/
dataccess.py
54 lines (43 loc) · 1.86 KB
/
dataccess.py
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from google.appengine.api import memcache
from models import Site, ObservationTimestep, ForecastTimestep
from utils import first, SparseList
from itertools import ifilter
def to_dict_excl_sites(o):
if o is not None:
return o.to_dict(excluding=['site'])
return None
def latest_obs_and_forecast(site_id):
result = memcache.get(site_id, "site_latest")
if result:
return result
site = Site.get_by_key_name(site_id)
if site is None:
return None
obs = ObservationTimestep.find_latest_by_site(site, limit=6)
result = None
if len(obs) > 0:
forecasts = ForecastTimestep.find_by_site_closest_by_date(site, first(obs).observation_datetime,
limit=50)
closest_forecast = first(forecasts)
if closest_forecast:
matching_obs = first(filter(lambda o: o.observation_datetime == closest_forecast.forecast_datetime, obs))
matching_forecasts = ifilter(lambda f: f.forecast_datetime == closest_forecast.forecast_datetime, forecasts)
if matching_obs:
#finally have both... a single obs report and multiple forecasts
obs_dict = to_dict_excl_sites(matching_obs)
obs_dict['best_forecast'] = map(to_dict_excl_sites, make_five_day_list(matching_forecasts))
result = {
'site': site.to_dict(),
'observation': obs_dict
}
memcache.set(site_id, result, 60 * 60, namespace='site_latest')
return result
def make_five_day_list(forecasts, min = 5):
slist = SparseList([None for i in range(0,min)])
for f in forecasts:
r = f.forecast_range()
if slist[r] is None:
slist[r] = [f]
else:
slist[r].append(f)
return map(lambda a: first(a), slist)