def process_share(geo_data, share_type):
"""Add share aggregate data to redis."""
log.debug('Processing as SHARE')
redis.incr(rkeys.SHARE_TOTAL)
redis.hincrby(rkeys.SHARE_ISSUES, share_type)
country = geo_data.get('country', geo_data.get('registered_country'))
if country:
country = country['iso_code']
redis.hincrby(rkeys.SHARE_COUNTRIES, country)
redis.hincrby(rkeys.SHARE_COUNTRY_ISSUES.format(country), share_type)
continent = geo_data.get('continent')
if continent:
continent = continent['code']
redis.hincrby(rkeys.SHARE_CONTINENTS, continent)
redis.hincrby(rkeys.SHARE_CONTINENT_ISSUES.format(continent), share_type)
def process_map(geo_data, timestamp):
"""Add download aggregate data to redis."""
redis.incr(rkeys.MAP_TOTAL)
try:
# rounding to aid in geo aggregation
location = {
'lat': round_map_coord(geo_data['location']['latitude']),
'lon': round_map_coord(geo_data['location']['longitude']),
}
except (KeyError, TypeError):
# this appears to mostly happen with anonymous proxies
log.info('Geo data contained no location.')
log.debug(geo_data)
return
geo_key = '{lat}:{lon}'.format(**location)
log.debug('Got location: ' + geo_key)
time_key = rkeys.MAP_GEO.format(timestamp)
log.debug('Got timestamp: %s' % timestamp)
redis.hincrby(time_key, geo_key, 1)
# store the timestamp used in a sorted set for use in milhouse
redis.zadd(rkeys.MAP_TIMESTAMPS, timestamp, timestamp)
