def test_current_badge(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
OfficerBadgeNumberFactory(officer=officer_1, star='123', current=True)
OfficerBadgeNumberFactory(officer=officer_2, current=False)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
expect(officer_1.current_badge).to.eq('123')
expect(officer_2.current_badge).to.eq(None)
def test_trr_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
TRRFactory.create_batch(2, officer=officer_1)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.trr_count).to.eq(2)
expect(officer_2.trr_count).to.eq(0)
def test_allegation_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
OfficerAllegationFactory.create_batch(2, final_finding='NS', officer=officer_1)
OfficerAllegationFactory(final_finding='SU', officer=officer_1)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.allegation_count).to.eq(3)
expect(officer_2.allegation_count).to.eq(0)
def test_discipline_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
OfficerAllegationFactory.create_batch(2, officer=officer_1, disciplined=True)
OfficerAllegationFactory(officer=officer_1, disciplined=False)
OfficerAllegationFactory(officer=officer_2, disciplined=False)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.discipline_count).to.eq(2)
expect(officer_2.discipline_count).to.eq(0)
def test_last_unit(self):
officer = OfficerFactory()
expect(officer.last_unit).to.equal(None)
last_unit = PoliceUnitFactory(unit_name='BDCH')
OfficerHistoryFactory(officer=officer, unit=PoliceUnitFactory(unit_name='CAND'), end_date=date(2000, 1, 1))
OfficerHistoryFactory(officer=officer, unit=last_unit, end_date=date(2002, 1, 1))
officer_cache_manager.build_cached_columns()
officer.refresh_from_db()
expect(officer.last_unit).to.eq(last_unit)
def test_major_award_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
AwardFactory(officer=officer_1, award_type='HONORED POLICE STAR')
AwardFactory(officer=officer_1, award_type='POLICE MEDAL')
AwardFactory(officer=officer_1, award_type='PIPE BAND AWARD')
AwardFactory(officer=officer_1, award_type='LIFE SAVING AWARD')
AwardFactory(officer=officer_2, award_type='LIFE SAVING AWARD')
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.major_award_count).to.eq(2)
expect(officer_2.major_award_count).to.eq(0)
def test_civilian_compliment_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
AwardFactory(officer=officer_1, award_type='Other')
AwardFactory(officer=officer_1, award_type='Complimentary Letter')
AwardFactory(officer=officer_1, award_type='Complimentary Letter')
AwardFactory(officer=officer_1, award_type='Honorable Mention')
AwardFactory(officer=officer_1, award_type='ABC Honorable Mention')
AwardFactory(officer=officer_2, award_type='Honorable Mention')
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.civilian_compliment_count).to.eq(2)
expect(officer_2.civilian_compliment_count).to.eq(0)
def test_current_salary(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
expect(officer_1.current_salary).to.be.none()
SalaryFactory(officer=officer_1, year=2010, salary=5000)
SalaryFactory(officer=officer_1, year=2012, salary=10000)
SalaryFactory(officer=officer_1, year=2015, salary=15000)
SalaryFactory(officer=officer_1, year=2017, salary=20000)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.current_salary).to.eq(20000)
expect(officer_2.current_salary).to.be.none()
def test_has_unique_name(self):
officer_1 = OfficerFactory(first_name='Jerome', last_name='Finnigan')
officer_2 = OfficerFactory(first_name='Jerome', last_name='Finnigan')
officer_3 = OfficerFactory(first_name='German', last_name='Finnigan')
officer_4 = OfficerFactory(first_name='Jerome', last_name='Piwinicki')
officer_5 = OfficerFactory(first_name='German', last_name='Piwinicki')
expect(officer_1.has_unique_name).to.be.false()
expect(officer_2.has_unique_name).to.be.false()
expect(officer_3.has_unique_name).to.be.false()
expect(officer_4.has_unique_name).to.be.false()
expect(officer_5.has_unique_name).to.be.false()
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
officer_3.refresh_from_db()
officer_4.refresh_from_db()
officer_5.refresh_from_db()
expect(officer_1.has_unique_name).to.be.false()
expect(officer_2.has_unique_name).to.be.false()
expect(officer_3.has_unique_name).to.be.true()
expect(officer_4.has_unique_name).to.be.true()
expect(officer_5.has_unique_name).to.be.true()
def test_request_complaint_summary(self):
allegation = AllegationFactory(crid='11',
incident_date=datetime(2002,
2,
28,
tzinfo=pytz.utc),
summary='Summary')
category = AllegationCategoryFactory(category='Use of Force')
OfficerAllegationFactory(
allegation=allegation,
officer=OfficerFactory(appointed_date=date(2001, 1, 1)),
start_date=date(2003, 2, 28),
end_date=date(2004, 4, 28),
allegation_category=category)
OfficerAllegationFactory(
allegation=allegation,
officer=OfficerFactory(appointed_date=date(2001, 1, 1)),
start_date=date(2003, 2, 28),
end_date=date(2004, 4, 28),
allegation_category=None)
officer_cache_manager.build_cached_yearly_percentiles()
officer_cache_manager.build_cached_columns()
allegation_cache_manager.cache_data()
response = self.client.get(reverse('api-v2:cr-complaint-summaries'))
expect(response.status_code).to.eq(status.HTTP_200_OK)
expect(response.data).to.eq([{
'crid':
'11',
'category_names': ['Unknown', 'Use of Force'],
'incident_date':
'2002-02-28',
'summary':
'Summary'
}])
def test_top_officers_by_allegation(self):
OfficerFactory(
id=1, first_name='Daryl', last_name='Mack',
trr_percentile=12.0000,
civilian_allegation_percentile=98.4344,
internal_allegation_percentile=99.7840,
complaint_percentile=99.3450,
race='White', gender='M', birth_year=1975,
rank='Police Officer'
)
OfficerFactory(
id=2,
first_name='Ronald', last_name='Watts',
trr_percentile=0.0000,
civilian_allegation_percentile=98.4344,
internal_allegation_percentile=99.7840,
complaint_percentile=99.5000,
race='White', gender='M', birth_year=1975,
rank='Detective'
)
OfficerFactory(
id=3,
first_name='Officer', last_name='low percentile',
trr_percentile=0.0000,
civilian_allegation_percentile=0.0000,
internal_allegation_percentile=0.0000,
complaint_percentile=96.3450,
race='White', gender='M', birth_year=1975,
rank=''
)
OfficerFactory(
id=4,
first_name='Officer', last_name='no visual token',
trr_percentile=0.0000,
internal_allegation_percentile=0.0000,
complaint_percentile=99.8800,
race='White', gender='M', birth_year=1975,
rank='Police Officer'
)
OfficerFactory(
id=5,
first_name='Officer', last_name='filter out',
trr_percentile=0.0000,
civilian_allegation_percentile=0.0000,
internal_allegation_percentile=0.0000,
complaint_percentile=99.2000,
race='White', gender='M', birth_year=1975,
rank='Detective'
)
OfficerFactory(
id=6,
first_name='Officer', last_name='no percentiles',
complaint_percentile=99.8000,
race='White', gender='M', birth_year=1975,
rank='Police Officer'
)
officer_cache_manager.build_cached_columns()
allegation_cache_manager.cache_data()
response = self.client.get(reverse('api-v2:officers-top-by-allegation'), {'limit': 2})
expect(response.status_code).to.eq(status.HTTP_200_OK)
expect(response.data).to.have.length(2)
expect(response.data).to.eq([{
'id': 2,
'full_name': 'Ronald Watts',
'complaint_count': 0,
'sustained_count': 0,
'birth_year': 1975,
'race': 'White',
'gender': 'Male',
'rank': 'Detective',
'percentile_allegation': '99.5000',
'percentile_allegation_civilian': '98.4344',
'percentile_allegation_internal': '99.7840',
'percentile_trr': '0.0000',
}, {
'id': 1,
'full_name': 'Daryl Mack',
'complaint_count': 0,
'sustained_count': 0,
'birth_year': 1975,
'race': 'White',
'gender': 'Male',
'rank': 'Police Officer',
'percentile_trr': '12.0000',
'percentile_allegation': '99.3450',
'percentile_allegation_civilian': '98.4344',
'percentile_allegation_internal': '99.7840',
}])
def test_summary(self):
officer = OfficerFactory(
tags=[],
first_name='Kevin', last_name='Kerl', id=123, race='White', gender='M',
appointed_date=date(2017, 2, 27), rank='PO', resignation_date=date(2017, 12, 27),
active=ACTIVE_YES_CHOICE, birth_year=1910, complaint_percentile=32.5,
sustained_count=1, allegation_count=1, discipline_count=1, trr_count=1,
civilian_compliment_count=1, honorable_mention_count=1, major_award_count=1,
last_unit_id=1, current_badge='123456', current_salary=90000, has_unique_name=True
)
allegation = AllegationFactory()
allegation_category = AllegationCategoryFactory(category='Use of Force')
OfficerHistoryFactory(officer=officer, unit=PoliceUnitFactory(id=1, unit_name='CAND', description=''))
ComplainantFactory(allegation=allegation, race='White', age=18, gender='F')
OfficerBadgeNumberFactory(officer=officer, star='123456', current=True)
OfficerAllegationFactory(
officer=officer, allegation=allegation, allegation_category=allegation_category,
final_finding='SU', start_date=date(2000, 1, 1), disciplined=True
)
AwardFactory(officer=officer, award_type='Complimentary Letter')
AwardFactory(officer=officer, award_type='Honored Police Star')
AwardFactory(officer=officer, award_type='Honorable Mention')
SalaryFactory(officer=officer, salary=50000, year=2015)
SalaryFactory(officer=officer, salary=90000, year=2017)
TRRFactory(officer=officer)
officer_cache_manager.build_cached_columns()
allegation_cache_manager.cache_data()
response = self.client.get(reverse('api-v2:officers-summary', kwargs={'pk': 123}))
expect(response.status_code).to.eq(status.HTTP_200_OK)
expected_data = {
'id': 123,
'unit': {
'id': 1,
'unit_name': 'CAND',
'description': '',
'long_unit_name': 'Unit CAND',
},
'date_of_appt': '2017-02-27',
'date_of_resignation': '2017-12-27',
'active': 'Active',
'rank': 'PO',
'full_name': 'Kevin Kerl',
'race': 'White',
'badge': '123456',
'historic_units': [{
'id': 1,
'unit_name': 'CAND',
'description': '',
'long_unit_name': 'Unit CAND'
}],
'gender': 'Male',
'birth_year': 1910,
'sustained_count': 1,
'civilian_compliment_count': 1,
'allegation_count': 1,
'discipline_count': 1,
'honorable_mention_count': 1,
'to': '/officer/123/kevin-kerl/',
'url': 'http://cpdb.lvh.me/officer/kevin-kerl/123',
'current_salary': 90000,
'trr_count': 1,
'major_award_count': 1,
'unsustained_count': 0,
'percentile_allegation': '32.5000',
'coaccusals': [],
'percentiles': [],
'tags': [],
'historic_badges': [],
'has_unique_name': True
}
expect(response.data).to.eq(expected_data)
def test_retrieve(self):
area = AreaFactory(name='Lincoln Square')
officer1 = OfficerFactory(
id=123,
first_name='Mr',
last_name='Foo',
gender='M',
race='White',
rank='Officer',
appointed_date=date(2001, 1, 1),
birth_year=1993,
complaint_percentile=4.4,
civilian_allegation_percentile=1.1,
internal_allegation_percentile=2.2,
trr_percentile=3.3,
allegation_count=1,
sustained_count=1,
)
OfficerBadgeNumberFactory(officer=officer1, star='12345', current=True)
allegation = AllegationFactory(crid='12345',
point=Point(12, 21),
incident_date=datetime(2002,
2,
28,
tzinfo=pytz.utc),
add1=3510,
add2='Michigan Ave',
city='Chicago',
location='Police Communications System',
beat=area,
is_officer_complaint=False,
summary='Summary',
first_start_date=date(2003, 3, 20),
first_end_date=date(2006, 5, 26))
ComplainantFactory(allegation=allegation,
gender='M',
race='Black',
age='18')
VictimFactory(allegation=allegation, gender='M', race='Black', age=53)
OfficerAllegationFactory(
officer=officer1,
allegation=allegation,
final_finding='SU',
disciplined=True,
final_outcome='Separation',
recc_outcome='10 Day Suspension',
start_date=date(2003, 3, 20),
end_date=date(2006, 5, 26),
allegation_category=AllegationCategoryFactory(
category='Operation/Personnel Violations',
allegation_name='Secondary/Special Employment'))
officer = OfficerFactory(
id=3,
first_name='Raymond',
last_name='Piwinicki',
appointed_date=date(2001, 5, 1),
complaint_percentile=4.4,
trr_percentile=5.5,
allegation_count=1,
sustained_count=1,
)
OfficerAllegationFactory(officer=officer,
final_finding='SU',
start_date=date(2003, 2, 28),
allegation__incident_date=datetime(
2002, 2, 28, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
PoliceWitnessFactory(officer=officer, allegation=allegation)
investigator = OfficerFactory(
id=1,
first_name='Ellis',
last_name='Skol',
appointed_date=date(2001, 5, 1),
complaint_percentile=6.6,
civilian_allegation_percentile=7.7,
internal_allegation_percentile=8.8,
allegation_count=1,
sustained_count=0,
)
OfficerAllegationFactory(officer=investigator,
final_finding='NS',
start_date=date(2003, 2, 28),
allegation__incident_date=datetime(
2002, 2, 28, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
investigator = InvestigatorFactory(officer=investigator)
InvestigatorAllegationFactory(allegation=allegation,
investigator=investigator,
current_rank='IPRA investigator')
AttachmentFileFactory(tag='TRR',
allegation=allegation,
title='CR document',
id='123456',
url='http://cr-document.com/',
file_type=MEDIA_TYPE_DOCUMENT)
AttachmentFileFactory(tag='TRR',
allegation=allegation,
title='CR arrest report document',
url='http://cr-document.com/',
file_type=MEDIA_TYPE_DOCUMENT)
AttachmentFileFactory(tag='AR',
allegation=allegation,
title='CR document 2',
id='654321',
url='http://AR-document.com/',
file_type=MEDIA_TYPE_DOCUMENT)
officer_cache_manager.build_cached_columns()
allegation_cache_manager.cache_data()
response = self.client.get(
reverse('api-v2:cr-detail', kwargs={'pk': '12345'}))
expect(response.status_code).to.eq(status.HTTP_200_OK)
expect(dict(response.data)).to.eq({
'crid':
'12345',
'most_common_category': {
'category': 'Operation/Personnel Violations',
'allegation_name': 'Secondary/Special Employment'
},
'coaccused': [{
'id': 123,
'full_name': 'Mr Foo',
'gender': 'Male',
'race': 'White',
'rank': 'Officer',
'birth_year': 1993,
'recommended_outcome': '10 Day Suspension',
'final_outcome': 'Separation',
'final_finding': 'Sustained',
'category': 'Operation/Personnel Violations',
'complaint_count': 1,
'sustained_count': 1,
'percentile_allegation': '4.4000',
'percentile_allegation_civilian': '1.1000',
'percentile_allegation_internal': '2.2000',
'percentile_trr': '3.3000',
'disciplined': True
}],
'complainants': [{
'race': 'Black',
'gender': 'Male',
'age': 18
}],
'victims': [{
'race': 'Black',
'gender': 'Male',
'age': 53
}],
'point': {
'lon': 12.0,
'lat': 21.0
},
'summary':
'Summary',
'incident_date':
'2002-02-28',
'start_date':
'2003-03-20',
'end_date':
'2006-05-26',
'address':
'3510 Michigan Ave, Chicago',
'location':
'Police Communications System',
'beat':
'Lincoln Square',
'involvements': [{
'involved_type': 'investigator',
'officer_id': 1,
'full_name': 'Ellis Skol',
'badge': 'CPD',
'percentile_allegation': '6.6000',
'percentile_allegation_civilian': '7.7000',
'percentile_allegation_internal': '8.8000',
}, {
'involved_type': 'police_witness',
'officer_id': 3,
'full_name': 'Raymond Piwinicki',
'allegation_count': 1,
'sustained_count': 1,
'percentile_trr': '5.5000',
'percentile_allegation': '4.4000',
}],
'attachments': [{
'title': 'CR document',
'file_type': 'document',
'url': 'http://cr-document.com/',
'id': '123456',
}]
})
def test_retrieve_data_range_too_small_cause_no_percentiles(self):
officer = OfficerFactory(
tags=[],
first_name='Kevin', last_name='Kerl', id=123, race='White', gender='M',
appointed_date=date(2002, 2, 27), rank='PO', resignation_date=date(2017, 12, 27),
active=ACTIVE_YES_CHOICE, birth_year=1960, complaint_percentile=32.5,
sustained_count=1, allegation_count=2, discipline_count=1, trr_count=1,
civilian_compliment_count=1, honorable_mention_count=1, major_award_count=1,
last_unit_id=1, current_badge='123456'
)
allegation = AllegationFactory(incident_date=datetime(2002, 3, 1, tzinfo=pytz.utc))
internal_allegation = AllegationFactory(
incident_date=datetime(2002, 4, 1, tzinfo=pytz.utc),
is_officer_complaint=True
)
allegation_category = AllegationCategoryFactory(category='Use of Force')
OfficerHistoryFactory(
officer=officer, effective_date=datetime(2002, 2, 27, tzinfo=pytz.utc),
unit=PoliceUnitFactory(id=1, unit_name='CAND', description='')
)
ComplainantFactory(allegation=allegation, race='White', age=18, gender='F')
OfficerBadgeNumberFactory(officer=officer, star='123456', current=True)
OfficerBadgeNumberFactory(officer=officer, star='789', current=False)
OfficerAllegationFactory(
officer=officer, allegation=allegation, allegation_category=allegation_category,
final_finding='SU', start_date=date(2002, 3, 2), disciplined=True
)
OfficerAllegationFactory(
officer=officer, allegation=internal_allegation,
final_finding='NS', start_date=date(2002, 3, 2), disciplined=False
)
AwardFactory(officer=officer, award_type='Complimentary Letter', start_date=date(2014, 5, 1))
AwardFactory(officer=officer, award_type='Honored Police Star', start_date=date(2014, 6, 1))
AwardFactory(officer=officer, award_type='Honorable Mention', start_date=date(2014, 7, 1))
SalaryFactory(officer=officer, salary=50000, year=2002)
SalaryFactory(officer=officer, salary=90000, year=2017)
TRRFactory(officer=officer, trr_datetime=datetime(2002, 3, 1, tzinfo=pytz.utc))
second_officer = OfficerFactory(
tags=[],
first_name='Kevin', last_name='Osborn', id=456, race='Black', gender='M',
appointed_date=date(2002, 1, 27), resignation_date=date(2017, 12, 27), rank='PO',
active=ACTIVE_YES_CHOICE, birth_year=1970
)
TRRFactory(officer=second_officer, trr_datetime=datetime(2002, 5, 1, tzinfo=pytz.utc))
TRRFactory(officer=second_officer, trr_datetime=datetime(2002, 12, 1, tzinfo=pytz.utc))
OfficerFactory(
tags=[],
first_name='Kevin', last_name='Edward', id=789, race='Black', gender='M',
appointed_date=date(2002, 3, 27), resignation_date=date(2017, 12, 27), rank='PO',
active=ACTIVE_YES_CHOICE, birth_year=1970
)
officer_cache_manager.build_cached_columns()
allegation_cache_manager.cache_data()
response = self.client.get(reverse('api-v2:officers-mobile-detail', kwargs={'pk': 123}))
expected_response = {
'officer_id': 123,
'unit': {
'unit_id': 1,
'unit_name': 'CAND',
'description': '',
},
'date_of_appt': '2002-02-27',
'date_of_resignation': '2017-12-27',
'active': 'Active',
'rank': 'PO',
'full_name': 'Kevin Kerl',
'race': 'White',
'badge': '123456',
'historic_badges': ['789'],
'gender': 'Male',
'birth_year': 1960,
'sustained_count': 1,
'unsustained_count': 1,
'civilian_compliment_count': 1,
'allegation_count': 2,
'discipline_count': 1,
'honorable_mention_count': 1,
'trr_count': 1,
'major_award_count': 1,
'percentile_allegation': '32.5000',
'percentiles': []
}
expect(response.data).to.eq(expected_response)