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Pythonic event-driven system for backtesting algorithmic trading strategies.

The open-source core for institutional-grade financial intelligence and AI-driven quantitative research.
The OpenBB SDK (now evolved into the OpenBB Platform) serves as the industry's most comprehensive open-source framework for financial data access. Built for data scientists, quantitative analysts, and AI developers, it provides a unified Python interface to over 100 diverse data providers including Bloomberg, Refinitiv, Tiingo, and Polygon.io. By 2026, the architecture has transitioned into a highly modular 'provider-agnostic' system, enabling seamless switching between data sources without refactoring code. The platform utilizes a standardized data model that normalizes disparate schemas from various vendors into a consistent structure, making it the premier choice for feeding financial context into Large Language Models (LLMs) and autonomous AI agents. Its technical architecture supports local execution, containerized deployment via Docker, and integration into enterprise pipelines through a REST API layer. As financial institutions move toward 'sovereign data' models, OpenBB's open-source nature allows for complete transparency in calculation methodologies and data lineage, bridging the gap between proprietary terminal silos and modern cloud-native quantitative workflows.
The OpenBB SDK (now evolved into the OpenBB Platform) serves as the industry's most comprehensive open-source framework for financial data access.
Explore all tools that specialize in market data aggregation. This domain focus ensures OpenBB SDK delivers optimized results for this specific requirement.
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Explore all tools that specialize in quantitative backtesting. This domain focus ensures OpenBB SDK delivers optimized results for this specific requirement.
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Pythonic event-driven system for backtesting algorithmic trading strategies.

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