diff --git a/lab-python-list-comprehension (2).ipynb b/lab-python-list-comprehension (2).ipynb new file mode 100644 index 0000000..ad8c34e --- /dev/null +++ b/lab-python-list-comprehension (2).ipynb @@ -0,0 +1,182 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "25d7736c-ba17-4aff-b6bb-66eba20fbf4e", + "metadata": {}, + "source": [ + "# Lab | List, Dict and Set Comprehension" + ] + }, + { + "cell_type": "markdown", + "id": "7dd3cbde-675a-4b81-92c3-f728846dbe06", + "metadata": {}, + "source": [ + "## Exercise: Managing Customer Orders Optimized with Comprehension" + ] + }, + { + "cell_type": "markdown", + "id": "5d500160-2fb7-4777-b5e4-09d45ebaf328", + "metadata": {}, + "source": [ + "In the previous exercise, you developed a program to manage customer orders and inventory. Now, let's take it a step further and incorporate comprehension into your code.\n", + "\n", + "Follow the steps below to complete the exercise:\n", + "\n", + "1. Review your code from the previous exercise and identify areas where you can apply comprehension to simplify and streamline your code. \n", + "\n", + " - *Hint: Apply it to initialize inventory, updating the inventory and printing the updated inventory.*\n", + " \n", + " - For example, in initializing the inventory, we could have:\n", + " \n", + " ```python\n", + " def initialize_inventory(products):\n", + " inventory = {product: int(input(f\"Enter the quantity of {product}s available: \")) for product in products}\n", + " return inventory\n", + "\n", + " ```\n", + "
\n", + " \n", + " \n", + "2. Modify the function get_customer_orders so it prompts the user to enter the number of customer orders and gathers the product names using a loop and user input. Use comprehension.\n", + "\n", + "3. Add a new function to calculate the total price of the customer order. For each product in customer_orders, prompt the user to enter the price of that product. Use comprehension to calculate the total price. Note: assume that the user can only have 1 unit of each product.\n", + "\n", + "4. Modify the update_inventory function to remove the product from the inventory if its quantity becomes zero after fulfilling the customer orders. Use comprehension to filter out the products with a quantity of zero from the inventory.\n", + "\n", + "5. Print the total price of the customer order.\n", + "\n", + "Your code should produce output similar to the following:\n", + "\n", + "```python\n", + "Enter the quantity of t-shirts available: 5\n", + "Enter the quantity of mugs available: 4\n", + "Enter the quantity of hats available: 3\n", + "Enter the quantity of books available: 2\n", + "Enter the quantity of keychains available: 1\n", + "Enter the number of customer orders: 2\n", + "Enter the name of a product that a customer wants to order: hat\n", + "Enter the name of a product that a customer wants to order: keychain\n", + "\n", + "Order Statistics:\n", + "Total Products Ordered: 2\n", + "Percentage of Unique Products Ordered: 40.0\n", + "\n", + "Updated Inventory:\n", + "t-shirt: 5\n", + "mug: 4\n", + "hat: 2\n", + "book: 2\n", + "Enter the price of keychain: 5\n", + "Enter the price of hat: 10\n", + "Total Price: 15.0\n", + "\n", + "```\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b6636b3e", + "metadata": {}, + "outputs": [], + "source": [ + "products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1327d4f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Customer orders: {'keychain', 'hat'}\n", + "t-shirt: 5\n", + "mug: 4\n", + "hat: 2\n", + "book: 2\n", + "keychain: 0\n", + "Order statistics: (2, 40.0)\n", + "Total products ordered: 2\n", + "Percentage of unique products ordered: 40.00%\n" + ] + } + ], + "source": [ + "#1. Review your code from the previous exercise and identify areas where you can apply comprehension to simplify and streamline your code. \n", + "#Apply it to initialize inventory, updating the inventory and printing the updated inventory. For example, in initializing the inventory, we could have:\n", + "def initialize_inventory(products):\n", + " inventory = {product: int(input(f\"Enter the quantity of {product}s available: \")) for product in products}\n", + " return inventory\n", + "inventory = initialize_inventory(products)\n", + "\n", + "#Updating the inventory could be:\n", + "\n", + "customer_orders = set()\n", + "while True:\n", + " product_name = input(\"Enter the name of a product that a customer wants to order: \")\n", + " customer_orders.add(product_name)\n", + " if len(customer_orders) == 2:\n", + " break\n", + "print(\"Customer orders:\", customer_orders)\n", + "\n", + "def update_inventory(customer_orders, inventory):\n", + " for product in customer_orders:\n", + " inventory[product] -= 1\n", + " return inventory\n", + "inventory = update_inventory(customer_orders, inventory)\n", + "\n", + "\n", + "def print_updated_inventory(inventory):\n", + " for product, quantity in inventory.items():\n", + " print(f\"{product}: {quantity}\")\n", + " return\n", + "print_updated_inventory(inventory)\n", + "\n", + "#Calculating order statistics could be:\n", + "def calculate_order_statistics(customer_orders, products):\n", + " total_products_ordered = len(customer_orders)\n", + " percentage_unique_ordered = (total_products_ordered / len(products)) * 100\n", + " return total_products_ordered, percentage_unique_ordered\n", + "order_statistics = calculate_order_statistics(customer_orders, products)\n", + "print(\"Order statistics:\", order_statistics)\n", + "\n", + "#Printing order statistics could be:\n", + "def print_order_statistics(order_statistics):\n", + " total_products_ordered, percentage_unique_ordered = order_statistics\n", + " print(f\"Total products ordered: {total_products_ordered}\")\n", + " print(f\"Percentage of unique products ordered: {percentage_unique_ordered:.2f}%\")\n", + " return\n", + "print_order_statistics(order_statistics)\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.13.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}