def test_csv_reader_malformed_data_contents(city_list_location_malformed):
"""
Sad Path Test
"""
with pytest.raises(ValueError) as exp:
data_processor.csv_reader(city_list_location_malformed)
assert str(
exp.value) == "could not convert string to float: 'not_an_altitude'"
def test_csv_reader_malformed_data_contents(city_list_location_malformed):
"""
Sad Path Test
We will need to wrap the following line
in the exceptions context manager:
"""
with pytest.raises(ValueError) as exp:
data_processor.csv_reader(city_list_location_malformed)
print(str(exp.value))
def test_csv_reader_malformed_data_contents(city_list_location_malformed):
"""
Sad Path Test
We will need to wrap the following line
in the exceptions context manager:
"""
with pytest.raises(ValueError) as exp:
data_processor.csv_reader(city_list_location_malformed)
assert str(exp.value) == "could not convert string to float: 'not_an_altitude'"
def test_data_population_no_update():
"""
Sad Path test: We don't want the data transformed twice
"""
map_data_location = 'tests/resources/cities/clean_map.csv'
data = data_processor.csv_reader(map_data_location)
data_to_transform = map_population_update.MapData(data, False)
population_dict = {
'Andorra': 77142,
'Argentina': 44780677,
'Cape Verde': 546388,
'Germany': 83670653,
'Greece': 10473455,
'India': 1366417754,
'Japan': 128860301,
'Morocco': 36471769,
'Senegal': 16296364,
'United States': 329064917
}
data_to_transform.add_population(
population_dict) # transform object in place
# Try calling the function again
with pytest.raises(Exception) as e:
data_to_transform.add_population(population_dict)
assert str(e.value) == 'You cannot transform the data twice'
def test_data_population_update():
"""
Happy Path test
"""
map_data_location = 'tests/resources/cities/clean_map.csv'
data = data_processor.csv_reader(map_data_location)
data_to_transform = map_population_update.MapData(data, False)
population_dict = {
'Andorra': 77142,
'Argentina': 44780677,
'Cape Verde': 546388,
'Germany': 83670653,
'Greece': 10473455,
'India': 1366417754,
'Japan': 128860301,
'Morocco': 36471769,
'Senegal': 16296364,
'United States': 329064917
}
data_to_transform.add_population(
population_dict) # transform object in place
for row in data_to_transform.get_data():
assert 'Population' in row
assert 'Updated' in row
def _specify_type(file_name_or_type):
for f in files:
if file_name_or_type != '.json':
data = data_processor.csv_reader(city_list_location + f)
else:
data = data_processor.json_reader(city_list_location + f)
return data
def _specify_type(filename):
for f in files:
if filename == f:
if filename.endswith('.json'):
data = data_processor.json_reader(city_list_location + f)
elif filename.endswith('.csv'):
data = data_processor.csv_reader(city_list_location + f)
return data
def prep_transform_data(map_data_location):
population_dict = {
'Andorra': 77142,
'Argentina': 44780677,
'Cape Verde': 546388,
'Germany': 83670653,
'Greece': 10473455,
'India': 1366417754,
'Japan': 128860301,
'Morocco': 36471769,
'Senegal': 16296364,
'United States': 329064917
}
data = data_processor.csv_reader(map_data_location)
data_to_transform = map_population_update.MapData(data, False)
yield data_to_transform, population_dict
def process_data(city_list_location):
yield data_processor.csv_reader(city_list_location)
