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Lab python functions completed #550

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326 changes: 323 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 +43,333 @@
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "1b3d2774-c203-4e7d-b642-bba2d9175291",
"metadata": {},
"outputs": [],
"source": [
"#1 Define a function named initialize_inventory that takes products as a parameter. \n",
"# Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
"\n",
"def initialize_inventory(products):\n",
" inventory = {}\n",
" for product in products:\n",
" quantity = int(input(f\"Please enter the quantity of {product}\"))\n",
" inventory[product] = quantity\n",
" return inventory\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "84621429-0779-45b5-b604-141558348dfa",
"metadata": {},
"outputs": [],
"source": [
"#2 Define a function named get_customer_orders that takes no parameters. \n",
"# Inside the function, implement the code for prompting the user to enter the product names using a loop. \n",
"# The function should return the customer_orders set.\n",
"\n",
"def get_customer_orders():\n",
" customer_orders = set()\n",
" max_products = len(products)\n",
" count = 0\n",
" \n",
" # Ask the user to input the name of three products that a customer wants to order (from those in the products list, meaning three products out of \"t-shirt\", \"mug\", \"hat\", \"book\" or \"keychain\". Add each product name to the customer_orders set.\n",
" while count < max_products: # adding this because it does not make sense to keep asking the customer to add more than the available products in the inventory, hence after 5 input, the loop should terminate\n",
" product_name = input(\"Please enter the name of a product you wish to order: \")\n",
" if product_name in products:\n",
" customer_orders.add(product_name)\n",
" count += 1\n",
" decision = input(\"Do you want to add another product to your order? yes or no: \")\n",
" while decision != \"yes\" and decision != \"no\":\n",
" print(\"Answer not accepted, question can only be answered with yes or no\")\n",
" decision = input(\"Do you want to add another product to your order? yes or no: \")\n",
" if decision != \"yes\":\n",
" break\n",
" else:\n",
" print(\"Please enter a product that is available in our shop\")\n",
"\n",
" return(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "f29c1b9c-4b3d-4a57-9738-e0642ac29be3",
"metadata": {},
"outputs": [],
"source": [
"#3 Define a function named update_inventory that takes customer_orders and inventory as parameters. \n",
"# Inside the function, implement the code for updating the inventory dictionary based on the customer orders.\n",
"\n",
"def update_inventory(customer_orders, inventory):\n",
" for product in inventory:\n",
" if product in customer_orders:\n",
" inventory[product] -= 1\n",
" return inventory\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 114,
"id": "3b9662d0-763f-45f4-bc5b-b84c40ee93e2",
"metadata": {},
"outputs": [],
"source": [
"#4 Define a function named calculate_order_statistics that takes customer_orders and products as parameters. \n",
"# Inside the function, implement the code for calculating the order statistics, \n",
"# (total products ordered, and percentage of unique products ordered). The function should return these values.\n",
"\n",
"def calculate_order_statistics(customer_orders, products):\n",
" total_of_products_ordered = 0\n",
" for product in products:\n",
" if product in customer_orders: \n",
" total_of_products_ordered += inventory[product]\n",
"\n",
" # Percentage of Products Ordered: The percentage of products ordered compared to the total available products.\n",
" total_inventory = sum(inventory.values())\n",
" \n",
" percentage_of_products_ordered = (total_of_products_ordered / total_inventory)*100\n",
" return total_of_products_ordered, percentage_of_products_ordered\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 124,
"id": "f5bee4a9-94d1-4e2d-a2ec-c020a126240e",
"metadata": {},
"outputs": [],
"source": [
"#5 Define a function named print_order_statistics that takes order_statistics as a parameter. \n",
"# Inside the function, implement the code for printing the order statistics.\n",
"\n",
"def print_order_statistics(order_statistics):\n",
" total_of_products_ordered, percentage_of_products_ordered = order_statistics\n",
" print(total_of_products_ordered)\n",
" print(f\"{percentage_of_products_ordered:.1f}%\")\n"
]
},
{
"cell_type": "code",
"execution_count": 125,
"id": "eee7b42f-4604-4e32-87f1-1949e97eb08f",
"metadata": {},
"outputs": [],
"source": [
"#6 Define a function named print_updated_inventory that takes inventory as a parameter. \n",
"# Inside the function, implement the code for printing the updated inventory.\n",
"\n",
"def print_updated_inventory(inventory):\n",
" print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 126,
"id": "18572ff7-b98b-4dd9-a406-e90e962cfbbc",
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 80,
"id": "e308eb5c-7bc3-466c-8f04-9f544a6eec04",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter the quantity of t-shirt 8\n",
"Please enter the quantity of mug 7\n",
"Please enter the quantity of hat 6\n",
"Please enter the quantity of book 5\n",
"Please enter the quantity of keychain 4\n"
]
}
],
"source": [
"# calling the function initialize_inventory to define the inventory\n",
"inventory = initialize_inventory(products)"
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "f0d0d480-e240-4589-bc57-3b30d26b3bdf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 8, 'mug': 7, 'hat': 6, 'book': 5, 'keychain': 4}"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# quick check if inventory has filled in correctly\n",
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "bbb15bbc-8a56-4b53-b183-e9c250d6d947",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please enter the name of a product you wish to order: mug\n",
"Do you want to add another product to your order? yes or no: book\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Answer not accepted, question can only be answered with yes or no\n"
]
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Do you want to add another product to your order? yes or no: yes\n",
"Please enter the name of a product you wish to order: hat\n",
"Do you want to add another product to your order? yes or no: yes\n",
"Please enter the name of a product you wish to order: book\n",
"Do you want to add another product to your order? yes or no: no\n"
]
}
],
"source": [
"customer_orders = get_customer_orders()"
]
},
{
"cell_type": "code",
"execution_count": 85,
"id": "c40359cb-e7d5-461d-9fc5-3e254fe45c3b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'book', 'hat', 'mug'}"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_orders"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "e07ec939-66f3-4a7f-bacb-552bf2fc5b8f",
"metadata": {},
"outputs": [],
"source": [
"inventory = update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "d0141be1-329d-46c8-9fa5-e01bee0e94f8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 8, 'mug': 6, 'hat': 5, 'book': 4, 'keychain': 4}"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# quick check if inventory has been correctly updated\n",
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 122,
"id": "492871f1-d50c-4b1e-9d90-d590f165dfdc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(15, 55.55555555555556)\n"
]
}
],
"source": [
"order_statistics = calculate_order_statistics(customer_orders, products)\n",
"stats = order_statistics\n",
"print(stats)"
]
},
{
"cell_type": "code",
"execution_count": 127,
"id": "68a899bb-5b8c-4ea0-a20f-673308a95913",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"15\n",
"55.6%\n",
"None\n"
]
}
],
"source": [
"cart_details = print_order_statistics(stats)\n",
"print(cart_details)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "78c780aa-5bd7-41b8-86a0-2ee01e1bceeb",
"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 +381,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.5"
}
},
"nbformat": 4,
Expand Down