import pandas as pd
from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials
import datetime
import argparse
import sys


argparser = argparse.ArgumentParser(add_help=False)
argparser.add_argument('--start_date', type=str,
                      help=('Start date of the requested date range in '
                            'YYYY-MM-DD format.'))
argparser.add_argument('--end_date', type=str,
                      help=('End date of the requested date range in '
                            'YYYY-MM-DD format.'))
args = argparser.parse_args()

data = []
columns = []
start_date = args.start_date
end_date = args.end_date
SCOPES = 'https://www.googleapis.com/auth/analytics.readonly'
KEY_FILE_LOCATION = 'path to the json file'
VIEW_ID = 'past here the view id number'
body = {
   'reportRequests': [
       {
           'viewId': VIEW_ID,
           'dateRanges': [{'startDate': start_date, 'endDate': end_date}],
           'metrics': [{'expression': 'your metrics1'},{'expression': 'your metrics2'}],
           'dimensions': [{'name': 'your dimensions1'},{'name': 'your dimensions2'}]
       }]
}
metrics_len = len(body.get('reportRequests')[0].get('metrics'))
dimensions_len = len(body.get('reportRequests')[0].get('dimensions'))





def initialize_analyticsreporting():
   """Initializes an Analytics Reporting API V4 service object.

   Returns:
     An authorized Analytics Reporting API V4 service object.
   """
   credentials = ServiceAccountCredentials.from_json_keyfile_name(
       KEY_FILE_LOCATION, SCOPES)

   # Build the service object.
   analytics = build('analyticsreporting', 'v4', credentials=credentials)

   return analytics


def get_report(analytics):
   """Queries the Analytics Reporting API V4.

   Args:
     analytics: An authorized Analytics Reporting API V4 service object.
   Returns:
     The Analytics Reporting API V4 response.
   """
   return analytics.reports().batchGet(body=body).execute()


def data_extract(response):
   for report in response.get('reports'):
       columnHeader = report.get('columnHeader', {})
       dimensionHeaders = columnHeader.get('dimensions', [0])
       metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries')
       for number in range(dimensions_len):
           columns.append(dimensionHeaders[number])
       for number in range(metrics_len):
           columns.append(metricHeaders[number].get('name'))
       for report in response.get('reports'):
           for rows in report.get('data').get('rows'):
               for dimensions, metrics in zip([rows.get('dimensions')], rows.get('metrics')):
                   temp = []
                   for number in range(dimensions_len):
                       temp.append(dimensions[number])
                   for number in range(metrics_len):
                       temp.append(metrics.get('values')[number])
                   data.append(temp)


def create_csv_file(data, columns):
   df = pd.DataFrame(data=data, columns=columns)
   df.to_csv(start_date + '_' + end_date + ".csv", index=False)


def main():
   analytics = initialize_analyticsreporting()
   response = get_report(analytics)
   data_extract(response)
   create_csv_file(data, columns)


if __name__ == '__main__':
   main()