🦀 TuskLang Rust Real-Time & Streaming Systems

"We don't bow to any king" - Rust Edition

Master real-time and streaming architectures with TuskLang Rust. From WebSockets to event streaming, from pub/sub to reactive APIs—build ultra-responsive, scalable systems with Rust and TuskLang.

⚡ Real-Time Communication

WebSocket Server with Actix

use actix::{Actor, StreamHandler};
use actix_web::{web, App, HttpRequest, HttpServer, Error, HttpResponse};
use actix_web_actors::ws;
struct MyWebSocket;
impl Actor for MyWebSocket {
    type Context = ws::WebsocketContext<Self>;
}
impl StreamHandler<Result<ws::Message, ws::ProtocolError>> for MyWebSocket {
    fn handle(&mut self, msg: Result<ws::Message, ws::ProtocolError>, ctx: &mut Self::Context) {
        if let Ok(ws::Message::Text(text)) = msg {
            ctx.text(format!("Echo: {}", text));
        }
    }
}
async fn ws_index(r: HttpRequest, stream: web::Payload) -> Result<HttpResponse, Error> {
    ws::start(MyWebSocket {}, &r, stream)
}
#[actix_web::main]
async fn main() -> std::io::Result<()> {
    HttpServer::new(|| App::new().route("/ws/", web::get().to(ws_index)))
        .bind("0.0.0.0:8080")?
        .run()
        .await
}

TSK-Driven WebSocket Config

[websocket]
enabled: true
port: 8080
max_connections: 1000
heartbeat_interval: "30s"
message_buffer_size: 1024
[security]
allowed_origins: ["https://myapp.com"]
rate_limit: 100

🔄 Event Streaming

Kafka Integration with rdkafka

use rdkafka::producer::{FutureProducer, FutureRecord};
use rdkafka::config::ClientConfig;
use std::time::Duration;
#[tokio::main]
async fn main() {
    let producer: FutureProducer = ClientConfig::new()
        .set("bootstrap.servers", "localhost:9092")
        .create()
        .expect("Producer creation error");
    let delivery_status = producer.send(
        FutureRecord::to("my-topic")
            .payload("hello world")
            .key("key1"),
        Duration::from_secs(0),
    ).await;
    println!("Delivery status: {:?}", delivery_status);
}

TSK Streaming Config

[streaming]
type: "kafka"
brokers: ["localhost:9092"]
topics: ["events", "metrics"]
consumer_group: "my-group"
max_batch_size: 500
commit_interval: "5s"
[security]
auth_type: "sasl"
username: @env("KAFKA_USER")
password: @env("KAFKA_PASS")

📡 Pub/Sub Messaging

NATS Integration

use nats::asynk::Connection;
#[tokio::main]
async fn main() -> std::io::Result<()> {
    let nc = nats::asynk::connect("localhost:4222").await.unwrap();
    nc.publish("updates", "Hello, NATS!").await.unwrap();
    let sub = nc.subscribe("updates").await.unwrap();
    if let Some(msg) = sub.next().await {
        println!("Received: {}", String::from_utf8_lossy(&msg.data));
    }
    Ok(())
}

TSK Pub/Sub Config

[pubsub]
type: "nats"
servers: ["localhost:4222"]
subjects: ["updates", "notifications"]
queue_group: "workers"
max_in_flight: 100

🔔 Reactive APIs

Server-Sent Events (SSE) with Actix

use actix_web::{web, App, HttpResponse, HttpServer, Responder};
use futures_util::stream::Stream;
use std::pin::Pin;
use std::time::Duration;
use tokio_stream::StreamExt;
async fn sse() -> impl Responder {
    let event_stream = tokio_stream::wrappers::IntervalStream::new(tokio::time::interval(Duration::from_secs(1)))
        .enumerate()
        .map(|(i, _)| Ok::<_, actix_web::Error>(format!("data: event {}\n\n", i)));
    HttpResponse::Ok()
        .content_type("text/event-stream")
        .streaming(event_stream)
}
#[actix_web::main]
async fn main() -> std::io::Result<()> {
    HttpServer::new(|| App::new().route("/events", web::get().to(sse)))
        .bind("0.0.0.0:8080")?
        .run()
        .await
}

TSK SSE Config

[sse]
enabled: true
endpoint: "/events"
heartbeat_interval: "5s"
max_clients: 500

🛡️ Security & Performance

- Use TLS for all real-time endpoints - Implement rate limiting and authentication - Monitor connection counts and latency - Use message batching and compression for streaming

🧪 Testing Real-Time Systems

#[tokio::test]
async fn test_websocket_echo() {
    use tokio_tungstenite::connect_async;
    let (mut ws_stream, _) = connect_async("ws://localhost:8080/ws/").await.unwrap();
    ws_stream.send(tokio_tungstenite::tungstenite::Message::Text("hello".into())).await.unwrap();
    if let Some(msg) = ws_stream.next().await {
        assert_eq!(msg.unwrap().into_text().unwrap(), "Echo: hello");
    }
}

🎯 What You've Learned

1. WebSockets - Real-time bidirectional communication 2. Event streaming - Kafka, NATS, and message brokers 3. Pub/Sub - Reactive, decoupled messaging 4. SSE - Server-sent events for push notifications 5. Security & performance - TLS, rate limiting, and monitoring

🚀 Next Steps

1. Integrate real-time features into your Rust apps 2. Experiment with Kafka, NATS, and WebSockets 3. Monitor and optimize latency and throughput 4. Add authentication and rate limiting 5. Build reactive APIs with TuskLang and Rust

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You now have complete real-time and streaming mastery with TuskLang Rust! From WebSockets to event streaming, from pub/sub to reactive APIs—TuskLang gives you the tools to build ultra-responsive, scalable systems with Rust.