def register(cls):
'''Utility for registering the managers to the current backend.
This should be used with care in parallel testing. All registered models
will be unregistered after the :meth:`tearDown` method.'''
if cls.backend:
for model in cls.models:
odm.register(model, cls.backend)
from datetime import date
from stdnet import odm
from stdnet.contrib.timeseries.models import TimeSeries
class FinanceTimeSeries(TimeSeries):
ticker = odm.SymbolField(unique=True)
def __unicode__(self):
return '%s - %s' % (self.ticker, self.data.size())
if __name__ == '__main__':
odm.register(FinanceTimeSeries)
ts = FinanceTimeSeries(ticker='GOOG').save()
ts.data[date(2010, 2, 25)] = 610.5
ts.save()
from stdnet import odm
from stdnet.odm.fields import SymbolField, CharField, IntegerField, DateTimeField
from stdnet.odm.models import StdModel
from config import Config
class Mirror(StdModel):
name = SymbolField(unique=True)
age = IntegerField(index=True)
lat = CharField()
lon = CharField()
def __unicode__(self):
return u"{self.name} -> {self.lat}:{self.lon}".format(self=self)
@staticmethod
def get_nearest_mirror(address):
from distance import DistanceCalculator
return DistanceCalculator().get_nearest_mirror(address)
@staticmethod
def get_mirror_distances(address):
from distance import DistanceCalculator, GeoIPLookupError
try:
return DistanceCalculator().get_mirror_distances(address)
except GeoIPLookupError:
return {}
odm.register(Mirror, Config.STDNET_DB_URL)
from datetime import date
from stdnet import odm
from stdnet.contrib.timeseries.models import TimeSeries
class FinanceTimeSeries(TimeSeries):
ticker = odm.SymbolField(unique = True)
def __unicode__(self):
return '%s - %s' % (self.ticker,self.data.size())
if __name__ == '__main__':
odm.register(FinanceTimeSeries)
ts = FinanceTimeSeries(ticker = 'GOOG').save()
ts.data[date(2010,2,25)] = 610.5
ts.save()
