def setupData(self):
productionStartDate = Date(month=7,day=25,year=2013)
lastLoadDate = Date(month=10,day=14,year=2013)
loadDate = productionStartDate
if not Location.objects.filter(name='Benchmark').exists():
location = Location()
location.name = 'Benchmark'
location.pricingDate = date(month=10,day=14,year=2013)
location.save()
location = Location.objects.get(name='Benchmark')
if not User.objects.filter(username='******').exists():
user = User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
user.is_staff = True
user.is_superuser = True
user.save()
user1 = User.objects.get(username='******')
if not UserProfile.objects.filter(user=user1).exists():
up1 = UserProfile()
up1.user = user1
up1.location = location
up1.marketId = 'EOD'
up1.save()
equities = Equity.objects.all()
for equity in equities:
# print equity
if not Portfolio.objects.filter(name=equity.ticker, user='******').exists():
portfolio =Portfolio()
portfolio.name = equity.ticker
portfolio.user = '******'
portfolio.save()
portfolio = Portfolio.objects.get(name=equity.ticker, user='******')
timeSteps = VARUtilities.VARTimePeriodsAndSteps()
timeSteps.generate(start=productionStartDate, end=lastLoadDate, num=1,
term=Enum.TimePeriod('D'), calendar=Calendar.Target())
for loadDate in timeSteps.timeSteps:
if not ModelPosition.objects.filter(asOf=loadDate, portfolio=portfolio,
positionType = Enum.PositionType('EQUITY'),
ticker = equity.ticker, amount = 100.0).exists():
position = ModelPosition()
position.asOf=loadDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('EQUITY')
position.ticker = equity.ticker
position.amount = 100.0
position.save()
def load_locations_from_environ():
location_mapping = {}
for env_key, value in environ.items():
if 'COLLECTION_MAP_ID' in env_key:
map_file_id = environ.get(env_key.replace('MAP_ID', 'FILE_ID'))
location_mapping[value] = Location.load_locations_from_collection(
value, file_id=map_file_id)
return location_mapping
def google_mapping_to_csv(map_id):
locations = Location.load_locations_from_collection(map_id)
rows = [Location.SUPPORTED_ATTRIBUTES]
for location in locations:
rows.append(location.to_row())
with open(f'{map_id}.csv', 'w') as outfile:
writer = csv.writer(outfile)
writer.writerows(rows)
def get_closest_locations(map_id: str, locations: List, data: Dict):
"""
Gets closest locations for a query
:param map_id: ID for the map to lookup relevant locations
:param locations: array of Location for this map_id
:param data: injected request body that contains needed query info
:return: {zoom_level: int, closest_location: Location, locations: [Location]}
"""
query_location = Location(**data)
location_limit = min([data.get('limit', 20), 20])
sig_figs = max([data.get('sig_figs', 2), 0])
distances = []
for location in locations:
distances.append(
(query_location.distance(location), location.to_dict()))
sorted_distances = sorted(distances, key=lambda d: d[0])
# Adding distance to locations
index_counter = 0
for sd in sorted_distances:
distance = sd[0]
location = sd[1]
location['distance'] = round(distance, sig_figs)
location['index'] = index_counter
index_counter += 1
closest_location = sorted_distances[0]
zoom_level = Location.best_zoom_level(closest_location[0])
other_locations = [cl[1] for cl in sorted_distances[:location_limit]]
response = {
'zoom_level': zoom_level,
'query': data,
'closest_location': closest_location[1],
'locations': other_locations
}
return jsonify(response)
def get_locations(transactions: list) -> list:
"""
Extract a list of unique locations from the transactions list. Each
location is assigned a UUID string
Returns
-------
list
A list containing the unique locations as dictionaries
"""
locations = [
Location(id=str(get_uuid()), name=location)
for location in set(transaction["location"] for transaction in transactions)
]
return locations
def transform_google_rows(rows):
locations = []
for row in rows:
locations.append(Location(**{
'id': row[0],
'name': row[1],
'street': row[2],
'city': row[3],
'state': row[4],
'zipcode': row[5],
'formatted_address': row[6],
'phone': row[7],
'lat': float(row[8]),
'lng': float(row[9]),
'url': row[10]
}))
return locations
def run_geocodes(candidates):
locations = []
for candidate in candidates:
name = candidate[0]
street = candidate[1]
city = candidate[2]
state = candidate[3]
lat = 0 if not candidate[4] else float(candidate[4])
lng = 0 if not candidate[5] else float(candidate[5])
print(f'Getting geocoding for {name}')
results = google_location_search(name, city, state)
if len(results) == 0:
print(f'WARNING:: Could not find match for {name} in {city}, {state}')
continue
elif len(results) == 1:
result = results[0]
else:
result = pick_best_result(results, name, street, city, state, lat, lng)
location = Location.build_from_google_id(result['place_id'])
locations.append(location)
return locations
def location_save():
post = json.loads(request.data)
with database.connection_context():
location = Location.create(**post)
return {"success": True, "id": location.id}
import psycopg2
from src.db import *
from src.models import Complaint, Location, Incident
conn = psycopg2.connect(database = 'nypd_complaints', user = '******', password = '******')
cursor = conn.cursor()
drop_records(cursor, conn, 'complaints')
drop_records(cursor, conn, 'locations')
drop_records(cursor, conn, 'incidents')
complaint_one = Complaint(id = '1', desc_offense = 'GRAND LARCENY OF MOTOR VEHICLE', level_offense = 'GRAND LARCENY',
dept_juris = 'N.Y. POLICE DEPT')
complaint_two = Complaint(id = '2', desc_offense = 'MURDER & NON-NEGL. MANSLAUGHTER', level_offense = 'FELONY',
dept_juris = 'N.Y. HOUSING POLICE')
save(complaint_one, conn, cursor)
save(complaint_two, conn, cursor)
location_one = Location(id = '123', latitude = -73.91575750399994, longitude = -74.00629428799994, borough = 'MANHATTAN', precinct = 6, setting = 'STREET')
location_two = Location(id = '456', latitude = 40.69866511400005, longitude = -73.91575750399994, borough = '', precinct = 18, setting = '')
save(location_one, conn, cursor)
save(location_two, conn, cursor)
incident_one = Incident(id = '900', incident_num = 453437883, complaint_id = '1', incident_date = '09/16/2020', incident_time = '21:20:00', location_id = '123')
incident_two = Incident(id = '800', incident_num = 774568604, complaint_id = '2', incident_date = '09/02/2020', incident_time = '12:30:00', location_id = '456')
save(incident_one, conn, cursor)
save(incident_two, conn, cursor)
def test_get_locations(mock_get_uuid):
actual = get_locations(sample_raw_transaction)
assert mock_get_uuid.called_once()
assert actual == [Location(id=sample_uuid, name="Isle of Wight")]
def dataForProductionStart(self):
#Setup initial data for Tim's portfolios as of 7/24/13
productionStartDate = Date(month=7,day=25,year=2013)
if not Batch.objects.filter(batchDate=productionStartDate):
batch = Batch()
batch.batchDate = productionStartDate
batch.save()
if not Location.objects.filter(name='Manhasset').exists():
location = Location()
location.name = 'Manhasset'
location.pricingDate = date(month=7,day=25,year=2013)
location.save()
if not User.objects.filter(username='******').exists():
#Enter email password
User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
cmt = User.objects.get(username='******')
if not UserProfile.objects.filter(user=cmt).exists():
up2 = UserProfile()
up2.user = cmt
up2.location = Location.objects.get(name='Manhasset')
up2.marketId = 'EOD'
up2.save()
#if it exists then make sure Location is Manhasset
else:
profile = UserProfile.objects.get(user=cmt)
profile.location = Location.objects.get(name='Manhasset')
profile.marketId = 'EOD'
profile.save()
#Setup portfolios
portfolioData = (['401K','cmt'],['ChaseIRA','cmt'],
['TDIRA','cmt'],['TDPostTaxIRA','cmt'],
['Just2Trade','cmt'],['TDEmergency','cmt'])
for p in portfolioData:
if not Portfolio.objects.filter(name=p[0],user=p[1]):
portfolio =Portfolio()
portfolio.name = p[0]
portfolio.user = p[1]
portfolio.save()
#Setup Equities and Prices as of productionStartDate
dataSet = (('NEIAX',32.57),('PTTDX',10.78),('EFA',61.06),
('GSG',32.67),('SAN-E',26.7301),('VWO',40.19),
('VNQ', 71.17))
for data in dataSet:
if not Equity.objects.filter(ticker=data[0]).exists():
equity = Equity()
equity.ticker = data[0]
equity.assetType = Enum.AssetType('EQUITYUS')
equity.save()
equity = Equity.objects.get(ticker=data[0])
stockPrice = StockPrice()
stockPrice.equity = equity
stockPrice.pricingDate = productionStartDate
stockPrice.marketId = 'EOD'
stockPrice.mid = data[1]
stockPrice.save()
#Setup Bond identifiers and TCBonds as of productionStartDate
dataSet = (('PortAuth_4.00_JAN42','73358WGG3',Date(month=1,day=15,year=2012),Date(month=1,day=15,year=2042),0.04,),)
for data in dataSet:
if not Identifier.objects.filter(name=data[1],type=BondIdentifierType('CUSIP')):
identifier = Identifier()
identifier.name = data[1]
identifier.type = BondIdentifierType('CUSIP')
identifier.save()
for data in dataSet:
if not TCBond.objects.filter(name=data[0]):
tcBond = TCBond()
tcBond.name = data[0]
tcBond.identifiers = Identifier.objects.get(name=data[1],type=BondIdentifierType('CUSIP'))
tcBond.startDate = data[2].toPythonDate()
tcBond.endDate = data[3].toPythonDate()
tcBond.coupon = data[4]
tcBond.assetType = Enum.AssetType('NYMUNIBOND')
tcBond.save()
#Setup OAS for production start date
if not BondOAS.objects.filter(tCBond=TCBond.objects.get(name='PortAuth_4.00_JAN42'), marketId='EOD',pricingDate=productionStartDate):
bondOAS = BondOAS(tCBond=TCBond.objects.get(name='PortAuth_4.00_JAN42'), marketId='EOD',pricingDate=productionStartDate,mid=0.014)
bondOAS.save()
#Setup Rates
fredLoader = FREDLoader.FREDLoader()
fredLoader.loadLiborCurvesForSpecificDates(marketId='EOD', datesToLoadFor=[productionStartDate])
#Setup transactions
dataSet = (('401K','INIT','EQUITY','NEIAX',8758.407),
('401K','INIT','EQUITY','PTTDX',10746.441),
('ChaseIRA','INIT','EQUITY','EFA',633.37038),
('TDIRA','INIT','EQUITY','EFA',47),
('TDIRA','INIT','EQUITY','GSG',610),
('TDIRA','INIT','EQUITY','VWO',1050),
('TDIRA','INIT','CASH','Cash',11151.23),
('TDPostTaxIRA','INIT','EQUITY','EFA',560),
('TDPostTaxIRA','INIT','EQUITY','VNQ',170),
('TDPostTaxIRA','INIT','CASH','Cash',951.33),
('Just2Trade','INIT','EQUITY','GSG',300),
('Just2Trade','INIT','EQUITY','VWO',430),
('TDEmergency','INIT','BOND','PortAuth_4.00_JAN42',100),
('TDEmergency','INIT','CASH','Cash',201.01))
for data in dataSet:
if not Transaction.objects.filter(portfolio=Portfolio.objects.get(name=data[0]),
transactionType=TransactionType(data[1]),
positionType=PositionType(data[2]),
ticker=data[3],
amount=data[4],
transactionDate = productionStartDate,
effectiveDate = productionStartDate):
transaction = Transaction()
transaction.portfolio =Portfolio.objects.get(name=data[0])
transaction.transactionType = TransactionType(data[1])
transaction.positionType = PositionType(data[2])
transaction.ticker = data[3]
transaction.amount = data[4]
transaction.transactionDate = productionStartDate
transaction.effectiveDate = productionStartDate
transaction.reflectedInPosition = False
transaction.save()
def dataForSuccessfulTest(self):
'''
This saves all data so that system tests run successfully
Pricing date is 9/12/2011 with market data id TEST1
'''
testDatePython = date(month=9,day=12,year=2011)
testDate = Date(month=9,day=12,year=2011)
testFirstDate = Date(month=8,day=30,year=2011)
if not Location.objects.filter(name='Test1').exists():
location = Location()
location.name = 'Test1'
location.pricingDate = date(month=9,day=12,year=2011)
location.save()
location = Location.objects.get(name='Test1')
if not User.objects.filter(username='******').exists():
user = User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
user.is_staff = True
user.is_superuser = True
user.save()
if not User.objects.filter(username='******').exists():
User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
if not User.objects.filter(username='******').exists():
User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
if not User.objects.filter(username='******').exists():
User.objects.create_user(username='******',email='*****@*****.**',\
password='******')
user1 = User.objects.get(username='******')
if not UserProfile.objects.filter(user=user1).exists():
up1 = UserProfile()
up1.user = user1
up1.location = location
up1.marketId = 'EOD'
up1.save()
user2 = User.objects.get(username='******')
if not UserProfile.objects.filter(user=user2).exists():
up2 = UserProfile()
up2.user = user2
up2.location = location
up2.marketId = 'EOD'
up2.save()
user3 = User.objects.get(username='******')
if not UserProfile.objects.filter(user=user3).exists():
up3 = UserProfile()
up3.user = user3
up3.location = location
up3.marketId = 'TEST1'
up3.save()
user4 = User.objects.get(username='******')
if not UserProfile.objects.filter(user=user4).exists():
up4 = UserProfile()
up4.user = user4
up4.location = location
up4.marketId = 'DEMO'
up4.save()
if not TCBond.objects.filter(name='TEST1').exists():
bond = TCBond()
bond.name = 'TEST1'
bond.ccy = 'USD'
cusip = Enum.BondIdentifierType('CUSIP')
if not Identifier.objects.filter(name='123456789', type=cusip):
identifier = Identifier()
identifier.name='123456789'
identifier.type=cusip
identifier.save()
identifier = Identifier.objects.get(name='123456789', type=cusip)
bond.identifiers = identifier
bond.startDate = Date(month=9,day=12,year=2010).toPythonDate()
bond.endDate = Date(month=9,day=12,year=2020).toPythonDate()
bond.coupon = 0.01
bond.basis = '30360'
bond.paymentFrequency = Enum.Frequency('S')
bond.paymentRollRule = Enum.Roll('MF')
bond.paymentCalendar = Calendar.createCalendar('US')
bond.assetType = Enum.AssetType('NYMUNIBOND')
bond.save()
if not Equity.objects.filter(ticker='TEST1').exists():
equity = Equity()
equity.ticker = 'TEST1'
equity.assetType = Enum.AssetType('EQUITYUS')
equity.save()
equity = Equity.objects.get(ticker='TEST1')
stockPrice = StockPrice()
stockPrice.equity = equity
stockPrice.pricingDate = testDate
stockPrice.marketId = 'TEST1'
stockPrice.mid = 123.45
stockPrice.save()
equity = Equity.objects.get(ticker='TEST1')
stockPrice = StockPrice()
stockPrice.equity = equity
stockPrice.pricingDate = testFirstDate
stockPrice.marketId = 'TEST1'
stockPrice.mid = 123.44
stockPrice.save()
if not Equity.objects.filter(ticker='TEST2').exists():
equity = Equity()
equity.ticker = 'TEST2'
equity.assetType = Enum.AssetType('EQUITYUS')
equity.save()
equity = Equity.objects.get(ticker='TEST2')
stockPrice = StockPrice()
stockPrice.equity = equity
stockPrice.pricingDate = testDate
stockPrice.marketId = 'TEST1'
stockPrice.mid = 543.21
stockPrice.save()
equity = Equity.objects.get(ticker='TEST2')
stockPrice = StockPrice()
stockPrice.equity = equity
stockPrice.pricingDate = testFirstDate
stockPrice.marketId = 'TEST1'
stockPrice.mid = 543.11
stockPrice.save()
if not Portfolio.objects.filter(name='TEST1', user='******').exists():
portfolio =Portfolio()
portfolio.name = 'TEST1'
portfolio.user = '******'
portfolio.save()
portfolio =Portfolio.objects.get(name='TEST1', user='******')
if not ModelPosition.objects.filter(asOf=testDate, portfolio=portfolio,
positionType = Enum.PositionType('EQUITY'),
ticker = 'TEST1', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('EQUITY')
position.ticker = 'TEST1'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testDate, portfolio=portfolio,
positionType = Enum.PositionType('EQUITY'),
ticker = 'TEST2', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('EQUITY')
position.ticker = 'TEST2'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testDate, portfolio=portfolio,
positionType = Enum.PositionType('BOND'),
ticker = 'TEST1', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('BOND')
position.ticker = 'TEST1'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testFirstDate, portfolio=portfolio,
positionType = Enum.PositionType('EQUITY'),
ticker = 'TEST1', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testFirstDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('EQUITY')
position.ticker = 'TEST1'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testFirstDate, portfolio=portfolio,
positionType = Enum.PositionType('EQUITY'),
ticker = 'TEST2', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testFirstDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('EQUITY')
position.ticker = 'TEST2'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testFirstDate, portfolio=portfolio,
positionType = Enum.PositionType('BOND'),
ticker = 'TEST1', amount = 100.0).exists():
position = ModelPosition()
position.asOf=testFirstDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('BOND')
position.ticker = 'TEST1'
position.amount = 100.0
position.save()
if not ModelPosition.objects.filter(asOf=testFirstDate, portfolio=portfolio,
positionType = Enum.PositionType('CASH'),
ticker = 'Cash', amount = 1000.0).exists():
position = ModelPosition()
position.asOf=testFirstDate
position.portfolio = portfolio
position.positionType = Enum.PositionType('CASH')
position.ticker = 'Cash'
position.amount = 1000.0
position.save()
curve = InterestRateCurve()
curve.ccy = 'USD'
curve.index = Enum.Index('LIBOR')
curve.term = Enum.TimePeriod('M')
curve.numTerms = 3
curve.pricingDate =testDate
curve.marketId = 'TEST1'
curve.addRate(InterestRate(type='Deposit', term=Enum.TimePeriod('M'),
numTerms=1,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Deposit', term=Enum.TimePeriod('M'),
numTerms=3,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=1,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=5,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=10,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=30,mid=0.01,curve=curve))
curve.save()
curve = InterestRateCurve()
curve.ccy = 'USD'
curve.index = Enum.Index('LIBOR')
curve.term = Enum.TimePeriod('M')
curve.numTerms = 3
curve.pricingDate = testFirstDate
curve.marketId = 'TEST1'
curve.addRate(InterestRate(type='Deposit', term=Enum.TimePeriod('M'),
numTerms=1,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Deposit', term=Enum.TimePeriod('M'),
numTerms=3,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=1,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=5,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=10,mid=0.01,curve=curve))
curve.addRate(InterestRate(type='Swap', term=Enum.TimePeriod('Y'),
numTerms=30,mid=0.01,curve=curve))
curve.save()
if not SwaptionVolatilitySurface.objects.filter(ccy=Enum.Currency('USD'), index=Enum.Index('LIBOR'), term=Enum.TimePeriod('M'), numTerms=3,
pricingDate=testDate, marketId='TEST1'):
#Special case where I just append the vols. Should use a function
vols = SwaptionVolatilitySurface(ccy=Enum.Currency('USD'), index=Enum.Index('LIBOR'), term=Enum.TimePeriod('M'), numTerms=3,
pricingDate=testDate, marketId='TEST1')
volPoints = []
volPoints.append(SwaptionVolatility(expiryTerm=Enum.TimePeriod('Y'), expiryNumTerms=1, underlyingTerm=Enum.TimePeriod('Y'),
underlyingNumTerms=3, mid=0.40, surface=vols))
volPoints.append(SwaptionVolatility(expiryTerm=Enum.TimePeriod('Y'), expiryNumTerms=3, underlyingTerm=Enum.TimePeriod('Y'),
underlyingNumTerms=3, mid=0.45, surface=vols))
volPoints.append(SwaptionVolatility(expiryTerm=Enum.TimePeriod('Y'), expiryNumTerms=1, underlyingTerm=Enum.TimePeriod('Y'),
underlyingNumTerms=5, mid=0.5, surface=vols))
volPoints.append(SwaptionVolatility(expiryTerm=Enum.TimePeriod('Y'), expiryNumTerms=3, underlyingTerm=Enum.TimePeriod('Y'),
underlyingNumTerms=5, mid=0.55, surface=vols))
vols.addVolatilities(volPoints)
vols.save()
if not BondOAS.objects.filter(tCBond=TCBond.objects.get(name='TEST1'),pricingDate=testDate,
marketId='TEST1'):
bondOAS = BondOAS(tCBond=TCBond.objects.get(name='TEST1'),pricingDate=testDate,
marketId='TEST1',mid=0.0012)
bondOAS.save()
#done for only one test BondPositionTest.testLoadAndSaveMarketData
if not BondOAS.objects.filter(tCBond=TCBond.objects.get(name='TEST1'),pricingDate=Date(month=1,day=1,year=2009),
marketId='EOD'):
bondOAS = BondOAS(tCBond=TCBond.objects.get(name='TEST1'),pricingDate=Date(month=1,day=1,year=2009),
marketId='EOD',mid=0.01)
bondOAS.save()
#now load zero oas for all dates we do testing
timePeriods = VARUtilities.VARTimePeriodsAndSteps()
timePeriods.generate(start = Date(month=8,day=30,year=2011), end = Date(month=9,day=12,year=2011),
num = 1, term = Enum.TimePeriod('D'), calendar = Calendar.US())
for timeStep in timePeriods.timeSteps:
if not BondOAS.objects.filter(tCBond=TCBond.objects.get(name='TEST1'), pricingDate=timeStep, marketId='TEST1'):
bondOAS = BondOAS(tCBond=TCBond.objects.get(name='TEST1'), pricingDate=timeStep, marketId='TEST1',mid=0.0)
bondOAS.save()
fileLoader = MarketDataLoader.EquityPriceLoader()
fileLoader.loadStockPriceFromCSVFile(ROOT_PATH+'/misc/data/StockPricesForHVaRTests.csv')
fileLoader.loadInterestRateFromCSVFile(ROOT_PATH+'/misc/data/InterestRatesForHVaRTests.csv')
if not HvarConfiguration.objects.filter(name='TEST1').exists():
config = HvarConfiguration()
config.name = 'TEST1'
config.startDate = Date(month=8,day=30,year=2011).toPythonDate()
config.endDate = Date(month=9,day=12,year=2011).toPythonDate()
config.stepSize = 1
config.stepUnit = Enum.TimePeriod('D')
config.calendar = Calendar.US()
config.confLevel = 0.95
config.marketId = 'TEST1'
config.save()