An open-source Python library, defeatbeta-api, offers an alternative to traditional market data APIs like yfinance. It addresses the need for reliable, high-volume historical financial data by sourcing it from Hugging Face's yahoo-finance-data dataset, thereby bypassing direct web scraping and its associated rate limits. The project targets developers and data analysts who require efficient data retrieval and analysis capabilities, providing extended financial metrics, earnings call transcripts, and news data. Its core advantage lies in its robust infrastructure and performance optimizations, making it suitable for bulk data analysis.

How It Works

The API leverages Hugging Face's infrastructure for reliable data access, eliminating rate limits and throttling issues common with other services. Data is stored in the efficient Parquet format and queried using DuckDB, an in-process OLAP engine. The cache_httpfs extension enables high-performance local disk caching, resulting in sub-second query latency for historical data. Additionally, the library incorporates Large Language Models (LLMs) to facilitate advanced analysis, such as extracting key financial data from earnings call transcripts and analyzing financial metric changes and forecasts.

Quick Start & Requirements

• Installation: Install via pip: pip install defeatbeta-api
• Prerequisites: Python. Windows users must use WSL or Docker due to cache_httpfs incompatibility on native Windows.
• Documentation: Usage examples are provided within the README.

Highlighted Details

• No Rate Limits: Data access is unthrottled, relying on Hugging Face's infrastructure.
• Performance Optimized: Employs DuckDB and cache_httpfs for fast data querying and local caching.
• Comprehensive Data: Includes standard market data plus extended financial metrics (e.g., TTM EPS, Market Cap), earnings call transcripts, and stock news.
• LLM Integration: Features for AI-driven analysis of financial documents and metrics.

Maintenance & Community

The provided README does not contain specific details regarding maintainers, community channels (e.g., Discord, Slack), or a public roadmap.

Licensing & Compatibility

The license under which defeatbeta-api is distributed is not specified in the README. Consequently, its compatibility for commercial use or integration into closed-source projects cannot be determined.

Limitations & Caveats

The primary limitation is that the data is not real-time; it is updated periodically, typically weekly, making it unsuitable for applications requiring live market feeds. Windows users face installation challenges due to the cache_httpfs dependency not being natively supported.