Production-grade quantitative finance library in pure Python.
Built for systematic traders who value correctness over marketing.
>>> from pyfundlib.portfolio import RiskParityAllocator
>>> from pyfundlib.data import DataFetcher
>>> prices = DataFetcher.get_prices(
... ["SPY", "TLT", "GLD", "DBC", "VNQ"], period="15y"
... )
>>> allocator = RiskParityAllocator(method="erc")
>>> weights = allocator.optimize(prices)
>>> print(weights)
{'SPY': 0.28, 'TLT': 0.41, 'GLD': 0.14, 'DBC': 0.09, 'VNQ': 0.08}
# True risk parity. One import. No configuration files.No "AI-powered alpha". Just tools used by systematic desks every day.
Works in scripts, Docker, cloud functions, and production servers.
Every calculation is vectorized, readable, and testable — no black boxes.
MIT license. Fork it. Deploy it. Own your IP.
No sign-up. No waitlist. Just install and run.