Quantlib: swap curve discount rate from spot rates

Question

I'm new to Quantlib on Python and I'd like to use the overnight swap rate from Bloomberg to derive the swap curve discount factors. I don't know which yield term structure I should specify?

I checked the QuantLib Python Cookbook and the QuantLib-Python Documentation https://quantlib-python-docs.readthedocs.io/en/latest/index.html.

Below is the code

import pandas   as pd
import numpy    as np
import QuantLib as ql

from xbbg     import blp
from datetime import date, timedelta

calendar = ql.TARGET ()

evaluationDate = date.today ()
settlementDay  = 2 

evaluationDate = ql.Date (evaluationDate.day, evaluationDate.month, evaluationDate.year)
ql.Settings.instance ().evaluationDate = evaluationDate

settlementDate = calendar.advance (evaluationDate, ql.Period (settlementDay, ql.Days))

estr  = ql.Estr ()

depositDayCounter       = ql.Actual360 ()
termStructureDayCounter = ql.Actual365Fixed ()

EUR_OVERNIGHT_RATE = 'ESTRON Index'
ON_dfObj = blp.bdp (tickers = EUR_OVERNIGHT_RATE, flds = ['PX_LAST', 'SECURITY_NAME'])

EUR_OIS_ESTR  = 'YCSW0514 Index'
dfObj = blp.bds (tickers = EUR_OIS_ESTR, flds = ['CURVE_MEMBERS'])
ESTR_dfObj = blp.bdp (tickers = dfObj ['curve_members'].tolist (), flds = ['PX_BID', 'SECURITY_NAME', 'MATURITY', 'SECURITY_TENOR_TWO'])
ESTR_dfObj ['maturity'] = pd.to_datetime (ESTR_dfObj ['maturity'])
ESTR_dfObj ['time_to_maturity'] = (ESTR_dfObj ['maturity'] - pd.to_datetime (date.today ())) / np.timedelta64 (1, 'Y')
ESTR_dfObj.sort_values (by = 'time_to_maturity', inplace = True)

helpers = [ql.DepositRateHelper (ON_dfObj ['px_last'].values [0], estr)]

zip_ = zip (ESTR_dfObj ['px_bid'].values, ESTR_dfObj ['security_tenor_two'].values)
tmp  = [ql.OISRateHelper (settlementDay, ql.Period (tenor), ql.QuoteHandle (ql.SimpleQuote (rate)), estr) for rate, tenor in zip_]
helpers += tmp

//Which structure should be used here?
ESTR_curve = ql.???? 

Any help will be most welcomed, thanks.