Create app.py

app.py

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+import os
+import re
+import time
+import requests
+import numpy as np
+import pandas as pd
+from bs4 import BeautifulSoup
+from playwright.sync_api import sync_playwright
+import gradio as gr
+import folium
+from folium.plugins import FloatImage
+
+# Configuration
+file_name = 'bathing_sites.csv'
+url = 'https://eau.gouvernement.lu/fr/domaines-activite/eauxbaignade/sites-de-baignade.html'
+
+# Data processing functions
+def get_final_url(url):
+    with sync_playwright() as p:
+        browser = p.chromium.launch(headless=True)
+        page = browser.new_page()
+        page.set_extra_http_headers({"max-redirects": "9"})
+        if (('&X=' not in url) or ('&X=' not in url)):
+            page.goto(url, timeout=5000)
+            page.wait_for_timeout(2000)
+            url = page.url
+            browser.close()
+    return url
+
+def extract_coordinates(url):
+    x_match = re.search(r'X=(\d+)', url)
+    y_match = re.search(r'Y=(\d+)', url)
+    
+    x = x_match.group(1) if x_match else None
+    y = y_match.group(1) if y_match else None
+
+    return pd.Series([x, y])
+
+def web_mercator_to_wgs84(x, y):
+    R = 6378137  # Earth's radius in meters
+    lon = (x / R) * (180 / np.pi)
+    lat = (180 / np.pi) * (2 * np.arctan(np.exp(y / R)) - np.pi / 2)
+    return lat, lon
+    
+def file_download():
+    df = pd.read_html(url)[0]
+
+    response = requests.get(url)
+    soup = BeautifulSoup(response.text, 'html.parser')
+
+    df['images'] = [tag.find("img")["src"] for tag in soup.select("td:has(img)")]
+    df['geoport'] = [tag.find("a")["href"] for tag in soup.select("td:has(a)") if 'geoportail' in tag.find("a")["href"]]
+
+    df['geoport'] = df['geoport'].apply(get_final_url)
+    
+    df.columns = ['Lake', 'Sector', 'Water Quality', 'Swimming allowed', 'Reason for ban', 'Traffic lights', 'URL coordinates']
+
+    name_trim = ['Lac de la ', 'Lac de ', 'Etangs de ', 'Lac d\'']
+    quality_dict = {'Excellente': 'Excellent', 'Bonne': 'Good', 'Suffisante': 'Adequate', 'Insuffisante': 'Inadequate'}
+    df['Water Quality'] = df['Water Quality'].map(quality_dict).fillna(df['Water Quality'])
+    df['Lake'] = df['Lake'].str.replace('|'.join(name_trim), '', regex=True)
+    df['Lake'] = df['Lake'].str.split('(').str[0].str.strip()
+    df['Sector'] = df['Sector'].astype(str).apply(lambda x: 'Designated Zone' if 'baignade' in x else x)
+    df['Reason for ban'] = df['Reason for ban'].astype(str).apply(lambda x: 'nan' if '* Les informations ' in x else x)
+    df['Reason for ban'] = df['Reason for ban'].replace({'nan': 'No ban'})
+    df['Swimming allowed'] = df['Swimming allowed'].astype('string')
+    df.loc[df['Traffic lights'].str.contains('greng'), 'Swimming allowed'] = 'Yes'
+    df.loc[df['Traffic lights'].str.contains('roud'), 'Swimming allowed'] = 'No'
+    df = df.fillna('N/A')
+
+    df[['X', 'Y']] = df['URL coordinates'].apply(extract_coordinates)
+    df[['X', 'Y']] = df[['X', 'Y']].apply(pd.to_numeric, errors='coerce')
+    df[['lat', 'long']] = df.apply(lambda row: web_mercator_to_wgs84(row['X'], row['Y']), axis=1, result_type='expand')
+    df.drop(columns=['Traffic lights', 'URL coordinates', 'X', 'Y'], inplace=True)
+
+    df.to_csv(file_name, index=False)
+    return df
+
+def load_data(force_refresh=False):
+    if force_refresh or (not os.path.exists(file_name)) or ((time.time() - os.path.getmtime(file_name)) > 3600):
+        return file_download()
+    return pd.read_csv(file_name)
+
+def create_map(force_refresh=False):
+    df = load_data(force_refresh)
+    
+    # Create base map with Luxembourg coordinates
+    if df.empty:
+        m = folium.Map(location=[49.8153, 6.1296], zoom_start=9)
+    else:
+        m = folium.Map(location=[df['lat'].mean(), df['long'].mean()], zoom_start=9)
+        
+        # Add markers
+        for _, row in df.iterrows():
+            color = 'green' if row['Swimming allowed'] == 'Yes' else \
+                    'red' if row['Swimming allowed'] == 'No' else 'gray'
+            
+            popup_text = f"""
+            <b>Lake:</b> {row['Lake']}<br>
+            <b>Sector:</b> {row['Sector']}<br>
+            <b>Latitude:</b> {row['lat']:.6f}<br>
+            <b>Longitude:</b> {row['long']:.6f}<br>
+            <b>Water Quality:</b> {row['Water Quality']}<br>
+            <b>Swimming allowed:</b> {row['Swimming allowed']}<br>
+            <b>Reason for ban:</b> {row['Reason for ban']}
+            """
+            
+            folium.CircleMarker(
+                location=[row['lat'], row['long']],
+                radius=8,
+                color=color,
+                fill=True,
+                fill_color=color,
+                fill_opacity=0.7,
+                popup=folium.Popup(popup_text, max_width=300)
+            ).add_to(m)
+    
+    # Use OpenStreetMap tiles
+    folium.TileLayer('openstreetmap').add_to(m)
+    
+    # Remove attribution completely
+    m.get_root().html.add_child(folium.Element("""
+        <style>
+            .leaflet-control-attribution {
+                display: none !important;
+            }
+        </style>
+    """))
+    
+    # Return HTML representation
+    return m._repr_html_()
+
+# Create Gradio interface
+with gr.Blocks(title="LuxSplash") as app:
+    gr.Markdown("# 🏊‍♂️ LuxSplash")
+    gr.Markdown("[Freedom Luxembourg](https://freeletz.lu)")
+    
+    with gr.Row():
+        refresh_btn = gr.Button("Refresh Data", variant="primary")
+    
+    map_html = gr.HTML()
+    
+    # Initial load
+    app.load(fn=lambda: create_map(False), inputs=None, outputs=map_html)
+    
+    # Refresh functionality
+    refresh_btn.click(
+        fn=lambda: create_map(True),
+        inputs=None,
+        outputs=map_html
+    )
+    gr.Markdown(
+        "Data sourced from the official Luxembourg government website, the only authoritative source for bathing site information: "
+        "[eau.gouvernement.lu](https://eau.gouvernement.lu/fr/domaines-activite/eauxbaignade/sites-de-baignade.html )"
+    )
+
+
+if __name__ == "__main__":
+    app.launch()