def report_main(config,
task,
name,
dateRange,
schedule,
advertiser,
campaign,
shadow=True):
if config.verbose:
print('DYNAMIC COSTS MAIN:', name)
# base report schema
schema = {
'kind': 'dfareporting#report',
'type': 'STANDARD',
'name': 'Dynamic Costs %s - Main Advertiser ( StarThinker )' % name,
'schedule': schedule,
'criteria': {
'dateRange':
dateRange,
'dimensionFilters': [{
'kind': 'dfareporting#dimensionValue',
'dimensionName': 'dfa:advertiser',
'id': advertiser,
'matchType': 'EXACT'
}, {
'kind': 'dfareporting#dimensionValue',
'dimensionName': 'dfa:campaign',
'id': campaign,
'matchType': 'EXACT'
}],
'dimensions': [{
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placement'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placementId'
}],
'metricNames': ['dfa:impressions', 'dfa:clicks']
}
}
# if not using shadow advertiser, pull DBM cost here
if not shadow:
schema['criteria']['metricNames'].append('dfa:dbmCost')
# create the report if it does not exist
report = report_build(config, task['auth'], task['account'], schema)
# fetch report file if it exists ( timeout = 0 means grab most reent ready )
filename, filedata = report_file(config, task['auth'], task['account'],
report['id'], None, 60, DCM_CHUNK_SIZE)
# write report to a table ( avoid collisions as best as possible )
table_name = 'Dynamic_Costs_%s_Main_Advertiser' % name
write_report(config, task, filedata, task['out']['dataset'], table_name)
return table_name
def report_shadow(config, task, name, dateRange, schedule, advertiser,
campaign):
if config.verbose:
print('DYNAMIC COSTS SHADOW:', name)
# create the report if it does not exist
report = report_build(
config, task['auth'], task['account'], {
'kind': 'dfareporting#report',
'type': 'STANDARD',
'name':
'Dynamic Costs %s - Shadow Advertiser ( StarThinker )' % name,
'schedule': schedule,
'criteria': {
'dateRange':
dateRange,
'dimensionFilters': [{
'dimensionName': 'dfa:advertiser',
'id': advertiser,
'kind': 'dfareporting#dimensionValue',
'matchType': 'EXACT'
}, {
'dimensionName': 'dfa:campaign',
'id': campaign,
'kind': 'dfareporting#dimensionValue',
'matchType': 'EXACT'
}],
'dimensions': [{
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placement'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placementId'
}],
'metricNames': ['dfa:dbmCost']
}
})
# fetch report file if it exists ( timeout = 0 means grab most reent ready )
filename, filedata = report_file(config, task['auth'], task['account'],
report['id'])
# write report to a table ( avoid collisions as best as possible )
table_name = 'Dynamic_Costs_%s_Shadow_Advertiser' % name
write_report(config, task, filedata, task['out']['dataset'], table_name)
return table_name
def dcm_replicate_create(config, task, account, advertisers, name, template):
print('DCM REPLICATE CREATE', name)
# check if report is to be deleted
if task['report'].get('delete', False):
report_delete(config, task['auth'], account, None, name)
# add account and advertiser filters ( return new disctionary)
body = report_filter(
config, task['auth'], template, {
'accountId': {
'values': account
},
'dfa:advertiser': {
'values': advertisers
}
})
body['name'] = name
#print('BODY', body)
# create and run the report if it does not exist
report = report_build(config, task['auth'], account, body)
def floodlight_report(config, task: dict, floodlight_id: int) -> int:
""" Create a report for a specific floodlight if it does not exist.
Args:
floodlight_id - the floodlight being monitored
Returns:
The id of the created report.
"""
account_id, subaccount_id = parse_account(config, task['auth'],
task['account'])
name = 'Floodlight Monitor %s %s ( StarThinker )' % (account_id,
floodlight_id)
if config.verbose:
print('FLOODLIGHT MONITOR REPORT: ', name)
# create report if it does not exists
report = report_build(
config, task['auth'], task['account'], {
'kind': 'dfareporting#report',
'type': 'FLOODLIGHT',
'accountId': account_id,
'name': name,
'fileName': name.replace('( ', '').replace(' )', '').replace(
' ', '_'),
'format': 'CSV',
'delivery': {
'emailOwner': False
},
'floodlightCriteria': {
'dateRange': {
'kind': 'dfareporting#dateRange',
'relativeDateRange': 'LAST_7_DAYS'
},
'dimensions': [{
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:date'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:floodlightConfigId'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activityGroupId'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activityGroup'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activityId'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activity'
}],
'floodlightConfigId': {
'dimensionName': 'dfa:floodlightConfigId',
'kind': 'dfareporting#dimensionValue',
'matchType': 'EXACT',
'value': floodlight_id
},
'metricNames': ['dfa:floodlightImpressions'],
'reportProperties': {
'includeUnattributedCookieConversions': False,
'includeUnattributedIPConversions': False
}
},
'schedule': {
'active': True,
'every': 1,
'repeats': 'DAILY',
'startDate': str(date.today()),
'expirationDate': str((date.today() + timedelta(days=365))),
},
})
return report['id']
def dcm(config, task):
if config.verbose:
print('DCM')
# stores existing report json
report = None
# check if report is to be deleted
if task.get('delete', False):
if config.verbose:
print(
'DCM DELETE', task['report'].get('name', None)
or task['report'].get('body', {}).get('name', None)
or task['report'].get('report_id', None))
report_delete(
config,
task['auth'],
task['report']['account'],
task['report'].get('report_id', None),
task['report'].get('name', None)
or task['report'].get('body', {}).get('name', None),
)
# check if report is to be run
if task.get('report_run_only', False):
if config.verbose:
print(
'DCM REPORT RUN', task['report'].get('name', None)
or task['report'].get('report_id', None))
report_run(
config,
task['auth'],
task['report']['account'],
task['report'].get('report_id', None),
task['report'].get('name', None),
)
# check if report is to be created
if 'body' in task['report']:
if config.verbose:
print('DCM BUILD', task['report']['body']['name'])
if 'filters' in task['report']:
task['report']['body'] = report_filter(config, task['auth'],
task['report']['body'],
task['report']['filters'])
report = report_build(
config, task['auth'], task['report']['body'].get('accountId')
or task['report']['account'], task['report']['body'])
# moving a report
if 'out' in task:
filename, report = report_file(
config,
task['auth'],
task['report']['account'],
task['report'].get('report_id', None),
task['report'].get('name', None)
or task['report'].get('body', {}).get('name', None),
task['report'].get('timeout', 10),
)
if report:
if config.verbose:
print('DCM FILE', filename)
# clean up the report
rows = report_to_rows(report)
rows = report_clean(rows)
# if bigquery, remove header and determine schema
schema = None
if 'bigquery' in task['out']:
schema = report_schema(next(rows))
task['out']['bigquery']['schema'] = schema
task['out']['bigquery']['skip_rows'] = 0
# write rows using standard out block in json ( allows customization across all scripts )
if rows:
put_rows(config, task['auth'], task['out'], rows)
def run_floodlight_reports(config, task):
if config.verbose:
print('Creating Floodlight reports')
body = {
"kind": "dfareporting#report",
"name": '', # this is updated below based on Floodlight Config ID
"format": "CSV",
"type": "FLOODLIGHT",
"floodlightCriteria": {
"dateRange": {
"kind": "dfareporting#dateRange",
"relativeDateRange": "LAST_60_DAYS"
},
"floodlightConfigId": {
"kind": "dfareporting#dimensionValue",
"dimensionName": "dfa:floodlightConfigId",
"value": 0, # updated below and replaced with Floodlight Config ID
"matchType": "EXACT"
},
"reportProperties": {
"includeUnattributedIPConversions": False,
"includeUnattributedCookieConversions": True
},
"dimensions": [
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:site"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:floodlightAttributionType"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:interactionType"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:pathType"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:browserPlatform"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:platformType"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:week"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:placementId"
},
{
"kind": "dfareporting#sortedDimension",
"name": "dfa:floodlightConfigId"
}],
"metricNames": [
"dfa:activityClickThroughConversions",
"dfa:activityViewThroughConversions",
"dfa:totalConversions",
"dfa:totalConversionsRevenue"
]
},
"schedule": {
"active": True,
"repeats": "WEEKLY",
"every": 1,
"repeatsOnWeekDays":["Sunday"]
},
"delivery": {
"emailOwner": False
}
}
reports = []
floodlightConfigs = task.get('floodlightConfigIds', None)
for configId in floodlightConfigs:
body['name'] = task.get('reportPrefix', '') + "_" + str(configId)
body['floodlightCriteria']['floodlightConfigId']['value'] = configId
report = report_build(
config, task['auth_cm'],
task['account'],
body
)
reports.append(report['id'])
if config.verbose:
print('Finished creating Floodlight reports - moving to BQ')
queries = []
for createdReportId in reports:
filename, report = report_file(
config, task['auth_cm'],
task['account'],
createdReportId,
None,
task.get('timeout', 10),
)
if report:
if config.verbose:
print('Floodlight config report ', filename)
# clean up the report
rows = report_to_rows(report)
rows = report_clean(rows)
# determine schema
schema = report_schema(next(rows))
out_block = {}
out_block['bigquery'] = {}
out_block['bigquery']['dataset'] = task['dataset']
out_block['bigquery']['schema'] = schema
out_block['bigquery']['skip_rows'] = 0
out_block['bigquery']['table'] = 'z_Floodlight_CM_Report_' + str(createdReportId)
# write rows using standard out block in json ( allows customization across all scripts )
if rows: put_rows(config, task['auth_bq'], out_block, rows)
queries.append('SELECT * FROM `{0}.{1}.{2}`'.format(config.project, out_block['bigquery']['dataset'], out_block['bigquery']['table']))
if config.verbose:
print('Moved reports to BQ tables - starting join')
finalQuery = ' UNION ALL '.join(queries)
query_to_table(
config, task['auth_bq'],
config.project,
task['dataset'],
CM_FLOODLIGHT_OUTPUT_TABLE,
finalQuery,
legacy=False
)
if config.verbose:
print('Finished with Floodlight Config reports')
def report_combos(config, task, name, dateRange, schedule, advertiser,
campaign, dynamicProfile):
if config.verbose:
print('DYNAMIC COSTS COMBOS:', name)
# basic report schema, with no dynamic elements
schema = {
'kind': 'dfareporting#report',
'type': 'STANDARD',
'name': 'Dynamic Costs %s - Dynamic Combos ( StarThinker )' % name,
'schedule': schedule,
'criteria': {
'dateRange':
dateRange,
'dimensionFilters': [{
'kind': 'dfareporting#dimensionValue',
'dimensionName': 'dfa:dynamicProfile',
'id': dynamicProfile,
'matchType': 'EXACT'
}, {
'kind': 'dfareporting#dimensionValue',
'dimensionName': 'dfa:advertiser',
'id': advertiser,
'matchType': 'EXACT'
}, {
'kind': 'dfareporting#dimensionValue',
'dimensionName': 'dfa:campaign',
'id': campaign,
'matchType': 'EXACT'
}],
'dimensions': [{
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placement'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:placementId'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activity'
}, {
'kind': 'dfareporting#sortedDimension',
'name': 'dfa:activityId'
}],
'metricNames':
['dfa:impressions', 'dfa:clicks', 'dfa:totalConversions']
}
}
# add in all reasonable dynamic elements
for i in range(1, 5 + 1): # 5 elements/feeds
for j in range(1, 6 + 1): # 6 fields per element
schema['criteria']['dimensions'].append({
'kind':
'dfareporting#sortedDimension',
'name':
'dfa:dynamicElement%iField%iValue' % (i, j)
})
print(json.dumps(schema, indent=2))
# create the report if it does not exist
report = report_build(config, task['auth'], task['account'], schema)
# fetch report file if it exists ( timeout = 0 means grab most reent ready )
filename, filedata = report_file(config, task['auth'], task['account'],
report['id'], None, 60, DCM_CHUNK_SIZE)
# write report to a table ( avoid collisions as best as possible )
table_name = 'Dynamic_Costs_%s_Dynamic_Combos' % name
write_report(config, task, filedata, task['out']['dataset'], table_name)
return table_name