def get_cr():
print("Getting CR stats")
data = get_stats()
# todo: enqueue every row to metric processor
# transform
# filter
out = (seq(data)
.map(lambda row: row['Stat'])
.filter(lambda row: (
int(row['clicks']) >= get_offer_min_clicks(row['offer_id'])))
.filter(lambda row: (
offer_exists_and_monitoring_true(row['offer_id'])))
.map(lambda row: update_in(row, ['clicks'], int))
.map(lambda row: update_in(row, ['conversions'], int))
.map(lambda row: (
assoc(row, 'value', cr(row['clicks'], row['conversions']))))
.to_list())
metric = Metric.objects.get(key='cr')
for row in out:
metric_log = MetricLog()
metric_log.offer_id = row['offer_id']
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
celery_pubsub.publish('metric.loaded', metric_log)
def get_capfill():
print("Gettings CAP stats")
prefs = get_prefs()
res = get_stats(prefs['lookback'])
out = (seq(res.data['data'])
.map(lambda row: row['Stat'])
# .filter(lambda row: int(row['clicks']) >= min_clicks)
.filter(lambda row: (
offer_exists_and_monitoring_true(row['offer_id'])))
.map(lambda row: update_in(row, ['conversions'], int))
.map(lambda row: (
assoc(row, 'conversion_cap',
get_conversion_cap(row['offer_id'],
row['affiliate_id']))))
.filter(lambda row: row['conversion_cap'] > 0)
.map(lambda row: (
assoc(row, 'value', ((row['conversions'] / prefs['lookback'])
/ row['conversion_cap']))))
.to_list())
metric = Metric.objects.get(key='cap_fill')
for row in out:
metric_log = MetricLog()
metric_log.offer_id = row['offer_id']
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
celery_pubsub.publish('metric.loaded', metric_log)
def get_cr():
res = get_stats()
out = (seq(res.data['data'])
.map(lambda row: row['Stat'])
.filter(lambda row: int(row['clicks']) >= get_offer_min_clicks(row['offer_id']))
.filter(lambda row: offer_exists_and_monitoring_true(row['offer_id']))
.map(lambda row: update_in(row, ['clicks'], int))
.map(lambda row: update_in(row, ['conversions'], int))
.map(lambda row: assoc(row, 'value', cr(row['clicks'], row['conversions'])))
.to_list())
metric = Metric.objects.get(key='cr')
for row in out:
metric_log = MetricLog()
metric_log.offer_id = row['offer_id']
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
min_cr_trigger.delay(metric_log)
max_cr_trigger.delay(metric_log)
def get_gr():
offer_ids = fetch_active_offers()
offer_ids = list(filter(offer_exists_and_monitoring_true, offer_ids))
offer_ids = list(filter(offer_has_goal, offer_ids))
for offer_id in offer_ids:
offer = Offer.objects.get(pk=offer_id)
# get stats for the offer
stats = get_stats(offer_id, offer.one_goal_id, offer.lookback)
out = (seq(stats)
.map(lambda row: update_in(row, ['conversions'], int))
.map(lambda row: update_in(row, ['goal_id'], int))
.map(lambda row: update_in(row, ['affiliate_id'], int))
.to_list())
conversions = seq(out).filter(lambda r: r['goal_id'] == 0).to_list() # [{aff_id, conversions, goal_id}]
goals = seq(out).filter(lambda r: r['goal_id'] == offer.one_goal_id).to_list()
# filter min_conversions
conversions = seq(conversions).filter(lambda r: r['conversions'] >= offer.min_conversions).to_list()
# populate with goal count
conversions = (seq(conversions)
.map(lambda r: assoc(r, 'goals', get_goals_count(r['affiliate_id'], goals)))
.to_list())
# populate with gr value
conversions = (seq(conversions)
.map(lambda r: assoc(r, 'value', gr(r['conversions'], r['goals'])))
.to_list())
# create metric
metric = Metric.objects.get(key='gtr')
for row in conversions:
metric_log = MetricLog()
metric_log.offer_id = offer_id
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
# run trigger worker
min_gr_trigger.delay(metric_log)
def get_pacc():
api = Hasoffers(network_token=settings.HASOFFERS_NETWORK_TOKEN,
network_id=settings.HASOFFERS_NETWORK_ID,
proxies=settings.PROXIES)
from_date = datetime.datetime.now(pytz.timezone(
settings.TIME_ZONE)) - datetime.timedelta(days=1)
res = api.Report.getStats(fields=['Stat.gross_clicks', 'Stat.profit'],
groups=['Stat.offer_id', 'Stat.affiliate_id'],
filters={
'Stat.date': {
'conditional':
'GREATER_THAN_OR_EQUAL_TO',
'values': str(from_date.date())
},
'Stat.hour': {
'conditional':
'GREATER_THAN_OR_EQUAL_TO',
'values': from_date.hour
}
},
limit=10000)
out = (seq(
res.data['data']).map(lambda row: row['Stat']).filter(lambda row: int(
row['gross_clicks']) >= get_offer_min_clicks(row['offer_id'])).
filter(lambda row: offer_exists_and_monitoring_true(row['offer_id'])
).map(lambda row: update_in(row, ['profit'], float)).
map(lambda row: update_in(row, ['gross_clicks'], int)).map(
lambda row: assoc(row, 'value', (row['profit'] - (row[
'gross_clicks'] * settings.CLICK_COST)))).to_list())
metric = Metric.objects.get(key='pacc')
for row in out:
metric_log = MetricLog()
metric_log.offer_id = row['offer_id']
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
pacc_trigger.delay(metric_log)
def get_clicks_if_zero_conv():
print("Getting Clicks stats")
api = Hasoffers(network_token=settings.HASOFFERS_NETWORK_TOKEN,
network_id=settings.HASOFFERS_NETWORK_ID,
proxies=settings.PROXIES)
from_date = (datetime.datetime.now(pytz.timezone(settings.TIME_ZONE)) -
datetime.timedelta(days=1))
res = api.Report.getStats(fields=['Stat.clicks', 'Stat.conversions'],
groups=['Stat.offer_id', 'Stat.affiliate_id'],
filters={
'Stat.date': {
'conditional':
'GREATER_THAN_OR_EQUAL_TO',
'values': str(from_date.date())
},
'Stat.hour': {
'conditional':
'GREATER_THAN_OR_EQUAL_TO',
'values': from_date.hour
}
},
limit=10000)
out = (seq(
res.data['data']).map(lambda row: row['Stat']).filter(lambda row: (int(
row['clicks']) >= get_offer_min_clicks(row['offer_id']))).filter(
lambda row: (offer_exists_and_monitoring_true(row['offer_id']))
).map(lambda row: update_in(row, ['conversions'], int)).map(
lambda row: update_in(row, ['clicks'], int)).filter(
lambda row: row['conversions'] == 0).map(lambda row: assoc(
row, 'value', row['clicks'])).to_list())
metric = Metric.objects.get(key='clicks_zero_conv')
for row in out:
metric_log = MetricLog()
metric_log.offer_id = row['offer_id']
metric_log.affiliate_id = row['affiliate_id']
metric_log.metric = metric
metric_log.value = row['value']
metric_log.save()
celery_pubsub.publish('metric.loaded', metric_log)