lab done

lab-python-list-comprehension.ipynb

@@ -75,11 +75,132 @@
     "\n",
     "```\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "7f2c4596",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 5, 'mug': 4, 'hat': 3, 'book': 2, 'keychain': 1}"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "products=[\"t-shirt\",\"mug\",\"hat\",\"book\",\"keychain\"]\n",
+    "inventory={product:int(input(f\"Enter the quantity of the {product} available:\")) for product in products}\n",
+    "inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4be4411c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'hat', 'keychain'}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_orders = int(input(\"Enter the number of customer orders: \"))\n",
+    "customer_orders={input(f\"Enter the name of a product that a customer want to order:\") for i in range(num_orders) }\n",
+    "\n",
+    "customer_orders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "024ed2c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{15.0}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "total_price=(sum(float(input(f\"Enter the price of {product}: \")) for product in customer_orders))\n",
+    "total_price\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "e154366e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "updated_inventory = {product:quantity - (1 if product in customer_orders else 0) for product, quantity in inventory.items() if quantity - (1 if product in customer_orders else 0) > 0}\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "39ae7cd5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'t-shirt': 5, 'mug': 4, 'hat': 2, 'book': 2}"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "updated_inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9c26f8f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total price: {15.0}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Total price: {total_price}\")"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -93,7 +214,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,