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"""Hello Analytics Reporting API V4."""
import argparse
from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials
import httplib2
from oauth2client import client
from oauth2client import file
from oauth2client import tools
from pprint import pprint
import time
SCOPES = ['https://www.googleapis.com/auth/analytics.readonly']
DISCOVERY_URI = ('https://analyticsreporting.googleapis.com/$discovery/rest')
KEY_FILE_LOCATION = '/auto/srg-sce-swinfra-usr/emb/users/itraviv/GoogleAnalytics/GA_ReportingAPI/My Project-da37fc42de8f.p12'
SERVICE_ACCOUNT_EMAIL = 'trex-cisco@i-jet-145907.iam.gserviceaccount.com'
VIEW_ID = '120207451'
def initialize_analyticsreporting():
"""Initializes an analyticsreporting service object.
Returns:
analytics an authorized analyticsreporting service object.
"""
credentials = ServiceAccountCredentials.from_p12_keyfile(
SERVICE_ACCOUNT_EMAIL, KEY_FILE_LOCATION, scopes=SCOPES)
http = credentials.authorize(httplib2.Http())
# Build the service object.
analytics = build('analytics', 'v4', http=http, discoveryServiceUrl=DISCOVERY_URI)
return analytics
def get_report(analytics,start_date='2016-11-06',end_date='2016-11-13'):
# Use the Analytics Service Object to query the Analytics Reporting API V4.
return analytics.reports().batchGet(
body={
'reportRequests': [
{
'viewId': VIEW_ID,
'dateRanges': [{'startDate': start_date, 'endDate': end_date}],
'metrics': [{'expression': 'ga:metric1','formattingType':'CURRENCY'},
{'expression': 'ga:metric2','formattingType':'CURRENCY'},
{'expression': 'ga:metric3','formattingType':'CURRENCY'},
{'expression': 'ga:totalEvents'}],
'dimensions': [{"name":"ga:eventAction"},{"name": "ga:dimension1"},{"name": "ga:dimension2"},{"name": "ga:dimension3"},{"name": "ga:dimension4"}]
}
]
}
).execute()
def print_response(response):
"""Parses and prints the Analytics Reporting API V4 response"""
for report in response.get('reports', []):
columnHeader = report.get('columnHeader', {})
dimensionHeaders = columnHeader.get('dimensions', [])
metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])
rows = report.get('data', {}).get('rows', [])
for row in rows:
dimensions = row.get('dimensions', [])
dateRangeValues = row.get('metrics', [])
for header, dimension in zip(dimensionHeaders, dimensions):
print header + ': ' + dimension
for i, values in enumerate(dateRangeValues):
print 'Date range (' + str(i) + ')'
for metricHeader, value in zip(metricHeaders, values.get('values')):
print metricHeader.get('name') + ': ' + value
def export_to_dict(response):
df = {'Test_name':[],'State':[],'Setup':[],'Test_type':[],'MPPS':[],'MPPS-Golden min':[],'MPPS-Golden max':[]}
for report in response.get('reports', []):
rows = report.get('data', {}).get('rows', [])
for row in rows:
dimensions = row.get('dimensions', [])
# print 'this is dimensions'
# print dimensions
df['Test_name'].append(dimensions[1])
df['State'].append(dimensions[2])
df['Setup'].append(dimensions[3])
df['Test_type'].append(dimensions[4])
dateRangeValues = row.get('metrics', [])
value = dateRangeValues[0].get('values',[])[0]
golden_min = dateRangeValues[0].get('values',[])[1]
golden_max = dateRangeValues[0].get('values',[])[2]
# print value
df['MPPS'].append(value)
df['MPPS-Golden min'].append(golden_min)
df['MPPS-Golden max'].append(golden_max)
return df
def export_to_tuples(response):
setups = set()
df = {}
for report in response.get('reports', []):
rows = report.get('data', {}).get('rows', [])
for row in rows:
data = []
dimensions = row.get('dimensions', [])
# print 'this is dimensions'
# print dimensions
data.append(dimensions[1]) #test name
data.append(dimensions[2]) # state
# data.append(dimensions[3]) # setup
data.append(dimensions[4]) # test_type
dateRangeValues = row.get('metrics', [])
value = dateRangeValues[0].get('values',[])[0] #MPPS
golden_min = dateRangeValues[0].get('values',[])[1] #golden min
golden_max = dateRangeValues[0].get('values',[])[2] #golden max
data.append(value)
data.append(golden_min)
data.append(golden_max)
if dimensions[3] in setups:
if dimensions[1] in df[dimensions[3]]:
df[dimensions[3]][dimensions[1]].append(tuple(data))
else:
df[dimensions[3]][dimensions[1]] = [tuple(data)]
else:
df[dimensions[3]] = {}
df[dimensions[3]][dimensions[1]] = [tuple(data)]
setups.add(dimensions[3])
return df, setups
def main():
analytics = initialize_analyticsreporting()
response = get_report(analytics)
print_response(response)
g_dict = export_to_dict(response)
print g_dict
pprint(g_dict)
#pprint(response)
if __name__ == '__main__':
main()
"""
response = {u'reports': [{u'columnHeader': {u'dimensions': [u'ga:dimension1',
u'ga:dimension2',
u'ga:dimension3',
u'ga:dimension4'],
u'metricHeader': {u'metricHeaderEntries': [{u'name': u'ga:metric1',
u'type': u'CURRENCY'}]}},
u'data': {u'isDataGolden': True,
u'maximums': [{u'values': [u'8532.0']}],
u'minimums': [{u'values': [u'2133.0']}],
u'rowCount': 4,
u'rows': [{u'dimensions': [u'test_name_to_date_9-10-161',
u'State_Less',
u'Setup_Name1',
u'Test_Type'],
u'metrics': [{u'values': [u'2133.0']}]},
{u'dimensions': [u'test_name_to_date_9-10-162',
u'State_Less',
u'Setup_Name2',
u'Test_Type'],
u'metrics': [{u'values': [u'4266.0']}]},
{u'dimensions': [u'test_name_to_date_9-10-163',
u'State_Less',
u'Setup_Name3',
u'Test_Type'],
u'metrics': [{u'values': [u'6399.0']}]},
{u'dimensions': [u'test_name_to_date_9-10-164',
u'State_Less',
u'Setup_Name4',
u'Test_Type'],
u'metrics': [{u'values': [u'8532.0']}]}],
u'totals': [{u'values': [u'21330.0']}]}}]}
"""
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