Skip to main content

Python bindings for a tiny library for quantitative finance (powered by Rust)

Project description

quantrs (python bindings)

tests MIT/Apache 2.0 licensed Crate docs.rs codecov-quantrs Crates.io MSRV Crates.io downloads

Quantrs is a tiny quantitative finance library for Rust. These are the Python bindings for it. It is designed to be as intuitive and easy to use as possible so that you can work with derivatives without the need to write complex code or have a PhD in reading QuantLib documentation. The library is still in the early stages of development and many features are not yet implemented.

Please check out the documentation for the original Rust crate here and at github.com/carlobortolan/quantrs.

Currently, the bindings only cover the FI module.

Installation

pip install quantrs

Usage

Day Count Conventions

import quantrs

# Create day count convention
day_count = quantrs.DayCount("ACT/365F")

# Calculate year fraction between dates
year_frac = day_count.year_fraction("2025-01-01", "2025-07-01")
print(f"Year fraction: {year_frac}")

# Calculate day count
days = day_count.day_count("2025-01-01", "2025-07-01")
print(f"Day count: {days}")

# Convenience function
year_frac = quantrs.calculate_year_fraction("2025-01-01", "2025-07-01", "ACT/365F")

Bond Pricing

import quantrs

# Create zero-coupon bond
bond = quantrs.ZeroCouponBond(face_value=1000.0, maturity="2030-12-31")

# Calculate bond price
price = bond.price(
    settlement="2025-06-19",
    ytm=0.04,  # 4% yield to maturity
    day_count=quantrs.DayCount("ACT/365F")
)
print(f"Bond price: ${price:.2f}")

Benchmarks

Compared to other popular and well-maintained (i.e., actively developed, well-documented, and feature-rich) options pricing libraries, quantrs (Rust) competes well in terms of performance: E.g., for pricing a European call with the Merton Black-Scholes model, quantrs is:

  • 87x faster than py_vollib
  • 29x faster than QuantLib (python bindings)
  • 15x faster than RustQuant
  • 3x faster than Q-Fin
  • 1.7x slower than QuantLib (cpp)
Library Mean Execution Time (μs) Median Execution Time (μs) Standard Deviation (μs) Operations / Second (OPS)
quantrs 0.0971 0.0970 0.0007 10,142,000
quantrs (py) TODO TODO TODO TODO
py_vollib 8.5341 8.5210 0.8129 117,176
QuantLib (py) 2.8551 2.8630 0.9391 350,250
RustQuant 1.4777 1.4750 0.0237 676,727
Q-Fin 0.2900 0.2906 0.0448 3,447,870
QuantLib (cpp) 0.0556 n.a. n.a. 17,958,600

You can find the benchmarks at quantrs.pages.dev/report.

Published benchmarks have been measured on a selfhosted VM with 32 GB RAM, AMD Ryzen 7 PRO 6850U @ 2.70GHz, and Manjaro Linux x86_64

Contributing

If you find any bugs or have suggestions for improvement, please open a new issue or PR. See OUTLOOK.md for a list of planned features and improvements.

You can generate and test the Python bindings with:

python -m venv .venv
source .venv/bin/activate
pip install maturin
# Build and install your package in editable mode
maturin develop --features python
# Run tests
pytest bindings/python/tests

Disclaimer

This library is not intended for professional use. It is a hobby project and should be treated as such.

The python bindings are automatically generated using PyO3 and may not cover all features of the Rust library.

License

This project is licensed under either of:

at your option.


© Carlo Bortolan

Carlo Bortolan  ·  GitHub carlobortolan  ·  contact via carlobortolan@gmail.com

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantrs-0.0.1.tar.gz (108.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantrs-0.0.1-cp313-cp313-manylinux_2_34_x86_64.whl (316.6 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

File details

Details for the file quantrs-0.0.1.tar.gz.

File metadata

  • Download URL: quantrs-0.0.1.tar.gz
  • Upload date:
  • Size: 108.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/1.9.4

File hashes

Hashes for quantrs-0.0.1.tar.gz
Algorithm Hash digest
SHA256 9bdbf82ca027af0463cf137835e164402e6d537c9f270e4dc7293bd00e9ad004
MD5 ab754b5d5c03f808215eabebc1e6fcb1
BLAKE2b-256 dada888a6021938e312c2856dd256bd6a9b0734ce69e0d001db23e29469d3277

See more details on using hashes here.

File details

Details for the file quantrs-0.0.1-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for quantrs-0.0.1-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 cfefa98532987afec1885c021b98b23bbaf0fddada1f9825eaa358a5ae7366d1
MD5 468263cf7f1b3434781467196b93e950
BLAKE2b-256 ab7003d53803369248062042b1bb4027c16fba5bb5c997825dd6d4914e2ab7da

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page