def test_biased_high_only(self):
fake_uniform = lambda low, high: low + high
fuzz = fuzzy.FuzzyFloat(8.0)
with mock.patch('factory.random.randgen.uniform', fake_uniform):
res = utils.evaluate_declaration(fuzz)
self.assertEqual(8.0, res)
def test_default_precision(self):
fake_uniform = lambda low, high: low + high + 0.000000000000011
fuzz = fuzzy.FuzzyFloat(8.0)
with mock.patch('factory.random.randgen.uniform', fake_uniform):
res = utils.evaluate_declaration(fuzz)
self.assertEqual(8.00000000000001, res)
class AssetStateFactory(Factory):
class Meta:
model = AssetState
id = Sequence(lambda x: x)
asset = SubFactory(AssetFactory)
start = fuzzy.FuzzyDate(START_DATE, END_DATE)
end = LazyAttribute(lambda x: x.start + timedelta(minutes=DEFAULT_MIN_DURATION))
available = True
charge = fuzzy.FuzzyFloat(MIN, MAX)
class InvoiceItemFactory(factory.DjangoModelFactory):
class Meta:
model = InvoiceItem
invoice = factory.SubFactory('invoices.test.factories.InvoiceFactory')
name = factory.Faker('job', locale='bg_BG')
measure = fuzzy.FuzzyChoice(["hours", "weeks"])
quantity = fuzzy.FuzzyInteger(1, 164)
unit_price = fuzzy.FuzzyFloat(5.5, 1000.4)
discount = 0
def test_definition(self):
"""Tests all ways of defining a FuzzyFloat."""
fuzz = fuzzy.FuzzyFloat(2.0, 3.0)
for _i in range(20):
res = utils.evaluate_declaration(fuzz)
self.assertTrue(2.0 <= res <= 3.0,
"value %d is not between 2.0 and 3.0" % res)
fuzz = fuzzy.FuzzyFloat(4.0)
for _i in range(20):
res = utils.evaluate_declaration(fuzz)
self.assertTrue(0.0 <= res <= 4.0,
"value %d is not between 0.0 and 4.0" % res)
fuzz = fuzzy.FuzzyDecimal(1.0, 4.0, precision=5)
for _i in range(20):
res = utils.evaluate_declaration(fuzz)
self.assertTrue(1.0 <= res <= 4.0,
"value %d is not between 1.0 and 4.0" % res)
self.assertTrue(res.as_tuple().exponent, -5)
class ContentTypeFactory(factory.DjangoModelFactory):
class Meta:
model = EnevoContentType
id = factory.Sequence(lambda n: n)
category = fuzzy.FuzzyInteger(0, 50)
category_name = fuzzy.FuzzyText(length=30)
name = fuzzy.FuzzyText(length=30)
state = fuzzy.FuzzyText(length=30)
weight_to_volume_ratio = fuzzy.FuzzyFloat(0.5, 100.0)
last_modified = fuzzy.FuzzyDateTime(start_dt=timezone.now())
class PayloadVersion1(factory.DictFactory):
id = factory.Faker('uuid4')
passageAt = factory.LazyFunction(timezone.now)
version = "passage-v1"
straat = factory.Faker('name')
rijstrook = fuzzy.FuzzyInteger(1, 10)
rijrichting = fuzzy.FuzzyChoice((-1, 1))
cameraId = factory.Faker('uuid4')
cameraNaam = factory.Faker('first_name')
cameraKijkrichting = fuzzy.FuzzyFloat(0, 360)
cameraLocatie = factory.LazyFunction(get_point_in_amsterdam_as_json)
kentekenLand = fuzzy.FuzzyText(length=2)
kentekenNummerBetrouwbaarheid = fuzzy.FuzzyInteger(1, 1000)
kentekenLandBetrouwbaarheid = fuzzy.FuzzyInteger(1, 1000)
kentekenKaraktersBetrouwbaarheid = factory.LazyFunction(
kenteken_karakter_betrouwbaarheid
)
indicatieSnelheid = fuzzy.FuzzyFloat(0, 500)
automatischVerwerkbaar = factory.Faker('boolean', chance_of_getting_true=50)
voertuigSoort = fuzzy.FuzzyChoice(VOERTUIG_SOORTEN)
merk = factory.Faker('first_name')
inrichting = factory.Faker('first_name')
datumEersteToelating = fuzzy.FuzzyDate(datetime.date(2008, 1, 1))
datumTenaamstelling = fuzzy.FuzzyDate(datetime.date(2008, 1, 1))
toegestaneMaximumMassaVoertuig = fuzzy.FuzzyInteger(1, 32000)
europeseVoertuigcategorie = fuzzy.FuzzyText(length=2)
europeseVoertuigcategorieToevoeging = fuzzy.FuzzyText(length=1)
taxiIndicator = factory.Faker('boolean', chance_of_getting_true=50)
maximaleConstructieSnelheidBromsnorfiets = fuzzy.FuzzyInteger(0, 500)
brandstoffen = factory.LazyFunction(get_brandstoffen_v1)
extraData = {}
diesel = factory.LazyAttribute(
lambda self: int('Diesel' in {x['brandstof'] for x in self.brandstoffen})
)
gasoline = factory.LazyAttribute(
lambda self: int('Benzine' in {x['brandstof'] for x in self.brandstoffen})
)
electric = factory.LazyAttribute(
lambda self: int('Elektriciteit' in {x['brandstof'] for x in self.brandstoffen})
)
versitKlasse = fuzzy.FuzzyText()
class StationFactory(factory.django.DjangoModelFactory):
"""Station model factory."""
owner = factory.SubFactory(UserFactory)
name = fuzzy.FuzzyText()
image = factory.django.ImageField()
alt = fuzzy.FuzzyInteger(0, 800)
lat = fuzzy.FuzzyFloat(-20, 70)
lng = fuzzy.FuzzyFloat(-180, 180)
featured = fuzzy.FuzzyChoice(choices=[True, False])
@factory.post_generation
def antennas(self, create, extracted, **kwargs):
if not create:
return
if extracted:
for antenna in extracted:
self.antenna.add(antenna)
class Meta:
model = Station
class PeakFactory(DjangoModelFactory):
class Meta:
model = Peak
exclude = ("lat", "lon", "alt", "srid")
lat = float(fake.latitude())
lon = float(fake.longitude())
alt = fuzzy.FuzzyFloat(1000, 5000)
srid = 4326
name = fake.name()
coordinates = factory.LazyAttribute(
lambda o: Point(o.lon, o.lat, o.alt, srid=o.srid))
class CountryWeeklyStatusFactory(django_factory.DjangoModelFactory):
country = SubFactory(CountryFactory)
year = fuzzy.FuzzyInteger(1900, 2200)
week = fuzzy.FuzzyInteger(1, 53)
schools_connected = fuzzy.FuzzyInteger(0, 1000)
schools_connectivity_unknown = fuzzy.FuzzyInteger(0, 1000)
schools_connectivity_no = fuzzy.FuzzyInteger(0, 1000)
schools_connectivity_moderate = fuzzy.FuzzyInteger(0, 1000)
schools_connectivity_good = fuzzy.FuzzyInteger(0, 1000)
connectivity_speed = fuzzy.FuzzyInteger(1, 1000000)
integration_status = fuzzy.FuzzyChoice(dict(CountryWeeklyStatus.INTEGRATION_STATUS_TYPES).keys())
avg_distance_school = fuzzy.FuzzyFloat(0.0, 1000.0)
class Meta:
model = CountryWeeklyStatus
class DrukteindexFactory(factory.DjangoModelFactory):
class Meta:
model = models.Drukteindex
index = fuzzy.FuzzyInteger(low=10000000000000, high=19000009999999)
timestamp = fuzzy.FuzzyDateTime(
datetime(2016, 1, 1, tzinfo=timezone.utc),
datetime(2017, 1, 1, tzinfo=timezone.utc))
vollcode = fuzzy.FuzzyText()
weekday = fuzzy.FuzzyInteger(0, 6)
hour = fuzzy.FuzzyFloat(0, 23)
google_live = fuzzy.FuzzyFloat(0, 1)
google_week = fuzzy.FuzzyFloat(0, 1)
gvb_buurt = fuzzy.FuzzyFloat(0, 1)
gvb_stad = fuzzy.FuzzyFloat(0, 1)
verblijversindex = fuzzy.FuzzyFloat(0, 1)
google = fuzzy.FuzzyFloat(0, 1)
gvb = fuzzy.FuzzyFloat(0, 1)
drukte_index = fuzzy.FuzzyFloat(0, 1)
class AssetFactory(Factory):
class Meta:
model = Asset
id = Sequence(lambda x: x)
name = LazyAttribute(lambda x: f"Asset {x.id}")
capacity = 100
running_cost_per_mw_hr = 0
min_required_profit = fuzzy.FuzzyFloat(MIN, MAX)
max_import_mw_hr = fuzzy.FuzzyFloat(MIN, MAX)
max_export_mw_hr = fuzzy.FuzzyFloat(MIN, MAX)
single_import_mw_hr = None
single_export_mw_hr = None
min_zero_time = fuzzy.FuzzyFloat(MIN, MAX)
min_non_zero_time = fuzzy.FuzzyFloat(MIN, MAX)
notice_to_deviate_from_zero = fuzzy.FuzzyFloat(MIN, MAX)
notice_to_deliver_bid = fuzzy.FuzzyFloat(MIN, MAX)
max_delivery_period = fuzzy.FuzzyFloat(MIN, MAX)
class MeteoFactory(factory.django.DjangoModelFactory):
class Meta:
model = 'testapp.Meteo'
date = factory.Faker('date')
provider = factory.SubFactory(ProviderFactory)
city = factory.Faker('city')
temperature = fuzzy.FuzzyFloat(-10, 50)
humidity = fuzzy.FuzzyInteger(0, 100)
@classmethod
def create_batch_provider(self, count, provider_count, **kwargs):
meteos = []
for _ in range(provider_count):
provider = ProviderFactory.create()
meteos.extend(self.create_batch(count, provider=provider,
**kwargs))
return meteos
class SubmissionAttemptFactory(factory.DjangoModelFactory):
class Meta:
model = SubmissionAttempt
class Params:
our_tz = get_current_timezone()
VISITS_START = datetime.datetime(2016, 2, 26, 8, 0, 10, tzinfo=our_tz)
VISITS_END = datetime.datetime(2016, 6, 16, 17, 35, 9, tzinfo=our_tz)
attempt_key = factory.Sequence(lambda n: "key %d" % n)
page = factory.SubFactory(PageFactory)
lms_user = factory.SubFactory(LMSUserFactory)
attempted_at = faker.Faker('date_time_between_dates',
datetime_start=Params.VISITS_START,
datetime_end=Params.VISITS_END)
grade = fuzzy.FuzzyFloat(10.0)
@classmethod
def _setup_next_sequence(cls):
return 1000000
class Voertuig(factory.DictFactory):
kenteken = factory.SubFactory(Kenteken)
jaarEersteToelating = fuzzy.FuzzyInteger(1990, 2020)
toegestaneMaximumMassaVoertuig = fuzzy.FuzzyInteger(0, 1000)
europeseVoertuigcategorie = fuzzy.FuzzyText(length=2)
europeseVoertuigcategorieToevoeging = fuzzy.FuzzyChoice(string.ascii_uppercase)
taxiIndicator = factory.Faker('boolean', chance_of_getting_true=50)
maximaleConstructiesnelheidBromSnorfiets = fuzzy.FuzzyInteger(0, 500)
versitKlasse = fuzzy.FuzzyText()
massaLedigVoertuig = fuzzy.FuzzyInteger(0, 500)
aantalAssen = fuzzy.FuzzyInteger(0, 10)
aantalStaanplaatsen = fuzzy.FuzzyInteger(0, 100)
aantalWielen = fuzzy.FuzzyInteger(0, 12)
aantalZitplaatsen = fuzzy.FuzzyInteger(0, 100)
handelsbenaming = factory.Faker('first_name')
lengte = fuzzy.FuzzyInteger(0, 500)
breedte = fuzzy.FuzzyInteger(0, 500)
maximumMassaTrekkenOngeremd = fuzzy.FuzzyInteger(0, 5000)
maximumMassaTrekkenGeremd = fuzzy.FuzzyInteger(0, 5000)
voertuigSoort = fuzzy.FuzzyChoice(VOERTUIG_SOORTEN)
merk = factory.Faker('first_name')
inrichting = factory.Faker('first_name')
brandstoffen = factory.LazyFunction(get_brandstoffen_v2)
indicatieSnelheid = fuzzy.FuzzyFloat(0, 150)
class Locatie(factory.DictFactory):
longitude = fuzzy.FuzzyFloat(*AMSTERDAM_LONGITUDE)
latitude = fuzzy.FuzzyFloat(*AMSTERDAM_LATITUDE)
class Camera(factory.DictFactory):
id = factory.Faker('uuid4')
kijkrichting = fuzzy.FuzzyFloat(0, 360)
locatie = factory.SubFactory(Locatie)
naam = factory.Faker('name')
straat = factory.Faker('name')
class CarFactory(MakeFactoryMixin, DjangoModelFactory):
REGIONAL_PREFIXES = (
"AA",
"KA",
"AB",
"KB",
"AC",
"KC",
"AE",
"KE",
"AH",
"KH",
"AI",
"KI",
"AK",
"KK",
"AM",
"KM",
"AO",
"KO",
"AP",
"KP",
"AT",
"KT",
"AX",
"KX",
"BA",
"HA",
"BB",
"HB",
"BC",
"HC",
"BE",
"HE",
"BH",
"HH",
"BI",
"HI",
"BK",
"HK",
"BM",
"HM",
"BO",
"HO",
"BP",
"HP",
"BT",
"HT",
"BX",
"HX",
"CA",
"IA",
"CB",
"IB",
"CC",
"IC",
"CE",
"IE",
"CH",
"IH",
"II",
)
COLORS = ("white", "black", "silver", "gray", "brown", "red", "blue", "green")
MODELS = {
"Peugeot": (
"108",
"208",
"301",
"308",
"408",
"508",
"Bipper",
"Partner",
"Expert",
"Boxer",
),
"Citroen": (
"C1",
"C3",
"C4",
"C5",
"DS 3",
"DS 4",
"DS 4S",
"DS 5",
"Berlingo",
"Jumper",
"Jumpy",
"Nemo",
),
"Suzuki": (
"Alto",
"Baleno",
"Celerio",
"Lapin",
"Spacia",
"Swift",
"Carry",
"Jimny",
"Vitara",
"Every",
"Landy",
),
"Fiat": (
"Panda",
"500",
"Uno",
"Linea",
"Tipo",
"Doblò",
"Ducato",
"Fiorino",
"Qubo",
"Talento",
),
"Honda": (
"Accord",
"Civic",
"Jazz",
"Insight",
"Inspire",
"Legend",
"Acty",
"Ridgeline",
"CR-V",
"HR-V",
"Acty",
"Freed",
"Odyssey",
),
"Ford": (
"C-Max",
"Fiesta",
"Figo",
"Fusion",
"Mondeo",
"Focus",
"Ka",
"Ranger",
"Super Duty",
"Galaxy",
"S-Max",
"Transit",
),
"Hyundai": (
"i10",
"i20",
"i30",
"Elantra",
"i40",
"Accent",
"Atos",
"Visto" "Elantra",
"Eon",
"ix20",
"Cargo Truck",
"Porter",
"Xcient",
),
"Kia": (
"Ceed",
"Cerato",
"Optima",
"Picanto",
"Quoris",
"Ray",
"Stinger",
"Carens",
"Carnival",
"Venga",
"Besta",
"Bongo",
),
"Renault": (
"Clio",
"Fluence",
"Mégane",
"Talisman",
"Twingo",
"Scénic",
"Captur",
"Espace",
"Kadjar",
"Kangoo",
"Trafic",
),
"Dacia": ("Logan", "Sandero", "Lodgy", "Duster", "Lodgy", "Dokker"),
"Nissan": (
"Altima",
"Cima",
"Fuga",
"Almera",
"Leaf",
"Micra",
"Navara",
"Patrol",
"Juke",
"Murano",
"Pathfinder",
"Clipper",
"Cabstar",
"Atlas",
),
"Toyota": (
"Auris",
"Aygo",
"Camry",
"Corolla",
"Prius",
"Yaris",
"Hilux",
"Land Cruiser",
"C-HR",
"RAV4",
"Avanza",
"Esquire",
"Estima",
"Innova",
"Pixis",
"Sienna",
"Dyna",
"ToyoAce",
),
"SEAT": ("Toledo", "Ibiza", "León", "Mii", "Alhambra", "Arona", "Ateca"),
"Škoda": ("Citigo", "Fabia", "Octavia", "Rapid", "Superb", "Kodiaq", "Karoq"),
"Volkswagen": (
"Bora",
"Fox",
"Golf",
"Jetta",
"Passat",
"Polo",
"Up",
"Vento",
"Voyage",
"T-Roc",
"Tiguan",
"Touareg",
"Caddy",
"Sharan",
"Suran",
"Touran",
"Amarok",
"Saveiro",
"Transporter",
"Crafter",
),
}
fuel_consumption = fuzzy.FuzzyFloat(3, 10)
country = fuzzy.FuzzyChoice(COUNTRIES)
class Meta:
model = Car
exclude = ("REGIONAL_PREFIXES", "COLORS", "MODELS")
@lazy_attribute
def plates(self):
return "{regional_prefix}{four_digits}{two_letters}".format(
regional_prefix=random.choice(self.REGIONAL_PREFIXES),
four_digits="".join(random.choices(string.digits, k=4)),
two_letters="".join(random.choices("ABEIKMHOPCTX", k=2)),
)
@lazy_attribute
def description(self):
manufacturer = random.choice(list(self.MODELS.keys()))
return "{color} {manufacturer} {model} {year}".format(
color=random.choice(self.COLORS).capitalize(),
manufacturer=manufacturer,
model=random.choice(self.MODELS[manufacturer]),
year=random.randrange(1990, now().year),
)
class ApartmentFactory(factory.Factory):
class Meta:
model = ApartmentTest
_language = fuzzy.FuzzyChoice(["en", "fi", "sv"])
project_id = fuzzy.FuzzyInteger(0, 9999999999)
project_uuid = str(uuid.uuid4())
project_housing_company = fuzzy.FuzzyText()
project_holding_type = "RIGHT_OF_RESIDENCE_APARTMENT"
project_street_address = fuzzy.FuzzyText()
project_postal_code = fuzzy.FuzzyText(length=6, chars=string.digits)
project_city = "Helsinki"
project_district = fuzzy.FuzzyText()
project_realty_id = fuzzy.FuzzyText()
project_construction_year = fuzzy.FuzzyInteger(2000, 3000)
project_new_development_status = fuzzy.FuzzyChoice(
NEW_DEVELOPMENT_STATUS_MAPPING.keys())
project_new_housing = True
project_apartment_count = fuzzy.FuzzyInteger(0, 9999999999)
project_parkingplace_count = fuzzy.FuzzyInteger(0, 9999999999)
project_has_elevator = True
project_has_sauna = True
project_construction_materials = factory.List(
[fuzzy.FuzzyText() for _ in range(2)])
project_roof_material = fuzzy.FuzzyText()
project_heating_options = factory.List(
[fuzzy.FuzzyText() for _ in range(2)])
project_energy_class = fuzzy.FuzzyText()
project_site_area = fuzzy.FuzzyFloat(0, 9999999999)
project_site_owner = fuzzy.FuzzyChoice(["Oma", "Vuokra"])
project_site_renter = fuzzy.FuzzyText()
project_sanitation = fuzzy.FuzzyText()
project_zoning_info = fuzzy.FuzzyText()
project_zoning_status = fuzzy.FuzzyText()
project_building_type = "BLOCK_OF_FLATS"
project_description = fuzzy.FuzzyText(length=200)
url = fuzzy.FuzzyText(length=20)
project_accessibility = fuzzy.FuzzyText()
project_smoke_free = fuzzy.FuzzyText()
project_publication_start_time = (fuzzy.FuzzyDateTime(
timezone.now()).fuzz().strftime("%Y-%m-%dT%H:%M:%S%z"))
project_publication_end_time = (fuzzy.FuzzyDateTime(
timezone.now()).fuzz().strftime("%Y-%m-%dT%H:%M:%S%z"))
project_premarketing_start_time = fuzzy.FuzzyDateTime(timezone.now())
project_premarketing_end_time = fuzzy.FuzzyDateTime(timezone.now())
project_application_start_time = fuzzy.FuzzyDateTime(timezone.now())
project_application_end_time = fuzzy.FuzzyDateTime(timezone.now())
project_material_choice_dl = fuzzy.FuzzyDate(date.today())
project_shareholder_meeting_date = fuzzy.FuzzyDate(date.today())
project_estimated_completion = fuzzy.FuzzyText()
project_estimated_completion_date = fuzzy.FuzzyDate(date.today())
project_completion_date = fuzzy.FuzzyDate(date.today())
project_posession_transfer_date = fuzzy.FuzzyDate(date.today())
project_attachment_urls = factory.List(
[fuzzy.FuzzyText() for _ in range(2)])
project_main_image_url = fuzzy.FuzzyText()
project_image_urls = factory.List([fuzzy.FuzzyText() for _ in range(2)])
project_virtual_presentation_url = fuzzy.FuzzyText()
project_acc_salesperson = fuzzy.FuzzyText()
project_acc_financeofficer = fuzzy.FuzzyText()
project_project_manager = fuzzy.FuzzyText()
project_constructor = fuzzy.FuzzyText()
project_housing_manager = fuzzy.FuzzyText()
project_estate_agent = fuzzy.FuzzyText()
project_estate_agent_email = Faker("email")
project_estate_agent_phone = fuzzy.FuzzyText()
project_coordinate_lat = fuzzy.FuzzyFloat(-90, 90)
project_coordinate_lon = fuzzy.FuzzyFloat(-180, 180)
project_state_of_sale = fuzzy.FuzzyChoice(ProjectStateOfSale)
apartment_state_of_sale = fuzzy.FuzzyChoice(ApartmentStateOfSale)
uuid = fuzzy.FuzzyAttribute(get_uuid)
apartment_address = fuzzy.FuzzyText()
apartment_number = fuzzy.FuzzyInteger(0, 99)
housing_shares = fuzzy.FuzzyText()
living_area = fuzzy.FuzzyFloat(0, 9999999999)
floor = fuzzy.FuzzyInteger(0, 9999999999)
floor_max = fuzzy.FuzzyInteger(0, 9999999999)
showing_times = factory.List([
fuzzy.FuzzyDateTime(
timezone.now()).fuzz().strftime("%Y-%m-%dT%H:%M:%S%z")
for _ in range(2)
])
apartment_structure = fuzzy.FuzzyText()
room_count = fuzzy.FuzzyInteger(0, 9999999999)
condition = "Uusi"
kitchen_appliances = fuzzy.FuzzyText()
has_yard = True
has_terrace = True
has_balcony = True
balcony_description = fuzzy.FuzzyText()
bathroom_appliances = fuzzy.FuzzyText()
storage_description = fuzzy.FuzzyText()
has_apartment_sauna = True
apartment_holding_type = "RIGHT_OF_RESIDENCE_APARTMENT"
view_description = fuzzy.FuzzyText()
sales_price = fuzzy.FuzzyInteger(0, 9999999999)
debt_free_sales_price = fuzzy.FuzzyInteger(0, 9999999999)
loan_share = fuzzy.FuzzyInteger(0, 9999999999)
price_m2 = fuzzy.FuzzyInteger(0, 9999999999)
housing_company_fee = fuzzy.FuzzyInteger(0, 9999999999)
financing_fee = fuzzy.FuzzyInteger(0, 9999999999)
financing_fee_m2 = fuzzy.FuzzyInteger(0, 9999999999)
maintenance_fee = fuzzy.FuzzyInteger(0, 9999999999)
maintenance_fee_m2 = fuzzy.FuzzyInteger(0, 9999999999)
water_fee = fuzzy.FuzzyInteger(0, 9999999999)
water_fee_explanation = fuzzy.FuzzyText()
parking_fee = fuzzy.FuzzyInteger(0, 9999999999)
parking_fee_explanation = fuzzy.FuzzyText()
other_fees = fuzzy.FuzzyText()
services_description = fuzzy.FuzzyText()
additional_information = fuzzy.FuzzyText()
application_url = fuzzy.FuzzyText()
image_urls = factory.List([fuzzy.FuzzyText() for _ in range(2)])
def get_point_in_amsterdam():
lat = fuzzy.FuzzyFloat(*AMSTERDAM_LATITUDE).fuzz()
lon = fuzzy.FuzzyFloat(*AMSTERDAM_LONGITUDE).fuzz()
return Point(float(lat), float(lon))
def get_puntje():
lat = fuzzy.FuzzyFloat(BBOX[0], BBOX[2]).fuzz()
lon = fuzzy.FuzzyFloat(BBOX[1], BBOX[3]).fuzz()
return Point(float(lat), float(lon))
class CarFactory(factory.DjangoModelFactory):
REGIONAL_PREFIXES = ('AA', 'KA', 'AB', 'KB', 'AC', 'KC', 'AE', 'KE', 'AH',
'KH', 'AI', 'KI', 'AK', 'KK', 'AM', 'KM', 'AO', 'KO',
'AP', 'KP', 'AT', 'KT', 'AX', 'KX', 'BA', 'HA', 'BB',
'HB', 'BC', 'HC', 'BE', 'HE', 'BH', 'HH', 'BI', 'HI',
'BK', 'HK', 'BM', 'HM', 'BO', 'HO', 'BP', 'HP', 'BT',
'HT', 'BX', 'HX', 'CA', 'IA', 'CB', 'IB', 'CC', 'IC',
'CE', 'IE', 'CH', 'IH', 'II')
COLORS = ('white', 'black', 'silver', 'gray', 'brown', 'red', 'blue',
'green')
MODELS = {
'Peugeot': ('108', '208', '301', '308', '408', '508', 'Bipper',
'Partner', 'Expert', 'Boxer'),
'Citroen': ('C1', 'C3', 'C4', 'C5', 'DS 3', 'DS 4', 'DS 4S', 'DS 5',
'Berlingo', 'Jumper', 'Jumpy', 'Nemo'),
'Suzuki': ('Alto', 'Baleno', 'Celerio', 'Lapin', 'Spacia', 'Swift',
'Carry', 'Jimny', 'Vitara', 'Every', 'Landy'),
'Fiat': ('Panda', '500', 'Uno', 'Linea', 'Tipo', 'Doblò', 'Ducato',
'Fiorino', 'Qubo', 'Talento'),
'Honda': ('Accord', 'Civic', 'Jazz', 'Insight', 'Inspire', 'Legend',
'Acty', 'Ridgeline', 'CR-V', 'HR-V', 'Acty', 'Freed',
'Odyssey'),
'Ford': ('C-Max', 'Fiesta', 'Figo', 'Fusion', 'Mondeo', 'Focus', 'Ka',
'Ranger', 'Super Duty', 'Galaxy', 'S-Max', 'Transit'),
'Hyundai': ('i10', 'i20', 'i30', 'Elantra', 'i40', 'Accent', 'Atos',
'Visto' 'Elantra', 'Eon', 'ix20', 'Cargo Truck', 'Porter',
'Xcient'),
'Kia': ('Ceed', 'Cerato', 'Optima', 'Picanto', 'Quoris', 'Ray',
'Stinger', 'Carens', 'Carnival', 'Venga', 'Besta', 'Bongo'),
'Renault': ('Clio', 'Fluence', 'Mégane', 'Talisman', 'Twingo',
'Scénic', 'Captur', 'Espace', 'Kadjar', 'Kangoo',
'Trafic'),
'Dacia': ('Logan', 'Sandero', 'Lodgy', 'Duster', 'Lodgy', 'Dokker'),
'Nissan': ('Altima', 'Cima', 'Fuga', 'Almera', 'Leaf', 'Micra',
'Navara', 'Patrol', 'Juke', 'Murano', 'Pathfinder',
'Clipper', 'Cabstar', 'Atlas'),
'Toyota': ('Auris', 'Aygo', 'Camry', 'Corolla', 'Prius', 'Yaris',
'Hilux', 'Land Cruiser', 'C-HR', 'RAV4', 'Avanza',
'Esquire', 'Estima', 'Innova', 'Pixis', 'Sienna', 'Dyna',
'ToyoAce'),
'SEAT': ('Toledo', 'Ibiza', 'León', 'Mii', 'Alhambra', 'Arona',
'Ateca'),
'Škoda': ('Citigo', 'Fabia', 'Octavia', 'Rapid', 'Superb', 'Kodiaq',
'Karoq'),
'Volkswagen': ('Bora', 'Fox', 'Golf', 'Jetta', 'Passat', 'Polo', 'Up',
'Vento', 'Voyage', 'T-Roc', 'Tiguan', 'Touareg',
'Caddy', 'Sharan', 'Suran', 'Touran', 'Amarok',
'Saveiro', 'Transporter', 'Crafter'),
}
mileage_unit = fuzzy.FuzzyChoice(k for k, _ in Car.UNITS)
fuel_consumption = fuzzy.FuzzyFloat(3, 10)
class Meta:
model = Car
exclude = ('REGIONAL_PREFIXES', 'COLORS', 'MODELS')
@factory.lazy_attribute
def plates(self):
return '{regional_prefix}{four_digits}{two_letters}'.format(
regional_prefix=random.choice(self.REGIONAL_PREFIXES),
four_digits=''.join(random.choices(string.digits, k=4)),
two_letters=''.join(random.choices('ABEIKMHOPCTX', k=2)),
)
@factory.lazy_attribute
def description(self):
manufacturer = random.choice(list(self.MODELS.keys()))
return '{color} {manufacturer} {model} {year}'.format(
color=random.choice(self.COLORS).capitalize(),
manufacturer=manufacturer,
model=random.choice(self.MODELS[manufacturer]),
year=random.randrange(1990, now().year),
)
def get_random_coordinates():
coord_generator = fuzzy.FuzzyFloat(-180.0, 180.0)
return [coord_generator.fuzz(), coord_generator.fuzz()]
