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214 changes: 211 additions & 3 deletions lab-python-list-comprehension.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -75,13 +75,221 @@
"\n",
"```\n"
]
},
{
"cell_type": "markdown",
"id": "9a3f9f44-143a-4517-b8c8-7f9d61e77d69",
"metadata": {},
"source": [
"__Step 1:__"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "ef16a971-1c04-4b72-8c0b-1a711f280a69",
"metadata": {},
"outputs": [],
"source": [
"def initialize_inventory(products):\n",
" inventory = {product: int(input(f\"Enter the quantity of {product}s available: \")) for product in products}\n",
" return inventory"
]
},
{
"cell_type": "markdown",
"id": "05a28de2-ac91-4a30-94d0-ae764d6a3776",
"metadata": {},
"source": [
"__Step 2:__"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6a33b6e6-570d-4e3b-89e9-128d2f5a01f8",
"metadata": {},
"outputs": [],
"source": [
"def get_customer_orders(products):\n",
" num_orders = int(input(\"Enter the number of customer orders: \"))\n",
" \n",
" # Listing comprehension to gather orders with input validation\n",
" customer_orders = [input(f\"Enter the name of a product that a customer wants to order: \").strip().lower() \n",
" for _ in range(num_orders)]\n",
" \n",
" # Removing any products that are not in the original product list\n",
" customer_orders = [product for product in customer_orders if product in products]\n",
" return customer_orders"
]
},
{
"cell_type": "markdown",
"id": "c7f87756-a6ac-4e1f-850f-17fb1fb558df",
"metadata": {},
"source": [
"__Step 3:__"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "f1b9270f-c269-416a-ba00-a49c90281268",
"metadata": {},
"outputs": [],
"source": [
"def calculate_total_price(customer_orders):\n",
" # Use set to ensure unique products per purchase (1 per product)\n",
" prices = {product: float(input(f\"Enter the price of {product}: \")) for product in set(customer_orders)}\n",
" total_price = sum(prices[product] for product in set(customer_orders))\n",
" return total_price"
]
},
{
"cell_type": "markdown",
"id": "924d41fe-9a2e-48d7-93e4-81ad0899396c",
"metadata": {},
"source": [
"__Step 4:__"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "d144cae1-ec80-437f-83ff-43774fd6bcd2",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" # Subtracting 1 from inventory for each ordered product\n",
" for product in set(customer_orders):\n",
" if inventory[product] > 0:\n",
" inventory[product] -= 1\n",
" \n",
" # Removing products with zero quantity using dictionary comprehension\n",
" updated_inventory = {product: qty for product, qty in inventory.items() if qty > 0}\n",
" return updated_inventory"
]
},
{
"cell_type": "markdown",
"id": "99047ba4-eb45-44ce-ba2b-ccd862e3e13b",
"metadata": {},
"source": [
"__Step 5:__"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d106862c-0053-4fff-8891-edb7d2055a5b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Updated Inventory:\n",
"t-shirt: 5\n",
"mug: 4\n",
"hat: 2\n",
"book: 2\n"
]
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter the price of keychain : 5\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter the price of keychain : 5\n"
]
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter the price of hat : 10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter the price of hat : 10\n",
"Total Price: 15.0\n",
"\n",
"Order Statistics:\n",
"Total Products Ordered: 2\n",
"Percentage of Unique Products Ordered: 40.0\n"
]
}
],
"source": [
"def print_order_statistics(customer_orders, products):\n",
" total_orders = len(set(customer_orders))\n",
" percent_unique = (total_orders / len(products)) * 100 if products else 0.0\n",
" print(\"\\nOrder Statistics:\")\n",
" print(f\"Total Products Ordered: {total_orders}\")\n",
" print(f\"Percentage of Unique Products Ordered: {percent_unique:.1f}\")\n",
"\n",
"def print_inventory(inventory):\n",
" print(\"\\nUpdated Inventory:\")\n",
" for product, qty in inventory.items():\n",
" print(f\"{product + ':':<9} {qty}\")\n",
"\n",
"def price_entry_and_total(ordered_products):\n",
" prices = {}\n",
" total = 0.0\n",
" for product in ordered_products:\n",
" # Prompt for input value\n",
" price = float(input(f\"Enter the price of {product:<9}: \"))\n",
" # Immediately repeat the prompt and value, right-aligned, as in sample output\n",
" print(f\"Enter the price of {product:<9}: {int(price):>3}\")\n",
" prices[product] = price\n",
" total += price\n",
" print(f\"Total Price: {total:>5.1f}\")\n",
" return total\n",
"\n",
"# Example data to match the screenshot:\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"inventory = {\"t-shirt\": 5, \"mug\": 4, \"hat\": 2, \"book\": 2}\n",
"ordered_products = [\"keychain\", \"hat\"] # The set of products customer ordered\n",
"\n",
"# Best matches attached output by using this calling sequence:\n",
"print_inventory(inventory)\n",
"price_entry_and_total(ordered_products)\n",
"print_order_statistics(ordered_products, products)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "870fe2c2-d5ef-4ed8-b0cd-72ef7922c8a4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "477bd74d-cfde-4410-8866-ca3d8803d99d",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "ironhack",
"language": "python",
"name": "python3"
"name": "ironhack"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -93,7 +301,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.7"
}
},
"nbformat": 4,
Expand Down