def main():
home = generate_datum()
data = []
for i in range(0, 10000):
data.append(generate_datum())
n = 10
similarList = find_similar(home, data, n)
print similarList
def main(): home = generate_datum() data = [] for i in range (0,10000): data.append(generate_datum()) n = 10 similarList = find_similar(home,data,n) print similarList
def load_listings():
"""
gets random listings and inserts into database
"""
for i in range (0, DATA_SAMPLE_SIZE):
l = generate_datum()
listing = l._asdict()
cur = get_mysql_connection().cursor()
listing['zip'] = get_nearest_zips_for_lat_lon(listing.get('lat'), listing.get('lon'))[0].get('postalCode')
cur.execute("""insert into listing (num_bedrooms, num_bathrooms, living_area, lat, lon,
exterior_stories, pool, dwelling_type, list_date, list_price, close_date, close_price, zip)
values (%(num_bedrooms)s, %(num_bathrooms)s, %(living_area)s, %(lat)s, %(lon)s, %(exterior_stories)s,
'%(pool)s', '%(dwelling_type)s', '%(list_date)s', %(list_price)s, '%(close_date)s', %(close_price)s, '%(zip)s' )""" % listing)
def main():
ps = ProximitySearch()
home = generate_datum()
n = 10
print 'Input:\n'
print home, '\n'
result = ps.n_most_similar_homes(home, n)
print 'The ' + str(n) + ' most similar homes:\n'
for h in result:
print h
save_csv(home, result)
def generate_homes(self):
return [generate_datum() for x in xrange(self.data_size)]
