qf-lib

QF-Lib is a Python library providing tools for quantitative finance, with a major focus on backtesting investment strategies. Its event-driven backtester simulates market events such as daily openings and closings and is designed to evaluate custom strategies across Crypto, Stocks, and Futures. The library supports flexible data sourcing through providers including Bloomberg, Quandl, Haver Analytics, and Portara, with optional dependencies documented for individual providers. It includes tools intended to prevent look-ahead bias in backtesting, data containers that extend pandas Series and DataFrame functionality, and configurable settings for extending existing functionality. QF-Lib can generate informative study summaries using available document templates. PDF export uses WeasyPrint, which may require additional platform-specific dependencies. The package can be installed from PyPI with pip or directly from source using setup.py. Documentation covers installation, configuration, and API usage, while the project accepts bug reports, fixes, documentation improvements, new features, and other contributions.