Update app.py

app.py

@@ -9,7 +9,9 @@ from datetime import date
 from bs4 import BeautifulSoup as bs
 from shapely.geometry import Point
 from google.oauth2.service_account import Credentials
+from streamlit_folium import folium_static
 import pickle
+import os
 #API='80ccf867-5353-4474-a01c-d1299496eca7'
 API='deb65d93-a965-4d1f-a09e-5a047ea959d7'
 
@@ -38,6 +40,11 @@ def GET_COORDS_YANDEX(adress):
 
 
 
+def first_try(data):
+    old_data=[data[0]]
+    len_old_data=1
+    return old_data, len_old_data
+
 
 
 def import_data():
@@ -55,30 +62,36 @@ def import_data():
     spr = gc.open_by_url("https://docs.google.com/spreadsheets/d/1Ol9039HJ99Q8xVVp1Wwz5iBdURxEKHLIcEvyqUc2pZM/edit#gid=642560994")
     wks=spr.worksheet('Консолидированный список')
     new_data=wks.get_all_values()
-    try:
-        with open('old_data.pickle', 'rb') as f:
+    new_data[0].pop(-1)
+    new_data[0].pop(-1)
+    with open('old_data.pickle', 'rb') as f:
+        if os.stat("file").st_size == 0:
+            old_data, len_old_data=first_try(new_data)
+        else:
             old_data=pickle.load(f)
             len_old_data=len(old_data)
-    except:
-        old_data=[]
-        len_old_data=1
+        
+            
     list_to_geocode=new_data[len_old_data::]
     for lead in list_to_geocode:
-        lead.append(GET_COORDS_YANDEX(lead[8]))
+        #lead.append(GET_COORDS_YANDEX(lead[8]))
+        lead.pop(-1)
+        lead.pop(-1)
+        lead.append('thee must be coords')
         lead.append(make_date(lead[3]))
     for lead in list_to_geocode:
         old_data.append(lead)
     if len(old_data[0])!=len(old_data[1]):
-        old_data[0].append('coords')
-        old_data[0].append('date')
+        old_data[0].append('coords1')
+        old_data[0].append('date1')
     with open('old_data.pickle', 'wb') as f:
-        pickle.dump(old_data, f, pickle.HIGHEST_PROTOCOL)
+        pickle.dump(old_data, f)
     DD=pd.DataFrame(old_data[1::], columns=old_data[0])
+    st.write(DD.head(3))
     return DD
     
         
 OBJECTS=import_data()
-st.write(OBJECTS.head(3))
 #OBJECTS=pd.DataFrame(
 #    {
 #        'комнатность':OBJECTS['Кол-во комнат'].values,
@@ -105,7 +118,7 @@ with st.sidebar:
 #Data_to_plot=GEO_OBJECTS.loc[(GEO_OBJECTS['Дата оценки']>min_date)&(GEO_OBJECTS['Дата оценки']<min_date)&(GEO_OBJECTS['комнатность'] in rooms)&(GEO_OBJECTS['площадь']>areamin)&(GEO_OBJECTS['площадь']<areamax)]
 
 
-#st.subheader('Карта оценок')
+st.subheader('Карта оценок')
 m = folium.Map(location=[55.87890, 37.71943], zoom_start=10, tiles='CartoDB positron')
 
 #for A in Data_to_plot.values:
@@ -117,9 +130,9 @@ m = folium.Map(location=[55.87890, 37.71943], zoom_start=10, tiles='CartoDB posi
     #if len(tag)>40:
     #    tag=tag[5:]
     #tag=f'хуувая квартира №{i}'
- #   tag+=str(A[-1])
- #   folium.Marker(location=[lat, log],         
- #   popup = tag).add_to(m)
-
-folium_static(m)
+#    tag+=str(A[-1])
+#    folium.Marker(location=[lat, log],         
+#    popup = tag).add_to(m)
 
+#folium_static(m)
+m