diff --git a/lab-python-list-comprehension.ipynb b/lab-python-list-comprehension.ipynb index 5a3c3e1..1f60248 100644 --- a/lab-python-list-comprehension.ipynb +++ b/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,