def _form_summary_string(
self,
summary: TrafficViolationsAggregatorResponse) -> Optional[str]:
num_vehicles = len(summary.plate_lookups)
vehicle_tickets = [
len(lookup.violations) for lookup in summary.plate_lookups
]
total_tickets = sum(vehicle_tickets)
fines_by_vehicle: List[FineData] = [
lookup.fines for lookup in summary.plate_lookups
]
vehicles_with_fines: int = len([
fine_data for fine_data in fines_by_vehicle if fine_data.fined > 0
])
aggregate_fines: FineData = FineData(
**{
field: sum(
getattr(lookup.fines, field)
for lookup in summary.plate_lookups)
for field in FineData.FINE_FIELDS
})
if aggregate_fines.fined > 0:
return [
f"You queried {num_vehicles} vehicles, of which "
f"{vehicles_with_fines} vehicle{L10N.pluralize(vehicles_with_fines)} "
f"{'has' if vehicles_with_fines == 1 else 'have collectively'} received {total_tickets} ticket{L10N.pluralize(total_tickets)} "
f"with at least {'${:,.2f}'.format(aggregate_fines.fined - aggregate_fines.reduced)} "
f"in fines, of which {'${:,.2f}'.format(aggregate_fines.paid)} has been paid.\n\n"
]
def test_look_up_vehicle_with_no_violations(self,
mocked_perform_query):
plate = 'ABC1234'
plate_types = 'PAS'
state = 'NY'
mocked_perform_query.side_effects = [{'data': {}} for _ in range(0, 8)]
plate_query = PlateQuery(
created_at='Tue Dec 31 19:28:12 -0500 2019',
message_id=random.randint(
1000000000000000000,
2000000000000000000),
message_source='status',
plate=plate,
plate_types=plate_types,
state=state,
username='******')
result = OpenDataServiceResponse(
data=OpenDataServicePlateLookup(
boroughs=[],
camera_streak_data=None,
fines=FineData(fined=0, outstanding=0, paid=0, reduced=0),
num_violations=0,
plate=plate,
plate_types=plate_types,
state=state,
violations=[],
years=[]),
success=True)
self.assertEqual(self.open_data_service.look_up_vehicle(plate_query),
result)
def _form_plate_lookup_response_parts(
self,
borough_data: List[Tuple[str, int]],
frequency: int,
fine_data: FineData,
plate: str,
plate_types: List[str],
state: str,
unique_identifier: str,
username: str,
violations: List[Tuple[str, int]],
year_data: List[Tuple[str, int]],
camera_streak_data: Optional[CameraStreakData] = None,
previous_lookup: Optional[PlateLookup] = None):
# response_chunks holds tweet-length-sized parts of the response
# to be tweeted out or appended into a single direct message.
response_chunks: List[str] = []
violations_string: str = ""
# Get total violations
total_violations: int = sum([s['count'] for s in violations])
LOG.debug(f'total_violations: {total_violations}')
# Append to initially blank string to build tweet.
violations_string += L10N.LOOKUP_SUMMARY_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate),
L10N.get_plate_types_string(plate_types), frequency,
L10N.pluralize(int(frequency)))
# If this vehicle has been queried before...
if previous_lookup:
previous_num_violations: int = previous_lookup.num_tickets
violations_string += self._create_repeat_lookup_string(
new_violations=(total_violations - previous_num_violations),
plate=plate,
previous_lookup=previous_lookup,
state=state,
username=username)
response_chunks += self._handle_response_part_formation(
collection=violations,
continued_format_string=L10N.LOOKUP_TICKETS_STRING_CONTD.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
cur_string=violations_string,
description='title',
default_description='No Year Available',
prefix_format_string=L10N.LOOKUP_TICKETS_STRING.format(
total_violations),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username=username)
if year_data:
response_chunks += self._handle_response_part_formation(
collection=year_data,
continued_format_string=L10N.LOOKUP_YEAR_STRING_CONTD.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
description='title',
default_description='No Year Available',
prefix_format_string=L10N.LOOKUP_YEAR_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username=username)
if borough_data:
response_chunks += self._handle_response_part_formation(
collection=borough_data,
continued_format_string=L10N.LOOKUP_BOROUGH_STRING_CONTD.
format(L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
description='title',
default_description='No Borough Available',
prefix_format_string=L10N.LOOKUP_BOROUGH_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username=username)
if fine_data and fine_data.fines_assessed():
cur_string = f"Known fines for {L10N.VEHICLE_HASHTAG.format(state, plate)}:\n\n"
max_count_length = len('${:,.2f}'.format(fine_data.max_amount()))
spaces_needed = (max_count_length * 2) + 1
for fine_type, amount in fine_data:
currency_string = '${:,.2f}'.format(amount)
count_length = len(str(currency_string))
# e.g., if spaces_needed is 5, and count_length is 2, we need
# to pad to 3.
left_justify_amount = spaces_needed - count_length
# formulate next string part
next_part = (f"{currency_string.ljust(left_justify_amount)}| "
f"{fine_type.replace('_', ' ').title()}\n")
# determine current string length if necessary
potential_response_length = len(username + ' ' + cur_string +
next_part)
# If username, space, violation string so far and new part are less or
# equal than 280 characters, append to existing tweet string.
if (potential_response_length <=
twitter_constants.MAX_TWITTER_STATUS_LENGTH):
cur_string += next_part
else:
response_chunks.append(cur_string)
cur_string = "Known fines for #{}_{}, cont'd:\n\n"
cur_string += next_part
# add to container
response_chunks.append(cur_string)
if camera_streak_data:
if camera_streak_data.max_streak and camera_streak_data.max_streak >= 5:
# formulate streak string
streak_string = (
f"Under @bradlander's proposed legislation, "
f"this vehicle could have been booted or impounded "
f"due to its {camera_streak_data.max_streak} camera violations "
f"(>= 5/year) from {camera_streak_data.min_streak_date}"
f" to {camera_streak_data.max_streak_date}.\n")
# add to container
response_chunks.append(streak_string)
unique_link: str = self._get_website_plate_lookup_link(
unique_identifier)
website_link_string = f'View more details at {unique_link}.'
response_chunks.append(website_link_string)
# Send it back!
return response_chunks
def _calculate_aggregate_data(self, plate_query: PlateQuery,
violations) -> OpenDataServicePlateLookup:
# Marshal all ticket data into form.
fines: FineData = FineData(fined=round(
sum(v['fined'] for v in violations.values() if v.get('fined')), 2),
reduced=round(
sum(v['reduced']
for v in violations.values()
if v.get('reduced')), 2),
paid=round(
sum(v['paid']
for v in violations.values()
if v.get('paid')), 2),
outstanding=round(
sum(v['outstanding']
for v in violations.values()
if v.get('outstanding')), 2))
tickets: List[Tuple[str, int]] = Counter([
v['violation'].title() for v in violations.values()
if v.get('violation') is not None
]).most_common()
years: List[Tuple[str, int]] = Counter([
datetime.strptime(v['issue_date'], self.TIME_FORMAT).strftime('%Y')
if v.get('has_date') else 'No Year Available'
for v in violations.values()
]).most_common()
boroughs: List[Tuple[str, int]] = Counter([
v['borough'].title() for v in violations.values()
if v.get('borough')
]).most_common()
camera_streak_data: Optional[
CameraStreakData] = self._find_max_camera_violations_streak(
sorted([
datetime.strptime(v['issue_date'], self.TIME_FORMAT)
for v in violations.values() if v.get('violation')
and v['violation'] in self.CAMERA_VIOLATIONS
]))
return OpenDataServicePlateLookup(
boroughs=[{
'count': v,
'title': k.title()
} for k, v in boroughs],
camera_streak_data=camera_streak_data,
fines=fines,
num_violations=len(violations),
plate=plate_query.plate,
plate_types=plate_query.plate_types,
state=plate_query.state,
violations=[{
'count': v,
'title': k.title()
} for k, v in tickets],
years=sorted([{
'count': v,
'title': k.title()
} for k, v in years],
key=lambda k: k['title']))
def test_look_up_vehicle_with_violations(self,
mocked_perform_query,
plate,
state=None,
medallion_query_result=None):
random_state_index = random.randint(
0, len(regexp_constants.STATE_ABBREVIATIONS) - 1)
random_plate_type_index = random.randint(
0, len(regexp_constants.PLATE_TYPES) - 1)
final_plate = plate if medallion_query_result is None else medallion_query_result[0][
'dmv_license_plate_number']
plate_type = regexp_constants.PLATE_TYPES[random_plate_type_index]
state = state if state else regexp_constants.STATE_ABBREVIATIONS[random_state_index]
all_borough_codes = [code for borough_list in list(
BOROUGH_CODES.values()) for code in borough_list]
all_precincts = [precinct for sublist in list(
PRECINCTS_BY_BOROUGH.values()) for precinct in sublist]
summons_numbers = set()
fiscal_year_databases_violations = []
for year, _ in FISCAL_YEAR_DATABASE_ENDPOINTS.items():
fy_violations = []
for _ in range(random.randint(10, 20)):
date = datetime(
year,
random.randint(1, 12),
random.randint(1, 28))
random_borough_code_index = random.randint(
0, len(all_borough_codes) - 1)
random_precinct_index = random.randint(
0, len(all_precincts) - 1)
random_violation_string_index = random.randint(
0, len(HUMANIZED_NAMES_FOR_FISCAL_YEAR_DATABASE_VIOLATIONS.keys())-1)
summons_number = random.randint(
1000000000,
9999999999)
while summons_number in summons_numbers:
summons_number = random.randint(
1000000000,
9999999999)
summons_numbers.add(summons_number)
fy_violations.append({
'date_first_observed': date.strftime('%Y-%m-%dT%H:%M:%S.%f'),
'feet_from_curb': '0 ft',
'from_hours_in_effect': '0800',
'house_number': '123',
'intersecting_street': '',
'issue_date': date.strftime('%Y-%m-%dT%H:%M:%S.%f'),
'issuer_code': '43',
'issuer_command': 'C',
'issuer_precinct': all_precincts[random_precinct_index],
'issuing_agency': 'TRAFFIC',
'law_section': '123 ABC',
'plate_id': plate,
'plate_type': plate_type,
'registration_state': state,
'street_code1': '123',
'street_code2': '456',
'street_code3': '789',
'street_name': 'Fake Street',
'sub_division': '23',
'summons_image': '',
'summons_number': summons_number,
'to_hours_in_effect': '2200',
'vehicle_body_type': 'SUV',
'vehicle_color': 'BLACK',
'vehicle_expiration_date': date + timedelta(days=180),
'vehicle_make': 'FORD',
'vehicle_year': '2017',
'violation_code': list(HUMANIZED_NAMES_FOR_FISCAL_YEAR_DATABASE_VIOLATIONS.keys())[random_violation_string_index],
'violation_county': all_borough_codes[random_borough_code_index],
'violation_in_front_of_or_opposite': '',
'violation_legal_code': '4-08',
'violation_location': '',
'violation_post_code': '12345',
'violation_precinct': all_precincts[random_precinct_index]})
fiscal_year_databases_violations.append(fy_violations)
open_parking_and_camera_violations = []
for _ in range(random.randint(10, 20)):
fine_amount = random.randint(10, 200)
interest_amount = round(float(random.randint(
0, math.floor(fine_amount/2)) + random.random()), 2)
penalty_amount = round(float(random.randint(
0, math.floor(fine_amount/2)) + random.random()), 2)
reduction_amount = round(float(random.randint(
0, math.floor(fine_amount/2)) + random.random()), 2)
payment_amount = round(float(random.randint(0, math.floor(
fine_amount + interest_amount + penalty_amount - reduction_amount))), 2)
amount_due = fine_amount + interest_amount + \
penalty_amount - reduction_amount - payment_amount
date = datetime(
random.randint(1999, 2020),
random.randint(1, 12),
random.randint(1, 28))
random_borough_code_index = random.randint(
0, len(all_borough_codes) - 1)
random_precinct_index = random.randint(
0, len(all_precincts) - 1)
random_violation_string_index = random.randint(
0, len(HUMANIZED_NAMES_FOR_OPEN_PARKING_AND_CAMERA_VIOLATIONS.keys())-1)
summons_number = random.randint(1000000000, 9999999999)
summons_numbers.add(summons_number)
open_parking_and_camera_violations.append({
'amount_due': amount_due,
'county': all_borough_codes[random_borough_code_index],
'fine_amount': fine_amount,
'interest_amount': interest_amount,
'issue_date': date.strftime('%m/%d/%Y'),
'issuing_agency': 'TRAFFIC',
'license_type': plate_type,
'payment_amount': payment_amount,
'penalty_amount': penalty_amount,
'plate': plate,
'precinct': all_precincts[random_precinct_index],
'reduction_amount': reduction_amount,
'state': state,
'summons': (f'http://nycserv.nyc.gov/NYCServWeb/'
f'ShowImage?searchID=VDBSVmQwNVVaekZ'
f'OZWxreFQxRTlQUT09&locationName='
f'_____________________'),
'summons_image_description': 'View Summons',
'summons_number': summons_number,
'violation': list(
HUMANIZED_NAMES_FOR_OPEN_PARKING_AND_CAMERA_VIOLATIONS.keys())[
random_violation_string_index],
'violation_status': 'HEARING HELD-GUILTY',
'violation_time': f'0{random.randint(1,9)}:{random.randint(10,59)}P'
})
side_effects = []
if medallion_query_result:
side_effects.append({'data': medallion_query_result})
side_effects.append({'data': copy.deepcopy(
open_parking_and_camera_violations)})
for violations_list in fiscal_year_databases_violations:
side_effects.append({'data': copy.deepcopy(violations_list)})
mocked_perform_query.side_effect = side_effects
open_parking_and_camera_violations_dict = {}
for summons in open_parking_and_camera_violations:
summons['borough'] = [boro for boro, precincts in PRECINCTS_BY_BOROUGH.items(
) if int(summons['precinct']) in precincts][0]
summons['has_date'] = True
summons['issue_date'] = datetime.strptime(
summons['issue_date'], '%m/%d/%Y').strftime('%Y-%m-%dT%H:%M:%S.%f')
summons['violation'] = HUMANIZED_NAMES_FOR_OPEN_PARKING_AND_CAMERA_VIOLATIONS[summons['violation']]
open_parking_and_camera_violations_dict[summons['summons_number']] = summons
fiscal_year_databases_violations_dict = {}
for violation_list in fiscal_year_databases_violations:
for summons in violation_list:
summons['borough'] = [boro for boro, precincts in PRECINCTS_BY_BOROUGH.items(
) if int(summons['violation_precinct']) in precincts][0]
summons['has_date'] = True
violation_code_definition = HUMANIZED_NAMES_FOR_FISCAL_YEAR_DATABASE_VIOLATIONS.get(summons['violation_code'])
humanized_description = None
if violation_code_definition:
if isinstance(violation_code_definition, list) and summons['issue_date']:
# Some violation codes have applied to multiple violations.
for possible_description in violation_code_definition:
if (datetime.strptime(possible_description['start_date'], '%Y-%m-%d').date() <
datetime.strptime(summons['issue_date'], '%Y-%m-%dT%H:%M:%S.%f').date()):
humanized_description = possible_description['description']
else:
humanized_description = violation_code_definition
summons['violation'] = humanized_description
fiscal_year_databases_violations_dict[summons['summons_number']] = summons
merged_violations = {**open_parking_and_camera_violations_dict,
**fiscal_year_databases_violations_dict}
for key, value in merged_violations.items():
if key in open_parking_and_camera_violations_dict and key in fiscal_year_databases_violations_dict:
merged_violations[key] = {**open_parking_and_camera_violations_dict[key], **fiscal_year_databases_violations_dict[key]}
fines_dict = {}
for prefix in ['fine', 'interest', 'penalty', 'reduction', 'payment']:
fines_dict[prefix] = sum(v[f'{prefix}_amount'] for v in merged_violations.values(
) if v.get(f'{prefix}_amount'))
fined = round(sum([fines_dict.get('fine', 0), fines_dict.get(
'interest', 0), fines_dict.get('penalty', 0)]), 2)
reduced = round(fines_dict.get('reduction', 0), 2)
paid = round(fines_dict.get('payment'), 2)
amount_due = round(fined - reduced - paid, 2)
fines: FineData = FineData(
fined=fined,
reduced=reduced,
paid=paid,
outstanding=amount_due)
tickets: list[Tuple[str, int]] = Counter([v['violation'].title() for v in merged_violations.values(
) if v.get('violation')]).most_common()
years: list[Tuple[str, int]] = Counter([datetime.strptime(v['issue_date'], '%Y-%m-%dT%H:%M:%S.%f').strftime('%Y') if v.get(
'has_date') else 'No Year Available' for v in merged_violations.values()]).most_common()
boroughs = Counter([v['borough'].title()
for v in merged_violations.values()]).most_common()
camera_streak_data = {
'Failure to Stop at Red Light': None,
'Mixed': None,
'School Zone Speed Camera Violation': None,
}
for violation_type in camera_streak_data:
if violation_type == 'Failure to Stop at Red Light':
violation_times = sorted(
[datetime.strptime(v['issue_date'], '%Y-%m-%dT%H:%M:%S.%f') for v in merged_violations.values(
) if v.get('violation') == 'Failure to Stop at Red Light'])
elif violation_type == 'Mixed':
violation_times = sorted(
[datetime.strptime(v['issue_date'], '%Y-%m-%dT%H:%M:%S.%f') for v in merged_violations.values(
) if v.get('violation') and v['violation'] in ['Failure to Stop at Red Light',
'School Zone Speed Camera Violation']])
elif violation_type == 'School Zone Speed Camera Violation':
violation_times = sorted(
[datetime.strptime(v['issue_date'], '%Y-%m-%dT%H:%M:%S.%f') for v in merged_violations.values(
) if v.get('violation') == 'School Zone Speed Camera Violation'])
if violation_times:
max_streak = 0
min_streak_date = None
max_streak_date = None
for date in violation_times:
year_later = date + \
(datetime(date.year + 1, 1, 1) - datetime(date.year, 1, 1))
year_long_tickets = [
comp_date for comp_date in violation_times if date <= comp_date < year_later]
this_streak = len(year_long_tickets)
if this_streak > max_streak:
max_streak = this_streak
min_streak_date = year_long_tickets[0]
max_streak_date = year_long_tickets[-1]
camera_streak_data[violation_type] = CameraStreakData(
min_streak_date=min_streak_date.strftime('%B %-d, %Y'),
max_streak=max_streak,
max_streak_date=max_streak_date.strftime('%B %-d, %Y'))
plate_query = PlateQuery(
created_at='Tue Dec 31 19:28:12 -0500 2019',
message_id=random.randint(
1000000000000000000,
2000000000000000000),
message_source='status',
plate=plate,
plate_types=plate_type,
state=state,
username='******')
result = OpenDataServiceResponse(
data=OpenDataServicePlateLookup(
boroughs=[{'count': v, 'title': k.title()}
for k, v in boroughs],
camera_streak_data=camera_streak_data,
fines=fines,
num_violations=len(merged_violations),
plate=final_plate,
plate_types=plate_query.plate_types,
state=plate_query.state,
violations=[{'count': v, 'title': k.title()}
for k, v in tickets],
years=sorted([{'count': v, 'title': k.title()}
for k, v in years], key=lambda k: k['title'])),
success=True)
self.assertEqual(self.open_data_service.look_up_vehicle(plate_query),
result)
def _form_plate_lookup_response_parts(
self,
borough_data: list[Tuple[str, int]],
frequency: int,
fine_data: FineData,
lookup_source: str,
plate: str,
plate_types: list[str],
state: str,
unique_identifier: str,
username: str,
violations: list[Tuple[str, int]],
year_data: list[Tuple[str, int]],
camera_streak_data: dict[str, CameraStreakData] = None,
previous_lookup: Optional[PlateLookup] = None):
# response_chunks holds tweet-length-sized parts of the response
# to be tweeted out or appended into a single direct message.
response_chunks: list[str] = []
violations_string: str = ""
# Get total violations
total_violations: int = sum([s['count'] for s in violations])
LOG.debug(f'total_violations: {total_violations}')
now_in_eastern_time = self.utc.localize(datetime.now())
time_prefix = now_in_eastern_time.strftime(
'As of %I:%M:%S %p on %B %-d, %Y:\n\n')
# Append username to blank string to start to build tweet.
violations_string += (f'@{username} {time_prefix}' if lookup_source
== lookup_sources.LookupSource.STATUS.value else
'')
# Append summary string.
violations_string += L10N.LOOKUP_SUMMARY_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate),
L10N.get_plate_types_string(plate_types), frequency,
L10N.pluralize(int(frequency)))
# If this vehicle has been queried before...
if previous_lookup:
previous_num_violations: int = previous_lookup.num_tickets
violations_string += self._create_repeat_lookup_string(
new_violations=(total_violations - previous_num_violations),
plate=plate,
previous_lookup=previous_lookup,
state=state,
username=username)
response_chunks.append(violations_string)
username_prefix = (
f'@{twitter_constants.HMDNY_TWITTER_HANDLE} {time_prefix}' if
lookup_source == lookup_sources.LookupSource.STATUS.value else '')
response_chunks += self._handle_response_part_formation(
collection=violations,
continued_format_string=L10N.LOOKUP_TICKETS_STRING_CONTD.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
description='title',
default_description='No Year Available',
prefix_format_string=L10N.LOOKUP_TICKETS_STRING.format(
total_violations),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username_prefix=username_prefix)
if year_data:
response_chunks += self._handle_response_part_formation(
collection=year_data,
continued_format_string=L10N.LOOKUP_YEAR_STRING_CONTD.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
description='title',
default_description='No Year Available',
prefix_format_string=L10N.LOOKUP_YEAR_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username_prefix=username_prefix)
if borough_data:
response_chunks += self._handle_response_part_formation(
collection=borough_data,
continued_format_string=L10N.LOOKUP_BOROUGH_STRING_CONTD.
format(L10N.VEHICLE_HASHTAG.format(state, plate)),
count='count',
description='title',
default_description='No Borough Available',
prefix_format_string=L10N.LOOKUP_BOROUGH_STRING.format(
L10N.VEHICLE_HASHTAG.format(state, plate)),
result_format_string=L10N.LOOKUP_RESULTS_DETAIL_STRING,
username_prefix=username_prefix)
if fine_data and fine_data.fines_assessed():
cur_string = (
f'{username_prefix}'
f'Known fines for {L10N.VEHICLE_HASHTAG.format(state, plate)}:\n\n'
)
max_count_length = len('${:,.2f}'.format(fine_data.max_amount()))
spaces_needed = (max_count_length * 2) + 1
for fine_type, amount in fine_data:
currency_string = '${:,.2f}'.format(amount)
count_length = len(str(currency_string))
# e.g., if spaces_needed is 5, and count_length is 2, we need
# to pad to 3.
left_justify_amount = spaces_needed - count_length
# formulate next string part
next_part = (f"{currency_string.ljust(left_justify_amount)}| "
f"{fine_type.replace('_', ' ').title()}\n")
# determine current string length if necessary
potential_response_length = len(cur_string + next_part)
# If violation string so far and new part are less or
# equal than 280 characters, append to existing tweet string.
if (potential_response_length <=
twitter_constants.MAX_TWITTER_STATUS_LENGTH):
cur_string += next_part
else:
response_chunks.append(cur_string)
cur_string = "Known fines for #{}_{}, cont'd:\n\n"
cur_string += next_part
# add to container
response_chunks.append(cur_string)
for camera_violation_type, threshold in self.CAMERA_THRESHOLDS.items():
violation_type_data = camera_streak_data[camera_violation_type]
if violation_type_data:
if (camera_violation_type == 'Failure to Stop at Red Light'
and violation_type_data.max_streak >= threshold):
# add to container
response_chunks.append(
L10N.
DANGEROUS_VEHICLE_ABATEMENT_ACT_REPEAT_OFFENDER_STRING.
format(username_prefix, violation_type_data.max_streak,
'red light', threshold,
violation_type_data.min_streak_date,
violation_type_data.max_streak_date))
elif (camera_violation_type
== 'School Zone Speed Camera Violation'
and violation_type_data.max_streak >= threshold):
# add to container
response_chunks.append(
L10N.
DANGEROUS_VEHICLE_ABATEMENT_ACT_REPEAT_OFFENDER_STRING.
format(username_prefix, violation_type_data.max_streak,
'school zone speed', threshold,
violation_type_data.min_streak_date,
violation_type_data.max_streak_date))
unique_link: str = self._get_website_plate_lookup_link(
unique_identifier)
website_link_string = f'View more details at {unique_link}.'
response_chunks.append(website_link_string)
# Send it back!
return response_chunks
def test_print_reckless_driver_retrospective(
self,
mocked_tweet_detection_service_tweet_exists,
mocked_traffic_violations_tweeter,
mocked_plate_lookup_get_all_in,
mocked_open_data_service_look_up_vehicle,
can_link_tweet=True,
dry_run=False,
new_camera_violations_string='10 new camera violations',
red_light_camera_tickets_after_previous_lookup=3,
red_light_camera_tickets_before_previous_lookup=5,
speed_camera_tickets_after_previous_lookup=7,
speed_camera_tickets_before_previous_lookup=15,
use_dvaa_thresholds: bool = False,
use_only_visible_tweets: bool = False):
job = RecklessDriverRetrospectiveJob()
mocked_tweet_detection_service_tweet_exists.return_value = can_link_tweet
plate = 'ABCDEFG'
plate_types = 'COM,PAS'
state = 'NY'
now = datetime.now()
previous_message_id = random.randint(1000000000000000000,
2000000000000000000)
previous_message_source = 'status'
previous_num_tickets = 123
previous_username = '******'
rdaa_max_streak = (red_light_camera_tickets_before_previous_lookup +
speed_camera_tickets_before_previous_lookup)
rdaa_min_streak_date = datetime(2018, 11, 26, 0, 0,
0).strftime('%B %-d, %Y')
rdaa_max_streak_date = datetime(2019, 11, 22, 0, 0,
0).strftime('%B %-d, %Y')
dvaa_red_light_camera_max_streak = red_light_camera_tickets_before_previous_lookup
dvaa_red_light_camera_min_streak_date = datetime(
2018, 9, 14, 0, 0, 0).strftime('%B %-d, %Y')
dvaa_red_light_camera_max_streak_date = datetime(
2019, 12, 17, 0, 0, 0).strftime('%B %-d, %Y')
dvaa_speed_camera_max_streak = speed_camera_tickets_before_previous_lookup
dvaa_speed_camera_min_streak_date = datetime(2018, 11, 26, 0, 0,
0).strftime('%B %-d, %Y')
dvaa_speed_camera_max_streak_date = datetime(2019, 11, 22, 0, 0,
0).strftime('%B %-d, %Y')
plate_lookup_to_return = PlateLookup(
bus_lane_camera_violations=2,
created_at=datetime(2020, 1, 3, 14, 37, 12),
message_id=previous_message_id,
message_source=previous_message_source,
num_tickets=previous_num_tickets,
plate=plate,
plate_types=plate_types,
red_light_camera_violations=
red_light_camera_tickets_before_previous_lookup,
speed_camera_violations=speed_camera_tickets_before_previous_lookup,
state=state,
username=previous_username)
below_dvaa_thresholds = (dvaa_red_light_camera_max_streak < 5
and dvaa_speed_camera_max_streak < 15)
new_camera_violations_exist = (
red_light_camera_tickets_after_previous_lookup +
speed_camera_tickets_after_previous_lookup) > 0
if use_dvaa_thresholds and below_dvaa_thresholds:
# We don't expect a lookup here.
expect_response = False
plate_lookups = []
elif use_only_visible_tweets and not can_link_tweet:
# We don't expect a lookup here.
expect_response = False
plate_lookups = [plate_lookup_to_return]
elif not new_camera_violations_exist:
# We don't expect a lookup here.
expect_response = False
plate_lookups = [plate_lookup_to_return]
elif dry_run:
# We don't expect a lookup here.
expect_response = False
plate_lookups = [plate_lookup_to_return]
else:
expect_response = True
plate_lookups = [plate_lookup_to_return]
mocked_plate_lookup_get_all_in.return_value = plate_lookups
open_data_plate_lookup_before_previous_lookup = OpenDataServicePlateLookup(
boroughs=[],
camera_streak_data={
'Failure to Stop at Red Light':
CameraStreakData(
min_streak_date=dvaa_red_light_camera_min_streak_date,
max_streak=dvaa_red_light_camera_max_streak,
max_streak_date=dvaa_red_light_camera_max_streak_date),
'Mixed':
CameraStreakData(min_streak_date=rdaa_min_streak_date,
max_streak=rdaa_max_streak,
max_streak_date=rdaa_max_streak_date),
'School Zone Speed Camera Violation':
CameraStreakData(
min_streak_date=dvaa_speed_camera_min_streak_date,
max_streak=dvaa_speed_camera_max_streak,
max_streak_date=dvaa_speed_camera_max_streak_date),
},
fines=FineData(),
num_violations=150,
plate=plate,
plate_types=plate_types,
state=state,
violations=[{
'count': red_light_camera_tickets_before_previous_lookup,
'title': 'Failure To Stop At Red Light'
}, {
'count': speed_camera_tickets_before_previous_lookup,
'title': 'School Zone Speed Camera Violation'
}],
years=[])
open_data_response_before_previous_lookup = OpenDataServiceResponse(
data=open_data_plate_lookup_before_previous_lookup, success=True)
open_data_plate_lookup_after_previous_lookup = OpenDataServicePlateLookup(
boroughs=[],
camera_streak_data={
'Failure to Stop at Red Light':
CameraStreakData(
min_streak_date=dvaa_red_light_camera_min_streak_date,
max_streak=dvaa_red_light_camera_max_streak,
max_streak_date=dvaa_red_light_camera_max_streak_date),
'Mixed':
CameraStreakData(min_streak_date=rdaa_min_streak_date,
max_streak=rdaa_max_streak,
max_streak_date=rdaa_max_streak_date),
'School Zone Speed Camera Violation':
CameraStreakData(
min_streak_date=dvaa_speed_camera_min_streak_date,
max_streak=dvaa_speed_camera_max_streak,
max_streak_date=dvaa_speed_camera_max_streak_date),
},
fines=FineData(),
num_violations=150,
plate=plate,
plate_types=plate_types,
state=state,
violations=[{
'count': red_light_camera_tickets_after_previous_lookup,
'title': 'Failure To Stop At Red Light'
}, {
'count': speed_camera_tickets_after_previous_lookup,
'title': 'School Zone Speed Camera Violation'
}],
years=[])
open_data_response_after_previous_lookup = OpenDataServiceResponse(
data=open_data_plate_lookup_after_previous_lookup, success=True)
mocked_open_data_service_look_up_vehicle.side_effect = [
open_data_response_before_previous_lookup,
open_data_response_after_previous_lookup
]
can_link_tweet_string = (
f' by @BarackObama: '
f'https://twitter.com/BarackObama/status/{previous_message_id}'
if can_link_tweet else '')
red_light_camera_tickets_diff_string = (
f'{red_light_camera_tickets_after_previous_lookup} | Red Light Camera Violations\n'
if red_light_camera_tickets_after_previous_lookup else '')
speed_camera_tickets_diff_string = (
f'{speed_camera_tickets_after_previous_lookup} | Speed Safety Camera Violations\n'
if speed_camera_tickets_after_previous_lookup else '')
summary_string = (
f'#NY_ABCDEFG was originally queried on January 3, 2020 at 09:37AM'
f'{can_link_tweet_string}.')
update_string = (
f'From November 26, 2018 to November 22, 2019, this vehicle '
f'received 20 camera violations. Over the past 12 months, this '
f'vehicle received {new_camera_violations_string}: \n\n'
f'{red_light_camera_tickets_diff_string}'
f'{speed_camera_tickets_diff_string}')
job.run(is_dry_run=dry_run,
use_only_visible_tweets=use_only_visible_tweets)
if expect_response:
mocked_traffic_violations_tweeter().send_status.assert_called_with(
message_parts=[summary_string, update_string],
on_error_message=(f'Error printing reckless driver update. '
f'Tagging @bdhowald.'))
else:
mocked_traffic_violations_tweeter().send_status.assert_not_called()
def test_print_reckless_driver_retrospective(self,
mocked_tweet_detection_service_tweet_exists,
mocked_traffic_violations_tweeter,
mocked_plate_lookup_get_all_in,
mocked_plate_lookup_query,
mocked_open_data_service_look_up_vehicle,
can_link_tweet=False,
dry_run=False,
new_camera_violations_string='10 new camera violations',
red_light_camera_tickets_after_previous_lookup=3,
speed_camera_tickets_after_previous_lookup=7,
red_light_camera_tickets_before_previous_lookup=8,
speed_camera_tickets_before_previous_lookup=12):
job = RecklessDriverRetrospectiveJob()
# mocked_plate_lookup_query.session.query(
# ).filter().group_by().all.return_value = [1,2,3]
mocked_tweet_detection_service_tweet_exists.return_value = can_link_tweet
plate = 'ABCDEFG'
plate_types = 'COM,PAS'
state = 'NY'
now = datetime.now()
previous_message_id = random.randint(1000000000000000000, 2000000000000000000)
previous_message_source = 'status'
previous_num_tickets = 123
previous_username = '******'
max_streak = 20
min_streak_date = datetime(2018, 11, 26, 0, 0, 0).strftime('%B %-d, %Y')
max_streak_date = datetime(2019, 11, 22, 0, 0, 0).strftime('%B %-d, %Y')
plate_lookups = [
PlateLookup(
bus_lane_camera_violations=2,
created_at=datetime(2020, 1, 3, 14, 37, 12),
message_id=previous_message_id,
message_source=previous_message_source,
num_tickets=previous_num_tickets,
plate=plate,
plate_types=plate_types,
red_light_camera_violations=red_light_camera_tickets_before_previous_lookup,
speed_camera_violations=speed_camera_tickets_before_previous_lookup,
state=state,
username=previous_username)]
mocked_plate_lookup_get_all_in.return_value = plate_lookups
open_data_plate_lookup_before_previous_lookup = OpenDataServicePlateLookup(
boroughs=[],
camera_streak_data=CameraStreakData(
min_streak_date=min_streak_date,
max_streak=max_streak,
max_streak_date=max_streak_date),
fines=FineData(),
num_violations=150,
plate=plate,
plate_types=plate_types,
state=state,
violations=[
{'count': red_light_camera_tickets_before_previous_lookup,
'title': 'Failure To Stop At Red Light'},
{'count': speed_camera_tickets_before_previous_lookup, 'title':
'School Zone Speed Camera Violation'}],
years=[])
open_data_response_before_previous_lookup = OpenDataServiceResponse(
data=open_data_plate_lookup_before_previous_lookup,
success=True)
open_data_plate_lookup_after_previous_lookup = OpenDataServicePlateLookup(
boroughs=[],
camera_streak_data=CameraStreakData(
min_streak_date=min_streak_date,
max_streak=max_streak,
max_streak_date=max_streak_date),
fines=FineData(),
num_violations=150,
plate=plate,
plate_types=plate_types,
state=state,
violations=[
{'count': red_light_camera_tickets_after_previous_lookup,
'title': 'Failure To Stop At Red Light'},
{'count': speed_camera_tickets_after_previous_lookup, 'title':
'School Zone Speed Camera Violation'}],
years=[])
open_data_response_after_previous_lookup = OpenDataServiceResponse(
data=open_data_plate_lookup_after_previous_lookup,
success=True)
mocked_open_data_service_look_up_vehicle.side_effect = [
open_data_response_before_previous_lookup, open_data_response_after_previous_lookup]
can_link_tweet_string = (
f' by @BarackObama: '
f'https://twitter.com/BarackObama/status/{previous_message_id}'
if can_link_tweet else '')
red_light_camera_tickets_diff_string = (
f'{red_light_camera_tickets_after_previous_lookup} | Red Light Camera Violations\n'
if red_light_camera_tickets_after_previous_lookup else '')
speed_camera_tickets_diff_string = (
f'{speed_camera_tickets_after_previous_lookup} | Speed Safety Camera Violations\n'
if speed_camera_tickets_after_previous_lookup else '')
summary_string = (
f'#NY_ABCDEFG was originally queried on January 3, 2020 at 09:37AM'
f'{can_link_tweet_string}.')
update_string = (
f'From November 26, 2018 to November 22, 2019, this vehicle '
f'received 20 camera violations. Over the past 12 months, this '
f'vehicle received {new_camera_violations_string}: \n\n'
f'{red_light_camera_tickets_diff_string}'
f'{speed_camera_tickets_diff_string}')
reckless_string = (
f'Thank you to @bradlander for making the Dangerous Driver '
f'Abatement Act a reality.')
job_should_be_run = (red_light_camera_tickets_after_previous_lookup +
speed_camera_tickets_after_previous_lookup) > 0
job.run(is_dry_run=dry_run)
if not dry_run and job_should_be_run:
mocked_traffic_violations_tweeter().send_status.assert_called_with(
message_parts=[summary_string, update_string, reckless_string],
on_error_message=(
f'Error printing reckless driver update. '
f'Tagging @bdhowald.'))