All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
0.1.0 - 2025-01-15
- Comprehensive Financial Data Library with standardized API across multiple providers
- Universal Parameters: Same interface works with Yahoo Finance, Alpha Vantage, Binance, CoinGecko, Twelve Data
- Identical Output Schemas: All providers return exact 12-column DataFrames for seamless analysis
- Mathematical Indicators with Python-validated accuracy:
- RSI (Relative Strength Index) - 100% accuracy vs Python
- DEMA (Double Exponential Moving Average) - 99.96% accuracy
- HMA (Hull Moving Average) - 100% accuracy vs Python
- KAMA (Kaufman Adaptive Moving Average) - 100% accuracy vs Python
- TEMA (Triple Exponential Moving Average) - 99.9988% accuracy
- WMA (Weighted Moving Average) - 100% accuracy vs Python
- Cross-Language Validation Framework: Comprehensive Python validation tests ensuring mathematical accuracy
- Multi-Provider Support:
- Yahoo Finance (free, no API key required)
- Alpha Vantage (premium, API key required)
- Binance (free crypto data, no API key required)
- CoinGecko (free crypto data, no API key required)
- Twelve Data (premium, API key required)
- Advanced Rate Limiting: ETS and Redis backends with provider-specific patterns
- Zero External HTTP Dependencies: Uses built-in Erlang
:httpcfor maximum reliability - Comprehensive Test Suite: 335 tests with 0 failures, including integration tests
- Production-Ready Architecture: Optimized for high-throughput financial analysis
- Explorer DataFrame First: All data returns as Explorer DataFrames for immediate analysis
- Standardization Engine: Automatic parameter translation and schema normalization
- Flexible API Keys: Pass inline or configure globally
- Streaming Support: Handle large datasets efficiently
- Type Safety: Full Dialyzer type specifications
- Error Handling: Comprehensive error types and graceful degradation
- Complete API documentation with examples
- Troubleshooting guide for common API issues
- Standardization guide explaining universal parameters
- Testing guide with both mocked and integration tests
- Livebook-ready examples for data science workflows
- Creative Commons Attribution-NonCommercial 4.0 International License
- Free for personal, educational, research, and non-profit use
- Commercial licensing available separately
- Protects against unauthorized commercial exploitation while ensuring community access