def search_city(state):
search_engine = ZipcodeSearchEngine()
state = search_engine.by_city(str(state))
cities = []
for i in state:
cities.append(i.City)
return cities
def filter_posts(self, service, location, company, rating):
search = ZipcodeSearchEngine()
if service != "None" and location != "None" and company == 'None' and rating == 'None':
res = search.by_city(location)
city_zips = []
for i in range(0, len(res)):
city_zips.append(res[i].Zipcode)
return Post.query.join(Company).filter(
Company.company_zipcode.in_(city_zips), Post.service_id == service)
def search_zip(city):
search_engine = ZipcodeSearchEngine()
city = search_engine.by_city(str(city))
zipcodes = []
for i in city:
zipcodes.append(i.Zipcode)
return zipcodes
df = pd.read_csv("inputDB.csv")
for i in range(len(df)):
if (i % 10000 == 0):
print("Cleaned", i, " rows")
zip = prepare_zip(df)
ssn = prepare_ssn(df)
clean_ssn(df, i, ssn)
if len(zip) == 5:
set_by_zip(zip, df, i)
else:
try:
L_city = search._find_city(df['City'].values[i], best_match=True)
df.iloc[i, df.columns.get_loc('City')] = L_city[0]
res = search.by_city(L_city[0])
if (len(res) == 0):
try:
L_state = search._find_city(df['State'].values[i],
best_match=True)
df.iloc[i, df.columns.get_loc('State')] = L_state[0]
res = search.by_state(L_state[0])
if (len(res) == 0):
set_unknown(df, i)
else:
set_by_state_and_city(res, L_state, df)
except ValueError:
set_unknown(df, i)
else:
set_by_city(df, i, res)
except ValueError:
