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OpenBB

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Basic Information

OpenBB is an open source financial data platform that provides programmatic access to market and economic data for analysts, developers, and AI integrations. The repository offers a Python library and a command-line interface to query equities, options, crypto, forex, macroeconomic and fixed income datasets, and it can be installed via PyPI. It includes an example usage showing how to fetch historical equity prices and convert results to a dataframe. The project also exposes a local API server that runs with FastAPI and Uvicorn, enabling integration with the enterprise OpenBB Workspace and third-party extensions. The codebase is maintained under AGPLv3 and is designed to be extensible with data backends and agent integrations referenced in companion repositories.

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49220
App URL
https://github.com/OpenBB-finance/OpenBB
Github Repository
https://github.com/OpenBB-finance/OpenBB/blob/main/README.md

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App Details

Features
The repo bundles a Python package for direct data access, a CLI package for terminal workflows, and an API server that can be launched locally using the openbb-api command. It supports multiple asset classes including equities, options, crypto, forex, macro and fixed income. Features include a unified programmatic interface that returns data objects convertible to dataframes, installation via pip for both core and all-dependencies builds, and examples for getting started. The README highlights integration points for an enterprise workspace, separate repositories for backends and AI agents, developer documentation, community contribution guidance, and distribution on PyPI.
Use Cases
OpenBB helps analysts, developers and organizations centralize financial data access and build analytics or AI-driven workflows quickly. Users can fetch multi-asset time series and other market data in Python or via the CLI, run a local API to serve that data to a visual workspace, and connect third-party data backends or agent integrations to extend functionality. The platform lowers integration overhead by providing a common interface to many vendors, supports prototyping of trading or research workflows, and fosters collaboration through documentation and community contribution channels. Licensing and a cautionary disclaimer are included to inform users about data accuracy and trading risks.

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