def test_wrong_gmaps_key(self):
address = Address(self.valid_address)
tmp = address.gmaps
address.gmaps = googlemaps.Client(key=self.BROKEN_GMAPS_KEY)
with self.assertRaises(addressClass.InvalidGmapsKey):
address._get_address_info(address.formatted_address)
address.gmaps = tmp
def test_address_init(self):
#This part success if address not in Chicago exception is raised
with self.assertRaises(ValueError):
address = Address(self.invalid_address)
#First part success if no exceptions are raised.
address = Address(self.valid_address)
self.assertAlmostEqual(address.lat, self.valid_lat_lon[0], places=3)
self.assertAlmostEqual(address.lon, self.valid_lat_lon[1], places=3)
self.assertAlmostEqual
def setUp(self):
self.address_wrong = 'asdf'
self.address = Address('4334 West Washington Blvd')
self.test_db = pd.DataFrame(
[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=['Year', 'Month', 'Arrest', 'District'])
self.test_CrimesDataFrame = CrimesDataFrame(self.test_db)
self.malformed_addresses_array = [1, 2, 3, 4]
self.addresses_array = [self.address, self.address]
self.zero_addresses_array = []
def test_wrong_gmaps_key(self):
address = Address(self.valid_address)
tmp = address.gmaps
address.gmaps = googlemaps.Client(key=self.BROKEN_GMAPS_KEY)
with self.assertRaises(addressClass.InvalidGmapsKey):
address._get_address_info(address.formatted_address)
address.gmaps = tmp
def setUp(self):
#Useful attributes for testing
self.good_address = Address('4334 W Washington Blv')
self.data = pd.read_csv('./tests/csv_for_test.csv')
def main():
# Maximum number of addresses for analysis allowed
MAX_ADDRESSES = 10
interface_utils.display_welcome_screen()
# Load DB of crimes. If Database is not clean, the program will clean it and the user will have the option to save it
crimes_database = databases_utils.get_crimes_db()
os.system('clear')
# Ask for user to choose a range of years and filter the Database accordingly
crimes_database = databases_utils.filter_db_by_timeframe(crimes_database)
# Ask for user to choose one or more types of crime and filter the Database accordingly
crimes_database = databases_utils.filter_db_by_crime(crimes_database)
# Create an instance of the CrimesDataFrame class with the filtered Database. This class is in charge of Statistics
crimes_database = CrimesDataFrame(crimes_database)
# Create lists to save addresses and addresses names of interest
user_addresses = []
user_addresses_names = []
# Create interface Options
interface_options = ['Add another address','Delete saved address',
'View saved address', 'Comparative analysis','Quit']
option = 'Add another address'
# Main loop of the program. It will ask for user input and show maps and analyses until 'Quit' is introduced
while 1:
if (not user_addresses) or option == 'Add another address':
try:
# Create an instance of Address class. It will ask user to input an address, validate it through
# Google Maps, and calculate/save several attributes of that address.
address = Address()
except NoInternetAccess:
print('No Internet connection found')
if interface_utils.yesno_question('Continue?'):
address = None # Continue with the normal loop without saving the address
else:
raise QuitProgram
# Create a District Heat Map with maps_builder class and show it.
if address:
interface_utils.computing_statistics_message()
address.summary = address_analysis(crimes_database, address)
address_analysis_output(address, crimes_database)
# User will have the option to save/discard the address after reviewing the Map and Statistics.
if interface_utils.yesno_question('Keep this address for comparative analysis?'):
if len(user_addresses) == MAX_ADDRESSES:
print 'Maximum number of addresses to save reached, delete one location before adding a new address'
else:
if address not in user_addresses:
user_addresses.append(address)
user_addresses_names.append(address.formatted_address)
# This option will allow the user to review the Map and Stats of an address that was saved.
elif option == 'View saved address':
option = interface_utils.get_options_from_user(user_addresses_names + ['Back'], multiple=False)
if option != 'Back':
address = user_addresses[user_addresses_names.index(option)]
interface_utils.computing_statistics_message()
address_analysis_output(address, crimes_database)
# This option will allow the user to delete one of the saved addresses.
elif option == 'Delete saved address':
option = interface_utils.get_options_from_user(user_addresses_names + ['Back'], multiple=False)
if option != 'Back':
user_addresses.pop(user_addresses_names.index(option))
user_addresses_names.pop(user_addresses_names.index(option))
# This option will create a comparative Map and statistics to analyze and compare the saved addresses.
elif option == 'Comparative analysis':
comparative_analysis_output(crimes_database, user_addresses)
# This option is the only way to end the loop and finish the program
elif option == 'Quit':
raise QuitProgram
# If user_addresses is empty start the loop again directly to ask for an address
# If there are addresses in user_addresses, offer options on how to continue
if user_addresses:
option = interface_utils.get_options_from_user(interface_options, multiple=False)
def main():
# Maximum number of addresses for analysis allowed
MAX_ADDRESSES = 10
interface_utils.display_welcome_screen()
# Load DB of crimes. If Database is not clean, the program will clean it and the user will have the option to save it
crimes_database = databases_utils.get_crimes_db()
os.system('clear')
# Ask for user to choose a range of years and filter the Database accordingly
crimes_database = databases_utils.filter_db_by_timeframe(crimes_database)
# Ask for user to choose one or more types of crime and filter the Database accordingly
crimes_database = databases_utils.filter_db_by_crime(crimes_database)
# Create an instance of the CrimesDataFrame class with the filtered Database. This class is in charge of Statistics
crimes_database = CrimesDataFrame(crimes_database)
# Create lists to save addresses and addresses names of interest
user_addresses = []
user_addresses_names = []
# Create interface Options
interface_options = [
'Add another address', 'Delete saved address', 'View saved address',
'Comparative analysis', 'Quit'
]
option = 'Add another address'
# Main loop of the program. It will ask for user input and show maps and analyses until 'Quit' is introduced
while 1:
if (not user_addresses) or option == 'Add another address':
try:
# Create an instance of Address class. It will ask user to input an address, validate it through
# Google Maps, and calculate/save several attributes of that address.
address = Address()
except NoInternetAccess:
print('No Internet connection found')
if interface_utils.yesno_question('Continue?'):
address = None # Continue with the normal loop without saving the address
else:
raise QuitProgram
# Create a District Heat Map with maps_builder class and show it.
if address:
interface_utils.computing_statistics_message()
address.summary = address_analysis(crimes_database, address)
address_analysis_output(address, crimes_database)
# User will have the option to save/discard the address after reviewing the Map and Statistics.
if interface_utils.yesno_question(
'Keep this address for comparative analysis?'):
if len(user_addresses) == MAX_ADDRESSES:
print 'Maximum number of addresses to save reached, delete one location before adding a new address'
else:
if address not in user_addresses:
user_addresses.append(address)
user_addresses_names.append(address.formatted_address)
# This option will allow the user to review the Map and Stats of an address that was saved.
elif option == 'View saved address':
option = interface_utils.get_options_from_user(
user_addresses_names + ['Back'], multiple=False)
if option != 'Back':
address = user_addresses[user_addresses_names.index(option)]
interface_utils.computing_statistics_message()
address_analysis_output(address, crimes_database)
# This option will allow the user to delete one of the saved addresses.
elif option == 'Delete saved address':
option = interface_utils.get_options_from_user(
user_addresses_names + ['Back'], multiple=False)
if option != 'Back':
user_addresses.pop(user_addresses_names.index(option))
user_addresses_names.pop(user_addresses_names.index(option))
# This option will create a comparative Map and statistics to analyze and compare the saved addresses.
elif option == 'Comparative analysis':
comparative_analysis_output(crimes_database, user_addresses)
# This option is the only way to end the loop and finish the program
elif option == 'Quit':
raise QuitProgram
# If user_addresses is empty start the loop again directly to ask for an address
# If there are addresses in user_addresses, offer options on how to continue
if user_addresses:
option = interface_utils.get_options_from_user(interface_options,
multiple=False)
def setUp(self):
self.good_address = Address('4334 W Washington Blv')
self.data = pd.read_csv('./tests/csv_for_test.csv')