def test_get_involvements(self, police_witness_serializer_mock, investigator_allegation_serializer_mock):
allegation = AllegationFactory()
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
PoliceWitnessFactory(officer=officer_1, allegation=allegation)
PoliceWitnessFactory(officer=officer_2, allegation=allegation)
OfficerBadgeNumberFactory(officer=officer_1, star='456789')
investigator_1 = InvestigatorFactory(officer=officer_1)
investigator_2 = InvestigatorFactory(officer=officer_2)
investigator_3 = InvestigatorFactory()
investigator_allegation_1 = InvestigatorAllegationFactory(allegation=allegation, investigator=investigator_1)
investigator_allegation_2 = InvestigatorAllegationFactory(allegation=allegation, investigator=investigator_2)
investigator_allegation_3 = InvestigatorAllegationFactory(allegation=allegation, investigator=investigator_3)
investigator_allegations = [investigator_allegation_1, investigator_allegation_2, investigator_allegation_3]
expected_has_badge_numbers = {
investigator_allegation_1.id: True,
investigator_allegation_2.id: False,
investigator_allegation_3.id: False,
}
result = CRSerializer(allegation).data
investigator_allegations_arg = investigator_allegation_serializer_mock.call_args[0][0]
police_witnesses_arg = police_witness_serializer_mock.call_args[0][0]
expect(set(investigator_allegations_arg)).to.eq(set(investigator_allegations))
for obj in investigator_allegations_arg:
expect(obj.has_badge_number).to.eq(expected_has_badge_numbers[obj.id])
expect(set(police_witnesses_arg)).to.eq(set([officer_1, officer_2]))
expect(result['involvements']).to.eq(
[{'officer_id': 1}, {'officer_id': 2}, {'officer_id': 4}, {'officer_id': 3}]
)
def test_extra_data_populated(self):
allegation = AllegationFactory(crid='1122123')
OfficerAllegationFactory(allegation=allegation)
InvestigatorAllegationFactory(allegation=allegation)
PoliceWitnessFactory(allegation=allegation)
indexer = CRPartialIndexer(updating_keys=['123', '456'])
expect(indexer.coaccused_dict['1122123']).to.have.length(1)
expect(indexer.investigator_dict['1122123']).to.have.length(1)
expect(indexer.policewitness_dict['1122123']).to.have.length(1)
def test_relevant_complaints_via_police_witnesses(self):
pinned_officer_1 = OfficerFactory(id=1)
pinned_officer_2 = OfficerFactory(id=2)
not_relevant_officer = OfficerFactory(id=999)
relevant_allegation_11 = AllegationFactory(crid='11',
incident_date=datetime(
2002,
2,
21,
tzinfo=pytz.utc))
relevant_allegation_12 = AllegationFactory(crid='12',
incident_date=datetime(
2002,
2,
22,
tzinfo=pytz.utc))
relevant_allegation_21 = AllegationFactory(crid='21',
incident_date=datetime(
2002,
2,
23,
tzinfo=pytz.utc))
not_relevant_allegation = AllegationFactory(crid='999')
pinboard = PinboardFactory(
title='Test pinboard',
description='Test description',
)
pinboard.officers.set([pinned_officer_1, pinned_officer_2])
PoliceWitnessFactory(allegation=relevant_allegation_11,
officer=pinned_officer_1)
PoliceWitnessFactory(allegation=relevant_allegation_12,
officer=pinned_officer_1)
PoliceWitnessFactory(allegation=relevant_allegation_21,
officer=pinned_officer_2)
PoliceWitnessFactory(allegation=not_relevant_allegation,
officer=not_relevant_officer)
relevant_complaints = list(pinboard.relevant_complaints)
expect(relevant_complaints).to.have.length(3)
expect(relevant_complaints[0].crid).to.eq('21')
expect(relevant_complaints[1].crid).to.eq('12')
expect(relevant_complaints[2].crid).to.eq('11')
def test_police_witness_counts(self):
officer = OfficerFactory()
OfficerAllegationFactory.create_batch(2, officer=officer, final_finding='SU')
OfficerAllegationFactory(officer=officer, final_finding='NS')
allegation = AllegationFactory()
PoliceWitnessFactory(officer=officer, allegation=allegation)
rows = self.extract_data()
expect(rows).to.have.length(4)
expect({len(row['involvements']) for row in rows}).to.eq({0, 1})
for row in rows:
if len(row['involvements']) == 1:
expect(row['involvements'][0]['allegation_count']).to.eq(3)
expect(row['involvements'][0]['sustained_count']).to.eq(2)
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_export_xlsx(self):
allegation = AllegationFactory(crid='1009678',
location='Tavern/Liquor Store',
add1='37XX',
add2='W 63RD ST',
city='CHICAGO IL',
old_complaint_address=None,
incident_date=datetime(2007,
9,
28,
0,
0,
tzinfo=pytz.utc),
beat=AreaFactory(name='0823'),
is_officer_complaint=True,
coaccused_count=19)
allegation1 = AllegationFactory(
crid='1012803',
location='Public Way - Other',
add1='31XX',
add2='N NEWCASTLE AVE',
city='CHICAGO IL',
old_complaint_address=None,
incident_date=datetime(2005, 11, 1, 0, 0, tzinfo=pytz.utc),
beat=AreaFactory(name='2511'),
is_officer_complaint=False,
coaccused_count=9)
officer = OfficerFactory(
id=8562,
first_name='Jerome',
last_name='Finnigan',
middle_initial='A',
middle_initial2=None,
suffix_name=None,
)
officer1 = OfficerFactory(
first_name='Jeffery',
last_name='Aaron',
middle_initial='M',
middle_initial2=None,
suffix_name=None,
gender='M',
race='White',
appointed_date=date(2005, 9, 26),
resignation_date=None,
rank='Sergeant of Police',
birth_year=1971,
active='Yes',
complaint_percentile=Decimal('61.2357'),
civilian_allegation_percentile=Decimal('61.2069'),
internal_allegation_percentile=Decimal('76.9384'),
trr_percentile=Decimal('79.8763'),
honorable_mention_percentile=Decimal('94.8669'),
allegation_count=6,
sustained_count=0,
honorable_mention_count=61,
unsustained_count=0,
discipline_count=0,
civilian_compliment_count=4,
trr_count=7,
major_award_count=0,
current_badge='1424',
last_unit=PoliceUnitFactory(unit_name='003'),
current_salary=101442,
)
officer2 = OfficerFactory(
first_name='Karina',
last_name='Aaron',
middle_initial=None,
middle_initial2=None,
suffix_name=None,
gender='F',
race='Hispanic',
appointed_date=date(2005, 9, 26),
resignation_date=None,
rank='Police Officer',
birth_year=1980,
active='Yes',
complaint_percentile=Decimal('72.0378'),
civilian_allegation_percentile=Decimal('76.4252'),
internal_allegation_percentile=Decimal('0.0000'),
trr_percentile=Decimal('67.4458'),
honorable_mention_percentile=Decimal('96.0992'),
allegation_count=8,
sustained_count=0,
honorable_mention_count=71,
unsustained_count=2,
discipline_count=0,
civilian_compliment_count=2,
trr_count=4,
major_award_count=0,
current_badge='20373',
last_unit=PoliceUnitFactory(unit_name='001'),
current_salary=94122,
)
allegation_category = AllegationCategoryFactory(
category='Illegal Search',
allegation_name='Improper Search Of Person',
)
allegation_category1 = AllegationCategoryFactory(
category='False Arrest',
allegation_name='Illegal Arrest / False Arrest',
)
OfficerAllegationFactory(
officer=officer,
allegation=allegation,
allegation_category=allegation_category,
start_date=date(2007, 9, 28),
end_date=None,
recc_finding='',
recc_outcome='Unknown',
final_finding='',
final_outcome='Unknown',
disciplined=None,
)
OfficerAllegationFactory(
officer=officer,
allegation=allegation1,
allegation_category=allegation_category1,
start_date=date(2007, 12, 21),
end_date=date(2008, 5, 29),
recc_finding='',
recc_outcome='Unknown',
final_finding='',
final_outcome='Unknown',
disciplined=None,
)
OfficerAllegationFactory(
officer=officer1,
allegation=allegation,
allegation_category=allegation_category,
start_date=date(1967, 10, 21),
end_date=date(1980, 8, 1),
recc_finding='',
recc_outcome='Unknown',
final_finding='SU',
final_outcome='30 Day Suspension',
disciplined=True,
)
OfficerAllegationFactory(
officer=officer2,
allegation=allegation,
allegation_category=allegation_category,
start_date=date(1970, 8, 13),
end_date=date(1973, 9, 15),
recc_finding='',
recc_outcome='Unknown',
final_finding='SU',
final_outcome='Suspended Over 30 Days',
final_outcome_class='',
disciplined=True,
)
VictimFactory(
allegation=allegation,
gender='M',
race='Hispanic',
birth_year=1973,
)
VictimFactory(
allegation=allegation1,
gender='',
race='',
birth_year=None,
)
witness = OfficerFactory(
first_name='Jeffery',
last_name='Aaron',
middle_initial='M',
middle_initial2=None,
suffix_name=None,
gender='M',
race='White',
appointed_date=date(2005, 9, 26),
resignation_date=None,
rank='Sergeant of Police',
birth_year=1971,
active='Yes',
complaint_percentile=Decimal('61.2357'),
civilian_allegation_percentile=Decimal('61.2069'),
internal_allegation_percentile=Decimal('76.9384'),
trr_percentile=Decimal('79.8763'),
honorable_mention_percentile=Decimal('94.8669'),
allegation_count=6,
sustained_count=0,
honorable_mention_count=61,
unsustained_count=0,
discipline_count=0,
civilian_compliment_count=4,
trr_count=7,
major_award_count=0,
current_badge='1424',
last_unit=PoliceUnitFactory(unit_name='003'),
current_salary=101442,
)
PoliceWitnessFactory(
officer=witness,
allegation=allegation,
)
writer = AccusedXlsxWriter(officer, self.test_output_dir)
writer.export_xlsx()
self.covert_xlsx_to_csv('accused.xlsx')
self.assert_csv_files_equal('accused_8562', [
'Allegation', 'Coaccused Officer', 'Beat', 'Police Witness',
'Victim'
])
def test_emit_correct_format(self):
allegation = AllegationFactory(
crid='12345',
summary='Summary',
point=Point(12, 21),
incident_date=datetime(2002, 2, 28, tzinfo=pytz.utc),
add1='3510',
add2='Michigan Ave',
city='Chicago',
location='Police Building',
beat=AreaFactory(name='23'),
is_officer_complaint=False,
first_start_date=date(2003, 3, 28),
first_end_date=date(2003, 4, 28),
)
coaccused = OfficerFactory(
id=1,
first_name='Foo',
last_name='Bar',
gender='M',
race='White',
birth_year=1986,
appointed_date=date(2001, 1, 1),
rank='Officer',
complaint_percentile=Decimal(0),
civilian_allegation_percentile=Decimal(1.1),
internal_allegation_percentile=Decimal(2.2),
trr_percentile=Decimal(3.3),
allegation_count=1,
sustained_count=1,
)
OfficerAllegationFactory(
officer=coaccused,
allegation=allegation,
final_finding='SU',
recc_outcome='Separation',
final_outcome='Reprimand',
start_date=date(2003, 3, 28),
end_date=date(2003, 4, 28),
allegation_category=AllegationCategoryFactory(
category='Operation/Personnel Violations',
allegation_name='NEGLECT OF DUTY/CONDUCT UNBECOMING - ON DUTY'
),
disciplined=True
)
ComplainantFactory(allegation=allegation, gender='M', race='White', age=30)
ComplainantFactory(allegation=allegation, gender='F', race='Black', age=25)
VictimFactory(allegation=allegation, gender='F', race='Black', age=25)
VictimFactory(allegation=allegation, gender='M', race='Hispanic', age=40)
officer = OfficerFactory(
id=2,
first_name='Jerome',
last_name='Finnigan',
gender='M',
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=3,
first_name='German',
last_name='Lauren',
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='Other',
allegation=allegation,
file_type='document',
title='CR document',
url='http://foo.com/',
preview_image_url='http://web.com/image',
)
AttachmentFileFactory(
tag='Other',
allegation=allegation,
file_type='document',
title='CR document',
url='http://foo.com/',
preview_image_url='http://web.com/image',
show=False
)
AttachmentFileFactory(
allegation=allegation,
file_type='document',
tag='OCIR',
title='CR document',
url='http://foo.com/',
preview_image_url='http://web.com/image',
)
indexer = CRIndexer()
rows = list(indexer.get_queryset())
row = [obj for obj in rows if obj['crid'] == '12345'][0]
result = indexer.extract_datum(row)
expect(dict(result)).to.eq({
'crid': '12345',
'most_common_category': {
'category': 'Operation/Personnel Violations',
'allegation_name': 'NEGLECT OF DUTY/CONDUCT UNBECOMING - ON DUTY'
},
'category_names': ['Operation/Personnel Violations'],
'coaccused': [
{
'id': 1,
'full_name': 'Foo Bar',
'abbr_name': 'F. Bar',
'gender': 'Male',
'race': 'White',
'rank': 'Officer',
'final_finding': 'Sustained',
'recc_outcome': 'Separation',
'final_outcome': 'Reprimand',
'category': 'Operation/Personnel Violations',
'subcategory': 'NEGLECT OF DUTY/CONDUCT UNBECOMING - ON DUTY',
'start_date': '2003-03-28',
'end_date': '2003-04-28',
'age': 32,
'allegation_count': 1,
'sustained_count': 1,
'percentile_allegation': Decimal('0'),
'percentile_allegation_civilian': Decimal('1.1'),
'percentile_allegation_internal': Decimal('2.2'),
'percentile_trr': Decimal('3.3'),
'disciplined': True
}
],
'complainants': [
{'gender': 'Male', 'race': 'White', 'age': 30},
{'gender': 'Female', 'race': 'Black', 'age': 25}
],
'victims': [
{'gender': 'Female', 'race': 'Black', 'age': 25},
{'gender': 'Male', 'race': 'Hispanic', 'age': 40}
],
'summary': 'Summary',
'point': {'lon': 12.0, 'lat': 21.0},
'incident_date': '2002-02-28',
'start_date': '2003-03-28',
'end_date': '2003-04-28',
'address': '3510 Michigan Ave, Chicago',
'location': 'Police Building',
'beat': '23',
'involvements': [
{
'involved_type': 'investigator',
'officer_id': 3,
'full_name': 'German Lauren',
'abbr_name': 'G. Lauren',
'num_cases': 1,
'current_rank': 'IPRA investigator',
'percentile_allegation': Decimal('6.6000'),
'percentile_allegation_civilian': Decimal('7.7000'),
'percentile_allegation_internal': Decimal('8.8000'),
'percentile_trr': None
},
{
'involved_type': 'police_witness',
'officer_id': 2,
'full_name': 'Jerome Finnigan',
'abbr_name': 'J. Finnigan',
'gender': 'Male',
'race': 'White',
'allegation_count': 1,
'sustained_count': 1,
'percentile_allegation': Decimal('4.4000'),
'percentile_allegation_civilian': None,
'percentile_allegation_internal': None,
'percentile_trr': Decimal('5.5000')
}
],
'attachments': [
{
'title': 'CR document',
'file_type': 'document',
'url': 'http://foo.com/',
'preview_image_url': 'http://web.com/image'
}
]
})