def dataset():
if project.verbose:
print('DATASET', project.id, project.task['dataset'])
if project.task.get('delete', False):
if project.verbose:
print('DATASET DELETE')
datasets_delete(
project.task['auth'],
project.id,
project.task['dataset']
)
if project.verbose:
print('DATASET CREATE')
datasets_create(
project.task['auth'],
project.id,
project.task['dataset']
)
if project.verbose:
print('DATASET ACCESS')
datasets_access(
project.task['auth'],
project.id,
project.task['dataset'],
emails=project.task.get('emails', []),
groups=project.task.get('groups', [])
)
def dataset():
if project.verbose: print("DATASET", project.id, project.task['dataset'])
# create dataset
datasets_create(project.task['auth'], project.id, project.task['dataset'])
datasets_access(project.task['auth'],
project.id,
project.task['dataset'],
emails=project.task.get('emails', []),
groups=project.task.get('groups', []))
def dataset(config, task):
if config.verbose:
print('DATASET', config.project, task['dataset'])
if task.get('delete', False):
if config.verbose:
print('DATASET DELETE')
# In order to fully delete a dataset, it needs to first have all tables
# deleted, which is done with the delete_contents=True, and then the actual
# dataset can be deleted, which is done with delete_contents=false.
datasets_delete(config,
task['auth'],
config.project,
task['dataset'],
delete_contents=True)
datasets_delete(config,
task['auth'],
config.project,
task['dataset'],
delete_contents=False)
else:
if task.get('clear', False):
if config.project:
print('DATASET CLEAR')
datasets_delete(config,
task['auth'],
config.project,
task['dataset'],
delete_contents=True)
if config.verbose:
print('DATASET CREATE')
datasets_create(config, task['auth'], config.project, task['dataset'])
if config.verbose:
print('DATASET ACCESS')
datasets_access(config,
task['auth'],
config.project,
task['dataset'],
emails=task.get('emails', []),
groups=task.get('groups', []))
def itp_audit_cm():
account_id = project.task['account']
# Read Advertiser Ids
advertiser_ids = list(
get_rows('service', project.task['read']['advertiser_ids']))
is_superuser, profile_id = get_profile_for_api('user', account_id)
datasets_create('user', project.id, project.task['dataset'])
placements = {}
campaignNames = {}
siteNames = {}
advertiserNames = {}
for c in API_DCM('user', iterate=True,
internal=is_superuser).campaigns().list(
archived=False,
profileId=profile_id,
accountId=account_id,
advertiserIds=advertiser_ids
if advertiser_ids else None).execute():
# only keep campaigns with end dates in the future or less than 90 days ago
if ((date.fromisoformat(c['endDate']) - date.today()).days > -90):
campaignNames[c['id']] = {
'id': c['id'],
'name': c['name'],
'startDate': c['startDate'],
'endDate': c['endDate']
}
validCampaignIds = [int(i) for i in campaignNames.keys()]
for s in API_DCM('user', iterate=True, internal=is_superuser).sites().list(
profileId=profile_id,
accountId=account_id,
campaignIds=validCampaignIds).execute():
siteNames[s['id']] = s['name']
for a in API_DCM('user', iterate=True,
internal=is_superuser).advertisers().list(
profileId=profile_id,
accountId=account_id,
ids=advertiser_ids[:500]
if advertiser_ids else None).execute():
advertiserNames[a['id']] = a['name']
if len(advertiser_ids) > 500:
for a in API_DCM('user', iterate=True,
internal=is_superuser).advertisers().list(
profileId=profile_id,
accountId=account_id,
ids=advertiser_ids[500:]
if advertiser_ids else None).execute():
advertiserNames[a['id']] = a['name']
for p in API_DCM(
'user', iterate=True, internal=is_superuser).placements().list(
archived=False,
profileId=profile_id,
accountId=account_id,
advertiserIds=advertiser_ids if advertiser_ids else None,
campaignIds=validCampaignIds).execute():
# exclude 1x1 tracking placements
if not (p['size']['height'] == 1 and p['size']['width'] == 1):
placements[p['id']] = {
'id': p['id'],
'name': p['name'],
'advertiserId': p['advertiserId'],
'advertiserName': advertiserNames[p['advertiserId']],
'campaignId': p['campaignId'],
'campaignName': campaignNames[p['campaignId']]['name'],
'siteId': p['siteId'],
'siteName': siteNames[p['siteId']],
'adsTotal': 0,
'adsNotImpacted': 0,
'adsFrequencyCapped': 0,
'adsAudienceSegmentation': 0,
'adsAudienceListTargeting': 0,
'adsDynamicCreative': 0,
'adsPlatformBrowserTargeting': 0
}
for ad in API_DCM('user', iterate=True, internal=is_superuser).ads().list(
type='AD_SERVING_STANDARD_AD',
profileId=profile_id,
accountId=account_id,
campaignIds=validCampaignIds).execute():
# only analyze standard, non-default priority ads that have been assigned 1+ placements and creatives
if ad['deliverySchedule'][
'priority'] != "AD_PRIORITY_16" and 'placementAssignments' in ad and 'creativeAssignments' in ad[
'creativeRotation']:
hasDynamicCreative = False
for creative in ad['creativeRotation']['creativeAssignments']:
if 'richMediaExitOverrides' in creative:
hasDynamicCreative = True
break
for p in ad['placementAssignments']:
if p['placementId'] in placements:
knownPlacement = placements[p['placementId']]
knownPlacement['adsTotal'] += 1
if 'frequencyCap' in ad['deliverySchedule']:
knownPlacement['adsFrequencyCapped'] += 1
if 'audienceSegmentId' in ad:
knownPlacement['adsAudienceSegmentation'] += 1
if 'remarketingListExpression' in ad:
knownPlacement['adsAudienceListTargeting'] += 1
if 'technologyTargeting' in ad and (
'browsers' in ad['technologyTargeting']
or 'platformTypes' in ad['technologyTargeting']):
knownPlacement['adsPlatformBrowserTargeting'] += 1
if hasDynamicCreative:
knownPlacement['adsDynamicCreative'] += 1
if not 'frequencyCap' in ad[
'deliverySchedule'] and not 'audienceSegmentId' in ad and not 'remarketingListExpression' in ad:
knownPlacement['adsNotImpacted'] += 1
write_data = []
for p in placements.values():
write_data.append([
p['name'] + ' - ' + str(p['id']), p['id'], p['name'],
p['advertiserName'] + ' - ' + str(p['advertiserId']),
p['advertiserId'], p['advertiserName'],
p['campaignName'] + ' - ' + str(p['campaignId']), p['campaignId'],
p['campaignName'], p['siteId'], p['siteName'], p['adsTotal'],
p['adsNotImpacted'], p['adsFrequencyCapped'],
p['adsAudienceListTargeting'], p['adsAudienceSegmentation'],
p['adsPlatformBrowserTargeting'], p['adsDynamicCreative']
])
placements_out = {}
placements_out["bigquery"] = {
"dataset": project.task['dataset'],
"table": CM_PLACEMENT_AUDIT_TABLE,
"is_incremental_load": False,
"datastudio": True,
"schema": PLACEMENTS_SCHEMA,
"skip_rows": 0
}
if placements: put_rows('service', placements_out, write_data)