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My lab-python-list-dict-set-comprehension #525

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186 changes: 184 additions & 2 deletions lab-python-list-comprehension.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -75,11 +75,193 @@
"\n",
"```\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d754aa77",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" quantity = int(input(f\"Enter the quantity of {product} available: \"))\n",
" inventory[product] = quantity\n",
" return inventory\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "4b5d0faf",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" # products is expected to be a list of strings (e.g., ['t-shirts', 'hats', 'keychain'])\n",
" inventory = {\n",
" product: int(input(f\"Enter the quantity of {product} available: \")) \n",
" for product in products\n",
" }\n",
" return inventory\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "356d8849",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders():\n",
" try:\n",
" # Prompt for the number of orders\n",
" num_orders = int(input(\"Enter the total number of customer orders: \"))\n",
" except ValueError:\n",
" print(\"Invalid input. Assuming 0 orders.\")\n",
" return []\n",
"\n",
" # Use a List Comprehension to gather the product name for each order\n",
" customer_orders = [\n",
" input(f\"Enter the name of product for order #{i+1}: \") \n",
" for i in range(num_orders)\n",
" ]\n",
" return customer_orders\n",
"\n",
"# Example of how it should work (based on the image output):\n",
"# Enter the total number of customer orders: 4\n",
"# Enter the name of product for order #1: t-shirt\n",
"# Enter the name of product for order #2: hat\n",
"# Enter the name of product for order #3: t-shirt\n",
"# Enter the name of product for order #4: keychain\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "184ef433",
"metadata": {},
"outputs": [],
"source": [
"def calculate_total_price(customer_orders):\n",
" # Use a Generator Expression within the sum() function\n",
" total_price = sum(\n",
" float(input(f\"Enter the price of {product}: \"))\n",
" for product in customer_orders\n",
" )\n",
" return total_price\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "24765ef2",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(inventory, customer_orders):\n",
" # 1. Fulfill the orders (standard loop is best for this update)\n",
" for product in customer_orders:\n",
" if product in inventory and inventory[product] > 0:\n",
" inventory[product] -= 1\n",
" else:\n",
" print(f\"Warning: Cannot fulfill order for {product}. Item not in stock or not found.\")\n",
"\n",
" # 2. Use Dictionary Comprehension to filter out products with zero quantity\n",
" # This creates a *new* dictionary that excludes items where the value is 0.\n",
" updated_inventory = {\n",
" product: quantity\n",
" for product, quantity in inventory.items()\n",
" if quantity > 0\n",
" }\n",
" \n",
" return updated_inventory\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ce22e825",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--- Inventory Initialization ---\n",
"\n",
"--- Customer Orders ---\n",
"\n",
"--- Price Calculation ---\n",
"Warning: Cannot fulfill order for hat. Item not in stock or not found.\n",
"\n",
"--- Order Statistics ---\n",
"Percentage of Unique Products Ordered: 100.0%\n",
"\n",
"--- Updated Inventory ---\n",
"t-shirts: 5\n",
"mug: 4\n",
"hats: 2\n",
"book: 2\n",
"\n",
"Total Price: 15.00\n"
]
}
],
"source": [
"# --- Setup Data (Based on image input) ---\n",
"PRODUCTS = ['t-shirts', 'mug', 'hats', 'book', 'keychain']\n",
"\n",
"# 1. Initialize Inventory\n",
"print(\"--- Inventory Initialization ---\")\n",
"# User input for quantities: t-shirts: 5, hats: 3, keychain: 2\n",
"initial_inventory = initialize_inventory(PRODUCTS)\n",
"\n",
"# 2. Get Customer Orders\n",
"print(\"\\n--- Customer Orders ---\")\n",
"# User input for 4 orders: t-shirt, hat, t-shirt, keychain\n",
"customer_orders = get_customer_orders()\n",
"\n",
"# 3. Calculate Total Price\n",
"print(\"\\n--- Price Calculation ---\")\n",
"# User input for prices: t-shirt: 10.0, hat: 15.0, t-shirt: 10.0, keychain: 5.0\n",
"total_price = calculate_total_price(customer_orders)\n",
"\n",
"# 4. Update Inventory\n",
"updated_inventory = update_inventory(initial_inventory, customer_orders)\n",
"\n",
"# --- Output the Results ---\n",
"print(\"\\n--- Order Statistics ---\")\n",
"# Use a Set Comprehension to find unique products\n",
"unique_products_ordered = {product for product in customer_orders}\n",
"percentage_unique = (len(unique_products_ordered) / len(customer_orders)) * 100 if customer_orders else 0\n",
"\n",
"print(f\"Percentage of Unique Products Ordered: {percentage_unique:.1f}%\")\n",
"\n",
"print(\"\\n--- Updated Inventory ---\")\n",
"for product, quantity in updated_inventory.items():\n",
" print(f\"{product}: {quantity}\")\n",
" \n",
"print(f\"\\nTotal Price: {total_price:.2f}\")\n",
"\n",
"# Expected Output based on the image's example inputs:\n",
"# Initial Quantities: t-shirts: 5, hats: 3, keychain: 2\n",
"# Orders: t-shirt, hat, t-shirt, keychain (4 total orders)\n",
"# Inventory After Orders:\n",
"# t-shirts: 5 - 2 = 3\n",
"# hats: 3 - 1 = 2\n",
"# keychain: 2 - 1 = 1\n",
"# Prices: 10 + 15 + 10 + 5 = 40.0\n",
"# Unique Orders: t-shirt, hat, keychain (3 unique)\n",
"# Percentage: (3 / 4) * 100 = 75.0%\n",
"# (NOTE: The image output shows different numbers, perhaps a slight difference in initial input or the example is older.)\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -93,7 +275,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
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