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Financial Data API: From Real-Time Data to Algorithmic Trading

DEV Community·San Si wu·about 1 month ago
#WuSd25JX
#ai#tutorial#python#software#trading#time
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Introduction: The Real-Time Revolution in FinTech In the financial trading domain, millisecond-level latency can mean the difference between millions of dollars in profit or loss. With the proliferation of quantitative trading and algorithmic execution, building a high-performance technical architecture from real-time quote acquisition to intelligent trade execution has become a core challenge for financial institutions and developers. Traditional HTTP polling solutions, plagued by severe resource waste and uncontrollable latency, can no longer meet the demands of modern financial scenarios. Empirical data shows that WebSocket-based quote push systems can reduce end-to-end latency to under 100ms—over 90% lower than HTTP polling—with system availability reaching 99.99% and data loss rates below 0.0001%.…

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