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.

Checkout the Wingfoil project page for more information.

• Fast: Ultra-low latency and high throughput with an efficient 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 a Python package, with plans to add WASM/JavaScript/TypeScript support.
• Backtesting: Replay historical data to backtest and optimise strategies.

The Wingfoil Python module is currently available as a beta release.

pip install wingfoil

This python code:

#!/usr/bin/env python3

from wingfoil import ticker

period = 1.0 # seconds
duration = 4.0 # seconds
stream = (
    ticker(period)
        .count()
        .logged("hello, world")
)
stream.run(realtime=True, duration=duration)

Produces this output:

[2025-11-02T18:42:18Z INFO  wingfoil] 0.000_092 hello, world 1
[2025-11-02T18:42:19Z INFO  wingfoil] 1.008_038 hello, world 2
[2025-11-02T18:42:20Z INFO  wingfoil] 2.012_219 hello, world 3

You can follow these instructions to build from source.

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
• Have any feedback

Please email us at hello@wingfoil.io or get involved in the wingfoil discussion. Take a look at the issues for ideas on ways to contribute.