def query_google(company_name, google_apikey, country_codes=None, additional_keywords=None):
additional_keywords = ['plant'] if additional_keywords is None else additional_keywords
google_maps = Client(key=google_apikey)
if country_codes is None:
raise Exception("""
List of ISO 3166-1 alpha-2 country codes required, e.g. country_code_list=['DE'].
See https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2 for codes.""")
all_res = []
for cc in country_codes:
country_res = google_maps.places(' '.join([company_name] + additional_keywords), region=cc).get('results')
if country_res:
all_res += [r for r in country_res if
any(
[company_name.lower() in r.get(f, '').lower() for f in ['formatted_address', 'name']]) and
not any(
[term in r.get('formatted_address', '').lower() for term in
[f'near {company_name}', f'behind {company_name}']])]
all_res = [r for r in all_res if not any([tag in r['types'] for tag in ['car_dealer', 'car_repair', 'store']])]
addresses = pd.DataFrame([[d['name'],
d['formatted_address'],
d['geometry']['location']['lat'],
d['geometry']['location']['lng']]
for d in all_res], columns=['name', 'address', 'lat', 'lng'])
addresses = addresses.assign(
source='places_apis'
)
return addresses
now = datetime.now()
directions_result = gmaps.directions("Sydney Town Hall",
"Parramatta, NSW",
mode="transit",
departure_time=now)
lat_long = (gmaps.geocode(
'326 Perkins Library, Durham, NC 27708')[0]['geometry']['location']['lat'],
gmaps.geocode('326 Perkins Library, Durham, NC 27708')[0]
['geometry']['location']['lng'])
print lat_long
duke = gmaps.reverse_geocode(lat_long)[0]['formatted_address']
print duke
local = gmaps.places('restaurant near ' + duke)
print local['results'][0]['formatted_address']
print local['results'][0]['name']
directions = gmaps.directions(duke, whitehouse)
print directions[0]['legs'][0]['distance']
for step in directions[0]['legs'][0]['steps']:
print step['html_instructions']
embassies = [[38.917228, -77.0522365], [38.9076502, -77.0370427],
[38.916944, -77.048739]]
# TODO: write code to answer the following questions:
# which embassy is closest to the White House in meters? how far?
destinations = []
def get_detail_from_address(address: str, client: googlemaps.Client):
return client.places(address)
def get_postal_code_from_address(address: str, client: googlemaps.Client):
return client.places(address)['results'][0]['formatted_address'][-6:]
query = st.text_input(label="What kind of place do you want to search for?")
radius = st.slider(label="Search Radius (m): ",
min_value=0,
max_value=25,
value=10)
op_time = st.radio("Place open now or later?: ", options=['Now', 'Later'])
if (address != '') and (query != ''):
geocode_result = gmaps.geocode(address)
latitude = geocode_result[0]['geometry']['location']['lat']
longitude = geocode_result[0]['geometry']['location']['lng']
lat_long = (latitude, longitude)
results = gmaps.places(query=query,
radius=radius,
location=lat_long,
open_now=True)
headers = results['results'][0].keys()
data_path = str(query) + str(now)
data_path = f'{data_path}' + '.csv'
with open(data_path, 'w') as f:
dict_writer = csv.DictWriter(f, headers)
dict_writer.writeheader()
dict_writer.writerows(results['results'])
nr = nearest_restaurants(f"{data_path}")
st.write("## Objectives: ")
st.write("- Transforming Coordinates Into Data via Google Maps API")
st.write("- Visualizing Data on a Map")
now = datetime.now()
directions_result = gmaps.directions("Sydney Town Hall",
"Parramatta, NSW",
mode="transit",
departure_time=now)
lat_long = (gmaps.geocode(
'326 Perkins Library, Durham, NC 27708')[0]['geometry']['location']['lat'],
gmaps.geocode('326 Perkins Library, Durham, NC 27708')[0]
['geometry']['location']['lng'])
print lat_long
duke = gmaps.reverse_geocode(lat_long)[0]['formatted_address']
print duke
local = gmaps.places('restaurant near ' + duke)
print local['results'][0]['formatted_address']
print local['results'][0]['name']
directions = gmaps.directions(duke, whitehouse)
print directions[0]['legs'][0]['distance']
for step in directions[0]['legs'][0]['steps']:
print step['html_instructions']
embassies = [[38.917228, -77.0522365], [38.9076502, -77.0370427],
[38.916944, -77.048739]]
def nearest_embassy(wh, embassy_list):
e_dist = distances(wh, embassy_list)
shortest = min(e_dist)
