def getStrategies(self):
google_service_type = "BiddingStrategyService"
client = Update(account_id, google_service_type).getClient()
service = client.GetService(google_service_type, version='v201809')
PAGE_SIZE = 100
offset = 0
selector = {
'fields': [
'BiddingScheme', 'Name', 'Id', 'Status', 'Type'
],
'paging': {
'startIndex': str(offset),
'numberResults': str(PAGE_SIZE)
}
}
results = []
more_pages = True
while more_pages:
page = service.get(selector)
# Display results.
if 'entries' in page:
for result_set in page['entries']:
results.append(result_set)
else:
print('No results were found.')
offset += PAGE_SIZE
selector['paging']['startIndex'] = str(offset)
more_pages = offset < int(page['totalNumEntries'])
def __init__(self, account_id, new_ads):
self.account_id = account_id
self.new_ads = new_ads
self.service_type = "AdGroupAdService"
self.operations = self.getOperations()
self.update = Update(self.account_id, self.service_type, self.operations)
self.sendRequest()
def __init__(self, account_id, bid_updates):
self.account_id = account_id
self.bid_updates = bid_updates
self.service_type = "AdGroupCriterionService"
self.operations = self.getOperations()
self.update = Update(self.account_id, self.service_type,
self.operations)
self.sendRequest()
class CreateAds(Update):
# Arg 1 is the account id
# Arg 2 is a dict of new_ads with each sub-dict containing an adgroup_id, criterion_id (keyword id) and new_bid
def __init__(self, account_id, new_ads):
self.account_id = account_id
self.new_ads = new_ads
self.service_type = "AdGroupAdService"
self.operations = self.getOperations()
self.update = Update(self.account_id, self.service_type, self.operations)
self.sendRequest()
def getOperations(self):
# TODO Chunk into 2000 or fewer changes
operations = [
{
'operator': 'ADD',
'operand': {
'xsi_type': 'AdGroupAd',
'adGroupId': self.new_ads[unique_id]["ad_group_id"],
'ad': {
'xsi_type': 'ExpandedTextAd',
'headlinePart1': self.new_ads[unique_id]["headlinePart1"],
'headlinePart2': self.new_ads[unique_id]["headlinePart2"],
'headlinePart3': self.new_ads[unique_id]["headlinePart3"],
'description': self.new_ads[unique_id]["description"],
'description2': self.new_ads[unique_id]["description2"],
'path1': self.new_ads[unique_id]["path1"],
'path2': self.new_ads[unique_id]["path2"],
'finalUrls': self.new_ads[unique_id]["finalUrls"],
},
# Optional fields.
'status': 'ENABLED'
}
} for unique_id in self.new_ads]
return operations
def checkOperations(self):
# keyword specific checks here
pass
def convertToMicros(self, bid):
return int(bid * 10) * 100000
def sendRequest(self):
keyword_response = self.update.send_request()
class UpdateKeywordBids(Update):
# Arg 1 is the account id
# Arg 2 is a dict of bid_updates with each sub-dict containing an adgroup_id, criterion_id (keyword id) and new_bid
def __init__(self, account_id, bid_updates):
self.account_id = account_id
self.bid_updates = bid_updates
self.service_type = "AdGroupCriterionService"
self.operations = self.getOperations()
self.update = Update(self.account_id, self.service_type,
self.operations)
self.sendRequest()
def getOperations(self):
operations = [{
'operator': 'SET',
'operand': {
'xsi_type': 'BiddableAdGroupCriterion',
'adGroupId': self.bid_updates[unique_id]["ad_group_id"],
'criterion': {
'id': self.bid_updates[unique_id]["criterion_id"],
},
'biddingStrategyConfiguration': {
'bids': [{
'xsi_type': 'CpcBid',
'bid': {
'microAmount':
self.convertToMicros(
self.bid_updates[unique_id]["bid"])
}
}]
}
}
} for unique_id in self.bid_updates]
return operations
def checkOperations(self):
# keyword specific checks here
pass
def convertToMicros(self, bid):
return int(bid * 10) * 100000
def sendRequest(self):
keyword_response = self.update.send_request()
def check(self):
"""
1. Get batch jobs with status != Done
2. Check status of batch job
3. If status = Done, Get mutations with batch job id = current batch job id (order by created)
4. Update mutations with results
"""
batch_jobs_query = self.batch_jobs_query()
batch_jobs_chunks = pd.read_sql(batch_jobs_query, Database().createEngine(), chunksize=10)
# Iterate over chunks
try:
batch_jobs_data_frame = next(batch_jobs_chunks)
except StopIteration:
return
# Mark the batch jobs data as is_checking equal to True
self.set_batch_jobs_to_processing(batch_jobs_data_frame)
for index, batch_job_data_frame in batch_jobs_data_frame.iterrows():
response = Update(
batch_job_data_frame['account_id'], ''
).check_batch_job_result(batch_job_data_frame['google_id'])
if response:
mutations_query = self.mutations_query_by_batch_job(batch_job_data_frame['id'])
mutations_data_frame_chunks = pd.read_sql(mutations_query, Database().createEngine(), chunksize=2000)
# Iterate over chunks
try:
mutations_data_frame = next(mutations_data_frame_chunks)
except StopIteration:
continue
mutations_data_frame["is_processing"] = 0
self.update_batch_job_mutations(mutations_data_frame, response)
# TODO: support all status for batch job
batch_jobs_data_frame.at[index, "status"] = 'DONE'
batch_jobs_data_frame["is_checking"] = 0
self.update_batch_jobs(batch_jobs_data_frame)
def process_account_mutations(self, account_data_frame, service_type):
""" Process mutations for up to 2000 rows. One account_id and one type at a time.
"""
google_service_type = self.services_map[service_type]
account_id = account_data_frame.account_id.values[0]
operations = []
for index, row in account_data_frame.iterrows():
operation = Operation(
row, service_type, row["action"], row["attribute"]
).get()
operations.append(operation)
try:
print("attempting {0} mutation...".format(google_service_type))
result = Update(account_id, google_service_type, operations).send_request()
except Exception as exception:
print("An exception has occurred: {0}".format(exception))
return [False, str(exception)]
return True, result