Update app.py

app.py

@@ -59,37 +59,6 @@ def get_location(lat, lon):
     location = geolocator.reverse(f"{lat},{lon}")
     return location.address
 
-def check(weather_data, lat, lon):
-    # Get current local Time
-    timezone = tf.timezone_at(lng=lon, lat=lat)
-    current_time = datetime.now(pytz.timezone(timezone))
-
-    def convert_to_local_time(utc_time):
-        dt = datetime.strptime(utc_time, "%Y-%m-%dT%H:%M:%SZ")
-        local_time = dt.astimezone(pytz.timezone(timezone))
-        return local_time.strftime("%Y-%m-%d %H")
-
-    # # Check if it's on time locally
-    # if(weather_data == None or (current_time.minute == 0 and current_time.second == 0)):
-    weather_url = f"https://api.tomorrow.io/v4/weather/forecast?location={lat},{lon}&apikey=Purg6j6hjn9LdzMVwRvToPbJVhnlSjAP"
-    response = requests.get(weather_url)
-    if response.status_code != 200:
-        raise Exception(f"Error fetching {weather_url}: {response.status_code}")
-    api_data = response.json()
-    hourly_data = api_data['timelines']['hourly']
-    weather_data = pd.DataFrame([{**{'time': item['time']}, **item['values']} for item in hourly_data])
-    weather_data.fillna(0, inplace=True)
-
-    # Using convert_to_local_time to process the column 'time' data into local datetime string
-    weather_data['time'] = weather_data['time'].apply(convert_to_local_time)
-    weather_data['datetime'] = weather_data['time'].copy()
-    weather_data.set_index('datetime', inplace=True)
-
-    print_with_line_number("Weather dataframe:")
-    # print(weather_data.shape)
-    # print(weather_data.head(5))
-
-    return weather_data
 
 def nav_controls(prefix: str) -> List[NavSetArg]:
     return [
@@ -183,10 +152,45 @@ app_ui = ui.page_fluid(
 
 # re-run when a user using the application
 def server(input, output, session):
-    global weather_data, remap_flag, address_line, weather_fig, m, unisession
+    global weather_data, remap_flag, address_line, weather_fig, m
     weather_data = None
     remap_flag = False
     address_line = None
+    weatherframe = reactive.Value(pd.DataFrame())
+
+    def check(weather_data, lat, lon):
+        # Get current local Time
+        timezone = tf.timezone_at(lng=lon, lat=lat)
+        current_time = datetime.now(pytz.timezone(timezone))
+
+        def convert_to_local_time(utc_time):
+            dt = datetime.strptime(utc_time, "%Y-%m-%dT%H:%M:%SZ")
+            local_time = dt.astimezone(pytz.timezone(timezone))
+            return local_time.strftime("%Y-%m-%d %H")
+
+        # # Check if it's on time locally
+        # if(weather_data == None or (current_time.minute == 0 and current_time.second == 0)):
+        weather_url = f"https://api.tomorrow.io/v4/weather/forecast?location={lat},{lon}&apikey=Purg6j6hjn9LdzMVwRvToPbJVhnlSjAP"
+        response = requests.get(weather_url)
+        if response.status_code != 200:
+            raise Exception(f"Error fetching {weather_url}: {response.status_code}")
+        api_data = response.json()
+        hourly_data = api_data['timelines']['hourly']
+        weather_data = pd.DataFrame([{**{'time': item['time']}, **item['values']} for item in hourly_data])
+        weather_data.fillna(0, inplace=True)
+
+        # Using convert_to_local_time to process the column 'time' data into local datetime string
+        weather_data['time'] = weather_data['time'].apply(convert_to_local_time)
+        weather_data['datetime'] = weather_data['time'].copy()
+        weather_data.set_index('datetime', inplace=True)
+
+        print_with_line_number("Weather dataframe:")
+        # print(weather_data.shape)
+        # print(weather_data.head(5))
+        weatherframe.set(weather_data)
+        
+        return weather_data
+
 
     m = ui.modal(
             "Please wait for progress...",
@@ -446,6 +450,11 @@ def server(input, output, session):
             update_plot()
         remap_flag = True
 
+        new_location = get_location(center[0],  center[1])
+        ui.update_text(id="address",
+                       label="Data for",
+                       value=new_location)
+
         # return ui.p(f"Latitude: {lat}", ui.br(), f"Longitude: {lon}")
     
     def update_plot():
@@ -478,7 +487,7 @@ def server(input, output, session):
     @output
     @render.data_frame
     async def weather_frame():
-        return weather_data
+        return weatherframe.get()
     
     @session.download(
         filename=lambda: f"data-{date.today().isoformat()}-{np.random.randint(100,999)}.csv"