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Completed lab - python flow controls #696

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236 changes: 236 additions & 0 deletions .ipynb_checkpoints/lab-python-flow-control-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "d3bfc191-8885-42ee-b0a0-bbab867c6f9f",
"metadata": {
"tags": []
},
"source": [
"# Lab | Flow Control"
]
},
{
"cell_type": "markdown",
"id": "3851fcd1-cf98-4653-9c89-e003b7ec9400",
"metadata": {},
"source": [
"## Exercise: Managing Customer Orders Optimized\n",
"\n",
"In the last lab, you were starting an online store that sells various products. To ensure smooth operations, you developed a program that manages customer orders and inventory.\n",
"\n",
"You did so without using flow control. Let's go a step further and improve this code.\n",
"\n",
"Follow the steps below to complete the exercise:\n",
"\n",
"1. Look at your code from the lab data structures, and improve repeated code with loops.\n",
"\n",
"2. Instead of asking the user to input the name of three products that a customer wants to order, do the following:\n",
" \n",
" a. Prompt the user to enter the name of a product that a customer wants to order.\n",
" \n",
" b. Add the product name to the \"customer_orders\" set.\n",
" \n",
" c. Ask the user if they want to add another product (yes/no).\n",
" \n",
" d. Continue the loop until the user does not want to add another product.\n",
"\n",
"3. Instead of updating the inventory by subtracting 1 from the quantity of each product, only do it for the products that were ordered (those in \"customer_orders\")."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "2b59555c-b038-4877-b244-90ea7376b51d",
"metadata": {},
"outputs": [],
"source": [
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "307c168c-979b-458b-8dae-e7ce6795f910",
"metadata": {},
"outputs": [],
"source": [
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "7d287ae8-a497-4821-a6bd-55cd93c5f9f4",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please add the quantity for t-shirt 5\n",
"Please add the quantity for mug 9\n",
"Please add the quantity for hat 7\n",
"Please add the quantity for book 4\n",
"Please add the quantity for keychain 6\n"
]
}
],
"source": [
"for product in products:\n",
" quantity = int(input(\"Please add the quantity for \" + product))\n",
" inventory[product] = quantity"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "205ef1fe-2388-46a5-bf40-a598c9ab9436",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 5, 'mug': 9, 'hat': 7, 'book': 4, 'keychain': 6}\n"
]
}
],
"source": [
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "0c66741a-f4a9-4dea-9055-eebccb5a1ca6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Available products: ['t-shirt', 'mug', 'hat', 'book', 'keychain']\n"
]
},
{
"name": "stdin",
"output_type": "stream",
"text": [
"Please add the product you would like to order: book\n",
"Would you like to continue ordering? Please answer with yes or no. yes\n",
"Please add the product you would like to order: mug\n",
"Would you like to continue ordering? Please answer with yes or no. yes\n",
"Please add the product you would like to order: hat\n",
"Would you like to continue ordering? Please answer with yes or no. no\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Thank you for your order.\n"
]
}
],
"source": [
"print (\"Available products: \", products)\n",
"customer_orders = set()\n",
"order_again = \"yes\" \n",
"while order_again == \"yes\": \n",
" product = input(\"Please add the product you would like to order:\")\n",
" customer_orders.add(product)\n",
" order_again = input(\"Would you like to continue ordering? Please answer with yes or no.\").lower().strip()\n",
"\n",
"print (\"Thank you for your order.\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "2960eba1-2565-40eb-9c2b-2ab307656430",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 5, 'mug': 9, 'hat': 7, 'book': 4, 'keychain': 6}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5deaa9d9-4851-4ea2-9cb5-301d037acac4",
"metadata": {},
"outputs": [],
"source": [
"for product in customer_orders:\n",
" inventory[product] -= 1"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "028c896f-d618-4a5c-b291-eb0abeecdbab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 5, 'mug': 8, 'hat': 6, 'book': 3, 'keychain': 6}\n"
]
}
],
"source": [
"print (inventory)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5fd8d8e5-afb8-4a13-9545-25d16a599850",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "92108459-e3ca-4b11-947a-94bdb77e413d",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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