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164 changes: 147 additions & 17 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,18 +2,14 @@
"cells": [
{
"cell_type": "markdown",
"id": "25d7736c-ba17-4aff-b6bb-66eba20fbf4e",
"metadata": {},
"source": [
"# Lab | Functions"
]
},
{
"cell_type": "markdown",
"id": "0c581062-8967-4d93-b06e-62833222f930",
"metadata": {
"tags": []
},
"metadata": {},
"source": [
"## Exercise: Managing Customer Orders with Functions\n",
"\n",
Expand All @@ -39,29 +35,163 @@
"\n",
"- Consider the input parameters required for each function and their return values.\n",
"- Utilize function parameters and return values to transfer data between functions.\n",
"- Test your functions individually to ensure they work correctly.\n",
"- Test your functions individually to ensure they work correctly.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**1.** `initialize_inventory(products)` — asks for a quantity per product, returns a fresh `inventory` dict. Builds it locally and returns it, instead of relying on a global `inventory` variable."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" quantity = int(input(f\"Enter the quantity of {product}s available: \"))\n",
" inventory[product] = quantity\n",
" return inventory"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**2.** `get_customer_orders()` — no parameters, same `while True` + \"add another? (yes/no)\" pattern from the flow-control lab. Returns the `customer_orders` set."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders():\n",
" customer_orders = set()\n",
" while True:\n",
" order = input(\"Enter the name of a product the customer wants to order: \")\n",
" customer_orders.add(order)\n",
"\n",
" another = input(\"Do you want to add another product? (yes/no): \")\n",
" if another.lower().strip() != \"yes\":\n",
" break\n",
" return customer_orders"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**3.** `update_inventory(customer_orders, inventory)` — subtracts 1 only for products that were actually ordered. Modifies the `inventory` dict it's given (no return needed, since dicts are mutable and the caller's dict is updated in place)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" for product in customer_orders:\n",
" if product in inventory:\n",
" inventory[product] -= 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**4.** `calculate_order_statistics(customer_orders, products)` — returns the `(total, percentage)` tuple."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def calculate_order_statistics(customer_orders, products):\n",
" total_products_ordered = len(customer_orders)\n",
" percentage_ordered = (total_products_ordered / len(products)) * 100\n",
" return total_products_ordered, percentage_ordered"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**5.** `print_order_statistics(order_statistics)` — takes the tuple, prints it."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(order_statistics):\n",
" print(\"Order Statistics:\")\n",
" print(f\"Total Products Ordered: {order_statistics[0]}\")\n",
" print(f\"Percentage of Products Ordered: {order_statistics[1]}%\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**6.** `print_updated_inventory(inventory)`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def print_updated_inventory(inventory):\n",
" for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**7.** Call everything in sequence. `products` is the only thing that still lives at the top level — everything else is passed between functions as arguments/return values, no globals used inside any function body."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"\n",
"\n"
"inventory = initialize_inventory(products)\n",
"customer_orders = get_customer_orders()\n",
"update_inventory(customer_orders, inventory)\n",
"order_statistics = calculate_order_statistics(customer_orders, products)\n",
"print_order_statistics(order_statistics)\n",
"print_updated_inventory(inventory)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.x"
}
},
"nbformat": 4,
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