def test_local_search(self):
"""Test googlemaps local_search()."""
gmaps = GoogleMaps(GMAPS_API_KEY, referrer_url='http://www.google.com/')
local = gmaps.local_search('sushi san francisco, ca')
result = local['responseData']['results'][0]
self.assertEqual(result['titleNoFormatting'], 'Sushi Groove')
results = gmaps.local_search('Starbucks Los Angeles, CA', numresults=GoogleMaps.MAX_LOCAL_RESULTS)
self.assertEqual(results['responseStatus'], googlemaps.STATUS_OK)
self.assertNotEqual(results['responseData'], None)
self.assertNotEqual(results['responseData']['cursor'], None)
results = results['responseData']['results']
self.assertEqual(len(results), GoogleMaps.MAX_LOCAL_RESULTS)
for result in results:
self.assertEqual(result['GsearchResultClass'], 'GlocalSearch')
self.assert_(result['titleNoFormatting'].lower().find('starbucks') >= 0)
self.assertEqual(result['region'], 'CA')
def FindPizza():
print "Enter in an address to find Pizza places near it"
address = raw_input()
gmaps = GoogleMaps("AIzaSyA5R4PnzAcoe2vpVRKyWWby-d6RrMmIwtQ")
lat, lng = gmaps.address_to_latlng(address)
destination = gmaps.latlng_to_address(lat, lng)
Pizza = gmaps.local_search('pizza near ' + destination)
directions = gmaps.directions(address, destination)
print "The nearest Pizza place is " + Pizza['responseData']['results'][0]['titleNoFormatting']
for step in directions['Directions']['Routes'][0]['Steps']:
print step['descriptionHtml']
def test_local_search(self):
"""Test googlemaps local_search()."""
gmaps = GoogleMaps(GMAPS_API_KEY,
referrer_url='http://www.google.com/')
local = gmaps.local_search('sushi san francisco, ca')
result = local['responseData']['results'][0]
self.assertEqual(result['titleNoFormatting'], 'Sushi Groove')
results = gmaps.local_search('Starbucks Los Angeles, CA',
numresults=GoogleMaps.MAX_LOCAL_RESULTS)
self.assertEqual(results['responseStatus'], googlemaps.STATUS_OK)
self.assertNotEqual(results['responseData'], None)
self.assertNotEqual(results['responseData']['cursor'], None)
results = results['responseData']['results']
self.assertEqual(len(results), GoogleMaps.MAX_LOCAL_RESULTS)
for result in results:
self.assertEqual(result['GsearchResultClass'], 'GlocalSearch')
self.assert_(
result['titleNoFormatting'].lower().find('starbucks') >= 0)
self.assertEqual(result['region'], 'CA')
def get_distance_from_railways(self, address, max_distance=3, retry_wait=1):
attempts = 0
results = []
while (True):
gmaps = GoogleMaps()
try:
lat, lng = gmaps.address_to_latlng(address)
local_search = gmaps.local_search('railway near ' + address)
except GoogleMapsError:
# Some sort of error occurred! Either the address is malformed,
# or the server is having some sort of issue. We'll wait a little bit
# and try again
if attempts < self.max_attempts:
attempts += 1
# Wait 1 seconds before trying again
time.sleep(retry_wait)
logger.debug("... ... ... Failed to parse the address. Trying again. Attempt #" + attempts)
continue
else:
logger.debug("... ... ... Failed all attempts. Skipping.")
return None
# Get our results
for result in local_search['responseData']['results']:
# Probably not accurate over this point... Weird things
# can get in
if int(result['accuracy']) > 5:
continue
distance = self.haversine(lng, lat,
float(result["lng"]), float(result["lat"]))
data = {
'line_name': result['titleNoFormatting'],
'distance': round(distance, 2)
}
if (distance < max_distance):
results.append(data)
return results
def get_places():
place_types = {'yoga': 'yoga', 'pole': 'pole dancing', 'coffee':'coffee shop',
'beer': 'brew pub', 'strip': 'strip club', 'bikes': 'bicycle shop', 'meditate': 'meditation',
'tattoo': 'tattoo'}
gmaps = GoogleMaps(api_key)
for place_type in place_types:
local = gmaps.local_search('%s near portland, or' % place_types[place_type],
numresults=GoogleMaps.MAX_LOCAL_RESULTS)
for result in local['responseData']['results']:
kwargs={'name': result['titleNoFormatting'].encode('utf-8'),
'address': result['streetAddress'].encode('utf-8')}
try:
p = Place.objects.get(**kwargs)
except Place.DoesNotExist:
p = Place(**dict((k,v) for (k,v) in kwargs.items() if '__' not in k))
p.static_map=result['staticMapUrl'].encode('utf-8')
p.point=Point(float(result['lng']), float(result['lat']))
p.place_type=place_type
p.save()
print "saved %s" % p.name
from googlemaps import GoogleMaps
api_key = 'AIzaSyA5nMPOn0fpv824YiL2sab5-NZejD9lXvA'
gmaps = GoogleMaps(api_key)
whitehouse = '1600 Pennsylvania Avenue, Washington, DC'
lat, lng = gmaps.address_to_latlng(whitehouse)
print lat, lng
destination = gmaps.latlng_to_address(38.897096, -77.036545)
print destination
dlat, dlng = gmaps.address_to_latlng('326 Perkins Library, Durham, NC 27708')
print dlat, dlng
duke = gmaps.latlng_to_address(dlat, dlng)
print duke
local = gmaps.local_search('restaurant near ' + duke)
print local['responseData']['results'][0]['titleNoFormatting']
directions = gmaps.directions(duke, whitehouse)
print directions['Directions']['Distance']['meters']
for step in directions['Directions']['Routes'][0]['Steps']:
print step['descriptionHtml']
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?
# what is its address?
from googlemaps import GoogleMaps
gmaps = GoogleMaps('AIzaSyCK5s0DXmGKoZ_CgwFMQ6G0dN1UcDBDv14')
f = open('escondido_list.txt', 'r')
for line in f:
#lat, lng = gmaps.
if line[:3] != '***':
local = gmaps.local_search(line + ' near 94305')
lat, lng = gmaps.address_to_latlng(local['responseData']['results'][0]['streetAddress'])
print lat
def xls_to_orm(self, columns=None):
row_excluded = []
file = self.attach
errors = []
#se seleccionan las columnas segun la decision del usuario. En caso de no elegir al menos una en particular el sistema importa la totalidad de las columnas
if columns:
columns = self.column_set.filter(pk__in=columns)
else:
columns = self.column_set.all()
self.delete_old_values()
src = self.open_source()
for column in columns:
#Para cada columna que el usuario haya seleccionado para importar, se recorren todos sus valores creando objetos del tipo ValueX donde X es el tipo del valor que se esta recorriendo
col_tp = src.col_types(column.csv_index,start_rowx=1)
for i, val in enumerate(src.col_values(column.csv_index,start_rowx=1)):
#Para cada valor asociado a la columna seleccionada (column) se crea una instancia del tipo Valor
if col_tp[i] == 1 and column.data_type=='point':
value = ValuePoint()
elif col_tp[i] == 1 and column.data_type=='area':
value = ValueArea()
elif col_tp[i] == 1 and column.data_type!='area' and column.data_type!='point':
value = ValueText()
elif col_tp[i] == 2:
value = ValueFloat()
elif col_tp[i] == 3:
value = ValueDate()
elif col_tp[i] == 4:
value = ValueBool()
value.value = val
value.data_type = col_tp[i]
value.column = column
try:
row_obj = Row.objects.filter(datasource=self,csv_index=i+1).first()
except:
#Se crea una nueva instancia de fila
row_obj = Row(datasource=self,csv_index=i+1)
row_obj.save()
value.row = row_obj
value.save()
search_term = slugify(value.value)
self.geopositionated = False
#SI LOS DATOS SON GEOPOSICIONADOS
if column.data_type == 'point':
gmaps = GoogleMaps(settings.GOOGLEMAPS_API_KEY)
self.geopositionated = True
#se debe hacer primero una consulta a la base local
results = MaapPoint.objects.filter(slug=search_term)
if len(results) >= 1:
#En este caso quiere decir que la consulta a la base local fue exitosa
for point in results:
value.point = point
value.map_url = point.static_url
value.save()
if len(results) < 1:
#Este caso quiere decir que la consulta a la base local no fue exitosa y por lo tanto se procede a buscarlo via web. Aca se debe controlar solo el caso que sea unico. Ahora esta asi porque hay muchos MaapPoint iguales
results = gmaps.local_search('%s, cordoba, argentina' %value.value )['responseData']['results']
for result in results:
latlng = [float(result.get('lng')), float(result.get('lat'))]
point = MaapPoint(
geom=Point(latlng).wkt,
name=value.value,
)
point.static_url = result.get('staticMapUrl', None)
point.save()
value.point = point
value.map_url = point.static_url
value.save()
#SI LOS DATOS SON GEOPOSICIONADOS
if column.data_type == 'area':
self.geopositionated = True
barrio = MaapArea.objects.filter(slug=search_term)
if len(barrio) == 1:
value.area = barrio[0]
value.save()
if len(errors) == 0:
self.is_dirty = False
self.save()
if self.geopositionated:
values_geo = Value.objects.filter(column__datasource=self,column__has_geodata=True)
for t in values_geo:
qs = Value.objects.filter(column__datasource=self,column__has_geodata=False,row=t.row)
for u in qs:
u.area = t.area
u.save()
print errors
return self.get_absolute_url()
api_key = "your api key from developers.google.com"
gmaps = GoogleMaps(api_key)
whitehouse = "1600 Pennsylvania Avenue, Washington, DC"
lat, lng = gmaps.address_to_latlng(whitehouse)
print lat, lng
destination = gmaps.latlng_to_address(38.897096, -77.036545)
print destination
dlat, dlng = gmaps.address_to_latlng("326 Perkins Library, Durham, NC 27708")
print dlat, dlng
duke = gmaps.latlng_to_address(dlat, dlng)
print duke
local = gmaps.local_search("restaurant near " + duke)
print local["responseData"]["results"][0]["titleNoFormatting"]
directions = gmaps.directions(duke, whitehouse)
print directions["Directions"]["Distance"]["meters"]
for step in directions["Directions"]["Routes"][0]["Steps"]:
print step["descriptionHtml"]
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?
# what is its address?
# if I wanted to hold a morning meeting there, which cafe would you suggest?
# if I wanted to hold an evening meeting there, which bar would you suggest?
print check
except:
print "Wystapil nieznany blad! Przepraszamy."
elif wybor == 2:
try:
cel1 = raw_input('Czego poszukujesz?: ')
address3 = raw_input('W jakiej okolicy?: ')
if address3 == "" or cel1 == "":
print ""
print "Prosze podac poprawne nazwy miejscowosci i punkty docelowe."
else:
lat3, lng3 = gmaps.address_to_latlng(cel1 + ' ' + address3)
lat6, lng6 = gmaps.address_to_latlng(address3)
miejsce = gmaps.latlng_to_address(lat6, lng6)
destination3 = gmaps.latlng_to_address(lat3, lng3)
local = gmaps.local_search(cel1 + ' ' + address3)
print local['responseData']['results'][0]['titleNoFormatting']
if miejsce != destination3:
print destination3
else:
pass
except:
print "Wystapil nieznany blad! Przepraszamy."
elif wybor == 3:
try:
address4 = raw_input('Podaj nazwe miejscowosci startowej: ')
cel2 = raw_input('Czego poszukujesz?: ')
address5 = raw_input('Podaj miejscowosc, w ktorej szukac: ')
if address4 == "" or address5 == "" or cel2 == "":
print ""
print "Prosze podac poprawne nazwy miejscowosci i punkty docelowe."
def xls_to_orm(self, columns=None):
row_excluded = []
file = self.attach
errors = []
#se seleccionan las columnas segun la decision del usuario. En caso de no elegir al menos una en particular el sistema importa la totalidad de las columnas
if columns:
columns = self.column_set.filter(pk__in=columns)
else:
columns = self.column_set.all()
self.delete_old_values()
src = self.open_source()
for column in columns:
#Para cada columna que el usuario haya seleccionado para importar, se recorren todos sus valores creando objetos del tipo ValueX donde X es el tipo del valor que se esta recorriendo
col_tp = src.col_types(column.csv_index, start_rowx=1)
for i, val in enumerate(
src.col_values(column.csv_index, start_rowx=1)):
#Para cada valor asociado a la columna seleccionada (column) se crea una instancia del tipo Valor
if col_tp[i] == 1 and column.data_type == 'point':
value = ValuePoint()
elif col_tp[i] == 1 and column.data_type == 'area':
value = ValueArea()
elif col_tp[
i] == 1 and column.data_type != 'area' and column.data_type != 'point':
value = ValueText()
elif col_tp[i] == 2:
value = ValueFloat()
elif col_tp[i] == 3:
value = ValueDate()
elif col_tp[i] == 4:
value = ValueBool()
value.value = val
value.data_type = col_tp[i]
value.column = column
try:
row_obj = Row.objects.filter(datasource=self,
csv_index=i + 1).first()
except:
#Se crea una nueva instancia de fila
row_obj = Row(datasource=self, csv_index=i + 1)
row_obj.save()
value.row = row_obj
value.save()
search_term = slugify(value.value)
self.geopositionated = False
#SI LOS DATOS SON GEOPOSICIONADOS
if column.data_type == 'point':
gmaps = GoogleMaps(settings.GOOGLEMAPS_API_KEY)
self.geopositionated = True
#se debe hacer primero una consulta a la base local
results = MaapPoint.objects.filter(slug=search_term)
if len(results) >= 1:
#En este caso quiere decir que la consulta a la base local fue exitosa
for point in results:
value.point = point
value.map_url = point.static_url
value.save()
if len(results) < 1:
#Este caso quiere decir que la consulta a la base local no fue exitosa y por lo tanto se procede a buscarlo via web. Aca se debe controlar solo el caso que sea unico. Ahora esta asi porque hay muchos MaapPoint iguales
results = gmaps.local_search(
'%s, cordoba, argentina' %
value.value)['responseData']['results']
for result in results:
latlng = [
float(result.get('lng')),
float(result.get('lat'))
]
point = MaapPoint(
geom=Point(latlng).wkt,
name=value.value,
)
point.static_url = result.get('staticMapUrl', None)
point.save()
value.point = point
value.map_url = point.static_url
value.save()
#SI LOS DATOS SON GEOPOSICIONADOS
if column.data_type == 'area':
self.geopositionated = True
barrio = MaapArea.objects.filter(slug=search_term)
if len(barrio) == 1:
value.area = barrio[0]
value.save()
if len(errors) == 0:
self.is_dirty = False
self.save()
if self.geopositionated:
values_geo = Value.objects.filter(column__datasource=self,
column__has_geodata=True)
for t in values_geo:
qs = Value.objects.filter(column__datasource=self,
column__has_geodata=False,
row=t.row)
for u in qs:
u.area = t.area
u.save()
print errors
return self.get_absolute_url()
