def calculate_distances(self, location_list):
'''
We allow users to look for tickets that are within x miles of their location.
Every user and every ticket will have an associated Location record, and every Location record has a latitude
and a longitude.
This function calculates the distance between every location record in the system and indexes them based on
whether they are less than the distance defined in TICKET_DISTANCE_CHOICES.
'''
distance_dict = {}
# The index is included so that we don't do every comparison twice. Obviously the distance between x and y is
# the same distance between y and x.
for index, location1 in enumerate(location_list):
for location2 in location_list[index + 1:]:
try:
distance = calculate_distance_between_zip_codes(location1, location2)
except ValueError:
return
for radius in TICKET_DISTANCE_CHOICES:
if distance <= radius:
if location1.zip_code in distance_dict:
if radius in distance_dict[location1.zip_code]:
distance_dict[location1.zip_code][radius].append(location2.zip_code)
else:
distance_dict[location1.zip_code] = {radius: [location2.zip_code]}
else:
distance_dict[location1.zip_code] = {radius: [location2.zip_code]}
if location2.zip_code in distance_dict:
if radius in distance_dict[location2.zip_code]:
distance_dict[location2.zip_code][radius].append(location1.zip_code)
else:
distance_dict[location2.zip_code] = {radius: [location1.zip_code]}
else:
distance_dict[location2.zip_code] = {radius: [location1.zip_code]}
logging.debug('Evaluating zip code {} with {}'.format(location1.zip_code, location2.zip_code))
self.write_json_file(distance_dict, self.output_file)
def read_zip_codes(self):
location_list = []
alias_list = []
same_city_state = []
# Note that these shadow the imported Alias and Location objects form within this function scope!
Location = namedtuple('Location', ['line_no', 'zip_code', 'latitude', 'longitude', 'primary_city', 'state',
'estimated_population', 'timezone'])
Alias = namedtuple('Alias', ['zip_code', 'name', 'state', 'estimated_population'])
city_state_combos = {}
try:
reader = csv.reader(open(self.input_file))
# If the file isn't available locally, get it from s3
except:
bucket, key = self.open_s3()
key.key = 'static_root/locations/csv/zip_code_database.csv'
# Handle everything in memory
csv_file = key.get_contents_as_string().decode("utf-8") #get_contents_as_string() is actually returning a bytes object
reader = csv.reader(StringIO(csv_file)) # csv.reader cannot take a string! It needs a file object
for (zip_code, mail_type, primary_city, aliases, unacceptable_cities, state, county, timezone, area_codes,
latitude, longitude, world_region, country, decommissioned, estimated_population, notes) in reader:
# Skip the line containing the column definitions
if reader.line_num == 1:
continue
# Do not handle any zip codes outside of the US
if country != 'US':
logging.debug('line #{}: country equal to {}'.format(reader.line_num, country))
continue
# Do not handle military zip codes
if mail_type == 'MILITARY':
logging.debug('line #{}: country equal to {}'.format(reader.line_num, mail_type))
continue
if state not in states_abbreviation_list:
logging.debug('line #{}: state equal to {}'.format(reader.line_num, state))
continue
else:
# All strings in the database are lowercase. Let's work with lowercase from the beginning.
state = state.lower()
if latitude:
latitude = float(latitude)
else:
logging.error('line #{}: Latitude not present.'.format(reader.line_num))
if longitude:
longitude = float(longitude)
else:
logging.error('line #{}: longitude not present.'.format(reader.line_num))
if not zip_code:
logging.error('line #{}: zipcode not present.'.format(reader.line_num))
if primary_city:
# All strings in the database are lowercase. Let's work with lowercase from the beginning.
primary_city = primary_city.strip().lower()
else:
logging.error('line #{}: primary_city not present.'.format(reader.line_num))
if not county:
logging.debug('line #{}: county not present.'.format(reader.line_num))
if not timezone:
logging.error('line #{}: timezone not present for zipcode {}'.format(reader.line_num, zip_code))
continue
if estimated_population:
estimated_population = int(estimated_population)
else:
logging.debug('line #{}: estimated populated not present. Marking as 0'.format(reader.line_num))
estimated_population = 0
if aliases:
aliases = [city.strip().lower() for city in aliases.split(',')]
for name in aliases:
alias = Alias(zip_code, name, state, estimated_population=estimated_population)
alias_list.append(alias)
location = Location(reader.line_num, zip_code, latitude, longitude,
primary_city, state, estimated_population, timezone)
location_list.append(location)
if not (primary_city, state) in city_state_combos:
city_state_combos[(primary_city, state)] = location
else:
location1 = city_state_combos[(primary_city, state)]
location2 = Location(line_no=reader.line_num, latitude=latitude, longitude=longitude,
primary_city=primary_city, state=state, zip_code=zip_code,
estimated_population=estimated_population, timezone=timezone)
if (location1.latitude, location1.longitude) != (location2.latitude, location2.longitude):
distance_apart = calculate_distance_between_zip_codes(location1, location2)
if distance_apart > 10:
same_city_state.append((distance_apart, location1, location2))
if same_city_state:
same_city_state = sorted(same_city_state, key=lambda loc: loc[0])
for match in same_city_state:
logging.critical('{distance:.2f}\n {loc1}\n {loc2}\n\n'.format(distance=match[0],
loc1=match[1],
loc2=match[2]))
return location_list, alias_list
