Update app.py

app.py

@@ -14,14 +14,14 @@ from glob import glob
 import wget
 
 ##
-def timer(start_time=None):
+def timer(start_time=None, message):
     if not start_time:
         start_time = datetime.now()
         return start_time
     elif start_time:
         thour, temp_sec = divmod((datetime.now() - start_time).total_seconds(), 3600)
         tmin, tsec = divmod(temp_sec, 60)
-        print('\n Time taken: %i hours %i minutes and %s seconds.' % (thour, tmin, round(tsec, 2)))
+        print('\n'+message+' Time taken: %i hours %i minutes and %s seconds.' % (thour, tmin, round(tsec, 2)))
 
 ##
 def predict(lat, lon):
@@ -45,24 +45,25 @@ def predict(lat, lon):
         return "Choose an area of ivory coast","","","",""
     
     else:
-        start_time = timer(None)
+        start_time_research = timer(None,'research tile')
         df = pd.read_csv("data/frame.csv")
         name = find_good_tile(df,point2)
-        timer(start_time)
+        timer(start_time_research,'research tile')
         if name ==404:
             reponse = "Sentinel-2 does not have data on this location to date"
             return reponse,"","","",""
         else:
-            start_time = timer(None)
+            start_time_download = timer(None,'download tile')
             path = "https://data354-public-assets.s3.eu-west-3.amazonaws.com/cisentineldata/"
             url = path+name
             wget.download(url)
-            timer(start_time)
+            timer(start_time_download,'download tile')
             
-            start_time = timer(None)
+            start_time_unzip = timer(None,'unzip data')
             unzip()
-            timer(start_time)
+            timer(start_time_unzip,'unzip data')
             
+            start_time_processing = timer(None,'processing data')
             name,cld_prob,days_ago = select_best_cloud_coverage_tile()
             bandes_path_10,bandes_path_20,bandes_path_60,tile_path,path_cld_20,path_cld_60 =paths(name)
             # create image dataset
@@ -90,6 +91,7 @@ def predict(lat, lon):
 
             # NDVI
             ndvi_index = ndvi(cord,name)
+            timer(start_time_processing,'processing data')
 
             # deleted download files
             delete_tiles()