Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
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Scalable, event-driven, deep-learning-friendly backtesting library
Python live trade execution library with zipline interface.
A Steam trading library for python 3
Oracle3: open-source trading engine and MCP server for prediction markets. Finds fee-adjusted no-arbitrage violations across related event contracts and trades them live on Kalshi, Polymarket and Solana, or on paper, under pre-trade risk limits. 13 MCP tools, JSON CLI, agent skills, 600+ tests.
Translated[Maintenance stopped] New version updates have been moved to the correspondingly named project under the IBATS project group. Connects to the Huobi exchange to get real-time and historical Huobi market data, saves it to a MySQL database and broadcasts it via Redis, for the ABAT trading platform to use for strategy backtesting, analysis, and trading.
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.