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Complete Python functions lab #717

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Complete Python functions lab #717

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155 changes: 154 additions & 1 deletion lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,159 @@
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "10c44d8c-7291-4705-a000-66f544b0efb3",
"metadata": {},
"outputs": [],
"source": [
"#1. initialize_inventory\n",
"def initialize_inventory(products):\n",
" inventory = {}\n",
"\n",
" for item in products:\n",
" quantity = int(input(f\"Enter {item} quantity: \"))\n",
" inventory[item] = quantity\n",
"\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "620b51d6-2737-494b-ba9c-931bc1764c69",
"metadata": {},
"outputs": [],
"source": [
"#2. get_customer_orders\n",
"def get_customer_orders():\n",
" customer_orders = set()\n",
"\n",
" add_product = \"yes\"\n",
"\n",
" while add_product == \"yes\":\n",
" item = input(\"What would you like to order: t-shirt, mug, hat, book or keychain? \").lower()\n",
"\n",
" if item in products:\n",
" customer_orders.add(item)\n",
" else:\n",
" print(\"Invalid product or wrongly written. Please choose one from the list.\")\n",
"\n",
" add_product = input(\"Do you want to add another product? (yes/no) \").lower()\n",
"\n",
" return customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9a905fe9-167d-4ba4-98c2-b69d31708749",
"metadata": {},
"outputs": [],
"source": [
"#3. update_inventory\n",
"def update_inventory(customer_orders, inventory):\n",
" for item in customer_orders:\n",
" inventory[item] -= 1"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "659838c5-89a5-40f9-8960-e690013459a0",
"metadata": {},
"outputs": [],
"source": [
"#4. calculate_order_statistics\n",
"def calculate_order_statistics(customer_orders, products):\n",
" total_products_ordered = len(customer_orders)\n",
" percentage_products_ordered = (total_products_ordered / len(products)) * 100\n",
"\n",
" return total_products_ordered, percentage_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "c8c3cb91-f714-42c5-b12d-5cc4afe4fedf",
"metadata": {},
"outputs": [],
"source": [
"#5. print_order_statistics\n",
"def print_order_statistics(order_statistics):\n",
" total_products_ordered, percentage_products_ordered = order_statistics\n",
"\n",
" labels = [\"Total Products Ordered:\", \"Percentage of Products Ordered:\"]\n",
"\n",
" for label, value in zip(labels, order_statistics):\n",
" print(label, value)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "a011121b-67e1-43bf-b50f-f702b738802c",
"metadata": {},
"outputs": [],
"source": [
"#6. print_updated_inventory\n",
"def print_updated_inventory(inventory):\n",
" for item, quantity in inventory.items():\n",
" print(item.title() + \":\", quantity)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "03cda061-2ceb-44b6-b951-2d43a51e819d",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter t-shirt quantity: 1\n",
"Enter mug quantity: 1\n",
"Enter hat quantity: 1\n",
"Enter book quantity: 1\n",
"Enter keychain quantity: 1\n",
"What would you like to order: t-shirt, mug, hat, book or keychain? mug\n",
"Do you want to add another product? (yes/no) yes\n",
"What would you like to order: t-shirt, mug, hat, book or keychain? hat\n",
"Do you want to add another product? (yes/no) no\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total Products Ordered: 2\n",
"Percentage of Products Ordered: 40.0\n",
"T-Shirt: 1\n",
"Mug: 0\n",
"Hat: 0\n",
"Book: 1\n",
"Keychain: 1\n"
]
}
],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"\n",
"inventory = initialize_inventory(products)\n",
"\n",
"customer_orders = get_customer_orders()\n",
"\n",
"order_statistics = calculate_order_statistics(customer_orders, products)\n",
"\n",
"print_order_statistics(order_statistics)\n",
"\n",
"update_inventory(customer_orders, inventory)\n",
"\n",
"print_updated_inventory(inventory)"
]
}
],
"metadata": {
Expand All @@ -61,7 +214,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.14.6"
}
},
"nbformat": 4,
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