How to use the quantlib.util.converter.pydate_to_qldate function in QuantLib

def _cfamounts(coupon_rate, pricing_date, maturity_date,
              period, basis):
    """
    cash flow schedule
    """

    _period = str_to_frequency(period)

    evaluation_date = pydate_to_qldate(pricing_date)

    settings = Settings()
    settings.evaluation_date = evaluation_date

    calendar = TARGET()
    termination_date = pydate_to_qldate(maturity_date)

    # effective date must be before settlement date, but do not
    # care about exact issuance date of bond

    effective_date = Date(termination_date.day, termination_date.month,
                          evaluation_date.year)
    effective_date = calendar.advance(
        effective_date, -1, Years, convention=Unadjusted)

    face_amount = 100.0
    redemption = 100.0

    fixed_bond_schedule = Schedule(
        effective_date,
        termination_date,
        Period(_period),

def _bndprice(bond_yield, coupon_rate, pricing_date, maturity_date,
              period, basis, compounding_frequency):
    """
    Clean price and accrued interest of a bond
    """

    _period = str_to_frequency(period)

    evaluation_date = pydate_to_qldate(pricing_date)

    settings = Settings()
    settings.evaluation_date = evaluation_date

    calendar = TARGET()
    termination_date = pydate_to_qldate(maturity_date)

    # effective date must be before settlement date, but do not
    # care about exact issuance date of bond

    effective_date = Date(termination_date.day, termination_date.month,
                          evaluation_date.year)
    effective_date = calendar.advance(
        effective_date, -1, Years, convention=Unadjusted)

    settlement_date = calendar.advance(
            evaluation_date, 2, Days, convention=ModifiedFollowing)

    face_amount = 100.0
    redemption = 100.0

    fixed_bond_schedule = Schedule(

def heston_helpers(df_option, dtTrade=None, df_rates=None, ival=None):
    """
    Create array of heston options helpers
    """

    if dtTrade is None:
        dtTrade = df_option['dtTrade'][0]
    DtSettlement = pydate_to_qldate(dtTrade)

    settings = Settings()
    settings.evaluation_date = DtSettlement

    calendar = TARGET()

    if df_rates is None:
        df_tmp = DataFrame.filter(df_option, items=['dtExpiry', 'IR', 'IDIV'])
        grouped = df_tmp.groupby('dtExpiry')
        df_rates = grouped.agg(lambda x: x[0])

    # convert data frame (date/value) into zero curve
    # expect the index to be a date, and 1 column of values

    risk_free_ts = df_to_zero_curve(df_rates['R'], dtTrade)
    dividend_ts = df_to_zero_curve(df_rates['D'], dtTrade)

ts = make_term_structure(rates, pricing_date)

    cnt = DayCounter.from_name(basis)

    if maturity_dates is None:
        # schedule of maturity dates from settlement date to last date on
        # the term structure

        s = Schedule(effective_date=ts.reference_date,
                     termination_date=ts.max_date,
                     tenor=Period(1, Months),
                     calendar=TARGET())
        maturity_dates = [qldate_to_pydate(dt) for dt in s.dates()]

    cp_freq = Compounding[compounding_freq]
    zc = [ts.zero_rate(pydate_to_qldate(dt),
                       day_counter=cnt,
                       compounding=cp_freq).rate for dt in maturity_dates]

    return (maturity_dates, zc)

def make_rate_helper(label, rate, dt_obs, currency='USD'):
    """
    Wrapper for deposit and swaps rate helpers makers
    For Swaps: assume USD swap fixed rates vs. 6M Libor
    TODO: make this more general
    """

    if(currency.upper() != 'USD'):
        raise Exception("Only supported currency is USD.")

    rate_type, tenor, period = _parse_rate_label(label)

    if not isinstance(dt_obs, Date):
        dt_obs = pydate_to_qldate(dt_obs)

    settings = Settings()
    calendar = JointCalendar(UnitedStates(), UnitedKingdom())
    # must be a business day
    eval_date = calendar.adjust(dt_obs)
    settings.evaluation_date = eval_date
    settlement_days = 2
    settlement_date = calendar.advance(eval_date, settlement_days, Days)
    # must be a business day
    settlement_date = calendar.adjust(settlement_date)
    end_of_month = True

    if((rate_type == 'SWAP') & (period == 'Y')):
        liborIndex = Libor(
            'USD Libor', Period(6, Months), settlement_days,
            USDCurrency(), calendar, Actual360()

def _bndprice(bond_yield, coupon_rate, pricing_date, maturity_date,
              period, basis, compounding_frequency):
    """
    Clean price and accrued interest of a bond
    """

    _period = str_to_frequency(period)

    evaluation_date = pydate_to_qldate(pricing_date)

    settings = Settings()
    settings.evaluation_date = evaluation_date

    calendar = TARGET()
    termination_date = pydate_to_qldate(maturity_date)

    # effective date must be before settlement date, but do not
    # care about exact issuance date of bond

    effective_date = Date(termination_date.day, termination_date.month,
                          evaluation_date.year)
    effective_date = calendar.advance(
        effective_date, -1, Years, convention=Unadjusted)

    settlement_date = calendar.advance(

def _set_evaluation_date(self, dt_obs):

        if not isinstance(dt_obs, Date):
            dt_obs = pydate_to_qldate(dt_obs)

        settings = Settings()
        calendar = JointCalendar(UnitedStates(), UnitedKingdom())
        # must be a business day
        eval_date = calendar.adjust(dt_obs)
        settings.evaluation_date = eval_date
        self._eval_date = eval_date
        return eval_date