def forecast_update2(site_key):
site = Site.get_by_key_name(site_key)
if site is None:
return Response(status=404)
forecast_url = "http://www.metoffice.gov.uk/public/data/PWSCache/BestForecast/Forecast/%s?format=application/json" % site_key
result = urlfetch.fetch(forecast_url)
if result.status_code == 200:
forecast = parse_forecast(result.content)
issued_date = parse_date(forecast["@dataDate"])
for date, data in timesteps(forecast):
forecast_timestep = ForecastTimestep.find_by_site_and_dates(
site, date, issued_date)
if forecast_timestep is None:
forecast_timestep = ForecastTimestep(
site=site,
forecast_datetime=date,
issued_datetime=issued_date,
forecast_date=date.date())
for k, v in data.items():
prop_name = snake_case(k)
if hasattr(forecast_timestep, prop_name):
if v == "missing":
v = None
setattr(forecast_timestep, prop_name, v)
forecast_timestep.save()
return Response(status=204)
def forecast_update2(site_key):
site = Site.get_by_key_name(site_key)
if site is None:
return Response(status = 404)
forecast_url = "http://www.metoffice.gov.uk/public/data/PWSCache/BestForecast/Forecast/%s?format=application/json" % site_key
result = urlfetch.fetch(forecast_url)
if result.status_code == 200:
forecast = parse_forecast(result.content)
issued_date = parse_date(forecast["@dataDate"])
for date, data in timesteps(forecast):
forecast_timestep = ForecastTimestep.find_by_site_and_dates(site, date, issued_date)
if forecast_timestep is None:
forecast_timestep = ForecastTimestep(site = site, forecast_datetime = date, issued_datetime = issued_date, forecast_date = date.date())
for k,v in data.items():
prop_name = snake_case(k)
if hasattr(forecast_timestep, prop_name):
if v == "missing":
v = None
setattr(forecast_timestep, prop_name, v)
forecast_timestep.save()
return Response(status = 204)
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 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 site_detail(site_id):
site = Site.get_by_key_name(site_id)
if site is None:
return Response(status = 404)
obs = ObservationTimestep.find_latest_by_site(site = site, limit = 24)
forecasts = []
if len(obs) > 0:
first_obs = first(obs)
last_obs = last(obs)
forecasts = ForecastTimestep.find_by_site_between_dates( site = site,
from_dt = last_obs.observation_datetime,
to_dt = first_obs.observation_datetime)
return Response(json.dumps({
'site': site.to_dict(),
'observations': map(lambda o: o.to_dict(excluding = ['site']), obs),
'forecasts': map(lambda f: f.to_dict(excluding = ['site']), forecasts)
}), content_type = "application/json")
