diff --git a/.ipynb_checkpoints/lab-python-flow-control-checkpoint.ipynb b/.ipynb_checkpoints/lab-python-flow-control-checkpoint.ipynb new file mode 100644 index 0000000..879fbb3 --- /dev/null +++ b/.ipynb_checkpoints/lab-python-flow-control-checkpoint.ipynb @@ -0,0 +1,262 @@ +{ + "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": 11, + "id": "1abf2b09-6690-45bd-a7af-861b7c37861e", + "metadata": {}, + "outputs": [], + "source": [ + "products = [\"tshirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n", + "inventory = {}" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a387e2f0-b788-47e0-b765-d256b9bcb50f", + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter quantity for tshirt: 22\n", + "Enter quantity for mug: 15\n", + "Enter quantity for hat: 11\n", + "Enter quantity for book: 7\n", + "Enter quantity for keychain: 3\n" + ] + } + ], + "source": [ + "for product in products:\n", + " quantity = input(f\"Enter quantity for {product}: \")\n", + " inventory[product] = int(quantity)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bdea4509-61ab-4ef3-bfba-3cb57ff820b6", + "metadata": {}, + "outputs": [], + "source": [ + "customer_orders = set()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "b7738418-1d35-40bc-abd8-fd58ffea2a99", + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter product to order: hat\n", + "Do you want to add another product? (yes/no): yes\n", + "Enter product to order: book\n", + "Do you want to add another product? (yes/no): yes\n", + "Enter product to order: keychain\n", + "Do you want to add another product? (yes/no): no\n" + ] + } + ], + "source": [ + "another = \"yes\"\n", + "while another == \"yes\":\n", + " order = input(\"Enter product to order: \")\n", + " customer_orders.add(order)\n", + " another = input(\"Do you want to add another product? (yes/no): \").lower()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "061bc2f5-e924-49c1-94bb-e8e7404c3e2a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'book', 'hat', 'keychain'}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_orders" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "4cca7c79-7608-486c-8a11-80787cb54774", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 60.0)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "total_products_ordered = len(customer_orders)\n", + "percentage_ordered = (len(customer_orders) / len(products)) * 100\n", + "order_status = (total_products_ordered, percentage_ordered)\n", + "order_status" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d327f508-9749-44ea-b792-3b02fbc9e31b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Order Statistics:\n", + "Total Products Ordered: 3\n", + "Percentage of Products Ordered: 60.0%\n" + ] + } + ], + "source": [ + "print(\"Order Statistics:\")\n", + "print(f\"Total Products Ordered: {total_products_ordered}\")\n", + "print(f\"Percentage of Products Ordered: {percentage_ordered}%\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "eab5aa66-9251-4c3e-aa9b-8670ecb14cdb", + "metadata": {}, + "outputs": [], + "source": [ + "for product in customer_orders:\n", + " inventory[product] -= 1" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "53c76ab2-ca9e-41be-a583-a1245fed1a61", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'tshirt': 22, 'mug': 15, 'hat': 10, 'book': 6, 'keychain': 2}\n" + ] + } + ], + "source": [ + "print(inventory)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "79a7d331-63f8-4338-ae9f-29559175d3e9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tshirt: 22\n", + "mug: 15\n", + "hat: 10\n", + "book: 6\n", + "keychain: 2\n" + ] + } + ], + "source": [ + "for product in inventory:\n", + " print(f\"{product}: {inventory[product]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4516bdb6-af15-4145-bdf7-f6e91945896b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/lab-python-flow-control.ipynb b/lab-python-flow-control.ipynb index f4c7391..879fbb3 100644 --- a/lab-python-flow-control.ipynb +++ b/lab-python-flow-control.ipynb @@ -37,13 +37,212 @@ "\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": 11, + "id": "1abf2b09-6690-45bd-a7af-861b7c37861e", + "metadata": {}, + "outputs": [], + "source": [ + "products = [\"tshirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n", + "inventory = {}" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a387e2f0-b788-47e0-b765-d256b9bcb50f", + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter quantity for tshirt: 22\n", + "Enter quantity for mug: 15\n", + "Enter quantity for hat: 11\n", + "Enter quantity for book: 7\n", + "Enter quantity for keychain: 3\n" + ] + } + ], + "source": [ + "for product in products:\n", + " quantity = input(f\"Enter quantity for {product}: \")\n", + " inventory[product] = int(quantity)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bdea4509-61ab-4ef3-bfba-3cb57ff820b6", + "metadata": {}, + "outputs": [], + "source": [ + "customer_orders = set()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "b7738418-1d35-40bc-abd8-fd58ffea2a99", + "metadata": {}, + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Enter product to order: hat\n", + "Do you want to add another product? (yes/no): yes\n", + "Enter product to order: book\n", + "Do you want to add another product? (yes/no): yes\n", + "Enter product to order: keychain\n", + "Do you want to add another product? (yes/no): no\n" + ] + } + ], + "source": [ + "another = \"yes\"\n", + "while another == \"yes\":\n", + " order = input(\"Enter product to order: \")\n", + " customer_orders.add(order)\n", + " another = input(\"Do you want to add another product? (yes/no): \").lower()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "061bc2f5-e924-49c1-94bb-e8e7404c3e2a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'book', 'hat', 'keychain'}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "customer_orders" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "4cca7c79-7608-486c-8a11-80787cb54774", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 60.0)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "total_products_ordered = len(customer_orders)\n", + "percentage_ordered = (len(customer_orders) / len(products)) * 100\n", + "order_status = (total_products_ordered, percentage_ordered)\n", + "order_status" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d327f508-9749-44ea-b792-3b02fbc9e31b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Order Statistics:\n", + "Total Products Ordered: 3\n", + "Percentage of Products Ordered: 60.0%\n" + ] + } + ], + "source": [ + "print(\"Order Statistics:\")\n", + "print(f\"Total Products Ordered: {total_products_ordered}\")\n", + "print(f\"Percentage of Products Ordered: {percentage_ordered}%\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "eab5aa66-9251-4c3e-aa9b-8670ecb14cdb", + "metadata": {}, + "outputs": [], + "source": [ + "for product in customer_orders:\n", + " inventory[product] -= 1" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "53c76ab2-ca9e-41be-a583-a1245fed1a61", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'tshirt': 22, 'mug': 15, 'hat': 10, 'book': 6, 'keychain': 2}\n" + ] + } + ], + "source": [ + "print(inventory)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "79a7d331-63f8-4338-ae9f-29559175d3e9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tshirt: 22\n", + "mug: 15\n", + "hat: 10\n", + "book: 6\n", + "keychain: 2\n" + ] + } + ], + "source": [ + "for product in inventory:\n", + " print(f\"{product}: {inventory[product]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4516bdb6-af15-4145-bdf7-f6e91945896b", + "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": { @@ -55,7 +254,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.13.9" } }, "nbformat": 4,