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Create a program that calculates and prints the amount of change to be returned to the customer after paying the bill, based on the manager's input in the system. Sample Input: Total Invoice amount(In Dollars): 200 Amount of Tip (In cents): 10 Total Payment received by card: 160 Service Charged on payment made by card: 4% Total Payment received in Cash(In Dollars): 100 Output: Change to be returned to the customer (In Dollars): 53.50 Note: If the return to the customer is negative, then it must print 'outstanding amount and need to be paid by customer:', and the amount need to be paid # Python solution: def calculate_change(invoice_amount, tip_amount, card_payment, service_charge, cash_payment): # Convert service charge percentage to decimal service_charge_decimal = service_charge / 100 # Calculate total payment made by card (including service charge) total_card_payment = card_payment * (1 + service_charge_decimal) # Calculate total payment (card + cash) total_payment = total_card_payment + cash_payment # Calculate the change to be returned change = total_payment - (invoice_amount + tip_amount) return change # Get user input invoice_amount = float(input("Total Invoice amount (In Dollars): ")) tip_amount = int(input("Amount of Tip (In cents): ")) card_payment = float(input("Total Payment received by card: ")) service_charge = float(input("Service Charged on payment made by card (%): ")) cash_payment = float(input("Total Payment received in Cash (In Dollars): ")) # Calculate and print the change change = calculate_change(invoice_amount, tip_amount, card_payment, service_charge, cash_payment) if change >= 0: print(f"Change to be returned to the customer (In Dollars): {change:.2f}") else: print(f"Outstanding amount and need to be paid by customer: {-change:.2f}") This program takes user inputs for the invoice amount, tip amount, card payment, service charge percentage, and cash payment. It then calculates the total payment, including the service charge, and determines the change to be returned. If the change is negative, it prints the outstanding amount that needs to be paid by the customer

In this lesson, we will cover the fundamental building blocks and common patterns. Basic Elements: 1. Literal Characters: • A regular expression can consist of literal characters that match exactly. For example, the regex `python` will match the string "python" in a text. 2. Character Classes: • Character classes are enclosed in square brackets ([]) and allow you to match any one of the characters within the brackets. For instance, `[aeiou]` matches any vowel. 3. Quantifiers: • Quantifiers specify how many times a character or group should appear. The asterisk `*` means zero or more occurrences, the plus `+` means one or more occurrences, and the question mark `? ` means zero or one occurrence. 4. Wildcards: • The dot (`.`) serves as a wildcard, matching any character except a newline. For example, `b.t` would match "bat," "bit," "but," etc. Examples: 1. Literal Characters: • Regex: `cat` • Matches: "cat" in "The cat is black." 2. Character Classes: • Regex: `[aeiou]` • Matches: Any vowel in "apple" or "orange." 3. Quantifiers: • Regex: `lo+l` • Matches: "lool" or "loooool" in "The cat is looking." 4. Wildcards: • Regex: `b.t` • Matches: "bat," "bit," "but," etc., in "The bat is in the box." Exercise: Write Simple Regular Expressions to Match Specific Patterns 1. Match Dates: • Write a regex pattern to match dates in the format "YYYY-MM-DD." Test it against strings like "2022-01-01" and "2023-12-31." 2. Match Email Addresses: • Create a regex pattern to match basic email addresses. Test it against strings like "user@example.com" and "john_doe123@gmail.com." 3. Match Phone Numbers: • Develop a regex pattern to match standard U.S. phone numbers in the format "(XXX) XXX-XXXX." Test it against numbers like "(555) 123-4567." 4. Match Hexadecimal Colors: • Construct a regex pattern to match hexadecimal color codes, such as "#RRGGBB." Test it against strings like "#1a2b3c" and "#ff9900." Remember to use online regex testers or Python's re module to validate and test your patterns against different strings. Practice refining your patterns based on the results and experiment with variations of the exercises.

Regular expressions (regex or regexp) are powerful and concise sequences of characters that define search patterns. They serve as a flexible tool for text processing, allowing you to describe and match complex patterns within strings. Regular expressions are widely used in programming, data validation, text manipulation, and search operations. Key Concepts: 1. Pattern Matching: • At its core, a regular expression is a pattern that describes a set of strings. It allows you to search for, match, and manipulate text based on this pattern. 2. Text Search and Manipulation: • Regular expressions provide a way to search for specific sequences of characters, validate input formats, replace text, and extract information from strings. 3. Concise Syntax: • Regular expressions have a concise syntax that enables you to express complex patterns using a relatively small amount of code. This makes them efficient for tasks involving text processing. 4. Versatility: • Regular expressions are not limited to a specific programming language or tool. They are supported across various programming languages, command-line utilities, and text editors. 5. Common Use Cases: • Regular expressions find applications in tasks such as data validation, parsing logs, searching for patterns in text files, and extracting information from structured data. Benefits: • Efficiency: • Regular expressions allow you to perform powerful text manipulations with minimal code, leading to more efficient and readable solutions. • Flexibility: • They provide a high degree of flexibility, allowing you to create patterns that match specific criteria and adapt to different scenarios. • Pattern Reusability: • Once you've defined a regular expression pattern, you can reuse it across multiple instances, promoting code reusability and maintainability. Applications: 1. Text Search: • Regular expressions excel at searching for specific patterns within text. Whether you're looking for keywords, dates, or other structured data, regex can help you locate and extract relevant information. 2. Data Validation: • Regular expressions are widely used for validating input formats. Whether it's email addresses, phone numbers, or credit card numbers, regex can help ensure that the data meets the required criteria. 3. Search and Replace: • Beyond just searching, regular expressions enable you to replace or modify text based on specific patterns. This is particularly useful when you need to make bulk changes to a document or dataset. 4. Validate with Regular Expressions: • Regular expressions can be employed to validate data against predefined patterns. For example, you can use regex to verify if a given string is a valid email address, adheres to a specific date format, or follows a custom pattern. Regular expressions are a fundamental tool in a programmer's toolkit, offering a concise and powerful way to work with textual data. Understanding how to construct and use regular expressions effectively can significantly enhance your ability to manipulate and analyze text in various programming and scripting contexts.