def load_product_data(self, data_date, zfile):
""" Load the daily product data."""
filename = "%s_product.txt" % data_date
data_date = timezone.make_aware(
datetime.strptime(data_date, '%Y%m%d'),
timezone.get_current_timezone())
product_reader = reader(StringIO.StringIO(zfile.read(filename)), delimiter='\t')
#Skip the first row as it contains column documentation
iterproducts = iter(product_reader)
next(iterproducts)
products = []
total_products = 0
for row in iterproducts:
total_products += 1
p = Product()
p.plan_id = int(row[0])
p.institution = row[1]
p.loan_purpose = row[2]
p.pmt_type = row[3]
p.loan_type = row[4]
p.loan_term = int(row[5])
p.int_adj_term = self.nullable_int(row[6])
p.adj_period = self.nullable_int(row[7])
p.io = self.string_to_boolean(row[8])
p.arm_index = self.nullable_string(row[9])
p.int_adj_cap = self.nullable_int(row[10])
p.annual_cap = self.nullable_int(row[11])
p.loan_cap = self.nullable_int(row[12])
p.arm_margin = self.nullable_decimal(row[13])
p.ai_value = self.nullable_decimal(row[14])
p.min_ltv = float(row[15])
p.max_ltv = float(row[16])
p.min_fico = int(row[17])
p.max_fico = int(row[18])
p.min_loan_amt = Decimal(row[19])
p.max_loan_amt = Decimal(row[20])
p.data_timestamp = data_date
products.append(p)
if len(products) > 1000:
Product.objects.bulk_create(products)
products[:] = []
Product.objects.bulk_create(products)
if not total_products or Product.objects.count() != total_products:
raise OaHException("Couldn't load product data from %s" % zfile.filename)
def setUp(self):
self.url = '/oah-api/rates/rate-checker'
REGIONS = [[1, 'DC'], [2, 'VA']]
PRODUCTS = [
# plan_id, institution, loan_purpose, pmt_type, loan_type, loan_term, int_adj_term, _, io, _, _, _, _, _, _,
# min_ltv, max_ltv, minfico, maxfico, min_loan_amt, max_loan_amt, single_family, condo, coop
[
11, 'Institution 1', 'PURCH', 'FIXED', 'CONF', 30, None, None,
0, None, None, None, None, None, None, 1, 95, 680, 700, 90000,
750000, 1, 0, 0
],
[
22, 'Institution 2', 'PURCH', 'FIXED', 'CONF', 30, None, None,
0, None, None, None, None, None, None, 1, 87, 680, 740, 90000,
550000, 1, 0, 0
],
[
33, 'Institution 3', 'PURCH', 'ARM', 'CONF', 15, 5, None, 0,
None, None, None, None, None, None, 1, 95, 680, 740, 90000,
550000, 1, 0, 0
],
[
44, 'Institution 4', 'PURCH', 'FIXED', 'CONF', 30, None, None,
0, None, None, None, None, None, None, 1, 87, 680, 740, 90000,
550000, 1, 0, 0
],
[
55, 'Institution 5', 'PURCH', 'ARM', 'CONF', 30, 5, None, 0,
None, None, None, None, None, None, 1, 87, 680, 740, 90000,
550000, 1, 0, 0
],
[
66, 'Institution 6', 'PURCH', 'FIXED', 'CONF', 30, None, None,
0, None, None, None, None, None, None, 1, 87, 680, 740, 90000,
550000, 1, 0, 0
],
[
77, 'Institution 7', 'PURCH', 'FIXED', 'FHA-HB', 15, None,
None, 0, None, None, None, None, None, None, 1, 87, 680, 740,
90000, 550000, 1, 0, 0
],
[
88, 'Institution 8', 'PURCH', 'FIXED', 'FHA', 30, None, None,
0, None, None, None, None, None, None, 1, 87, 680, 740, 90000,
550000, 1, 0, 0
],
]
RATES = [
# rate_id, product_id, region_id, lock, base_rate, total_points
[111, 11, 1, 50, '3.150', '0.5'],
[112, 11, 2, 60, '4.350', '-0.5'],
[113, 11, 1, 60, '2.125', '0.125'],
[221, 22, 1, 60, '3.555', '0.125'],
[331, 33, 1, 60, '3.250', '0.125'],
[332, 33, 2, 60, '4.650', '-0.5'],
[441, 44, 1, 50, '3.125', '1.25'],
[551, 55, 1, 50, '0.125', '0.125'],
[661, 66, 1, 60, '3.705', '0.5'],
[771, 77, 2, 60, '1.705', '0.25'],
[772, 77, 2, 60, '2.705', '1.25'],
[881, 88, 1, 60, '3.000', '0.5'],
[882, 88, 1, 60, '2.005', '0.25'],
[883, 88, 1, 60, '1.005', '-0.25'],
]
ADJUSTMENTS = [
# rule_id, product_id, affect_rate_type, adj_value, min_loan_amt, max_loan_amt
# prop_type, minfico, maxfico, minltv, maxltv, state
[
1, 11, 'P', '-0.35', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'DC'
],
[
2, 11, 'P', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'DC'
],
[
3, 11, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'DC'
],
[
4, 22, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'VA'
],
[
5, 22, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'DC'
],
[
6, 33, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'DC'
],
[
7, 77, 'P', '0.125', 100000, 500000, 'CONDO', 660, 780, 30, 95,
'VA'
],
]
FEES = [
# plan_id, product_id, state_id, lender , single_family, condo, coop,
# origination_dollar, origination_percent, third_party
[11, 11111, 'DC', 'SMPL', 1, 1, 1, 1608.0000, .000, 587.2700],
[11, 11111, 'DC', 'SMPL1', 1, 0, 1, 1610.0000, .000, 589.2700],
[10, 11001, 'DC', 'SMPL1', 0, 1, 0, 1610.0000, .000, 589.2700],
[11, 11111, 'VA', 'SMPL2', 1, 1, 1, 1610.0000, .000, 589.2700],
]
NOW = timezone.now()
for region in REGIONS:
reg = Region(region_id=region[0],
state_id=region[1],
data_timestamp=NOW)
reg.save()
for p in PRODUCTS:
product = Product(plan_id=p[0],
institution=p[1],
loan_purpose=p[2],
pmt_type=p[3],
loan_type=p[4],
loan_term=p[5],
int_adj_term=p[6],
adj_period=p[7],
io=p[8],
arm_index=p[9],
int_adj_cap=p[10],
annual_cap=p[11],
loan_cap=p[12],
arm_margin=p[13],
ai_value=p[14],
min_ltv=p[15],
max_ltv=p[16],
min_fico=p[17],
max_fico=p[18],
min_loan_amt=p[19],
max_loan_amt=p[20],
single_family=p[21],
condo=p[22],
coop=p[23],
data_timestamp=NOW)
product.save()
for r in RATES:
rate = Rate(rate_id=r[0],
product_id=r[1],
region_id=r[2],
lock=r[3],
base_rate=r[4],
total_points=r[5],
data_timestamp=NOW)
rate.save()
for a in ADJUSTMENTS:
adjustment = Adjustment(rule_id=a[0],
product_id=a[1],
affect_rate_type=a[2],
adj_value=a[3],
min_loan_amt=a[4],
max_loan_amt=a[5],
prop_type=a[6],
min_fico=a[7],
max_fico=a[8],
min_ltv=a[9],
max_ltv=a[10],
state=a[11],
data_timestamp=NOW)
adjustment.save()
for f in FEES:
fee = Fee(plan_id=f[0],
product_id=f[1],
state_id=f[2],
lender=f[3],
single_family=f[4],
condo=f[5],
coop=f[6],
origination_dollar=Decimal("%s" % f[7]),
origination_percent=Decimal("%s" % f[8]),
third_party=Decimal("%s" % f[9]),
data_timestamp=NOW)
fee.save()
def create_product(self, row):
""" Helper function to save a product."""
p = Product()
p.plan_id = int(row[0])
p.institution = row[1]
p.loan_purpose = row[2]
p.pmt_type = row[3]
p.loan_type = row[4]
p.loan_term = int(row[5])
p.int_adj_term = self.c.nullable_int(row[6])
p.adj_period = self.c.nullable_int(row[7])
p.io = self.c.string_to_boolean(row[8])
p.arm_index = self.c.nullable_string(row[9])
p.int_adj_cap = self.c.nullable_int(row[10])
p.annual_cap = self.c.nullable_int(row[11])
p.loan_cap = self.c.nullable_int(row[12])
p.arm_margin = self.c.nullable_decimal(row[13])
p.ai_value = self.c.nullable_decimal(row[14])
p.min_ltv = float(row[15])
p.max_ltv = float(row[16])
p.min_fico = int(row[17])
p.max_fico = int(row[18])
p.min_loan_amt = Decimal(row[19])
p.max_loan_amt = Decimal(row[20])
p.data_timestamp = datetime.strptime('20140101', '%Y%m%d')
p.save()
return p
def load_product_data(self, data_date, product_filename):
""" Load the daily product data."""
with open(product_filename) as product_csv:
product_reader = reader(product_csv, delimiter="\t")
# Skip the first row as it contains column documentation
iterproducts = iter(product_reader)
next(iterproducts)
products = []
for row in iterproducts:
p = Product()
p.plan_id = int(row[0])
p.institution = row[1]
p.loan_purpose = row[2]
p.pmt_type = row[3]
p.loan_type = row[4]
p.loan_term = int(row[5])
p.int_adj_term = self.nullable_int(row[6])
p.adj_period = self.nullable_int(row[7])
p.io = self.string_to_boolean(row[8])
p.arm_index = self.nullable_string(row[9])
p.int_adj_cap = self.nullable_int(row[10])
p.annual_cap = self.nullable_int(row[11])
p.loan_cap = self.nullable_int(row[12])
p.arm_margin = self.nullable_decimal(row[13])
p.ai_value = self.nullable_decimal(row[14])
p.min_ltv = float(row[15])
p.max_ltv = float(row[16])
p.min_fico = int(row[17])
p.max_fico = int(row[18])
p.min_loan_amt = Decimal(row[19])
p.max_loan_amt = Decimal(row[20])
p.data_timestamp = data_date
products.append(p)
if len(products) > 1000:
Product.objects.bulk_create(products)
products[:] = []
Product.objects.bulk_create(products)
def setUp(self):
self.url = "/oah-api/rates/rate-checker"
REGIONS = [[1, "DC"], [2, "VA"]]
PRODUCTS = [
# plan_id, institution, loan_purpose, pmt_type, loan_type, loan_term, int_adj_term, _, io, _, _, _, _, _, _, # noqa
# min_ltv, max_ltv, minfico, maxfico, min_loan_amt, max_loan_amt, single_family, condo, coop # noqa
[
11,
"Institution 1",
"PURCH",
"FIXED",
"CONF",
30,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
95,
680,
700,
90000,
750000,
1,
0,
0,
],
[
22,
"Institution 2",
"PURCH",
"FIXED",
"CONF",
30,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
[
33,
"Institution 3",
"PURCH",
"ARM",
"CONF",
15,
5,
None,
0,
None,
None,
None,
None,
None,
None,
1,
95,
680,
740,
90000,
550000,
1,
0,
0,
],
[
44,
"Institution 4",
"PURCH",
"FIXED",
"CONF",
30,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
[
55,
"Institution 5",
"PURCH",
"ARM",
"CONF",
30,
5,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
[
66,
"Institution 6",
"PURCH",
"FIXED",
"CONF",
30,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
[
77,
"Institution 7",
"PURCH",
"FIXED",
"FHA-HB",
15,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
[
88,
"Institution 8",
"PURCH",
"FIXED",
"FHA",
30,
None,
None,
0,
None,
None,
None,
None,
None,
None,
1,
87,
680,
740,
90000,
550000,
1,
0,
0,
],
]
RATES = [
# rate_id, product_id, region_id, lock, base_rate, total_points
[111, 11, 1, 50, "3.150", "0.5"],
[112, 11, 2, 60, "4.350", "-0.5"],
[113, 11, 1, 60, "2.125", "0.125"],
[221, 22, 1, 60, "3.555", "0.125"],
[331, 33, 1, 60, "3.250", "0.125"],
[332, 33, 2, 60, "4.650", "-0.5"],
[441, 44, 1, 50, "3.125", "1.25"],
[551, 55, 1, 50, "0.125", "0.125"],
[661, 66, 1, 60, "3.705", "0.5"],
[771, 77, 2, 60, "1.705", "0.25"],
[772, 77, 2, 60, "2.705", "1.25"],
[881, 88, 1, 60, "3.000", "0.5"],
[882, 88, 1, 60, "2.005", "0.25"],
[883, 88, 1, 60, "1.005", "-0.25"],
]
ADJUSTMENTS = [
# rule_id, product_id, affect_rate_type, adj_value, min_loan_amt,
# max_loan_amt, prop_type, minfico, maxfico, minltv, maxltv, state
[
1,
11,
"P",
"-0.35",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"DC",
],
[
2,
11,
"P",
"0.25",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"DC",
],
[
3,
11,
"R",
"0.15",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"DC",
],
[
4,
22,
"R",
"0.25",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"VA",
],
[
5,
22,
"R",
"0.15",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"DC",
],
[
6,
33,
"R",
"0.25",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"DC",
],
[
7,
77,
"P",
"0.125",
100000,
500000,
"CONDO",
660,
780,
30,
95,
"VA",
],
]
NOW = timezone.now()
for region in REGIONS:
reg = Region(region_id=region[0],
state_id=region[1],
data_timestamp=NOW)
reg.save()
for p in PRODUCTS:
product = Product(
plan_id=p[0],
institution=p[1],
loan_purpose=p[2],
pmt_type=p[3],
loan_type=p[4],
loan_term=p[5],
int_adj_term=p[6],
adj_period=p[7],
io=p[8],
arm_index=p[9],
int_adj_cap=p[10],
annual_cap=p[11],
loan_cap=p[12],
arm_margin=p[13],
ai_value=p[14],
min_ltv=p[15],
max_ltv=p[16],
min_fico=p[17],
max_fico=p[18],
min_loan_amt=p[19],
max_loan_amt=p[20],
single_family=p[21],
condo=p[22],
coop=p[23],
data_timestamp=NOW,
)
product.save()
for r in RATES:
rate = Rate(
rate_id=r[0],
product_id=r[1],
region_id=r[2],
lock=r[3],
base_rate=r[4],
total_points=r[5],
data_timestamp=NOW,
)
rate.save()
for a in ADJUSTMENTS:
adjustment = Adjustment(
rule_id=a[0],
product_id=a[1],
affect_rate_type=a[2],
adj_value=a[3],
min_loan_amt=a[4],
max_loan_amt=a[5],
prop_type=a[6],
min_fico=a[7],
max_fico=a[8],
min_ltv=a[9],
max_ltv=a[10],
state=a[11],
data_timestamp=NOW,
)
adjustment.save()
def load_product_data(self, data_date, zfile):
""" Load the daily product data."""
filename = "%s_product.txt" % data_date
data_date = timezone.make_aware(datetime.strptime(data_date, '%Y%m%d'),
timezone.get_current_timezone())
product_reader = reader(StringIO.StringIO(zfile.read(filename)),
delimiter='\t')
#Skip the first row as it contains column documentation
iterproducts = iter(product_reader)
next(iterproducts)
products = []
total_products = 0
for row in iterproducts:
total_products += 1
p = Product()
p.plan_id = int(row[0])
p.institution = row[1]
p.loan_purpose = row[2]
p.pmt_type = row[3]
p.loan_type = row[4]
p.loan_term = int(row[5])
p.int_adj_term = self.nullable_int(row[6])
p.adj_period = self.nullable_int(row[7])
p.io = self.string_to_boolean(row[8])
p.arm_index = self.nullable_string(row[9])
p.int_adj_cap = self.nullable_int(row[10])
p.annual_cap = self.nullable_int(row[11])
p.loan_cap = self.nullable_int(row[12])
p.arm_margin = self.nullable_decimal(row[13])
p.ai_value = self.nullable_decimal(row[14])
p.min_ltv = Decimal(row[15]).quantize(Decimal('.001'))
p.max_ltv = Decimal(row[16]).quantize(Decimal('.001'))
p.min_fico = int(row[17])
p.max_fico = int(row[18])
p.min_loan_amt = Decimal(row[19])
p.max_loan_amt = Decimal(row[20])
p.data_timestamp = data_date
products.append(p)
if len(products) > 1000:
Product.objects.bulk_create(products)
products[:] = []
Product.objects.bulk_create(products)
if not total_products or Product.objects.count() != total_products:
raise OaHException("Couldn't load product data from %s" %
zfile.filename)
def setUp(self):
self.url = '/oah-api/rates/rate-checker'
REGIONS = [[1, 'DC'], [2, 'VA']]
PRODUCTS = [
# plan_id, institution, loan_purpose, pmt_type, loan_type, loan_term, int_adj_term, _, io, _, _, _, _, _, _,
# min_ltv, max_ltv, minfico, maxfico, min_loan_amt, max_loan_amt, single_family, condo, coop
[11, 'Institution 1', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 95, 680, 700, 90000, 750000, 1, 0, 0],
[22, 'Institution 2', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[33, 'Institution 3', 'PURCH', 'ARM', 'CONF', 15, 5, None, 0, None, None, None, None, None, None, 1, 95, 680, 740, 90000, 550000, 1, 0, 0],
[44, 'Institution 4', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[55, 'Institution 5', 'PURCH', 'ARM', 'CONF', 30, 5, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[66, 'Institution 6', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[77, 'Institution 7', 'PURCH', 'FIXED', 'FHA-HB', 15, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[88, 'Institution 8', 'PURCH', 'FIXED', 'FHA', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
]
RATES = [
# rate_id, product_id, region_id, lock, base_rate, total_points
[111, 11, 1, 50, '3.150', '0.5'],
[112, 11, 2, 60, '4.350', '-0.5'],
[113, 11, 1, 60, '2.125', '0.125'],
[221, 22, 1, 60, '3.555', '0.125'],
[331, 33, 1, 60, '3.250', '0.125'],
[332, 33, 2, 60, '4.650', '-0.5'],
[441, 44, 1, 50, '3.125', '1.25'],
[551, 55, 1, 50, '0.125', '0.125'],
[661, 66, 1, 60, '3.705', '0.5'],
[771, 77, 2, 60, '1.705', '0.25'],
[772, 77, 2, 60, '2.705', '1.25'],
[881, 88, 1, 60, '3.000', '0.5'],
[882, 88, 1, 60, '2.005', '0.25'],
[883, 88, 1, 60, '1.005', '-0.25'],
]
ADJUSTMENTS = [
# rule_id, product_id, affect_rate_type, adj_value, min_loan_amt, max_loan_amt
# prop_type, minfico, maxfico, minltv, maxltv, state
[1, 11, 'P', '-0.35', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[2, 11, 'P', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[3, 11, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[4, 22, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'VA'],
[5, 22, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[6, 33, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[7, 77, 'P', '0.125', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'VA'],
]
NOW = timezone.now()
for region in REGIONS:
reg = Region(region_id=region[0], state_id=region[1], data_timestamp=NOW)
reg.save()
for p in PRODUCTS:
product = Product(
plan_id=p[0], institution=p[1], loan_purpose=p[2], pmt_type=p[3],
loan_type=p[4], loan_term=p[5], int_adj_term=p[6], adj_period=p[7], io=p[8],
arm_index=p[9], int_adj_cap=p[10], annual_cap=p[11], loan_cap=p[12], arm_margin=p[13],
ai_value=p[14], min_ltv=p[15], max_ltv=p[16], min_fico=p[17], max_fico=p[18],
min_loan_amt=p[19], max_loan_amt=p[20], single_family=p[21], condo=p[22],
coop=p[23], data_timestamp=NOW
)
product.save()
for r in RATES:
rate = Rate(
rate_id=r[0], product_id=r[1], region_id=r[2], lock=r[3], base_rate=r[4],
total_points=r[5], data_timestamp=NOW
)
rate.save()
for a in ADJUSTMENTS:
adjustment = Adjustment(
rule_id=a[0], product_id=a[1], affect_rate_type=a[2],
adj_value=a[3], min_loan_amt=a[4], max_loan_amt=a[5], prop_type=a[6],
min_fico=a[7], max_fico=a[8], min_ltv=a[9], max_ltv=a[10], state=a[11],
data_timestamp=NOW
)
adjustment.save()
def create_product(self, row):
""" Helper function to save a product."""
p = Product()
p.plan_id = int(row[0])
p.institution = row[1]
p.loan_purpose = row[2]
p.pmt_type = row[3]
p.loan_type = row[4]
p.loan_term = int(row[5])
p.int_adj_term = self.c.nullable_int(row[6])
p.adj_period = self.c.nullable_int(row[7])
p.io = self.c.string_to_boolean(row[8])
p.arm_index = self.c.nullable_string(row[9])
p.int_adj_cap = self.c.nullable_int(row[10])
p.annual_cap = self.c.nullable_int(row[11])
p.loan_cap = self.c.nullable_int(row[12])
p.arm_margin = self.c.nullable_decimal(row[13])
p.ai_value = self.c.nullable_decimal(row[14])
p.min_ltv = Decimal(row[15]).quantize(Decimal('.001'))
p.max_ltv = Decimal(row[16]).quantize(Decimal('.001'))
p.min_fico = int(row[17])
p.max_fico = int(row[18])
p.min_loan_amt = Decimal(row[19])
p.max_loan_amt = Decimal(row[20])
p.data_timestamp = datetime.strptime('20140101', '%Y%m%d')
p.save()
return p
def setUp(self):
REGIONS = [[1, 'DC'], [2, 'VA'], [3, 'MD']]
PRODUCTS = [
# plan_id, institution, loan_purpose, pmt_type, loan_type, loan_term, int_adj_term, _, io, _, _, _, _, _, _,
# min_ltv, max_ltv, minfico, maxfico, min_loan_amt, max_loan_amt, single_family, condo, coop
[11, 'Institution 1', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 95, 680, 700, 90000, 750000, 1, 0, 0],
[22, 'Institution 2', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[33, 'Institution 3', 'PURCH', 'ARM', 'CONF', 15, 5, None, 0, None, None, None, None, None, None, 1, 95, 680, 740, 90000, 550000, 1, 0, 0],
[44, 'Institution 4', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[55, 'Institution 5', 'PURCH', 'ARM', 'CONF', 30, 5, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[66, 'Institution 6', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[77, 'Institution 7', 'PURCH', 'FIXED', 'FHA-HB', 15, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[88, 'Institution 8', 'PURCH', 'FIXED', 'FHA', 30, None, None, 0, None, None, None, None, None, None, 1, 87, 680, 740, 90000, 550000, 1, 0, 0],
[98, 'Institution 8', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 95, 680, 740, 90000, 550000, 1, 1, 0],
[99, 'Institution 8', 'PURCH', 'FIXED', 'CONF', 30, None, None, 0, None, None, None, None, None, None, 1, 90, 680, 740, 90000, 550000, 1, 1, 0],
]
RATES = [
# rate_id, product_id, region_id, lock, base_rate, total_points
[111, 11, 1, 50, '3.150', '0.5'],
[112, 11, 2, 60, '4.350', '-0.5'],
[113, 11, 1, 60, '2.125', '0.125'],
[221, 22, 1, 60, '3.555', '0.125'],
[331, 33, 1, 60, '3.250', '0.125'],
[332, 33, 2, 60, '4.650', '-0.5'],
[441, 44, 1, 50, '3.125', '1.25'],
[551, 55, 1, 50, '0.125', '0.125'],
[661, 66, 1, 60, '3.705', '0.5'],
[771, 77, 2, 60, '1.705', '0.25'],
[772, 77, 2, 60, '2.705', '1.25'],
[881, 88, 1, 60, '3.000', '0.5'],
[882, 88, 1, 60, '2.005', '0.25'],
[883, 88, 1, 60, '1.005', '-0.25'],
[884, 98, 3, 60, '3.000', '0.5'],
[885, 98, 3, 60, '2.985', '0'],
[886, 98, 3, 60, '1.985', '-0.25'],
[887, 99, 3, 60, '3.000', '0.5'],
[888, 99, 3, 60, '2.995', '0'],
[889, 99, 3, 60, '1.995', '-0.25'],
]
ADJUSTMENTS = [
# rule_id, product_id, affect_rate_type, adj_value, min_loan_amt, max_loan_amt
# prop_type, minfico, maxfico, minltv, maxltv, state
[1, 11, 'P', '-0.35', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[2, 11, 'P', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[3, 11, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[4, 22, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'VA'],
[5, 22, 'R', '0.15', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[6, 33, 'R', '0.25', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'DC'],
[7, 77, 'P', '0.125', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'VA'],
[8, 98, 'P', '0.125', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'MD'],
[9, 99, 'P', '0.125', 100000, 500000, 'CONDO', 660, 780, 30, 95, 'MD'],
]
FEES = [
# plan_id, product_id, state_id, lender , single_family, condo, coop,
# origination_dollar, origination_percent, third_party
[11, 88, 'DC', 'Institution 8', 1, 1, 1, 1608.0000, .000, 587.2700],
[11, 88, 'DC', 'Institution 8', 1, 0, 1, 1612.0000, .000, 591.2700],
[10, 88, 'DC', 'Institution 8', 0, 1, 0, 1610.0000, .000, 589.2700],
[11, 87, 'VA', 'Institution 7', 1, 1, 1, 1610.0000, .000, 589.2700],
]
self.NOW = timezone.now()
NOW = self.NOW
for region in REGIONS:
reg = Region(region_id=region[0], state_id=region[1], data_timestamp=NOW)
reg.save()
for p in PRODUCTS:
product = Product(
plan_id=p[0], institution=p[1], loan_purpose=p[2], pmt_type=p[3],
loan_type=p[4], loan_term=p[5], int_adj_term=p[6], adj_period=p[7], io=p[8],
arm_index=p[9], int_adj_cap=p[10], annual_cap=p[11], loan_cap=p[12], arm_margin=p[13],
ai_value=p[14], min_ltv=p[15], max_ltv=p[16], min_fico=p[17], max_fico=p[18],
min_loan_amt=p[19], max_loan_amt=p[20], single_family=p[21], condo=p[22],
coop=p[23], data_timestamp=NOW
)
product.save()
for r in RATES:
rate = Rate(
rate_id=r[0], product_id=r[1], region_id=r[2], lock=r[3], base_rate=r[4],
total_points=r[5], data_timestamp=NOW
)
rate.save()
for a in ADJUSTMENTS:
adjustment = Adjustment(
rule_id=a[0], product_id=a[1], affect_rate_type=a[2],
adj_value=a[3], min_loan_amt=a[4], max_loan_amt=a[5], prop_type=a[6],
min_fico=a[7], max_fico=a[8], min_ltv=a[9], max_ltv=a[10], state=a[11],
data_timestamp=NOW
)
adjustment.save()
for f in FEES:
fee = Fee(
plan_id=f[0], product_id=f[1], state_id=f[2], lender=f[3], single_family=f[4],
condo=f[5], coop=f[6], origination_dollar=Decimal("%s" % f[7]),
origination_percent=Decimal("%s" % f[8]), third_party=Decimal("%s" % f[9]),
data_timestamp=NOW
)
fee.save()