Showing 3 open source projects for "environment-modules"

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  • 1
    Hummingbot

    Hummingbot

    Build trading bots that run on any exchange or blockchain

    Hummingbot is an open-source project that integrates cryptocurrency trading on both centralized exchanges and decentralized protocols. It allows users to run a client that executes customized, automated trading strategies for cryptocurrencies. Hummingbot is software that helps you build and run automated trading strategies or bots. Its codebase is free and publicly available on Github under the Apache 2.0 open source license. Hummingbot Foundation is a not-for-profit foundation that...
    Downloads: 2 This Week
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  • 2
    Cortex AI Infrastructure

    Cortex AI Infrastructure

    Open-source multi-chain data routing & low-latency scanning framework.

    Cortex AI Infrastructure is an institutional-grade open-source crypto arbitrage bot framework for low-latency multi-chain data routing across TON, Solana, and EVM layers. The engine optimizes high-frequency distributed pipelines to eliminate execution lag and network jitter. Core Technical Modules: 1. Cross-Exchange Telemetry Scanner: Monitors order book depth and spreads across 18 venues concurrently (Binance, ByBit, OKX, HTX) with zero thread-locking. 2. Polymarket Analytics Engine: Tracks open prediction markets and volume anomalies using high-throughput CLOB data streams. 3. Solana & TON Node Routing: An asynchronous broker client optimized for private RPC nodes, tailored for high-frequency solana trading bot execution loops and automated TON/USDT spread environments (sub-28ms processing). 4. ...
    Downloads: 10 This Week
    Last Update:
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  • 3
    Catalyst

    Catalyst

    An Algorithmic Trading Library for Crypto-Assets in Python

    Catalyst is an algorithmic trading library for crypto-assets written in Python, originally developed to let quants and developers design, backtest, and deploy trading strategies in a unified environment. It builds on top of Zipline, extending that ecosystem to support crypto exchanges and high-resolution historical data (daily and minute bars). Users can express strategies in Python, run backtests against historical price data, and analyze performance through built-in metrics and analytics to evaluate profitability, risk, and behavior under different market conditions. ...
    Downloads: 0 This Week
    Last Update:
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