def new_demographic_row(department_id):
department = Department.get_by_id(department_id)
if not department:
abort(404)
DemographicValue.create(
department_id=department_id,
race=request.form["race"],
count=int(request.form["count"]),
department_value=request.form["department_or_city"] == "department")
return redirect(
url_for('department.edit_demographics', department_id=department_id))
def new_demographic_row(department_id):
department = Department.get_by_id(department_id)
if not department:
abort(404)
DemographicValue.create(
department_id=department_id,
race=request.form["race"],
count=int(request.form["count"]),
department_value=request.form["department_or_city"] == "department")
return redirect(url_for(
'department.edit_demographics', department_id=department_id
))
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 load_test_data():
department = Department.query.filter_by(
name="Indianapolis Metropolitan Police Department",
short_name="IMPD").first()
if not department:
department = Department.create(
name="Indianapolis Metropolitan Police Department",
short_name="IMPD")
if not User.query.filter_by(username="******").first():
User.create(username="******",
email="*****@*****.**",
password="******",
active=True,
department_id=department.id)
for filename in glob.glob('data/testdata/complaints/complaints.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for complaint in reader:
officer_identifier = hashlib.md5(
(complaint.get("OFFNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5(
(complaint.get("INCNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
CitizenComplaint.create(
opaque_id=opaque_id,
department_id=department.id,
occured_date=parse_csv_date(
complaint.get("OCCURRED_DT", None)),
division=complaint.get("UDTEXT24A", None),
precinct=complaint.get("UDTEXT24B", None),
shift=complaint.get("UDTEXT24C", None),
beat=complaint.get("UDTEXT24D", None),
disposition=complaint.get("FINDING", None),
allegation_type=complaint.get("ALG_CLASS", None),
allegation=complaint.get("ALLEGATION", None),
census_tract=None,
resident_race=complaint.get("RACE", None),
officer_race=complaint.get("OFF_RACE", None),
resident_sex=complaint.get("SEX", None),
officer_sex=complaint.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=complaint.get(
"OFF_YR_EMPLOY", None),
officer_age=complaint.get("OFF_AGE", None),
resident_age=complaint.get("CIT_AGE", None))
for filename in glob.glob('data/testdata/uof/uof.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for incident in reader:
officer_identifier = hashlib.md5(
(incident.get("OFFNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5(
(incident.get("INCNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
UseOfForceIncident.create(
department_id=department.id,
opaque_id=opaque_id,
occured_date=parse_csv_date(
incident.get("OCCURRED_DT", None)),
division=incident.get("UDTEXT24A", None),
precinct=incident.get("UDTEXT24B", None),
shift=incident.get("UDTEXT24C", None),
beat=incident.get("UDTEXT24D", None),
disposition=incident.get("DISPOSITION", None),
census_tract=None,
officer_force_type=incident.get("UOF_FORCE_TYPE", None),
resident_resist_type=None,
officer_weapon_used=None,
resident_weapon_used=None,
service_type=incident.get("SERVICE_TYPE", None),
arrest_made=incident.get("CIT_ARRESTED", None),
arrest_charges=incident.get("CITCHARGE_TYPE", None),
resident_injured=incident.get("CIT_INJURED", None),
resident_hospitalized=incident.get("CIT_HOSPITAL", None),
officer_injured=incident.get("OFF_INJURED", None),
officer_hospitalized=incident.get("OFF_HOSPITAL", None),
use_of_force_reason=incident.get("UOF_REASON", None),
resident_race=incident.get("RACE", None),
officer_race=incident.get("OFF_RACE", None),
resident_sex=incident.get("SEX", None),
officer_sex=incident.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=incident.get(
"OFF_YR_EMPLOY", None),
officer_age=incident.get("OFF_AGE", None),
resident_age=incident.get("CIT_AGE", None),
officer_condition=incident.get("OFF_COND_TYPE", None),
resident_condition=incident.get("CIT_COND_TYPE", None))
for filename in glob.glob('data/testdata/ois/ois.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for incident in reader:
officer_identifier = hashlib.md5(
(incident.get("OFFNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5(
(incident.get("INCNUM", None) +
Config.SECRET_KEY).encode('UTF-8')).hexdigest()
OfficerInvolvedShooting.create(
department_id=department.id,
opaque_id=opaque_id,
occured_date=parse_csv_date(
incident.get("OCCURRED_DT", None)),
division=incident.get("UDTEXT24A", None),
precinct=incident.get("UDTEXT24B", None),
shift=incident.get("UDTEXT24C", None),
beat=incident.get("UDTEXT24D", None),
disposition=incident.get("DISPOSITION", None),
census_tract=None,
officer_weapon_used=incident.get("WEAPON_TYPE", None),
resident_weapon_used=incident.get("CIT_WEAPON_TYPE", None),
service_type=incident.get("SERVICE_TYPE", None),
resident_race=incident.get("RACE", None),
officer_race=incident.get("OFF_RACE", None),
resident_sex=incident.get("SEX", None),
officer_sex=incident.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=incident.get(
"OFF_YR_EMPLOY", None),
officer_age=incident.get("OFF_AGE", None),
resident_age=incident.get("CIT_AGE", None),
officer_condition=incident.get("OFF_COND_TYPE", None),
resident_condition=incident.get("CIT_COND_TYPE", None))
for filename in glob.glob('data/testdata/denominators/denominators.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for month in reader:
DenominatorValue.create(department_id=department.id,
month=month.get("month", None),
year=month.get("year", None),
officers_out_on_service=month.get(
"officers out on service", None))
for filename in glob.glob('data/testdata/demographics/demographics.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for value in reader:
DemographicValue.create(department_id=department.id,
race=value.get("race", None),
count=value.get("count", None),
department_value=value.get(
"cityOrDepartment",
None) == "department")
def load_test_data():
department = Department.query.filter_by(name="Indianapolis Metropolitan Police Department", short_name="IMPD").first()
if not department:
department = Department.create(name="Indianapolis Metropolitan Police Department", short_name="IMPD")
if not User.query.filter_by(username="******").first():
User.create(username="******", email="*****@*****.**", password="******", active=True, department_id=department.id)
for filename in glob.glob('data/testdata/complaints/complaints.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for complaint in reader:
officer_identifier = hashlib.md5((complaint.get("OFFNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5((complaint.get("INCNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
CitizenComplaint.create(
opaque_id=opaque_id,
department_id=department.id,
occured_date=parse_csv_date(complaint.get("OCCURRED_DT", None)),
division=complaint.get("UDTEXT24A", None),
precinct=complaint.get("UDTEXT24B", None),
shift=complaint.get("UDTEXT24C", None),
beat=complaint.get("UDTEXT24D", None),
disposition=complaint.get("FINDING", None),
allegation_type=complaint.get("ALG_CLASS", None),
allegation=complaint.get("ALLEGATION", None),
census_tract=None,
resident_race=complaint.get("RACE", None),
officer_race=complaint.get("OFF_RACE", None),
resident_sex=complaint.get("SEX", None),
officer_sex=complaint.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=complaint.get("OFF_YR_EMPLOY", None),
officer_age=complaint.get("OFF_AGE", None),
resident_age=complaint.get("CIT_AGE", None)
)
for filename in glob.glob('data/testdata/uof/uof.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for incident in reader:
officer_identifier = hashlib.md5((incident.get("OFFNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5((incident.get("INCNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
UseOfForceIncident.create(
department_id=department.id,
opaque_id=opaque_id,
occured_date=parse_csv_date(incident.get("OCCURRED_DT", None)),
division=incident.get("UDTEXT24A", None),
precinct=incident.get("UDTEXT24B", None),
shift=incident.get("UDTEXT24C", None),
beat=incident.get("UDTEXT24D", None),
disposition=incident.get("DISPOSITION", None),
census_tract=None,
officer_force_type=incident.get("UOF_FORCE_TYPE", None),
resident_resist_type=None,
officer_weapon_used=None,
resident_weapon_used=None,
service_type=incident.get("SERVICE_TYPE", None),
arrest_made=incident.get("CIT_ARRESTED", None),
arrest_charges=incident.get("CITCHARGE_TYPE", None),
resident_injured=incident.get("CIT_INJURED", None),
resident_hospitalized=incident.get("CIT_HOSPITAL", None),
officer_injured=incident.get("OFF_INJURED", None),
officer_hospitalized=incident.get("OFF_HOSPITAL", None),
use_of_force_reason=incident.get("UOF_REASON", None),
resident_race=incident.get("RACE", None),
officer_race=incident.get("OFF_RACE", None),
resident_sex=incident.get("SEX", None),
officer_sex=incident.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=incident.get("OFF_YR_EMPLOY", None),
officer_age=incident.get("OFF_AGE", None),
resident_age=incident.get("CIT_AGE", None),
officer_condition=incident.get("OFF_COND_TYPE", None),
resident_condition=incident.get("CIT_COND_TYPE", None)
)
for filename in glob.glob('data/testdata/ois/ois.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for incident in reader:
officer_identifier = hashlib.md5((incident.get("OFFNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
opaque_id = hashlib.md5((incident.get("INCNUM", None) + Config.SECRET_KEY).encode('UTF-8')).hexdigest()
OfficerInvolvedShooting.create(
department_id=department.id,
opaque_id=opaque_id,
occured_date=parse_csv_date(incident.get("OCCURRED_DT", None)),
division=incident.get("UDTEXT24A", None),
precinct=incident.get("UDTEXT24B", None),
shift=incident.get("UDTEXT24C", None),
beat=incident.get("UDTEXT24D", None),
disposition=incident.get("DISPOSITION", None),
census_tract=None,
officer_weapon_used=incident.get("WEAPON_TYPE", None),
resident_weapon_used=incident.get("CIT_WEAPON_TYPE", None),
service_type=incident.get("SERVICE_TYPE", None),
resident_race=incident.get("RACE", None),
officer_race=incident.get("OFF_RACE", None),
resident_sex=incident.get("SEX", None),
officer_sex=incident.get("OFF_SEX", None),
officer_identifier=officer_identifier,
officer_years_of_service=incident.get("OFF_YR_EMPLOY", None),
officer_age=incident.get("OFF_AGE", None),
resident_age=incident.get("CIT_AGE", None),
officer_condition=incident.get("OFF_COND_TYPE", None),
resident_condition=incident.get("CIT_COND_TYPE", None)
)
for filename in glob.glob('data/testdata/denominators/denominators.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for month in reader:
DenominatorValue.create(
department_id=department.id,
month=month.get("month", None),
year=month.get("year", None),
officers_out_on_service=month.get("officers out on service", None)
)
for filename in glob.glob('data/testdata/demographics/demographics.csv'):
with open(filename, 'rt') as f:
reader = csv.DictReader(f)
for value in reader:
DemographicValue.create(
department_id=department.id,
race=value.get("race", None),
count=value.get("count", None),
department_value=value.get("cityOrDepartment", None) == "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)