Top Related Projects
A modern runtime for JavaScript and TypeScript.
Web framework built on Web Standards
Spin is the open source developer tool for building and running serverless applications powered by WebAssembly.
🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten
A fast and secure runtime for WebAssembly
Quick Overview
Cloudflare Workers-rs is a Rust-based framework for building and deploying serverless applications on Cloudflare Workers. It provides a set of tools and libraries that allow developers to write Workers in Rust, leveraging the language's performance and safety features while taking advantage of Cloudflare's global network.
Pros
- High performance due to Rust's efficiency and low-level control
- Strong type safety and memory safety guarantees
- Seamless integration with Cloudflare Workers ecosystem
- Access to Rust's rich ecosystem of libraries and tools
Cons
- Steeper learning curve compared to JavaScript-based Workers
- Limited runtime environment may restrict some Rust features
- Potentially longer cold start times compared to JavaScript Workers
- Smaller community and fewer resources compared to JavaScript Workers
Code Examples
- Hello World Worker:
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Response::ok("Hello, World!")
}
- Handling different HTTP methods:
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
match req.method() {
Method::Get => Response::ok("This is a GET request"),
Method::Post => Response::ok("This is a POST request"),
_ => Response::error("Method not allowed", 405),
}
}
- Interacting with KV storage:
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
let kv = env.kv("MY_KV")?;
let value = kv.get("my_key").text().await?;
match value {
Some(v) => Response::ok(v),
None => Response::error("Key not found", 404),
}
}
Getting Started
- Install wrangler:
npm install -g @cloudflare/wrangler
- Create a new project:
wrangler generate my-worker https://github.com/cloudflare/workers-rs-template
- Navigate to the project:
cd my-worker
- Build and deploy:
wrangler publish
For more detailed instructions, refer to the official documentation.
Competitor Comparisons
A modern runtime for JavaScript and TypeScript.
Pros of Deno
- Broader ecosystem and runtime support beyond serverless
- Built-in TypeScript support without additional configuration
- More comprehensive standard library and APIs
Cons of Deno
- Less specialized for Cloudflare Workers environment
- Potentially larger bundle sizes for serverless deployments
- May require additional setup for Cloudflare-specific features
Code Comparison
Deno:
import { serve } from "https://deno.land/std@0.140.0/http/server.ts";
serve((req) => new Response("Hello World!"));
Workers-rs:
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Response::ok("Hello World!")
}
Key Differences
- Deno uses JavaScript/TypeScript, while Workers-rs uses Rust
- Workers-rs is tailored specifically for Cloudflare Workers
- Deno offers a more general-purpose runtime for various environments
- Workers-rs provides lower-level control and potentially better performance
- Deno has a larger community and more third-party modules available
Use Cases
- Choose Deno for broader JavaScript/TypeScript projects beyond Cloudflare
- Opt for Workers-rs when focusing exclusively on Cloudflare Workers with Rust
- Consider Deno for rapid prototyping and easier onboarding for JS developers
- Select Workers-rs for performance-critical applications within Cloudflare's ecosystem
Web framework built on Web Standards
Pros of Hono
- Lightweight and fast: Hono is designed to be minimal and performant
- Extensive middleware ecosystem: Offers a wide range of built-in and community-created middleware
- TypeScript-first approach: Provides excellent TypeScript support out of the box
Cons of Hono
- Limited to JavaScript/TypeScript: Not suitable for developers preferring Rust
- Less integrated with Cloudflare: May require additional setup for some Cloudflare-specific features
Code Comparison
Hono (JavaScript/TypeScript):
import { Hono } from 'hono'
const app = new Hono()
app.get('/', (c) => c.text('Hello Hono!'))
export default app
Workers-rs (Rust):
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Router::new().get("/", |_, _| Response::ok("Hello Workers-rs!")).run(req, env).await
}
Both frameworks offer concise routing and request handling, but Workers-rs provides a more native Rust experience, while Hono focuses on JavaScript/TypeScript developers.
Spin is the open source developer tool for building and running serverless applications powered by WebAssembly.
Pros of Spin
- Supports multiple languages (Rust, JavaScript, Python, Go) for serverless applications
- Provides a local development environment for testing and debugging
- Offers a plugin system for extending functionality
Cons of Spin
- Less mature ecosystem compared to Workers
- Limited to WebAssembly-compatible languages
- May have a steeper learning curve for developers new to WebAssembly
Code Comparison
Spin (Rust):
#[http_component]
fn handle_request(req: Request) -> Response {
Response::builder()
.status(200)
.body(Some("Hello from Spin!".into()))
.unwrap()
}
Workers (Rust):
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Response::ok("Hello from Workers!")
}
Both Spin and Workers-rs are frameworks for building serverless applications, but they have different focuses. Spin aims to be a multi-language platform using WebAssembly, while Workers-rs is specifically designed for Cloudflare's Workers platform using Rust. Spin offers more flexibility in terms of language choice and local development, but Workers-rs benefits from tighter integration with Cloudflare's ecosystem and potentially easier deployment for Cloudflare users.
🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten
Pros of Wasmer
- More versatile: Supports multiple languages and can run WebAssembly outside the browser
- Standalone runtime: Can be used independently of any specific cloud platform
- Active community: Larger user base and more frequent updates
Cons of Wasmer
- Steeper learning curve: Requires more setup and configuration
- Less integrated: Doesn't offer built-in serverless features like Workers-rs
- Broader focus: May not be optimized specifically for edge computing scenarios
Code Comparison
Workers-rs:
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Response::ok("Hello, World!")
}
Wasmer:
use wasmer::{Store, Module, Instance};
let module = Module::new(&store, wasm_bytes)?;
let instance = Instance::new(&module, &imports)?;
let result = instance.exports.get_function("main")?.call(&[])?;
Summary
Workers-rs is tailored for Cloudflare's edge computing platform, offering a simpler development experience for serverless functions. Wasmer, on the other hand, provides a more general-purpose WebAssembly runtime with broader language support and use cases beyond edge computing. The choice between them depends on specific project requirements and deployment preferences.
A fast and secure runtime for WebAssembly
Pros of Wasmtime
- More general-purpose WebAssembly runtime, suitable for various applications beyond serverless
- Offers deeper control over WebAssembly execution and memory management
- Actively developed by a consortium of major tech companies, ensuring broad industry support
Cons of Wasmtime
- Steeper learning curve for developers new to WebAssembly concepts
- Requires more setup and configuration compared to Workers-rs's streamlined approach
- Less integrated with specific cloud provider ecosystems
Code Comparison
Wasmtime (initializing a runtime and running a module):
let engine = Engine::default();
let module = Module::from_file(&engine, "example.wasm")?;
let store = Store::new(&engine, ());
let instance = Instance::new(&store, &module, &[])?;
Workers-rs (defining a worker):
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
Response::ok("Hello, World!")
}
Summary
Wasmtime is a versatile WebAssembly runtime suitable for various applications, offering deep control but with a steeper learning curve. Workers-rs, on the other hand, provides a more streamlined approach specifically tailored for Cloudflare Workers, making it easier to develop serverless functions but with less flexibility outside that ecosystem.
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Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual CopilotREADME
Work-in-progress ergonomic Rust bindings to Cloudflare Workers environment. Write your entire worker in Rust!
Read the Notes and FAQ
Example Usage
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
console_log!(
"{} {}, located at: {:?}, within: {}",
req.method().to_string(),
req.path(),
req.cf().unwrap().coordinates().unwrap_or_default(),
req.cf().unwrap().region().unwrap_or("unknown region".into())
);
if !matches!(req.method(), Method::Post) {
return Response::error("Method Not Allowed", 405);
}
if let Some(file) = req.form_data().await?.get("file") {
return match file {
FormEntry::File(buf) => {
Response::ok(&format!("size = {}", buf.bytes().await?.len()))
}
_ => Response::error("`file` part of POST form must be a file", 400),
};
}
Response::error("Bad Request", 400)
}
Getting Started
The project uses wrangler for running and publishing your Worker.
Use cargo generate to start from a template:
$ cargo generate cloudflare/workers-rs
There are several templates to chose from. You should see a new project layout with a src/lib.rs
.
Start there! Use any local or remote crates and modules (as long as they compile to the wasm32-unknown-unknown
target).
Once you're ready to run your project, run your worker locally:
npx wrangler dev
Finally, go live:
# configure your routes, zones & more in your worker's `wrangler.toml` file
npx wrangler deploy
If you would like to have wrangler
installed on your machine, see instructions in wrangler repository.
http
Feature
worker
0.0.21
introduced an http
feature flag which starts to replace custom types with widely used types from the http
crate.
This makes it much easier to use crates which use these standard types such as axum
and hyper
.
This currently does a few things:
- Introduce
Body
, which implementshttp_body::Body
and is a simple wrapper aroundweb_sys::ReadableStream
. - The
req
argument when using the[event(fetch)]
macro becomeshttp::Request<worker::Body>
. - The expected return type for the fetch handler is
http::Response<B>
whereB
can be anyhttp_body::Body<Data=Bytes>
. - The argument for
Fetcher::fetch_request
ishttp::Request<worker::Body>
. - The return type of
Fetcher::fetch_request
isResult<http::Response<worker::Body>>
.
The end result is being able to use frameworks like axum
directly (see example):
pub async fn root() -> &'static str {
"Hello Axum!"
}
fn router() -> Router {
Router::new().route("/", get(root))
}
#[event(fetch)]
async fn fetch(
req: HttpRequest,
_env: Env,
_ctx: Context,
) -> Result<http::Response<axum::body::Body>> {
Ok(router().call(req).await?)
}
We also implement try_from
between worker::Request
and http::Request<worker::Body>
, and between worker::Response
and http::Response<worker::Body>
. This allows you to convert your code incrementally if it is tightly coupled to the original types.
Or use the Router
:
Parameterize routes and access the parameter values from within a handler. Each handler function takes a
Request
, and a RouteContext
. The RouteContext
has shared data, route params, Env
bindings, and more.
use serde::{Deserialize, Serialize};
use worker::*;
#[event(fetch)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
// Create an instance of the Router, which can use parameters (/user/:name) or wildcard values
// (/file/*pathname). Alternatively, use `Router::with_data(D)` and pass in arbitrary data for
// routes to access and share using the `ctx.data()` method.
let router = Router::new();
// useful for JSON APIs
#[derive(Deserialize, Serialize)]
struct Account {
id: u64,
// ...
}
router
.get_async("/account/:id", |_req, ctx| async move {
if let Some(id) = ctx.param("id") {
let accounts = ctx.kv("ACCOUNTS")?;
return match accounts.get(id).json::<Account>().await? {
Some(account) => Response::from_json(&account),
None => Response::error("Not found", 404),
};
}
Response::error("Bad Request", 400)
})
// handle files and fields from multipart/form-data requests
.post_async("/upload", |mut req, _ctx| async move {
let form = req.form_data().await?;
if let Some(entry) = form.get("file") {
match entry {
FormEntry::File(file) => {
let bytes = file.bytes().await?;
}
FormEntry::Field(_) => return Response::error("Bad Request", 400),
}
// ...
if let Some(permissions) = form.get("permissions") {
// permissions == "a,b,c,d"
}
// or call `form.get_all("permissions")` if using multiple entries per field
}
Response::error("Bad Request", 400)
})
// read/write binary data
.post_async("/echo-bytes", |mut req, _ctx| async move {
let data = req.bytes().await?;
if data.len() < 1024 {
return Response::error("Bad Request", 400);
}
Response::from_bytes(data)
})
.run(req, env).await
}
Durable Object, KV, Secret, & Variable Bindings
All "bindings" to your script (Durable Object & KV Namespaces, Secrets, Variables and Version) are
accessible from the env
parameter provided to both the entrypoint (main
in this example), and to
the route handler callback (in the ctx
argument), if you use the Router
from the worker
crate.
use worker::*;
#[event(fetch, respond_with_errors)]
pub async fn main(req: Request, env: Env, _ctx: worker::Context) -> Result<Response> {
utils::set_panic_hook();
let router = Router::new();
router
.on_async("/durable", |_req, ctx| async move {
let namespace = ctx.durable_object("CHATROOM")?;
let stub = namespace.id_from_name("A")?.get_stub()?;
// `fetch_with_str` requires a valid Url to make request to DO. But we can make one up!
stub.fetch_with_str("http://fake_url.com/messages").await
})
.get("/secret", |_req, ctx| {
Response::ok(ctx.secret("CF_API_TOKEN")?.to_string())
})
.get("/var", |_req, ctx| {
Response::ok(ctx.var("BUILD_NUMBER")?.to_string())
})
.post_async("/kv", |_req, ctx| async move {
let kv = ctx.kv("SOME_NAMESPACE")?;
kv.put("key", "value")?.execute().await?;
Response::empty()
})
.run(req, env).await
}
For more information about how to configure these bindings, see:
- https://developers.cloudflare.com/workers/cli-wrangler/configuration#keys
- https://developers.cloudflare.com/workers/learning/using-durable-objects#configuring-durable-object-bindings
- https://developers.cloudflare.com/workers/runtime-apis/bindings/version-metadata/
Durable Objects
Define a Durable Object in Rust
To define a Durable Object using the worker
crate you need to implement the DurableObject
trait
on your own struct. Additionally, the #[durable_object]
attribute macro must be applied to both
your struct definition and the trait impl
block for it.
use worker::*;
#[durable_object]
pub struct Chatroom {
users: Vec<User>,
messages: Vec<Message>,
state: State,
env: Env, // access `Env` across requests, use inside `fetch`
}
#[durable_object]
impl DurableObject for Chatroom {
fn new(state: State, env: Env) -> Self {
Self {
users: vec![],
messages: vec![],
state: state,
env,
}
}
async fn fetch(&mut self, _req: Request) -> Result<Response> {
// do some work when a worker makes a request to this DO
Response::ok(&format!("{} active users.", self.users.len()))
}
}
You'll need to "migrate" your worker script when it's published so that it is aware of this new
Durable Object, and include a binding in your wrangler.toml
.
- Include the Durable Object binding type in you
wrangler.toml
file:
# ...
[durable_objects]
bindings = [
{ name = "CHATROOM", class_name = "Chatroom" } # the `class_name` uses the Rust struct identifier name
]
[[migrations]]
tag = "v1" # Should be unique for each entry
new_classes = ["Chatroom"] # Array of new classes
- For more information about migrating your Durable Object as it changes, see the docs here: https://developers.cloudflare.com/workers/learning/using-durable-objects#durable-object-migrations-in-wranglertoml
Queues
Enabling queues
As queues are in beta you need to enable the queue
feature flag.
Enable it by adding it to the worker dependency in your Cargo.toml
:
worker = {version = "...", features = ["queue"]}
Example worker consuming and producing messages:
use worker::*;
use serde::{Deserialize, Serialize};
#[derive(Serialize, Debug, Clone, Deserialize)]
pub struct MyType {
foo: String,
bar: u32,
}
// Consume messages from a queue
#[event(queue)]
pub async fn main(message_batch: MessageBatch<MyType>, env: Env, _ctx: Context) -> Result<()> {
// Get a queue with the binding 'my_queue'
let my_queue = env.queue("my_queue")?;
// Deserialize the message batch
let messages = message_batch.messages()?;
// Loop through the messages
for message in messages {
// Log the message and meta data
console_log!(
"Got message {:?}, with id {} and timestamp: {}",
message.body(),
message.id(),
message.timestamp().to_string()
);
// Send the message body to the other queue
my_queue.send(message.body()).await?;
// Ack individual message
message.ack();
// Retry individual message
message.retry();
}
// Retry all messages
message_batch.retry_all();
// Ack all messages
message_batch.ack_all();
Ok(())
}
You'll need to ensure you have the correct bindings in your wrangler.toml
:
# ...
[[queues.consumers]]
queue = "myqueueotherqueue"
max_batch_size = 10
max_batch_timeout = 30
[[queues.producers]]
queue = "myqueue"
binding = "my_queue"
RPC Support
workers-rs
has experimental support for Workers RPC.
For now, this relies on JavaScript bindings and may require some manual usage of wasm-bindgen
.
Not all features of RPC are supported yet (or have not been tested), including:
- Function arguments and return values
- Class instances
- Stub forwarding
RPC Server
Writing an RPC server with workers-rs
is relatively simple. Simply export methods using wasm-bindgen
. These
will be automatically detected by worker-build
and made available to other Workers. See
example.
RPC Client
Creating types and bindings for invoking another Worker's RPC methods is a bit more involved. You will need to
write more complex wasm-bindgen
bindings and some boilerplate to make interacting with the RPC methods more
idiomatic. See example.
With manually written bindings, it should be possible to support non-primitive argument and return types, using
serde-wasm-bindgen
.
Generating Client Bindings
There are many routes that can be taken to describe RPC interfaces. Under the hood, Workers RPC uses Cap'N Proto. A possible future direction is for Wasm guests to include Cap'N Proto serde support and speak directly to the RPC protocol, bypassing JavaScript. This would likely involve defining the RPC interface in Cap'N Proto schema and generating Rust code from that.
Another popular interface schema in the WebAssembly community is
WIT. This is a lightweight format
designed for the WebAssembly Component model. workers-rs
includes an experimental code generator which
allows you to describe your RPC interface using WIT and generate JavaScript bindings as shown in the
rpc-client example. The easiest way to use this code generator is using a build script as shown in the example.
This code generator is pre-alpha, with no support guarantee, and implemented only for primitive types at this time.
Testing with Miniflare
In order to test your Rust worker locally, the best approach is to use Miniflare. However, because Miniflare is a Node package, you will need to write your end-to-end tests in JavaScript or TypeScript in your project. The official documentation for writing tests using Miniflare is available here. This documentation being focused on JavaScript / TypeScript codebase, you will need to configure as follows to make it work with your Rust-based, WASM-generated worker:
Step 1: Add Wrangler and Miniflare to your devDependencies
npm install --save-dev wrangler miniflare
Step 2: Build your worker before running the tests
Make sure that your worker is built before running your tests by calling the following in your build chain:
wrangler deploy --dry-run
By default, this should build your worker under the ./build/
directory at the
root of your project.
Step 3: Configure your Miniflare instance in your JavaScript / TypeScript tests
To instantiate the Miniflare
testing instance in your tests, make sure to
configure its scriptPath
option to the relative path of where your JavaScript
worker entrypoint was generated, and its moduleRules
so that it is able to
resolve the *.wasm
file imported from that JavaScript worker:
// test.mjs
import assert from "node:assert";
import { Miniflare } from "miniflare";
const mf = new Miniflare({
scriptPath: "./build/worker/shim.mjs",
modules: true,
modulesRules: [
{ type: "CompiledWasm", include: ["**/*.wasm"], fallthrough: true }
]
});
const res = await mf.dispatchFetch("http://localhost");
assert(res.ok);
assert.strictEqual(await res.text(), "Hello, World!");
D1 Databases
Enabling D1 databases
As D1 databases are in alpha, you'll need to enable the d1
feature on the worker
crate.
worker = { version = "x.y.z", features = ["d1"] }
Example usage
use worker::*;
#[derive(Deserialize)]
struct Thing {
thing_id: String,
desc: String,
num: u32,
}
#[event(fetch, respond_with_errors)]
pub async fn main(request: Request, env: Env, _ctx: Context) -> Result<Response> {
Router::new()
.get_async("/:id", |_, ctx| async move {
let id = ctx.param("id").unwrap()?;
let d1 = ctx.env.d1("things-db")?;
let statement = d1.prepare("SELECT * FROM things WHERE thing_id = ?1");
let query = statement.bind(&[id])?;
let result = query.first::<Thing>(None).await?;
match result {
Some(thing) => Response::from_json(&thing),
None => Response::error("Not found", 404),
}
})
.run(request, env)
.await
}
Notes and FAQ
It is exciting to see how much is possible with a framework like this, by expanding the options
developers have when building on top of the Workers platform. However, there is still much to be
done. Expect a few rough edges, some unimplemented APIs, and maybe a bug or two here and there. Itâs
worth calling out here that some things that may have worked in your Rust code might not work here -
itâs all WebAssembly at the end of the day, and if your code or third-party libraries donât target
wasm32-unknown-unknown
, they canât be used on Workers. Additionally, youâve got to leave your
threaded async runtimes at home; meaning no Tokio or async_std support. However, async/await syntax
is still available and supported out of the box when you use the worker
crate.
We fully intend to support this crate and continue to build out its missing features, but your help and feedback is a must. We donât like to build in a vacuum, and weâre in an incredibly fortunate position to have brilliant customers like you who can help steer us towards an even better product.
So give it a try, leave some feedback, and star the repo to encourage us to dedicate more time and resources to this kind of project.
If this is interesting to you and you want to help out, weâd be happy to get outside contributors started. We know there are improvements to be made such as compatibility with popular Rust HTTP ecosystem types (we have an example conversion for Headers if you want to make one), implementing additional Web APIs, utility crates, and more. In fact, weâre always on the lookout for great engineers, and hiring for many open roles - please take a look.
FAQ
- Can I deploy a Worker that uses
tokio
orasync_std
runtimes?
- Currently no. All crates in your Worker project must compile to
wasm32-unknown-unknown
target, which is more limited in some ways than targets for x86 and ARM64.
- The
worker
crate doesn't have X! Why not?
- Most likely, it should, we just haven't had the time to fully implement it or add a library to wrap the FFI. Please let us know you need a feature by opening an issue.
- My bundle size exceeds Workers size limits, what do I do?
- We're working on solutions here, but in the meantime you'll need to minimize the number of crates
your code depends on, or strip as much from the
.wasm
binary as possible. Here are some extra steps you can try: https://rustwasm.github.io/book/reference/code-size.html#optimizing-builds-for-code-size
â ï¸ Caveats
- Upgrading worker package to version
0.0.18
and higher
- While upgrading your worker to version
0.0.18
an error "error[E0432]: unresolved importcrate::sys::IoSourceState
" can appear. In this case, upgradepackage.edition
toedition = "2021"
inwrangler.toml
[package]
edition = "2021"
Releasing
- Trigger a workflow to create a release PR.
- Review version changes and merge PR.
- A draft GitHub release will be created. Author release notes and publish when ready.
- Crates (
worker-sys
,worker-macros
,worker
) will be published automatically.
Contributing
Your feedback is welcome and appreciated! Please use the issue tracker to talk about potential implementations or make feature requests. If you're interested in making a PR, we suggest opening up an issue to talk about the change you'd like to make as early as possible.
Project Contents
- worker: the user-facing crate, with Rust-familiar abstractions over the Rust<->JS/WebAssembly interop via wrappers and convenience library over the FFI bindings.
- worker-sys: Rust extern "C" definitions for FFI compatibility with the Workers JS Runtime.
- worker-macros: exports
event
anddurable_object
macros for wrapping Rust entry point in afetch
method of an ES Module, and code generation to create and interact with Durable Objects. - worker-sandbox: a functioning Cloudflare Worker for testing features and ergonomics.
- worker-build: a cross-platform build command for
workers-rs
-based projects.
Top Related Projects
A modern runtime for JavaScript and TypeScript.
Web framework built on Web Standards
Spin is the open source developer tool for building and running serverless applications powered by WebAssembly.
🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten
A fast and secure runtime for WebAssembly
Convert designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot