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Update app.py
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app.py
CHANGED
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import os
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import subprocess
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import pandas as pd
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import requests
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from PIL import Image
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import io
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# --- INSTALACIÓN DE DEPENDENCIAS ---
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try:
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subprocess.run(["pip", "install", "fake-useragent"], check=True)
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from fake_useragent import UserAgent
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# ---
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def descargar_imagen(url, idx):
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if not url or url.startswith("data:"):
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return None
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try:
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r = requests.get(url, timeout=5, headers={"User-Agent": "Mozilla/5.0"})
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img.save(path, format="JPEG")
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return path
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except:
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return None
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# --- 1. GENERADOR DE URLS ---
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lineas = [l.strip() for l in texto.split('\n') if len(l.strip()) > 5]
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if len(lineas) > 1:
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for linea in lineas[1:4]:
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if "$" not in linea and not linea.isdigit():
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return linea[:60]
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return "Ubicación en zona solicitada"
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# --- 3. MOTOR DE EXTRACCIÓN SÍNCRONO
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def motor_tramitia_visual(operacion, barrio, ciudad, area, m2_min, m2_max, tipo, hab, ban, park, antiguedad, ascensor, piscina):
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resultados = []
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args=['--disable-blink-features=AutomationControlled', '--no-sandbox', '--disable-dev-shm-usage', f'--user-agent={ua.random}']
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)
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context = browser.new_context(viewport={'width': 1366, 'height': 768})
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img_url = img_el.get_attribute("src") or img_el.get_attribute("data-src") or ""
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for card in cards[:15]:
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txt = card.inner_text()
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precio = extraer_precio(txt, operacion)
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if precio > 0:
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enlace_el = card.query_selector("a")
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img_el = card.query_selector("img")
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href = enlace_el.get_attribute("href") if enlace_el else ""
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img_url = ""
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if img_el:
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img_url = img_el.get_attribute("src") or img_el.get_attribute("data-src") or ""
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"Portal": "Metrocuadrado",
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"Precio": precio,
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"Precio_M2": precio / area,
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"Ubicacion": extraer_ubicacion(txt),
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"Descripcion": txt.replace('\n', ' | ')[:120] + "...",
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"URL": f"https://www.metrocuadrado.com{href}" if href.startswith("/") else href,
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"Imagen": img_url
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})
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page.close()
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except Exception as e: log_visible += f"⚠️ Error MC: {e}\n"
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browser.close()
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df_fr = df_crudo[df_crudo['Portal'] == 'Finca Raiz'].head(6)
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df_mc = df_crudo[df_crudo['Portal'] == 'Metrocuadrado'].head(6)
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df_final = pd.concat([df_fr, df_mc]).reset_index(drop=True)
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try:
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pdf.image(img_path, x=10, y=y_start, w=45, h=30)
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text_x = 60
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except: pass
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pdf.line(10, pdf.get_y(), 200, pdf.get_y())
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pdf.ln(5)
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os.remove(img_path)
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pdf.output(pdf_path)
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# --- CÁLCULOS ---
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promedio = df_final['Precio_M2'].mean() * area
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resumen = (
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f"💰 **ESTIMACIÓN DE {operacion.upper()}**\n"
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f"🔹 **Valor Sugerido:** ${promedio:,.0f}\n"
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f"📉 Mínimo Zona: ${df_final['Precio'].min():,.0f}\n"
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f"📈 Máximo Zona: ${df_final['Precio'].max():,.0f}"
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)
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df_mostrar = df_final[['Portal', 'Precio', 'Ubicacion', 'Descripcion', 'URL']]
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return f"{log_visible}\n✅ PDF Visual Generado con Éxito.", df_mostrar, pdf_path, resumen
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futuro = executor.submit(motor_tramitia_visual, *args)
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return futuro.result()
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# --- INTERFAZ GRÁFICA ---
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("## 📸 TramitIA Pro: Generador Visual
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Row():
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t = gr.Dropdown(["Apartamento", "Casa", "Bodega", "Lote", "Oficina"], label="Tipo", value="Apartamento")
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a = gr.Number(label="Área M2
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with gr.Row():
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m2_min = gr.Number(label="M2 Mínimo", value=10)
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p = gr.Number(label="Park", value=1)
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e = gr.Dropdown(["Menos de 1 año", "1 a 8 años", "9 a 15 años", "16 a 30 años", "Más de 30 años"], label="Antigüedad", value="1 a 8 años")
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btn = gr.Button("GENERAR REPORTE
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with gr.Column(scale=2):
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res_fin = gr.Markdown("### 💰
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with gr.Tabs():
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with gr.TabItem("Descargar
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with gr.TabItem("Tabla de Datos"): out_df = gr.Dataframe()
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with gr.TabItem("Auditoría"): msg = gr.Textbox(lines=10)
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btn.click(ejecutor_aislado, [op, b, c, a, m2_min, m2_max, t, h, ban, p, e, ascensor, piscina], [msg, out_df, out_pdf, res_fin])
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demo.launch()
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import sys
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# Silenciador del error fantasma de Linux (No congela, solo oculta el texto rojo)
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def silenciador_errores_basura(unraisable):
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if unraisable.exc_type == ValueError and "Invalid file descriptor: -1" in str(unraisable.exc_value): pass
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else: sys.__unraisablehook__(unraisable)
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sys.unraisablehook = silenciador_errores_basura
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import os
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import subprocess
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import pandas as pd
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import requests
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from PIL import Image
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import io
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import traceback
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# --- INSTALACIÓN DE DEPENDENCIAS ---
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try:
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subprocess.run(["pip", "install", "fake-useragent"], check=True)
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from fake_useragent import UserAgent
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# --- DESCARGA SEGURA DE FOTOS ---
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def descargar_imagen(url, idx):
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if not url or len(url) < 10 or url.startswith("data:"):
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return None
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try:
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r = requests.get(url, timeout=5, headers={"User-Agent": "Mozilla/5.0"})
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img.save(path, format="JPEG")
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return path
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except:
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return None # Si falla, devuelve None silenciosamente
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return None
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# --- 1. GENERADOR DE URLS ---
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lineas = [l.strip() for l in texto.split('\n') if len(l.strip()) > 5]
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if len(lineas) > 1:
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for linea in lineas[1:4]:
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if "$" not in linea and not linea.isdigit() and "m²" not in linea:
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return linea[:60]
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return "Ubicación en zona solicitada"
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# --- 3. MOTOR DE EXTRACCIÓN (SÍNCRONO Y ESTABLE) ---
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def motor_tramitia_visual(operacion, barrio, ciudad, area, m2_min, m2_max, tipo, hab, ban, park, antiguedad, ascensor, piscina):
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resultados = []
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log_visible = ""
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try:
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url_fr, url_mc = construir_urls_final(operacion, barrio, ciudad, tipo, hab, ban, park, antiguedad, m2_min, m2_max, ascensor, piscina)
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log_visible = f"✅ INICIANDO EXTRACCIÓN:\nFR: {url_fr}\nMC: {url_mc}\n\n"
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ua = UserAgent()
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with sync_playwright() as p:
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browser = p.chromium.launch(headless=True, args=['--disable-blink-features=AutomationControlled', '--no-sandbox'])
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context = browser.new_context(viewport={'width': 1366, 'height': 768}, user_agent=ua.random)
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# --- FINCA RAÍZ ---
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try:
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page = context.new_page()
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log_visible += "🔄 FR: Buscando inmuebles...\n"
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page.goto(url_fr, wait_until="domcontentloaded", timeout=60000)
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for _ in range(3):
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page.mouse.wheel(0, 1000)
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time.sleep(1.5)
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cards = page.query_selector_all("article, div[class*='card']")
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for card in cards[:12]:
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try:
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txt = card.inner_text()
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precio = extraer_precio(txt, operacion)
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if precio > 0:
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enlace_el = card.query_selector("a")
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img_el = card.query_selector("img")
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href = enlace_el.get_attribute("href") if enlace_el else ""
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img_url = img_el.get_attribute("src") if img_el else ""
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if href:
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resultados.append({
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"Portal": "Finca Raiz",
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"Precio": precio,
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"Precio_M2": precio / area,
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"Ubicacion": extraer_ubicacion(txt),
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"Descripcion": txt.replace('\n', ' | ')[:120] + "...",
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"URL": f"https://www.fincaraiz.com.co{href}" if href.startswith("/") else href,
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"Imagen": img_url
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})
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except: continue # Si una tarjeta falla, salta a la siguiente
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page.close()
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except Exception as e: log_visible += f"⚠️ Error buscando en FR.\n"
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# --- METROCUADRADO ---
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try:
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page = context.new_page()
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log_visible += "🔄 MC: Buscando inmuebles...\n"
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page.goto(url_mc, wait_until="domcontentloaded", timeout=60000)
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for _ in range(4):
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page.mouse.wheel(0, 1000)
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time.sleep(1.5)
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cards = page.query_selector_all("li, div.property-card")
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for card in cards[:12]:
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try:
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txt = card.inner_text()
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precio = extraer_precio(txt, operacion)
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if precio > 0:
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enlace_el = card.query_selector("a")
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img_el = card.query_selector("img")
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href = enlace_el.get_attribute("href") if enlace_el else ""
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img_url = img_el.get_attribute("src") if img_el else ""
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if href:
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resultados.append({
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"Portal": "Metrocuadrado",
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"Precio": precio,
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"Precio_M2": precio / area,
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"Ubicacion": extraer_ubicacion(txt),
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"Descripcion": txt.replace('\n', ' | ')[:120] + "...",
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"URL": f"https://www.metrocuadrado.com{href}" if href.startswith("/") else href,
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"Imagen": img_url
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})
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except: continue
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page.close()
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except Exception as e: log_visible += f"⚠️ Error buscando en MC.\n"
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browser.close()
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if not resultados:
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return f"{log_visible}\n❌ NO SE ENCONTRARON DATOS.", pd.DataFrame(), None, "---"
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# --- LIMPIEZA ---
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df_crudo = pd.DataFrame(resultados).drop_duplicates(subset=['URL'])
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df_fr = df_crudo[df_crudo['Portal'] == 'Finca Raiz'].head(6)
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df_mc = df_crudo[df_crudo['Portal'] == 'Metrocuadrado'].head(6)
|
| 189 |
+
df_final = pd.concat([df_fr, df_mc]).reset_index(drop=True)
|
| 190 |
|
| 191 |
+
log_visible += f"\n✨ PROCESANDO PDF CON {len(df_final)} INMUEBLES..."
|
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|
| 192 |
|
| 193 |
+
# --- PDF ---
|
| 194 |
+
pdf_path = f"Reporte_Visual_{int(time.time())}.pdf"
|
| 195 |
+
pdf = FPDF()
|
| 196 |
+
pdf.add_page()
|
| 197 |
+
|
| 198 |
+
pdf.set_font("Arial", 'B', 16)
|
| 199 |
+
pdf.set_fill_color(40, 53, 147)
|
| 200 |
+
pdf.set_text_color(255, 255, 255)
|
| 201 |
+
pdf.cell(0, 15, f" REPORTE INMOBILIARIO: {barrio.upper()} ({operacion.upper()})", ln=True, fill=True)
|
| 202 |
+
pdf.set_text_color(0, 0, 0)
|
| 203 |
+
pdf.ln(5)
|
| 204 |
|
| 205 |
+
for idx, r in df_final.iterrows():
|
| 206 |
+
if pdf.get_y() > 220: pdf.add_page()
|
| 207 |
+
|
| 208 |
+
y_start = pdf.get_y()
|
| 209 |
+
img_path = descargar_imagen(r['Imagen'], idx)
|
| 210 |
+
text_x = 10
|
| 211 |
|
| 212 |
+
if img_path and os.path.exists(img_path):
|
| 213 |
+
try:
|
| 214 |
+
pdf.image(img_path, x=10, y=y_start, w=45, h=30)
|
| 215 |
+
text_x = 60
|
| 216 |
+
except: pass
|
|
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|
|
|
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|
|
| 217 |
|
| 218 |
+
pdf.set_xy(text_x, y_start)
|
| 219 |
+
pdf.set_font("Arial", 'B', 12)
|
| 220 |
+
pdf.cell(0, 6, f"${r['Precio']:,.0f} COP", ln=True)
|
| 221 |
+
|
| 222 |
+
pdf.set_x(text_x)
|
| 223 |
+
pdf.set_font("Arial", 'B', 9)
|
| 224 |
+
pdf.set_text_color(100, 100, 100)
|
| 225 |
+
pdf.cell(0, 5, f"📍 {r['Ubicacion']} | Fuente: {r['Portal']}", ln=True)
|
| 226 |
+
|
| 227 |
+
pdf.set_x(text_x)
|
| 228 |
+
pdf.set_font("Arial", '', 8)
|
| 229 |
+
pdf.set_text_color(0, 0, 0)
|
| 230 |
+
pdf.multi_cell(0, 4, f"{r['Descripcion']}")
|
| 231 |
+
|
| 232 |
+
pdf.set_x(text_x)
|
| 233 |
+
pdf.set_font("Arial", 'U', 8)
|
| 234 |
+
pdf.set_text_color(0, 102, 204)
|
| 235 |
+
pdf.cell(0, 5, "🔗 Hacer clic aquí para ver publicación", link=r['URL'], ln=True)
|
| 236 |
+
pdf.set_text_color(0, 0, 0)
|
| 237 |
+
|
| 238 |
+
y_end = pdf.get_y()
|
| 239 |
+
pdf.set_y(max(y_start + 35, y_end + 5))
|
| 240 |
+
|
| 241 |
+
pdf.set_draw_color(200, 200, 200)
|
| 242 |
+
pdf.line(10, pdf.get_y(), 200, pdf.get_y())
|
| 243 |
+
pdf.ln(5)
|
| 244 |
+
|
| 245 |
+
if img_path and os.path.exists(img_path):
|
| 246 |
+
try: os.remove(img_path)
|
| 247 |
+
except: pass
|
| 248 |
+
|
| 249 |
+
pdf.output(pdf_path)
|
| 250 |
|
| 251 |
+
# --- CÁLCULOS ---
|
| 252 |
+
promedio = df_final['Precio_M2'].mean() * area
|
| 253 |
+
resumen = (
|
| 254 |
+
f"💰 **ESTIMACIÓN DE {operacion.upper()}**\n"
|
| 255 |
+
f"🔹 **Valor Sugerido:** ${promedio:,.0f}\n"
|
| 256 |
+
f"📉 Mínimo Zona: ${df_final['Precio'].min():,.0f}\n"
|
| 257 |
+
f"📈 Máximo Zona: ${df_final['Precio'].max():,.0f}"
|
| 258 |
+
)
|
| 259 |
|
| 260 |
+
df_mostrar = df_final[['Portal', 'Precio', 'Ubicacion', 'Descripcion', 'URL']]
|
|
|
|
|
|
|
| 261 |
|
| 262 |
+
return f"{log_visible}\n✅ PDF Generado Exitosamente.", df_mostrar, pdf_path, resumen
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 263 |
|
| 264 |
+
except Exception as error_fatal:
|
| 265 |
+
# PARACAÍDAS: Si todo colapsa, te mostrará exactamente DÓNDE y POR QUÉ en la pantalla
|
| 266 |
+
traza = traceback.format_exc()
|
| 267 |
+
return f"❌ ERROR GRAVE DEL SISTEMA:\n{str(error_fatal)}\n\nDetalles:\n{traza}", pd.DataFrame(), None, "⚠️ Falló la ejecución"
|
|
|
|
|
|
|
| 268 |
|
| 269 |
# --- INTERFAZ GRÁFICA ---
|
| 270 |
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
| 271 |
+
gr.Markdown("## 📸 TramitIA Pro: Generador Visual (Versión Estable)")
|
| 272 |
|
| 273 |
with gr.Row():
|
| 274 |
with gr.Column(scale=1):
|
|
|
|
| 278 |
|
| 279 |
with gr.Row():
|
| 280 |
t = gr.Dropdown(["Apartamento", "Casa", "Bodega", "Lote", "Oficina"], label="Tipo", value="Apartamento")
|
| 281 |
+
a = gr.Number(label="Área M2", value=70)
|
| 282 |
|
| 283 |
with gr.Row():
|
| 284 |
m2_min = gr.Number(label="M2 Mínimo", value=10)
|
|
|
|
| 294 |
p = gr.Number(label="Park", value=1)
|
| 295 |
|
| 296 |
e = gr.Dropdown(["Menos de 1 año", "1 a 8 años", "9 a 15 años", "16 a 30 años", "Más de 30 años"], label="Antigüedad", value="1 a 8 años")
|
| 297 |
+
btn = gr.Button("GENERAR REPORTE", variant="primary")
|
| 298 |
|
| 299 |
with gr.Column(scale=2):
|
| 300 |
+
res_fin = gr.Markdown("### 💰 El resultado aparecerá aquí...")
|
| 301 |
with gr.Tabs():
|
| 302 |
+
with gr.TabItem("Descargar PDF"): out_pdf = gr.File()
|
| 303 |
with gr.TabItem("Tabla de Datos"): out_df = gr.Dataframe()
|
| 304 |
with gr.TabItem("Auditoría"): msg = gr.Textbox(lines=10)
|
| 305 |
|
| 306 |
+
btn.click(motor_tramitia_visual, [op, b, c, a, m2_min, m2_max, t, h, ban, p, e, ascensor, piscina], [msg, out_df, out_pdf, res_fin])
|
|
|
|
| 307 |
|
| 308 |
demo.launch()
|