4 projects for "data capture framework" with 2 filters applied:

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  • 1
    Jesse

    Jesse

    An advanced crypto trading bot written in Python

    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.
    Downloads: 5 This Week
    Last Update:
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  • 2
    Crypto Trading Bot

    Crypto Trading Bot

    Cryptocurrency trading bot in javascript for Bitfinex

    ...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.
    Downloads: 5 This Week
    Last Update:
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  • 3
    Starknet Foundry

    Starknet Foundry

    Blazing fast toolkit for developing Starknet contracts

    Starknet Foundry is a fast development toolkit for building and testing Starknet smart contracts. It is written in Rust and built around native Cairo testing and Starknet-specific execution infrastructure. The project includes snforge for contract testing and sncast for interacting with deployed Starknet contracts from the command line. It is useful for developers who need testing, deployment, transaction handling, chain data access, and contract interaction tools in one workflow. The...
    Downloads: 4 This Week
    Last Update:
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  • 4
    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. 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.
    Downloads: 0 This Week
    Last Update:
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