def get_available_pageviews(targets, start, end, datestr=False, ignore=None):
pageviews_by_sr_name = {}
all_campaigns = set()
targets, is_single = tup(targets, ret_is_single=True)
target_srs = chain.from_iterable(
target.subreddits_slow for target in targets)
all_sr_names = set()
srs = set(target_srs)
# get all campaigns in target_srs and pull in campaigns from other
# subreddits that are targeted
while srs:
all_sr_names |= {sr.name for sr in srs}
new_pageviews_by_sr_name = get_predicted_pageviews(srs)
pageviews_by_sr_name.update(new_pageviews_by_sr_name)
new_campaigns_by_date = get_campaigns_by_date(srs, start, end, ignore)
new_campaigns = set(chain.from_iterable(
new_campaigns_by_date.itervalues()))
all_campaigns.update(new_campaigns)
new_sr_names = set(chain.from_iterable(
campaign.target.subreddit_names for campaign in new_campaigns
))
new_sr_names -= all_sr_names
srs = set(Subreddit._by_name(new_sr_names).values())
# determine booked impressions by target for each day
dates = set(get_date_range(start, end))
booked_by_target_by_date = {date: defaultdict(int) for date in dates}
for campaign in all_campaigns:
camp_dates = set(get_date_range(campaign.start_date, campaign.end_date))
sr_names = tuple(sorted(campaign.target.subreddit_names))
daily_impressions = campaign.impressions / campaign.ndays
for date in camp_dates.intersection(dates):
booked_by_target_by_date[date][sr_names] += daily_impressions
datekey = lambda dt: dt.strftime('%m/%d/%Y') if datestr else dt
ret = {}
for target in targets:
name = make_target_name(target)
ret[name] = {}
for date in dates:
booked_by_target = booked_by_target_by_date[date]
pageviews = get_maximized_pageviews(
target.subreddit_names, booked_by_target, pageviews_by_sr_name)
ret[name][datekey(date)] = max(0, pageviews)
if is_single:
name = make_target_name(targets[0])
return ret[name]
else:
return ret
def get_available_pageviews(targets,
start,
end,
location=None,
datestr=False,
ignore=None):
"""
Return the available pageviews by date for the targets and location.
Available pageviews depends on all equal and higher level locations:
A location is: subreddit > country > metro
e.g. if a campaign is targeting /r/funny in USA/Boston we need to check that
there's enough inventory in:
* /r/funny (all campaigns targeting /r/funny regardless of location)
* /r/funny + USA (all campaigns targeting /r/funny and USA with or without
metro level targeting)
* /r/funny + USA + Boston (all campaigns targeting /r/funny and USA and
Boston)
The available inventory is the smallest of these values.
"""
# assemble levels of location targeting, None means untargeted
locations = [None]
if location:
locations.append(location)
if location.metro:
locations.append(Location(country=location.country))
# get all the campaigns directly and indirectly involved in our target
targets, is_single = tup(targets, ret_is_single=True)
target_srs = list(
chain.from_iterable(target.subreddits_slow for target in targets))
all_campaigns = find_campaigns(target_srs, start, end, ignore)
# get predicted pageviews for each subreddit and location
all_sr_names = set(sr.name for sr in target_srs)
all_sr_names |= set(
chain.from_iterable(campaign.target.subreddit_names
for campaign in all_campaigns))
all_srs = Subreddit._by_name(all_sr_names).values()
pageviews_dict = {
location: get_predicted_pageviews(all_srs, location)
for location in locations
}
# determine booked impressions by target and location for each day
dates = set(get_date_range(start, end))
booked_dict = {}
for date in dates:
booked_dict[date] = {}
for location in locations:
booked_dict[date][location] = defaultdict(int)
for campaign in all_campaigns:
camp_dates = set(get_date_range(campaign.start_date,
campaign.end_date))
sr_names = tuple(sorted(campaign.target.subreddit_names))
daily_impressions = campaign.impressions / campaign.ndays
for location in locations:
if location and not location.contains(campaign.location):
# campaign's location is less specific than location
continue
for date in camp_dates.intersection(dates):
booked_dict[date][location][sr_names] += daily_impressions
# calculate inventory for each target and location on each date
datekey = lambda dt: dt.strftime('%m/%d/%Y') if datestr else dt
ret = {}
for target in targets:
name = make_target_name(target)
subreddit_names = target.subreddit_names
ret[name] = {}
for date in dates:
pageviews_by_location = {}
for location in locations:
# calculate available impressions for each location
booked_by_target = booked_dict[date][location]
pageviews_by_sr_name = pageviews_dict[location]
pageviews_by_location[location] = get_maximized_pageviews(
subreddit_names, booked_by_target, pageviews_by_sr_name)
# available pageviews is the minimum from all locations
min_pageviews = min(pageviews_by_location.values())
ret[name][datekey(date)] = max(0, min_pageviews)
if is_single:
name = make_target_name(targets[0])
return ret[name]
else:
return ret
def get_available_pageviews(targets, start, end, location=None, datestr=False,
ignore=None):
"""
Return the available pageviews by date for the targets and location.
Available pageviews depends on all equal and higher level locations:
A location is: subreddit > country > metro
e.g. if a campaign is targeting /r/funny in USA/Boston we need to check that
there's enough inventory in:
* /r/funny (all campaigns targeting /r/funny regardless of location)
* /r/funny + USA (all campaigns targeting /r/funny and USA with or without
metro level targeting)
* /r/funny + USA + Boston (all campaigns targeting /r/funny and USA and
Boston)
The available inventory is the smallest of these values.
"""
# assemble levels of location targeting, None means untargeted
locations = [None]
if location:
locations.append(location)
if location.metro:
locations.append(Location(country=location.country))
# get all the campaigns directly and indirectly involved in our target
targets, is_single = tup(targets, ret_is_single=True)
target_srs = list(chain.from_iterable(
target.subreddits_slow for target in targets))
all_campaigns = find_campaigns(target_srs, start, end, ignore)
# get predicted pageviews for each subreddit and location
all_sr_names = set(sr.name for sr in target_srs)
all_sr_names |= set(chain.from_iterable(
campaign.target.subreddit_names for campaign in all_campaigns
))
all_srs = Subreddit._by_name(all_sr_names).values()
pageviews_dict = {location: get_predicted_pageviews(all_srs, location)
for location in locations}
# determine booked impressions by target and location for each day
dates = set(get_date_range(start, end))
booked_dict = {}
for date in dates:
booked_dict[date] = {}
for location in locations:
booked_dict[date][location] = defaultdict(int)
for campaign in all_campaigns:
camp_dates = set(get_date_range(campaign.start_date, campaign.end_date))
sr_names = tuple(sorted(campaign.target.subreddit_names))
daily_impressions = campaign.impressions / campaign.ndays
for location in locations:
if location and not location.contains(campaign.location):
# campaign's location is less specific than location
continue
for date in camp_dates.intersection(dates):
booked_dict[date][location][sr_names] += daily_impressions
# calculate inventory for each target and location on each date
datekey = lambda dt: dt.strftime('%m/%d/%Y') if datestr else dt
ret = {}
for target in targets:
name = make_target_name(target)
subreddit_names = target.subreddit_names
ret[name] = {}
for date in dates:
pageviews_by_location = {}
for location in locations:
# calculate available impressions for each location
booked_by_target = booked_dict[date][location]
pageviews_by_sr_name = pageviews_dict[location]
pageviews_by_location[location] = get_maximized_pageviews(
subreddit_names, booked_by_target, pageviews_by_sr_name)
# available pageviews is the minimum from all locations
min_pageviews = min(pageviews_by_location.values())
ret[name][datekey(date)] = max(0, min_pageviews)
if is_single:
name = make_target_name(targets[0])
return ret[name]
else:
return ret
