问拥有xirr和xnpv函数的financial python库？

EN

def xirr(transactions):
    years = [(ta[0] - transactions[0][0]).days / 365.0 for ta in transactions]
    residual = 1
    step = 0.05
    guess = 0.05
    epsilon = 0.0001
    limit = 10000
    while abs(residual) > epsilon and limit > 0:
        limit -= 1
        residual = 0.0
        for i, ta in enumerate(transactions):
            residual += ta[1] / pow(guess, years[i])
        if abs(residual) > epsilon:
            if residual > 0:
                guess += step
            else:
                guess -= step
                step /= 2.0
    return guess-1

from datetime import date
tas = [ (date(2010, 12, 29), -10000),
    (date(2012, 1, 25), 20),
    (date(2012, 3, 8), 10100)]
print xirr(tas) #0.0100612640381

import scipy.optimize

def xnpv(rate, values, dates):
    '''Equivalent of Excel's XNPV function.

    >>> from datetime import date
    >>> dates = [date(2010, 12, 29), date(2012, 1, 25), date(2012, 3, 8)]
    >>> values = [-10000, 20, 10100]
    >>> xnpv(0.1, values, dates)
    -966.4345...
    '''
    if rate <= -1.0:
        return float('inf')
    d0 = dates[0]    # or min(dates)
    return sum([ vi / (1.0 + rate)**((di - d0).days / 365.0) for vi, di in zip(values, dates)])

def xirr(values, dates):
    '''Equivalent of Excel's XIRR function.

    >>> from datetime import date
    >>> dates = [date(2010, 12, 29), date(2012, 1, 25), date(2012, 3, 8)]
    >>> values = [-10000, 20, 10100]
    >>> xirr(values, dates)
    0.0100612...
    '''
    try:
        return scipy.optimize.newton(lambda r: xnpv(r, values, dates), 0.0)
    except RuntimeError:    # Failed to converge?
        return scipy.optimize.brentq(lambda r: xnpv(r, values, dates), -1.0, 1e10)

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 tuples
xirr(zip(dates, amounts))

# feed DataFrame
import pandas as pd
xirr(pd.DataFrame({"dates": dates, "amounts": amounts}))