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207 changes: 204 additions & 3 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -43,13 +43,214 @@
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "c5be3342-a087-4059-9a43-6d4690a4938d",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter the qty of ['t-shirt', 'mug', 'hat', 'book', 'keychain'] 5\n",
"Enter the qty of ['t-shirt', 'mug', 'hat', 'book', 'keychain'] 4\n",
"Enter the qty of ['t-shirt', 'mug', 'hat', 'book', 'keychain'] 2\n",
"Enter the qty of ['t-shirt', 'mug', 'hat', 'book', 'keychain'] 1\n",
"Enter the qty of ['t-shirt', 'mug', 'hat', 'book', 'keychain'] 4\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Initialized Inventory: {'t-shirt': 5, 'mug': 4, 'hat': 2, 'book': 1, 'keychain': 4}\n"
]
}
],
"source": [
"#1\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"\n",
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" qty = int(input(f\"Enter the qty of {products}\"))\n",
" inventory [product] = qty\n",
" return inventory \n",
"inventory = initialize_inventory(products)\n",
"print (\"Initialized Inventory:\", inventory)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "3c80f155-9808-48f1-ae6b-5bb6cbf45c2c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"the customer orders are : {'mug', 'hat', 'book'}\n"
]
}
],
"source": [
"#2\n",
"\n",
"def get_customer_orders():\n",
" customer_orders = set()\n",
"\n",
" while True: # Loop continues until break\n",
" product_name = input(\"Enter a product name you would like to order or type 'stop' to finish: \")\n",
" \n",
" # Check if the user entered 'stop', with lowercasing and stripping for safety\n",
" if product_name == \"stop\":\n",
" break # Exit the loop\n",
"\n",
" customer_orders.add(product_name) # Add the product name to the set\n",
" \n",
" return customer_orders\n",
"print(\"the customer orders are :\",customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "3dd0392f-975c-4a58-9b36-43cf0fbb17e2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Update_inventory is: {'t-shirt': 5, 'mug': 4, 'hat': 2, 'book': 1, 'keychain': 4}\n"
]
}
],
"source": [
"#3\n",
"\n",
"def update_inventory(customer_orders, inventory):\n",
" for product in customer_orders:\n",
" if product in inventory:\n",
" print(f\"{product} is in stock.\")\n",
" else:\n",
" print(f\"Product {product} not found in inventory.\")\n",
" return inventory \n",
"print (\" Update_inventory is:\", inventory)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "6d6a1a4d-da20-4d93-8c9d-907d199178f8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"the statistics are: 3 60.0\n"
]
}
],
"source": [
"#4 #5\n",
"\n",
"def calculate_order_statistics (customer_orders, inventory):\n",
" total_products_ordered = len(customer_orders)\n",
" percentage_of_unique_products_ordered = (total_products_ordered / len(products))*100\n",
"\n",
" return total_products_ordered,percentage_of_unique_products_ordered \n",
"\n",
"customer_orders = {'mug', 'hat', 'book'}\n",
"inventory = {'t-shirt': 5, 'mug': 4, 'hat': 2, 'book': 1, 'keychain': 4}\n",
"\n",
"## Call the function and capture its return values\n",
"total_products_ordered, percentage_of_unique_products_ordered = calculate_order_statistics(customer_orders, inventory) \n",
"\n",
"print(\"the statistics are:\",total_products_ordered, percentage_of_unique_products_ordered)\n",
" \n",
" \n",
" \n",
" \n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "81840795-b741-4f79-a28e-b3b565e809f1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" total products ordered are: 3\n",
"percentage of unique products ordered is: 60.0\n"
]
}
],
"source": [
"#5\n",
"\n",
"def print_order_statistics (order_statistics): # tuple ( total products, % unique value)\n",
" print (order_statistics)\n",
"\n",
"print(f\" total products ordered are: {total_products_ordered}\")\n",
"print(f\"percentage of unique products ordered is: {percentage_of_unique_products_ordered}\")"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "384bbc9e-9114-4114-85b8-48935c072932",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated Inventory:\n",
"- t-shirt: 5\n",
"- mug: 4\n",
"- hat: 2\n",
"- book: 1\n",
"- keychain: 4\n"
]
}
],
"source": [
"#6\n",
"\n",
"def print_updated_inventory(inventory):# dictionaty key,Values\n",
" print(\"Updated Inventory:\")\n",
" for product, quantity in inventory.items():\n",
" print(f\"- {product}: {quantity}\")\n",
" \n",
"inventory = {'t-shirt': 5, 'mug': 4, 'hat': 2, 'book': 1, 'keychain': 4} \n",
"print_updated_inventory(inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "dc01b3c8-eca1-4b97-85b3-c2b851680f68",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python [conda env:base] *",
"language": "python",
"name": "python3"
"name": "conda-base-py"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -61,7 +262,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
Expand Down