def makeListener(ip, connected, client):
conn = int(connected.strip())
now = datetime.datetime.now()
start = now - datetime.timedelta(seconds=conn)
since = start.strftime('%H:%M:%S' if start.day is now.day else '%A, %H:%M')
time = int((start - EPOCH).total_seconds())
geocode = Geocode.geocode(ip)
return dict(ip=ip, geocode=geocode or '', time=time, client=client, since=since)
def locations(request):
regions, table = viewLists.listTableMoreInputs()
if request.method == 'POST':
# center's maps
num_clusters = int(request.POST.get('num_clusters'))
colors = ColorsRandom.generate_colors(num_clusters)
country = request.POST.get('country')
state = request.POST.get('state')
city = request.POST.get('city')
center = Geocode.geocode([country + ' ' + state + ' ' + city, city], isCenter=True)
center = str(center['lat']) + "," + str(center['lng'])
# ceps's locations
ceps_list = [
[country + ' ' +
state + ' ' +
city + ' ' +
i, i] for i in request.POST.get('ceps').split(';')]
# items = Geocode.parallelGeocode(ceps_list)
items = []
for i in ceps_list:
items.append(Geocode.geocode(i))
points, centroids = k_means.k_means_lists(num_clusters, 20, items)
dic = k_means.sse(points, centroids)
t = get_template('maps.html')
html = t.render(
Context(
{
'regions' : regions,
'table': table,
'center' : center ,
'localizations' : points,
'colors' : colors,
'centroids' : centroids,
'sse' : dic,
'hospitals' : MongoDB.list_all_healths(),
'csrf_token' : csrf(request)['csrf_token']
}
)
)
html = html.replace("'", "'")
return HttpResponse(html)
# return render_to_response(
# 'index.html',
# context_instance=RequestContext(request))
t = get_template('index.html')
html = t.render(
Context(
{
'regions' : regions,
'table': table,
'csrf_token' : csrf(request)['csrf_token']
}
)
)
html = html.replace("'", "'")
return HttpResponse(html)
def run_component():
sys.setrecursionlimit(50000)
api_key = "AIzaSyCXXvQOEt31dz8Nw070bye9pwEDBEl0g1o"
#received 2018/01/24/15:52 [email protected], 1st "BC Doctors1"
file_list = [
f for f in os.listdir('data_subsets') if not f.startswith('.')
]
#to capture how many requests were made with the given api_key
search_counter = 0
for file in file_list:
pickle_file = "data_subsets/" + file
data = pickle.load(open(pickle_file, 'rb'))
num_docs = len(data)
update_freq = 75
upload_freq = 50
counter = 0
#for each doctor
for doc_key in data:
counter += 1
doctor = data[doc_key]
#check if it has been googled already
if 'googled' in doctor['GOOGLE']:
if doctor['GOOGLE']['googled']:
continue
#set up dictionary
doctor['GOOGLE'].update({'googled': False})
doctor['GOOGLE'].update({'geo_data': {}})
#for each search result for a given doctor
for result_number in doctor['HTML_PARSING']['parsed_infos']:
address = doctor['HTML_PARSING']['parsed_infos'][
result_number]['address']
#don't want to waste a request on empty address
if (address != "" and not address.isspace()):
geocode = G.Geocode(api_key, address)
geocode.search()
search_counter += 1
doctor['GOOGLE']['geo_data'].update(
{result_number: geocode._dict})
#update boolean
doctor['GOOGLE'].update({'googled': True})
if (counter % update_freq == 0):
print("percentage completed to google for %s is: %s" %
(file, counter * 100 / num_docs))
print('number of geocode queries made is: %s' %
(search_counter))
print("==")
if (counter % upload_freq == 0):
pickle.dump(data, open(pickle_file, 'wb'))
print('..saved..')
pickle.dump(data, open(pickle_file, 'wb'))
