Abstract:

This workshop explores the implementation of an event-driven asynchronous architecture for real-time financial data processing using PyTorch. Drawing from a trading system, we'll demonstrate how to effectively manage parallel streams of market data and news sentiment using asyncio, ensuring responsive model inference without blocking operations. We'll cover practical patterns for handling API timeouts, managing concurrent data sources, and maintaining system stability in a production environment where milliseconds matter.