Search Results for "data capture framework"

Jesse is an open-source AI agent framework designed to help developers build and orchestrate intelligent workflows that combine large language models (LLMs) with external tools, automation logic, and real-world actions. It acts as an agent manager where you can define tasks, contexts, and tool integrations so that AI reasoning is reliably connected to deterministic procedures like API calls, data retrieval, and task execution.

...It aims to go beyond basic buy-and-sell signal bots by supporting more practical trading mechanics such as stop-loss or stop-limit-style behavior where available. The project is explicitly not production-ready, so it should be treated as an educational and experimental trading framework rather than a safe financial automation system. It is useful for developers learning algorithmic trading architecture, exchange APIs, market data handling, and strategy testing.

A fast cryptocurrency trading bot framework implemented in Go. Ninjabot permits users to create and test custom strategies for spot markets. Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct...

...The framework is non-custodial,

Jesse Bot: Advanced AI-Powered Python Best Crypto Trading Bot & Framework (2026) Jesse Bot — free open-source Python crypto trading bot & robust framework for cryptocurrency markets. Build, backtest, AI-optimize, and execute precise automated strategies with zero look-ahead bias. Use JesseGPT — built-in AI assistant — to write, debug, and refine strategies effortlessly, even as a beginner. Secure live trading on Binance, Bybit & major exchanges, full risk management, leverage/futures...

This project provides a framework for scanning and executing various trading strategies on the TON blockchain ecosystem. It retrieves market data from multiple decentralized exchanges (DEXs) and applies a range of trading strategies to identify potential opportunities. This open-source, AI-powered bot is a versatile tool designed to run seamlessly on both Windows and macOS platforms.

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. Beyond backtesting, Catalyst was designed to support live trading on multiple crypto exchanges such as Binance, Bitfinex, Bittrex, and Poloniex, bridging simulation and production within the same framework.