Trabajo en la rama solucion

lab-web-scraping.ipynb

@@ -117,7 +117,78 @@
       },
       "outputs": [],
       "source": [
-        "# Your solution goes here"
+        "import requests\n",
+        "from bs4 import BeautifulSoup\n",
+        "import pandas as pd\n",
+        "import textwrap\n",
+        "import time  # para evitar bloqueos por exceso de peticiones\n",
+        "\n",
+        "# Diccionario para convertir palabras de rating a números\n",
+        "rating_map = {'One': 1, 'Two': 2, 'Three': 3, 'Four': 4, 'Five': 5}\n",
+        "\n",
+        "# Función principal que acepta parámetros\n",
+        "def scrape_books(min_rating, max_price):\n",
+        "    all_books = []  # Lista para guardar los libros\n",
+        "\n",
+        "    # Recorremos las 50 páginas del sitio\n",
+        "    for page in range(1, 51):\n",
+        "        url = f'http://books.toscrape.com/catalogue/page-{page}.html'\n",
+        "        response = requests.get(url)\n",
+        "        soup = BeautifulSoup(response.text, 'html.parser')\n",
+        "\n",
+        "        # Encontramos todos los libros en la página\n",
+        "        books = soup.find_all('article', class_='product_pod')\n",
+        "\n",
+        "        for book in books:\n",
+        "            title = book.h3.a['title']\n",
+        "            price = float(book.find('p', class_='price_color').text[2:])\n",
+        "            rating_word = book.find('p', class_='star-rating')['class'][1]\n",
+        "            rating = rating_map[rating_word]\n",
+        "\n",
+        "            # Aplicamos los filtros usando los parámetros\n",
+        "            if rating >= min_rating and price <= max_price:\n",
+        "                link = book.h3.a['href']\n",
+        "                detail_url = 'http://books.toscrape.com/catalogue/' + link\n",
+        "                detail_response = requests.get(detail_url)\n",
+        "                detail_soup = BeautifulSoup(detail_response.text, 'html.parser')\n",
+        "\n",
+        "                # Extraemos los datos adicionales\n",
+        "                upc = detail_soup.find('th', string='UPC').find_next('td').text\n",
+        "                genre = detail_soup.select('ul.breadcrumb li')[2].text.strip()\n",
+        "                availability = detail_soup.find('p', class_='instock availability').text.strip()\n",
+        "\n",
+        "                desc_tag = detail_soup.find('div', id='product_description')\n",
+        "                if desc_tag:\n",
+        "                    description = desc_tag.find_next('p').text.strip()\n",
+        "                else:\n",
+        "                    description = 'No description available'\n",
+        "\n",
+        "                # Formateamos la descripción para que se vea bonita\n",
+        "                description = textwrap.fill(description, width=60)\n",
+        "\n",
+        "                # Guardamos los datos en un diccionario\n",
+        "                book_info = {\n",
+        "                    'UPC': upc,\n",
+        "                    'Title': title,\n",
+        "                    'Price (£)': price,\n",
+        "                    'Rating': rating,\n",
+        "                    'Genre': genre,\n",
+        "                    'Availability': availability,\n",
+        "                    'Description': description\n",
+        "                }\n",
+        "\n",
+        "                # Añadimos el libro a la lista\n",
+        "                all_books.append(book_info)\n",
+        "\n",
+        "                # Esperamos medio segundo para no saturar el servidor\n",
+        "                time.sleep(0.5)\n",
+        "\n",
+        "    # Convertimos la lista en un DataFrame\n",
+        "    return pd.DataFrame(all_books)\n",
+        "\n",
+        "# Ejemplo de uso\n",
+        "books_df = scrape_books(min_rating=4, max_price=20)\n",
+        "print(books_df.head())  # Mostramos los primeros libros"
       ]
     }
   ],