pyxirr 0.5.0

Rust-powered collection of financial functions.

PyXIRR

Rust-powered collection of financial functions.

Features:

• correct
• blazingly fast
• works with iterators
• works with unordered input
• no external dependencies

Installation

pip install pyxirr

Benchmarks

Rust implementation has been tested against existing xirr package (uses scipy.optimize under the hood) and the implementation from the Stack Overflow (pure python).

PyXIRR is ~10-20x faster than other solutions!

Powered by github-action-benchmark.

Live benchmarks are hosted on Github Pages.

Examples

from datetime import date
from pyxirr import xirr

dates = [date(2020, 1, 1), date(2021, 1, 1), date(2022, 1, 1)]
amounts = [-1000, 1000, 1000]

# feed columnar data
xirr(dates, amounts)
# feed iterators
xirr(iter(dates), (x for x in amounts))
# feed an iterable of tuples
xirr(zip(dates, amounts))
# feed a dictionary
xirr(dict(zip(dates, amounts)))

Numpy and Pandas support

import numpy as np
import pandas as pd

# feed numpy array
xirr(np.array([dates, amounts]))
xirr(np.array(dates), np.array(amounts))
# feed DataFrame (columns names doesn't matter; ordering matters)
xirr(pd.DataFrame({"a": dates, "b": amounts}))

API reference

Let's define type annotations:

# `None` if the calculation fails to converge or result is NAN.
# could return `inf` or `-inf`
FloatOrNone = Optional[float]

DateLike = Union[datetime.date, datetime.datetime, numpy.datetime64, pandas.Timestamp]
Rate = float  # rate as decimal, not percentage, normally between [-1, 1]
Guess = Optional[Rate]
Amount = Union[int, float, Decimal]
Payment = Tuple[DateLike, Amount]

DateLikeArray = Iterable[DateLike]
AmountArray = Iterable[Amount]
CashFlowTable = Iterable[Payment]
CashFlowDict = Dict[DateLike, Amount]

Exceptions

• InvalidPaymentsError. Occurs if either:
  • the amounts and dates arrays (AmountArray, DateLikeArray) are of different lengths
  • the given arrays do not contain at least one negative and at least one positive value

XIRR

# raises: InvalidPaymentsError
def xirr(
    dates: Union[CashFlowTable, CashFlowDict, DateLikeArray],
    amounts: Optional[AmountArray] = None,
    guess: Guess = None,
) -> FloatOrNone

XNPV

# raises: InvalidPaymentsError
def xnpv(
    rate: Rate,
    dates: Union[CashFlowTable, CashFlowDict, DateLikeArray],
    amounts: Optional[AmountArray] = None,
) -> FloatOrNone

IRR

Compute the Internal Rate of Return (IRR)

# raises: InvalidPaymentsError
def irr(amounts: AmountArray, guess: Guess = None) -> FloatOrNone

NPV

Compute the Net Present Value.

# raises: InvalidPaymentsError
def npv(rate: Rate, amounts: AmountArray) -> FloatOrNone

FV

Compute the future value.

def fv(
    rate: Rate, # Rate of interest per period
    nper: int, # Number of compounding periods
    pmt: Amount, # Payment
    pv: Amount, # Present value
    pmt_at_begining: bool = False  # When payments are due
) -> FloatOrNone

PV

Compute the present value.

def pv(
    rate: Rate, # Rate of interest per period
    nper: int, # Number of compounding periods
    pmt: Amount, # Payment
    fv: Amount = 0, # Future value
    pmt_at_begining: bool = False  # When payments are due
) -> FloatOrNone

MIRR

Modified internal rate of return.

def pv(
    values: AmountArray, # Cash flows. Must contain at least one positive and one negative value or nan is returned.
    finance_rate: Rate, # Interest rate paid on the cash flows
    reinvest_rate: Rate, # Interest rate received on the cash flows upon reinvestment
) -> FloatOrNone

Roadmap

• NumPy support
• XIRR
• XNPV
• NPV
• IRR
• FV
• PV
• MIRR
• Improve docs, add more tests
• other functions from numpy-financial

Development

Running tests with pyo3 is a bit tricky. In short, you need to compile your tests without extension-module feature to avoid linking errors. See the following issues for the details: #341, #771.

If you are using pyenv, make sure you have the shared library installed (check for ${PYENV_ROOT}/versions/<version>/lib/libpython3.so file).

$ PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install <version>

Install dev-requirements

$ pip install -r dev-requirements.txt

Building

$ maturin develop

Testing

$ LD_LIBRARY_PATH=${PYENV_ROOT}/versions/3.8.6/lib cargo test --no-default-features

Building and distribution

This library uses maturin to build and distribute python wheels.

$ docker run --rm -v $(pwd):/io konstin2/maturin build --release --manylinux 2010 --strip
$ maturin upload target/wheels/pyxirr-${version}*