Lab 4 done

lab-python-list-comprehension.ipynb

@@ -75,13 +75,81 @@
     "\n",
     "```\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d127f463-6433-4891-8ce4-269b43058393",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
+    "\n",
+    "def initialize_inventory(products):\n",
+    "    print(\"Inventory:\")\n",
+    "    inventory = {p: int(input(f\"Enter the number of {p}s available: \")) for p in products}\n",
+    "    return inventory\n",
+    "\n",
+    "def get_customer_orders():\n",
+    "    print(\"Customer order:\")\n",
+    "    print(\"Available products:\", products)\n",
+    "    n = int(input(\"Number of customer orders: \"))\n",
+    "    entries = [input(\"Name of a product that a customer wants to order: \").strip().lower()\n",
+    "               for _ in range(n)]\n",
+    "    customer_orders = {name for name in entries if name in products}\n",
+    "    return customer_orders\n",
+    "\n",
+    "def update_inventory(customer_orders, inventory):\n",
+    "    updated = {k: (v - 1 if k in customer_orders else v) for k, v in inventory.items()}\n",
+    "    updated = {k: v for k, v in updated.items() if v > 0}\n",
+    "    return updated\n",
+    "\n",
+    "def calculate_order_statistics(customer_orders, products):\n",
+    "    total_ordered = len(customer_orders)\n",
+    "    percentage = (total_ordered / len(products)) * 100\n",
+    "    return total_ordered, percentage\n",
+    "\n",
+    "def print_order_statistics(order_statistics):\n",
+    "    total_ordered, percentage = order_statistics\n",
+    "    print(\"Order Statistics:\")\n",
+    "    print(\"Total Products Ordered:\", total_ordered)\n",
+    "    print(\"Percentage of Unique Products Ordered:\", percentage)\n",
+    "\n",
+    "def print_updated_inventory(inventory):\n",
+    "    print(\"Updated Inventory:\")\n",
+    "    [print(f\"{k}: {v}\") for k, v in inventory.items()]  # uso de comprensión para imprimir\n",
+    "\n",
+    "def calculate_total_price(customer_orders):\n",
+    "    # Precios por producto con dict comprehension, luego sumamos\n",
+    "    prices = {p: float(input(f\"Enter the price of {p}: \")) for p in customer_orders}\n",
+    "    total = sum(prices.values())\n",
+    "    return total\n",
+    "\n",
+    "# Secuencia\n",
+    "inventory = initialize_inventory(products)\n",
+    "customer_orders = get_customer_orders()\n",
+    "stats = calculate_order_statistics(customer_orders, products)\n",
+    "print_order_statistics(stats)\n",
+    "inventory = update_inventory(customer_orders, inventory)\n",
+    "print_updated_inventory(inventory)\n",
+    "total_price = calculate_total_price(customer_orders)\n",
+    "print(\"Total Price:\", total_price)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8af600d5-5369-4f64-a9f9-4be10fb60fbc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python [conda env:base] *",
    "language": "python",
-   "name": "python3"
+   "name": "conda-base-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -93,7 +161,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,