(Python) Pulling data from UA Google Analytics with more than 100k rows into csv.

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(Python) Pulling data from UA Google Analytics with more than 100k rows into csv. Works fine for 57k

import pandas as pd
from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials
from datetime import datetime
import datetime as datetime2
from datetime import date, timedelta
import time
from dates import StartDay, StartMonth, StartYear, EndDay,EndYear,EndMonth

SCOPES = ['https://www.googleapis.com/auth/analytics.readonly']
KEY_FILE_LOCATION = './XXXXXXX.json'
VIEW_ID = 'XXXXXXX'
PAGESIZE = 100000

#StartDate = '2022-10-13'
#EndDate = '2022-10-14'

#RangeStart = datetime2.date(2022, 9, 1)
#RangeEnd = datetime2.date(2022, 9, 1)
#RangeStart = datetime2.date(2022, 1, 3) # from and inluding this date
#RangeEnd = datetime2.date(2022, 1, 4) # up to this date (not including)


RangeStart = datetime2.date(StartYear, StartMonth, StartDay) # from and inluding this date
RangeEnd = datetime2.date(EndYear, EndMonth, EndDay) # up to this date (not including)

delta = datetime2.timedelta(days=1)

#main.RangeStart

def initialize_analyticsreporting():
    credentials = ServiceAccountCredentials.from_json_keyfile_name(
        KEY_FILE_LOCATION, SCOPES)
    analytics = build('analyticsreporting', 'v4', credentials=credentials)
    return analytics


# Get one report page
def get_report(analytics, pageTokenVar):
    return analytics.reports().batchGet(
        body={

            ##################################################################################

            'reportRequests': [
                {
                    'viewId': VIEW_ID,
                    'dateRanges': [{'startDate': startingDateFeed, 'endDate': singleDateFeed}],
                    'metrics': [
                        {'expression': 'ga:users'},
                        {'expression': 'ga:newUsers'},
                        #{'expression': 'ga:pageviews'},
                        #{'expression': 'ga:bounces'},
                        #{'expression': 'ga:sessions'},
                        #{'expression': 'ga:searchUniques'},
                        #{'expression': 'ga:timeOnPage'}
                        {'expression': 'ga:searchUniques'},
                        {'expression': 'ga:bounces'},
                        {'expression': 'ga:bounceRate'},
                        {'expression': 'ga:sessionDuration'},
                        {'expression': 'ga:avgSessionDuration'},
                        {'expression': 'ga:avgTimeOnPage'},
                        {'expression': 'ga:organicSearches'}
                    ],
                    'dimensions': [
                        {'name': 'ga:userType'},
                        {'name': 'ga:sessionCount'},
                        {'name': 'ga:dateHourMinute'},
                        #{'name': 'ga:sourceMedium'},
                        #{'name': 'ga:deviceCategory'},
                        #{'name': 'ga:cityId'},
                        #{'name': 'ga:countryIsoCode'},
                        #{'name': 'ga:landingPagePath'},
                        #{'name': 'ga:pagePath'},
                        {'name': 'ga:campaign'},
                        #{'name' : 'ga:searchUniques'}
                        #{'name': 'ga:pagePathLevel1'},
                        #{'name': 'ga:pagePathLevel2'},
                        #{'name': 'ga:pagePathLevel3'},
                        #{'name': 'ga:pagePathLevel4'}
                    ],
                    'samplingLevel': 'LARGE',
                    'pageSize': PAGESIZE
                }]

            ##################################################################################

        }
    ).execute()


def handle_report(analytics, pagetoken, rows):
    response = get_report(analytics, pagetoken)

    # Header, Dimentions Headers, Metric Headers
    columnHeader = response.get("reports")[0].get('columnHeader', {})
    dimensionHeaders = columnHeader.get('dimensions', [])
    metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])

    # Pagination
    pagetoken = response.get("reports")[0].get('nextPageToken', None)

    # Rows
    rowsNew = response.get("reports")[0].get('data', {}).get('rows', [])
    rows = rows + rowsNew
    print("len(rows): " + str(len(rows)))
    print(pagetoken)
    print(response.get('nextPageToken'))

    #print(response.get('rows', []))

    # Recursivly query next page
    if pagetoken != None:
        return handle_report(analytics, pagetoken, rows)
    else:
        # nicer results
        nicerows = []
        for row in rows:
            dic = {}
            dimensions = row.get('dimensions', [])
            dateRangeValues = row.get('metrics', [])

            for header, dimension in zip(dimensionHeaders, dimensions):
                dic[header] = dimension

            for i, values in enumerate(dateRangeValues):
                for metric, value in zip(metricHeaders, values.get('values')):
                    if ',' in value or ',' in value:
                        dic[metric.get('name')] = float(value)
                    else:
                        dic[metric.get('name')] = float(value)
            nicerows.append(dic)
        return nicerows


# Start
def main():

    #while (RangeStart <= RangeEnd):
    analytics = initialize_analyticsreporting()

    global dfanalytics
    dfanalytics = []

    rows = []
    rows = handle_report(analytics, '0', rows)

    dfanalytics = pd.DataFrame(list(rows))
    YYYYmmddHHMMSS = datetime.today().strftime('%Y%m%d%H%M%S')
    dfanalytics.to_csv("./outputRAW/behaviour28/behaviour28days"+singleDateFeed+"_PULLED_ON_{}.csv".format(YYYYmmddHHMMSS))
    dfanalytics.to_csv("./outputRAW/behaviour28/backupCopy/behaviour28days" + singleDateFeed + "_PULLED_ON_{}.csv".format(YYYYmmddHHMMSS))

        #RangeStart += delta



#if __name__ == '__main__':
#    main()

def daterange(RangeStart,RangeEnd):

    for n in range(int((RangeEnd - RangeStart).days)):
        yield RangeStart + timedelta(n)

for singleDate in daterange(RangeStart,RangeEnd):
    #print(singleDate.strftime("%Y-%m-%d"))
    singleDateMinusSeven = singleDate + timedelta(days=-7)

    #print(singleDate + timedelta(days=-7))
    singleDateFeed = singleDate.strftime("%Y-%m-%d")
    startingDateFeed = singleDateMinusSeven.strftime("%Y-%m-%d")
    #endingDateFeed = startingDateFeed + timedelta(days=-7)
    #endingDateFeed = singleDate.strftime("%Y-%m-%d") + timedelta(days=-7)
    main()

    print(startingDateFeed)
    print(singleDateFeed)
    #print(endingDateFeed)
    #time.sleep(3) #Sleep for a number of secoonds before running the next day - to decrease number of api calls


#dateTest = datetime2.date(2022, 2, 1)
#print (dateTest, end="\n")

Help!

My code just keeps outputting: len(rows): 100000

100000

None

len(rows): 200000

100000

None

len(rows): 300000

100000

None

len(rows): 400000

100000

None

len(rows): 500000

100000

None

looping forever rather than pulling the next page.

I appreciate I'm not asking very well, but what basic thing have I missed to make it pull the next page and append?

 #Recursivly query next page
    if pagetoken != None:
        return handle_report(analytics, pagetoken, rows)

It's this bit that doesn't seem to work This runs fine when there are 57k rows, but when I expand the range, the above happens. Many thanks in advance, and thank you for your patience!