M...
(one ts_proto_opt
per mapping). - Note: Proto files that match mapped imports will not be generated.
-
With --ts_proto_opt=useMapType=true
, the generated code for protobuf map<key_type, value_type>
will become Map<key_type, value_type>
that uses JavaScript Map type.
The default behavior is useMapType=false
, which makes it generate the code for protobuf map<key_type, value_type
with the key-value pair like {[key: key_type]: value_type}
.
-
With --ts_proto_opt=useReadonlyTypes=true
, the generated types will be declared as immutable using typescript's readonly
modifer.
-
With --ts_proto_opt=useSnakeTypeName=false
will remove snake casing from types.
Example Protobuf
message Box {
message Element {
message Image {
enum Alignment {
LEFT = 1;
CENTER = 2;
RIGHT = 3;
}
}
}
}
by default this is enabled which would generate a type of Box_Element_Image_Alignment
. By disabling this option the type that is generated would be BoxElementImageAlignment
.
-
With --ts_proto_opt=outputExtensions=true
, the generated code will include proto2 extensions
Extension encode/decode methods are compliant with the outputEncodeMethods
option, and if unknownFields=true
,
the setExtension
and getExtension
methods will be created for extendable messages, also compliant with outputEncodeMethods
(setExtension = encode, getExtension = decode).
-
With --ts_proto_opt=outputIndex=true
, index files will be generated based on the proto package namespaces.
This will disable exportCommonSymbols
to avoid name collisions on the common symbols.
-
With --emitDefaultValues=json-methods
, the generated toJSON method will emit scalars like 0
and ""
as json fields.
NestJS Support
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.
Watch Mode
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\""
Basic gRPC implementation
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) => {
const path = `/${service}/${method}`;
return new Promise((resolve, reject) => {
const resultCallback: UnaryCallback<any> = (err, res) => {
if (err) {
return reject(err);
}
resolve(res);
};
function passThrough(argument: any) {
return argument;
}
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.
Development
This section describes how to contribute directly to ts-proto, i.e. it's not required for running ts-proto
in protoc
or using the generated TypeScript.
Requirements
- Docker
yarn
— npm install -g yarn
Setup
The commands below assume you have Docker installed. 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
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
- Add/update an integration test for your use case
- Either find an existing
integration/*
test that is close enough to your use case, e.g. has a parameters.txt
that matches the ts_proto_opt
params necessary to reproduce your use case - If creating a new integration test:
- Make a new
integration/your-new-test/parameters.txt
with the necessary ts_proto_opt
params - Create a minimal
integration/your-new-test/your-new-test.proto
schema to reproduce your use case
- After any changes to
your-new-test.proto
, or an existing integration/*.proto
file, run yarn proto2bin
- You can also leave
yarn watch
running, and it should "just do the right thing"
- Add/update a
integration/your-new-test/some-test.ts
unit test, even if it's as trivial as just making sure the generated code compiles
- Modify the
ts-proto
code generation logic:
- Most important logic is found in src/main.ts.
- After any changes to
src/*.ts
files, run yarn bin2ts
to re-codegen all integration tests
- Or
yarn bin2ts your-new-test
to re-codegen a specific test - Again leaving
yarn watch
running should "just do the right thing"
- Run
yarn test
to verify your changes pass all existing tests - Commit and submit a PR
- Run
yarn format
to format the typescript files. - Make sure to
git add
all of the *.proto
, *.bin
, and *.ts
files in integration/your-new-test
- Sometimes checking in generated code is frowned upon, but given ts-proto's main job is to generate code, seeing the codegen diffs in PRs is helpful
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:
. aliases.sh
protoc --plugin=/ts-proto/protoc-gen-ts_proto --ts_proto_out=./output -I=./protos ./protoc/*.proto
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.
Assumptions
- TS/ES6 module name is the proto package
Todo
- 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
OneOf Handling
By default, ts-proto models oneof
fields "flatly" in the message, e.g. a message like:
message Foo {
oneof either_field { string field_a = 1; string field_b = 2; }
}
Will generate a Foo
type with two fields: field_a: string | undefined;
and 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.
Instead, 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.
(Note that eitherField
is optional b/c oneof
in Protobuf means "at most one field" is set, and does not mean one of the fields must be set.)
In ts-proto's currently-unscheduled 2.x release, oneof=unions
will become the default behavior.
Default values and unset fields
In core Protobuf (and so also ts-proto
), values that are unset or equal to the default value are not sent over the wire.
For example, the default value of a message is undefined
. Primitive types take their natural default value, e.g. string
is ''
, number
is 0
, etc.
Protobuf chose/enforces this behavior because it enables forward compatibility, as primitive fields will always have a value, even when omitted by outdated agents.
This is good, but it also means default and unset values cannot be distinguished in ts-proto
fields; it's just fundamentally how Protobuf works.
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;
Foo.decode(protobufBytes);
Foo.encode({ bar: "" });
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({});
Foo.fromJSON({ bar: "" });
Foo.fromJSON({ bar: "baz" });
When writing JSON, ts-proto
normalizes messages by omitting unset fields and fields set to their default values.
Foo.toJSON({});
Foo.toJSON({ bar: undefined });
Foo.toJSON({ bar: "" });
Foo.toJSON({ bar: "baz" });
Well-Known Types
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.
Wrapper Types
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;
}
interface ExampleMessage {
name: string | undefined;
}
When encoding a message the primitive value is converted back to its corresponding wrapper type:
ExampleMessage.encode({ name: "foo" });
When calling toJSON, the value is not converted, because wrapper types are idiomatic in JSON.
ExampleMessage.toJSON({ name: "foo" });
JSON Types (Struct Types)
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"
.
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;
}
interface ExampleMessage {
anything: any | undefined;
}
Encoding a JSON value embedded in a message, converts it to a Struct Type:
ExampleMessage.encode({ anything: { name: "hello" } });
ExampleMessage.encode({ anything: true });
Timestamp
The representation of google.protobuf.Timestamp
is configurable by the useDate
flag.
The useJsonTimestamp
flag controls precision when useDate
is false
.
Protobuf well-known type | Default/useDate=true | useDate=false | useDate=string |
---|
google.protobuf.Timestamp | Date | { seconds: number, nanos: number } | string |
When using useDate=false
and useJsonTimestamp=raw
timestamp is represented as { seconds: number, nanos: number }
, but has nanosecond precision.
Number Types
Numbers are by default assumed to be plain JavaScript number
s.
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:
Protobuf number types | Default/forceLong=number | forceLong=long | forceLong=string |
---|
double | number | number | number |
float | number | number | number |
int32 | number | number | number |
int64 | number* | Long | string |
uint32 | number | number | number |
uint64 | number* | Unsigned Long | string |
sint32 | number | number | number |
sint64 | number* | Long | string |
fixed32 | number | number | number |
fixed64 | number* | Unsigned Long | string |
sfixed32 | number | number | number |
sfixed64 | number* | Long | string |
Where (*) indicates they might throw an error at runtime.
Current Status of Optional Values
- 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
.