# load the advertiser account instance
account = client.accounts(ACCOUNT_ID)
# limit request count and grab the first 10 line items from Cursor
line_items = list(account.line_items(None, count=10))[:10]
# the list of metrics we want to fetch, for a full list of possible metrics
# see: https://dev.twitter.com/ads/analytics/metrics-and-segmentation
metric_groups = [METRIC_GROUP.BILLING]
# fetching stats on the instance
line_items[0].stats(metric_groups)
# fetching stats for multiple line items
ids = map(lambda x: x.id, line_items)
LineItem.all_stats(account, ids, metric_groups)
# fetching async stats on the instance
queued_job = LineItem.queue_async_stats_job(account, ids, metric_groups)
# get the job_id:
job_id = queued_job['id']
# let the job complete
seconds = 15
time.sleep(seconds)
async_stats_job_result = LineItem.async_stats_job_result(account,
[job_id]).first
async_data = LineItem.async_stats_job_data(account,
# https://dev.twitter.com/ads/analytics/metrics-derived from twitter_ads.client import Client from twitter_ads.campaign import LineItem CONSUMER_KEY = 'your consumer key' CONSUMER_SECRET = 'your consumer secret' ACCESS_TOKEN = 'access token' ACCESS_TOKEN_SECRET = 'access token secret' ACCOUNT_ID = 'account id' # initialize the client client = Client(CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET) # load the advertiser account instance account = client.accounts(ACCOUNT_ID) # limit request count and grab the first 10 line items from Cursor line_items = list(account.line_items(None, count=10))[:10] # the list of metrics we want to fetch, for a full list of possible metrics # see: https://dev.twitter.com/ads/analytics/metrics-and-segmentation metrics = ['billed_engagements', 'billed_follows'] # fetching stats on the instance line_items[0].stats(metrics) # fetching stats for multiple line items ids = map(lambda x: x.id, line_items) LineItem.all_stats(account, ids, metrics)
# load the advertiser account instance account = client.accounts(ACCOUNT_ID) # limit request count and grab the first 10 line items from Cursor line_items = list(account.line_items(None, count=10))[:10] # the list of metrics we want to fetch, for a full list of possible metrics # see: https://dev.twitter.com/ads/analytics/metrics-and-segmentation metric_groups = [METRIC_GROUP.BILLING] # fetching stats on the instance line_items[0].stats(metric_groups) # fetching stats for multiple line items ids = map(lambda x: x.id, line_items) LineItem.all_stats(account, ids, metric_groups) # fetching async stats on the instance queued_job = LineItem.queue_async_stats_job(account, ids, metric_groups) # get the job_id: job_id = queued_job['id'] # let the job complete seconds = 15 time.sleep(seconds) async_stats_job_result = LineItem.async_stats_job_result(account, job_id) async_data = LineItem.async_stats_job_data(account, async_stats_job_result['url'])
metric_groups = [METRIC_GROUP.BILLING]
# fetching stats on the instance
line_items[0].stats(metric_groups)
# fetching stats for multiple line items
ids = list(map(lambda x: x.id, line_items))
if not ids:
print('Error: A minimum of 1 items must be provided for entity_ids')
sys.exit()
sync_data = []
# Sync/Async endpoint can handle max 20 entity IDs per request
# so split the ids list into multiple requests
for chunk_ids in split_list(ids, 20):
sync_data.append(LineItem.all_stats(account, chunk_ids, metric_groups))
print(sync_data)
# create async stats jobs and get job ids
queued_job_ids = []
for chunk_ids in split_list(ids, 20):
queued_job_ids.append(
LineItem.queue_async_stats_job(account, chunk_ids, metric_groups).id)
print(queued_job_ids)
# let the job complete
seconds = 30
time.sleep(seconds)
end = remove_minutes(end) + timedelta(hours=1)
return start, end
# Date range for analytics request
start, end = date_range(active_entities)
# Analytics request for specific Line Item IDs
# Granularity is set to `HOUR`
# Based on the activity start and end times
# only one hour of data is being requested
# which is why the arrays have a single element
LineItem.all_stats(account,
ids,
metric_groups,
granularity=granularity,
placement=placement,
start_time=start,
end_time=end)
"""
[
{
"id": "eeukx",
"id_data": [
{
"metrics": {
"app_clicks": None,
"card_engagements": None,
"carousel_swipes": None,
"clicks": [
71
