Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,4 +1,4 @@
-# Fichier: app.py
+# Fichier: src/app.py
 
 # ===================================================================================
 # WAHIS SCRAPER - VERSION TABLEAU DE BORD STREAMLIT (APPROCHE FINALE ET ROBUSTE)
@@ -11,17 +11,16 @@ from datetime import datetime
 from pathlib import Path
 import warnings
 import asyncio
-import subprocess
 from playwright.async_api import async_playwright
 from playwright_stealth import stealth_async
 from streamlit_folium import st_folium
 import folium
+import traceback
 
 # --- Configuration de la Page Streamlit ---
 st.set_page_config(layout="wide", page_title="WAHIS Animal Disease Dashboard")
 
 # --- Classes et Fonctions de Scraping (inchangées) ---
-# ... (la logique de scraping est parfaite, on la garde telle quelle)
 class WAHISScraper:
     def __init__(self): self.logs = []
     def log(self, message):
@@ -34,6 +33,7 @@ class WAHISScraper:
             browser = None
             try:
                 self.log("🔧 Lancement d'un navigateur Chromium...")
+                # L'argument --no-sandbox est crucial dans les environnements conteneurisés
                 browser = await p.chromium.launch(headless=True, args=["--no-sandbox"])
                 page = await browser.new_page()
                 self.log("🕵️ Application du camouflage 'stealth'...")
@@ -65,28 +65,22 @@ class WAHISScraper:
             finally:
                 if browser and browser.is_connected(): await browser.close()
                 
-# --- Fonctions de Traitement des Données ---
 def process_data(reports, outbreaks, additional_infos):
     valid_additional_infos = [info for info in additional_infos if isinstance(info, dict)]
     additional_info_map = {info.get('outbreakId'): info for info in valid_additional_infos}
-    
     report_map = {report['eventId']: {'disease': report['disease']} for report in reports}
-
     for outbreak in outbreaks:
         event_info = report_map.get(outbreak.get('eventId'), {})
         outbreak['diseaseName'] = event_info.get('disease')
         outbreak_id = outbreak.get('outbreakId')
-        if outbreak_id in additional_info_map:
-            outbreak.update(additional_info_map[outbreak_id])
-    
+        if outbreak_id in additional_info_map: outbreak.update(additional_info_map[outbreak_id])
     return pd.DataFrame(outbreaks)
 
 # --- Construction de l'Interface Streamlit ---
 
+st.set_page_config(layout="wide", page_title="WAHIS Animal Disease Dashboard")
 st.title("🤖 Tableau de Bord WAHIS")
-st.info("Ce tableau de bord extrait et affiche les derniers foyers de maladies animales signalés à l'Organisation Mondiale de la Santé Animale (WOAH).")
 
-# Utilisation du "session_state" pour stocker les données après le premier chargement
 if 'df_outbreaks' not in st.session_state:
     st.session_state.df_outbreaks = pd.DataFrame()
     st.session_state.logs = ""
@@ -95,71 +89,44 @@ if 'df_outbreaks' not in st.session_state:
 if st.button("🚀 Lancer l'extraction des données"):
     with st.spinner("Extraction en cours... (cela peut prendre 2-3 minutes)"):
         scraper = WAHISScraper()
-        reports, outbreaks, additional, logs = asyncio.run(scraper.run_extraction_async())
-        if reports:
-            st.session_state.df_outbreaks = process_data(reports, outbreaks, additional)
-            st.session_state.logs = logs
-            st.success("Extraction terminée avec succès !")
-        else:
-            st.error("L'extraction a échoué. Veuillez consulter les logs.")
-            st.session_state.logs = logs
+        try:
+            reports, outbreaks, additional, logs = asyncio.run(scraper.run_extraction_async())
+            if reports:
+                st.session_state.df_outbreaks = process_data(reports, outbreaks, additional)
+                st.session_state.logs = logs
+                st.success("Extraction terminée avec succès !")
+                st.experimental_rerun() # Rafraîchir l'interface pour afficher les résultats
+            else:
+                st.error("L'extraction a échoué. Veuillez consulter les logs.")
+                st.session_state.logs = logs
+        except Exception as e:
+            st.error("Une erreur critique est survenue pendant l'exécution.")
+            st.text(traceback.format_exc())
 
 if not st.session_state.df_outbreaks.empty:
     df = st.session_state.df_outbreaks
-
-    # --- Barre Latérale avec les Filtres ---
     st.sidebar.header("🔍 Filtres")
     all_diseases = ["Toutes"] + sorted(df['diseaseName'].dropna().unique())
     all_species = ["Toutes"] + sorted(df['species'].dropna().unique())
-    
     selected_disease = st.sidebar.selectbox("Filtrer par Maladie", all_diseases)
     selected_species = st.sidebar.selectbox("Filtrer par Espèce", all_species)
     
-    # Filtrage du DataFrame
     filtered_df = df.copy()
-    if selected_disease != "Toutes":
-        filtered_df = filtered_df[filtered_df['diseaseName'] == selected_disease]
-    if selected_species != "Toutes":
-        filtered_df = filtered_df[filtered_df['species'] == selected_species]
+    if selected_disease != "Toutes": filtered_df = filtered_df[filtered_df['diseaseName'] == selected_disease]
+    if selected_species != "Toutes": filtered_df = filtered_df[filtered_df['species'] == selected_species]
 
-    # --- Affichage Principal : Carte et Détails ---
     st.header(f"🗺️ Carte de {len(filtered_df)} Foyers")
-    
     if filtered_df.empty or not all(k in filtered_df for k in ['latitude', 'longitude']):
-        st.warning("Aucun foyer ne correspond à vos filtres, ou les données GPS sont manquantes.")
+        st.warning("Aucun foyer ne correspond à vos filtres.")
     else:
-        # Création de la carte avec Folium
         m = folium.Map(location=[filtered_df['latitude'].mean(), filtered_df['longitude'].mean()], zoom_start=2)
-        
         for _, row in filtered_df.iterrows():
-            popup_html = f"""
-            <b>Lieu:</b> {row.get('locationName', 'N/A')}<br>
-            <b>Maladie:</b> {row.get('diseaseName', 'N/A')}<br>
-            <b>Espèce:</b> {row.get('species', 'N/A')}<br>
-            <b>Cas:</b> {row.get('cases', 0)} | <b>Morts:</b> {row.get('deaths', 0)}
-            """
-            iframe = folium.IFrame(popup_html, width=250, height=100)
-            popup = folium.Popup(iframe, max_width=250)
-            folium.Marker(
-                location=[row['latitude'], row['longitude']],
-                popup=popup,
-                tooltip=row.get('diseaseName', 'N/A')
-            ).add_to(m)
-
-        # Affichage de la carte et récupération du dernier point cliqué
-        map_data = st_folium(m, width='100%')
-        if map_data and map_data['last_object_clicked_popup']:
-            st.session_state.last_click = map_data['last_object_clicked_popup']['html']
+            popup_html = f"<b>Lieu:</b> {row.get('locationName', 'N/A')}<br><b>Maladie:</b> {row.get('diseaseName', 'N/A')}<br><b>Espèce:</b> {row.get('species', 'N/A')}"
+            folium.Marker(location=[row['latitude'], row['longitude']], popup=popup_html, tooltip=row.get('diseaseName', 'N/A')).add_to(m)
+        st_folium(m, width='100%')
 
-    # Affichage des détails du dernier point cliqué
-    if st.session_state.last_click:
-        st.header("📋 Détails du Foyer Sélectionné")
-        st.markdown(st.session_state.last_click, unsafe_allow_html=True)
-        
-    # --- Affichage du tableau de données ---
     with st.expander("Voir le tableau de données des foyers filtrés"):
         st.dataframe(filtered_df)
 
-# --- Affichage des logs ---
 with st.expander("Voir le journal d'exécution"):
     st.text_area("Logs", st.session_state.logs, height=300)