API Reference¶

This section provides documentation for PyQuantLib classes and functions.

Module Overview¶

PyQuantLib organizes QuantLib classes into logical groups:

Time: Date arithmetic, calendars, day counters, schedules
Core: Settings, constants, rounding, interest rates
Math: Arrays, matrices, optimization
Quotes: Market observables (spot, rates, vol)
Currencies: Currency definitions and exchange rates
Cash Flows: Coupon and cash flow implementations
Indexes: Interest rate and other indexes
Term Structures: Yield curves, volatility surfaces
Processes: Stochastic processes (Black-Scholes, Heston)
Models: Pricing models (Heston, etc.)
Methods: Monte Carlo paths, Brownian bridges, generators
Instruments: Financial instruments (options, etc.)
Pricing Engines: Analytic, Monte Carlo, finite difference
Experimental: Experimental QuantLib features (SVI, etc.)

Import Conventions¶

Most classes are available directly from the top-level namespace:

import pyquantlib as ql

# Use classes directly
date = ql.Date(15, 6, 2025)
calendar = ql.TARGET()
quote = ql.SimpleQuote(100.0)

Abstract Base Classes¶

For subclassing, import from pyquantlib.base:

from pyquantlib.base import (
    Observer,
    Observable,
    LazyObject,
    CashFlow,
    Coupon,
    PricingEngine,
    StochasticProcess,
    # ... etc
)

API Documentation¶

Note

API documentation is auto-generated from docstrings in the C++ bindings. Abstract base classes are available in pyquantlib.base.