Update app.py

app.py

@@ -1,76 +1,90 @@
 import gradio as gr
 import folium
 from folium import plugins
-import requests
 import pandas as pd
 from datetime import datetime
 import time
 import numpy as np
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
+from opensky_api import OpenSkyApi  # OpenSky API 클래스 import
 
-# OpenSky API URL
-BASE_URL = "https://opensky-network.org/api"
+# OpenSky API 인증 정보
+USERNAME = "seawolf2357"
+PASSWORD = "Time2175!@"
+api = OpenSkyApi(USERNAME, PASSWORD)
 
-def get_states(bounds=None):
-    """Get current aircraft states from OpenSky Network"""
-    try:
-        response = requests.get(f"{BASE_URL}/states/all", 
-                              params=bounds if bounds else {},
-                              timeout=10)  # 타임아웃 추가
-        if response.status_code == 200:
-            return response.json()
-        else:
-            print(f"API Error: {response.status_code}")
+def get_states(bounds=None, max_retries=3):
+    """Get current aircraft states from OpenSky Network with retry logic"""
+    for attempt in range(max_retries):
+        try:
+            if bounds:
+                # bbox = (min latitude, max latitude, min longitude, max longitude)
+                states = api.get_states(bbox=(
+                    bounds.get('lamin', None),
+                    bounds.get('lamax', None),
+                    bounds.get('lomin', None),
+                    bounds.get('lomax', None)
+                ))
+            else:
+                states = api.get_states()
+            
+            if states:
+                return {'states': states.states}
+            else:
+                if attempt < max_retries - 1:
+                    wait_time = min(2 ** attempt, 60)
+                    print(f"Retrying in {wait_time} seconds...")
+                    time.sleep(wait_time)
+                    continue
+                return None
+                
+        except Exception as e:
+            print(f"Error fetching data: {e}")
+            if attempt < max_retries - 1:
+                time.sleep(5)
+                continue
             return None
-    except Exception as e:
-        print(f"Error fetching data: {e}")
-        return None
+    return None
 
 def create_monitoring_dashboard(states):
     """Create monitoring dashboard using Plotly"""
     if not states:
         return go.Figure()
 
-    # Create subplots with specific types
+    # StateVector 객체에서 데이터 추출
+    altitudes = [s.geo_altitude for s in states if s.geo_altitude is not None]
+    speeds = [s.velocity for s in states if s.velocity is not None]
+    countries = pd.Series([s.origin_country for s in states if s.origin_country])
+    
+    # Create subplots
     fig = make_subplots(
         rows=2, cols=2,
         subplot_titles=('Altitude Distribution', 'Speed Distribution', 
                        'Aircraft by Country', 'Aircraft Categories'),
         specs=[
             [{"type": "xy"}, {"type": "xy"}],
-            [{"type": "xy"}, {"type": "domain"}]  # pie chart를 위한 domain type
+            [{"type": "xy"}, {"type": "domain"}]
         ]
     )
 
-    # Altitude distribution
-    altitudes = [state[7] for state in states if state[7]]
+    # Add traces
     fig.add_trace(
-        go.Histogram(
-            x=altitudes, 
-            name="Altitude",
-            marker_color='#4a90e2'
-        ),
+        go.Histogram(x=altitudes, name="Altitude", marker_color='#4a90e2'),
         row=1, col=1
     )
-
-    # Speed distribution
-    speeds = [state[9] for state in states if state[9]]
+    
     fig.add_trace(
-        go.Histogram(
-            x=speeds, 
-            name="Speed",
-            marker_color='#50C878'
-        ),
+        go.Histogram(x=speeds, name="Speed", marker_color='#50C878'),
         row=1, col=2
     )
-
-    # Aircraft by country
-    countries = pd.Series([state[2] for state in states if state[2]]).value_counts()
+    
+    # Top 10 countries
+    top_countries = countries.value_counts().head(10)
     fig.add_trace(
         go.Bar(
-            x=countries.index[:10], 
-            y=countries.values[:10], 
+            x=top_countries.index,
+            y=top_countries.values,
             name="Countries",
             marker_color='#FF6B6B'
         ),
@@ -82,7 +96,7 @@ def create_monitoring_dashboard(states):
     values = [40, 30, 20, 10]  # Example distribution
     fig.add_trace(
         go.Pie(
-            labels=categories, 
+            labels=categories,
             values=values,
             name="Categories",
             marker=dict(colors=['#4a90e2', '#50C878', '#FF6B6B', '#FFD700'])
@@ -106,11 +120,9 @@ def create_monitoring_dashboard(states):
         )
     )
 
-    # Update axes
     fig.update_xaxes(gridcolor='rgba(255,255,255,0.1)', zeroline=False)
     fig.update_yaxes(gridcolor='rgba(255,255,255,0.1)', zeroline=False)
 
-    # Update subplot titles
     for i in fig['layout']['annotations']:
         i['font'] = dict(size=12, color='white')
 
@@ -118,14 +130,12 @@ def create_monitoring_dashboard(states):
 
 def create_map(region="world"):
     """Create aircraft tracking map"""
-    # 기본 맵 생성
     m = folium.Map(
         location=[30, 0],
         zoom_start=3,
         tiles='CartoDB dark_matter'
     )
 
-    # 데이터 가져오기
     bounds = {
         "world": None,
         "europe": {"lamin": 35.0, "lomin": -15.0, "lamax": 60.0, "lomax": 40.0},
@@ -135,7 +145,7 @@ def create_map(region="world"):
 
     data = get_states(bounds.get(region))
     
-    if not data or 'states' not in data or not data['states']:
+    if not data or not data['states']:
         return (
             m._repr_html_(), 
             create_monitoring_dashboard([]),
@@ -145,13 +155,12 @@ def create_map(region="world"):
     states = data['states']
     heat_data = []
 
-    # Add aircraft markers
     for state in states:
-        if state[6] and state[5]:  # latitude and longitude check
-            lat, lon = state[6], state[5]
-            callsign = state[1] if state[1] else 'N/A'
-            altitude = state[7] if state[7] else 'N/A'
-            velocity = state[9] if state[9] else 'N/A'
+        if state.latitude and state.longitude:
+            lat, lon = state.latitude, state.longitude
+            callsign = state.callsign if state.callsign else 'N/A'
+            altitude = state.geo_altitude if state.geo_altitude else 'N/A'
+            velocity = state.velocity if state.velocity else 'N/A'
             
             heat_data.append([lat, lon, 1])
             
@@ -161,7 +170,7 @@ def create_map(region="world"):
                 <p><b>Callsign:</b> {callsign}</p>
                 <p><b>Altitude:</b> {altitude}m</p>
                 <p><b>Velocity:</b> {velocity}m/s</p>
-                <p><b>Origin:</b> {state[2]}</p>
+                <p><b>Origin:</b> {state.origin_country}</p>
             </div>
             """
             
@@ -170,19 +179,17 @@ def create_map(region="world"):
                 popup=folium.Popup(popup_content, max_width=300),
                 icon=folium.DivIcon(
                     html=f'''
-                        <div style="transform: rotate({state[10] if state[10] else 0}deg)">✈️</div>
+                        <div style="transform: rotate({state.true_track if state.true_track else 0}deg)">✈️</div>
                     ''',
                     icon_size=(20, 20)
                 )
             ).add_to(m)
 
-    # Add heatmap
     plugins.HeatMap(heat_data, radius=15).add_to(m)
     
-    # Statistics
     total_aircraft = len(states)
-    countries = len(set(state[2] for state in states if state[2]))
-    avg_altitude = np.mean([state[7] for state in states if state[7]]) if states else 0
+    countries = len(set(s.origin_country for s in states if s.origin_country))
+    avg_altitude = np.mean([s.geo_altitude for s in states if s.geo_altitude is not None]) if states else 0
     
     stats = f"""
     📊 Real-time Statistics:
@@ -195,6 +202,8 @@ def create_map(region="world"):
 
     return m._repr_html_(), create_monitoring_dashboard(states), stats
 
+
+
 # Custom CSS
 custom_css = """
 .gradio-container {