Wingfoil

Wingfoil is a blazingly fast, highly scalable stream processing framework designed for latency-critical use cases such as electronic trading and real-time AI systems.

Wingfoil simplifies receiving, processing and distributing streaming data across your entire stack.

Features

• Fast: Ultra-low latency and high throughput with a efficent DAG based execution engine.
• Simple and obvious to use: Define your graph of calculations; Wingfoil manages its execution.
• Multi-language: currently available as a Rust crate and as a beta release, python package with plans to add WASM/JavaScript/TypeScript support.
• Backtesting: Replay historical data to backtest and optimise strategies.
• Async/Tokio: seamless integration, allows you to leverage async at your graph edges.
• Multi-threading: distribute graph execution across cores.

Quick Start

use wingfoil::*;
use std::time::Duration;
fn main() {
    let period = Duration::from_secs(1);
    ticker(period)
        .count()
        .map(|i| format!("hello, world {:}", i))
        .print()
        .run(RunMode::RealTime, RunFor::Duration(period*3)
    );
}

This output is produced:

hello, world 1
hello, world 2
hello, world 3

You can download from crates.io, read the documentation, review the benchmarks or jump straight into one of the examples. You can download the wingfoil Python module from pypi.

Get Involved!

We want to hear from you! Especially if you:

• are interested in contributing
• know of a project that wingfoil would be well-suited for
• would like to request a feature or report a bug
• have any feedback

Please email us at [email protected], submit an issue or get involved in the discussion.