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318 changes: 287 additions & 31 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
@@ -1,53 +1,309 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "25d7736c-ba17-4aff-b6bb-66eba20fbf4e",
"cell_type": "code",
"execution_count": 14,
"id": "1eef9dfb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['t-shirt', 'mug', 'hat', 'book', 'keychain']\n"
]
}
],
"source": [
"# Lab | Functions"
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"print(products)"
]
},
{
"cell_type": "markdown",
"id": "0c581062-8967-4d93-b06e-62833222f930",
"metadata": {
"tags": []
},
"cell_type": "code",
"execution_count": 12,
"id": "214d37a8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{}\n"
]
}
],
"source": [
"## Exercise: Managing Customer Orders with Functions\n",
"\n",
"In the previous exercise, you improved the code for managing customer orders by using loops and flow control. Now, let's take it a step further and refactor the code by introducing functions.\n",
"\n",
"Follow the steps below to complete the exercise:\n",
"\n",
"1. Define a function named `initialize_inventory` that takes `products` as a parameter. Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
"\n",
"2. Define a function named `get_customer_orders` that takes no parameters. Inside the function, implement the code for prompting the user to enter the product names using a loop. The function should return the `customer_orders` set.\n",
"\n",
"3. Define a function named `update_inventory` that takes `customer_orders` and `inventory` as parameters. Inside the function, implement the code for updating the inventory dictionary based on the customer orders.\n",
"\n",
"4. Define a function named `calculate_order_statistics` that takes `customer_orders` and `products` as parameters. Inside the function, implement the code for calculating the order statistics (total products ordered, and percentage of unique products ordered). The function should return these values.\n",
"inventory = {}\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "dbdd893a",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {}\n",
"\n",
"5. Define a function named `print_order_statistics` that takes `order_statistics` as a parameter. Inside the function, implement the code for printing the order statistics.\n",
" for product in products:\n",
" quantity = int(input(f\"Enter the quantity of {product}: \"))\n",
" inventory[product] = quantity\n",
"\n",
"6. Define a function named `print_updated_inventory` that takes `inventory` as a parameter. Inside the function, implement the code for printing the updated inventory.\n",
" return inventory"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "82676f4c",
"metadata": {},
"outputs": [],
"source": [
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "272c0c67",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"set()\n"
]
}
],
"source": [
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "2d09090d",
"metadata": {},
"outputs": [],
"source": [
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e6927b60",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders():\n",
" customer_orders = set()\n",
"\n",
"7. Call the functions in the appropriate sequence to execute the program and manage customer orders.\n",
" while True:\n",
" product = input(\"Enter a product to order: \")\n",
" customer_orders.add(product)\n",
" add_another = input(\"Do you want to add another product? (yes/no): \")\n",
"\n",
"Hints for functions:\n",
" if add_another.lower() != \"yes\":\n",
" break\n",
"\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",
" return customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "996bce40",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'mug', 'hat', 'book'}\n"
]
}
],
"source": [
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5258135e",
"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",
"\n",
"\n"
" return total_products_ordered, percentage_ordered"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7933d360",
"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": "code",
"execution_count": 36,
"id": "e6a0dab9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_status[0]"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "8c632478",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"60.0"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"order_status[1]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "269df459",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" for product in customer_orders:\n",
" inventory[product] -= 1"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f68141b0",
"metadata": {},
"outputs": [],
"source": [
"def print_updated_inventory(inventory):\n",
" print(\"Updated Inventory:\")\n",
" for product, quantity in inventory.items():\n",
" print(f\"{product}: {quantity}\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "726556fb",
"metadata": {},
"outputs": [],
"source": [
"inventory = initialize_inventory(products)\n",
"customer_orders = get_customer_orders()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "b1bee755",
"metadata": {},
"outputs": [],
"source": [
"update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "041714c0",
"metadata": {},
"outputs": [],
"source": [
"order_statistics = calculate_order_statistics(customer_orders, products)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "1bd45071",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0%\n"
]
}
],
"source": [
"print_order_statistics(order_statistics)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "e52b1644",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated Inventory:\n",
"t-shirt: 10\n",
"mug: 14\n",
"hat: 19\n",
"book: 24\n",
"keychain: 30\n"
]
}
],
"source": [
"print_updated_inventory(inventory)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": ".venv (3.14.7.final.0)",
"language": "python",
"name": "python3"
},
Expand All @@ -61,7 +317,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.14.7"
}
},
"nbformat": 4,
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