get_timeseries - Historical fields inconsistencies (interval = TAS)

Hello all,

I have the following code returning either 27 or 52 fields depending on the end date.

(the difference lies in line 2, startdate definition)

Scenario 1: 52 fields returned

endDate = datetime.datetime(year=2020,month=3,day=10)
startDate=datetime.datetime(year=2020,month=3,day=4)

tickreq = ek.get_timeseries('BNPP.PA', fields='*', start_date=startDate, end_date=endDate, interval='tas', calendar=None, corax=None, normalize=False, raw_output=True, debug=False)
#--------------Fields and data extraction from raw data
lfields=[]
for i in tickreq['timeseriesData'][0]['fields']:
    lfields.append(i['name'])
tickdf=pd.DataFrame(tickreq['timeseriesData'][0]['dataPoints'], columns =lfields)

Scenario 2: 27 fields returned

endDate = datetime.datetime(year=2020,month=3,day=10)
startDate=datetime.datetime(year=2020,month=3,day=8)

tickreq = ek.get_timeseries('BNPP.PA', fields='*', start_date=startDate, end_date=endDate, interval='tas', calendar=None, corax=None, normalize=False, raw_output=True, debug=False)
#--------------Fields and data extraction from raw data
lfields=[]
for i in tickreq['timeseriesData'][0]['fields']:
    lfields.append(i['name'])
tickdf=pd.DataFrame(tickreq['timeseriesData'][0]['dataPoints'], columns =lfields)

I understand 08032020 is a sunday, so no trades to be found in theory, but I would still expect to get the same data structure, as I'am asking for all fields.

Is this normal behaviour?

Thank you for your help