def test_client():
delete_everything()
department = Department.create(name="Busy Town Police Department", short_name="BTPD", load_defaults=True)
user = User.create(username="******", email="*****@*****.**", password="******", active=True, is_admin=True)
user.departments.append(department)
user.save()
test_client = JSONTestClient()
# missing_data_mutator = MissingDataMutator()
# fuzzed_data_mutator = FuzzedDataMutator()
# known_bad_data_mutator = KnownBadDataMutator()
# empty_data_mutator = EmptyDataMutator()
# casing_mutator = CasingMutator()
# condenisng_date_mutator = CondenisngDateMutator()
# gap_date_mutator = GapDateMutator()
test_client.run(department, [])
def test_client():
''' Erase the database and load in a full suite of test data
'''
if not prompt_bool(
"Are you sure you want to destroy and recreate Comport's database?"
):
return
delete_everything()
# create a fake PD and admin user
department = Department.create(
name="Izquierda Metropolitan Police Department",
short_name="IMPD",
load_defaults=True)
user = User.create(username="******",
email="*****@*****.**",
password="******",
active=True,
is_admin=True)
user.departments.append(department)
user.save()
# create some fake officer out on service data
date_now = datetime.datetime.now()
date_step = date_now - relativedelta(months=30)
while date_step.year < date_now.year or date_step.month < date_now.month:
DenominatorValue.create(
department_id=department.id,
month=date_step.month,
year=date_step.year,
officers_out_on_service=(100000 + (randint(0, 46000) - 23000)))
date_step = date_step + relativedelta(months=1)
# create some fake demographic data
demo_template = [
dict(race="Asian", city_factor=0.0194, dept_factor=0.0013),
dict(race="Black", city_factor=0.2452, dept_factor=0.1402),
dict(race="Hispanic", city_factor=0.0861, dept_factor=0.0253),
dict(race="Other", city_factor=0.0699, dept_factor=0.0101),
dict(race="White", city_factor=0.5794, dept_factor=0.8231)
]
# for the city
city_population = 100000 + round(100000 * ((randint(0, 16) / 100) - .08))
for value in demo_template:
DemographicValue.create(department_id=department.id,
race=value["race"],
count=round(city_population *
value["city_factor"]),
department_value=False)
# for the department
dept_population = 1500 + round(1500 * ((randint(0, 16) / 100) - .08))
for value in demo_template:
DemographicValue.create(department_id=department.id,
race=value["race"],
count=round(dept_population *
value["dept_factor"]),
department_value=True)
# create a JSON test client and run it
test_client = JSONTestClient()
mutations = []
# mutations.append(MissingDataMutator())
# mutations.append(FuzzedDataMutator())
# mutations.append(KnownBadDataMutator())
# mutations.append(EmptyDataMutator())
# mutations.append(CasingMutator())
# mutations.append(CondenisngDateMutator())
# mutations.append(GapDateMutator())
test_client.run(department, mutations)
def test_client():
''' Erase the database and load in a full suite of test data
'''
if not prompt_bool("Are you sure you want to destroy and recreate Comport's database?"):
return
delete_everything()
# create a fake PD and admin user
department = Department.create(name="Izquierda Metropolitan Police Department", short_name="IMPD", load_defaults=True)
user = User.create(username="******", email="*****@*****.**", password="******", active=True, is_admin=True)
user.departments.append(department)
user.save()
# create some fake officer out on service data
date_now = datetime.datetime.now()
date_step = date_now - relativedelta(months=30)
while date_step.year < date_now.year or date_step.month < date_now.month:
DenominatorValue.create(
department_id=department.id,
month=date_step.month,
year=date_step.year,
officers_out_on_service=(100000 + (randint(0, 46000) - 23000))
)
date_step = date_step + relativedelta(months=1)
# create some fake demographic data
demo_template = [
dict(race="Asian", city_factor=0.0194, dept_factor=0.0013),
dict(race="Black", city_factor=0.2452, dept_factor=0.1402),
dict(race="Hispanic", city_factor=0.0861, dept_factor=0.0253),
dict(race="Other", city_factor=0.0699, dept_factor=0.0101),
dict(race="White", city_factor=0.5794, dept_factor=0.8231)
]
# for the city
city_population = 100000 + round(100000 * ((randint(0, 16) / 100) - .08))
for value in demo_template:
DemographicValue.create(
department_id=department.id,
race=value["race"],
count=round(city_population * value["city_factor"]),
department_value=False
)
# for the department
dept_population = 1500 + round(1500 * ((randint(0, 16) / 100) - .08))
for value in demo_template:
DemographicValue.create(
department_id=department.id,
race=value["race"],
count=round(dept_population * value["dept_factor"]),
department_value=True
)
# create a JSON test client and run it
test_client = JSONTestClient()
mutations = []
# mutations.append(MissingDataMutator())
# mutations.append(FuzzedDataMutator())
# mutations.append(KnownBadDataMutator())
# mutations.append(EmptyDataMutator())
# mutations.append(CasingMutator())
# mutations.append(CondenisngDateMutator())
# mutations.append(GapDateMutator())
test_client.run(department, mutations)
