def step1_get_data(year, month, observer_id=None, region_id=None, get_new=True, make_pickle=False, data_description="no_description_given"):
"""Gets data for one month and prepares for plotting
:param year: [int]
:param month: [int]
:param observer_id: [int or list of ints]
:param region_id [int]
:param get_new: [bool] get data with a new request or use local pickle
:param make_pickle: [bool] only matters if getting new data, make a pickle in local storage
:param data_description [string] Custom description for naming pickle-files
:return dates: [list of DayData objects]
"""
if data_description is not None:
pickle_file_name = "{0}{1}_{2}{3:02d}.pickle".format(env.local_storage, data_description, year, month)
else:
if region_id is not None:
pickle_file_name = "{0}runPlotRegionData_{1}_{2}{3:02d}.pickle".format(env.local_storage, region_id, year, month)
else:
if observer_id is not None:
pickle_file_name = "{0}runPlotObserverData_{1}_{2}{3:02d}.pickle".format(env.local_storage, observer_id, year, month)
else:
print 'Need Observerid and/or forecastRegionTID to make this work.'
return []
first, last = cal.monthrange(year, month)
from_date = dt.date(year, month, 1)
to_date = dt.date(year, month, last) + dt.timedelta(days=1)
if get_new:
all_observations = go.get_all_registrations(from_date, to_date, output='DataFrame', geohazard_tid=10,
observer_ids=observer_id, region_ids=region_id)
# for all dates in the requested from-to interval
dates = []
for d in _get_dates(from_date, to_date, dt.timedelta(days=1)):
if observer_id is not None and region_id is None: # if only data for one observer
dd = DayData(d, observer_id=observer_id)
else: # else whish to have data for some/all observervers in a region
dd = DayData(d, region_id=region_id)
obstyp = []
regids = []
nicks = []
loc_pr_regid = {}
obs_pr_regid = {}
nic_pr_regid = {}
# loop through all observations
for i in all_observations.index:
this_date = all_observations.iloc[i].DtObsTime.date()
# append all observations where dates match
if this_date == d:
regid = all_observations.iloc[i].RegID
# location on regid (only one location pr RegID)
if regid not in loc_pr_regid.keys():
loc_pr_regid[regid] = all_observations.iloc[i].ForecastRegionName
# get the nicname use on the regid (only one pr RegID)
if regid not in nic_pr_regid.keys():
nic_pr_regid[regid] = all_observations.iloc[i].NickName
# observations pr regid (might be more)
if regid not in obs_pr_regid.keys():
obs_pr_regid[regid] = [all_observations.iloc[i].RegistrationName]
else:
obs_pr_regid[regid].append(all_observations.iloc[i].RegistrationName)
# list of all observations on this date
if all_observations.iloc[i].RegistrationName == 'Bilde':
if all_observations.iloc[i].TypicalValue1 == 'Bilde av: Snoeprofil':
obstyp.append('Snoeprofil')
else:
obstyp.append(all_observations.iloc[i].RegistrationName)
else:
obstyp.append(all_observations.iloc[i].RegistrationName)
# list of all regids - this counts occurances
regids.append(int(all_observations.iloc[i].RegID))
# list of all observers nickanmes - this counts occurances
nicks.append(all_observations.iloc[i].NickName)
# add to object for plotting
dd.add_loc_pr_regid(loc_pr_regid)
dd.add_obs_pr_regid(obs_pr_regid)
dd.add_nic_pr_regid(nic_pr_regid)
dd.add_observations(obstyp)
dd.add_regids(regids)
dd.add_nicks(nicks)
dates.append(dd)
if make_pickle:
mp.pickle_anything(dates, pickle_file_name)
else:
dates = mp.unpickle_anything(pickle_file_name)
return dates
self.RowNumber = d.RowNumber
self.GeoHazardName = d.GeoHazardName
self.RegistrationName = d.RegistrationName
self.TypicalValue1 = d.TypicalValue1
self.TypicalValue2 = d.TypicalValue2
self.LangKey = d.LangKey
self.Picture = d.Picture
if __name__ == "__main__":
from_date = dt.date(2016, 4, 1)
to_date = dt.date(2016, 5, 1)
region_ids = 116
all_data = go.get_all_registrations(from_date, to_date, region_ids)
Base.metadata.create_all()
Session = sessionmaker(bind=engine)
s = Session()
all_data_ny_mapping = []
for d in all_data:
all_data_ny_mapping.append(AllRegistrations(d))
s.add_all(all_data_ny_mapping)
s.commit()
a = 1