Summary  
This chapter shows how to integrate variables, control flow statements, functions and data structures into unified code that performs a complete task.

General domain of usage  
automation tasks

import unittest
import importlib
import io
import sys
import re

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

class TestUserCode(unittest.TestCase):

    def test_receipt_title_and_divider(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        
        pattern = r"^\s*Shopping Receipt\s*$"
        divider_pattern = r"^\s*-{2,}\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[0]) and re.match(divider_pattern, output[1]),
            "The receipt title and divider line are printed correctly.",
            "Expected receipt title and divider to be printed correctly."
        )

    def test_first_item_price_correct(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        expected_price = 162 * 1.2
        pattern = rf"^\s*Item\s*1:\s*\$\s*{expected_price}\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[2]),
            f"The first item price is calculated correctly as ${expected_price}.",
            f"Expected first item price to be ${expected_price}, but got `{output[2]}`."
        )

    def test_second_item_price_correct(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        expected_price = 25 - 3
        pattern = rf"^\s*Item\s*2:\s*\$\s*{expected_price}\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[3]),
            f"The second item price is calculated correctly as ${expected_price}.",
            f"Expected second item price to be ${expected_price}, but got `{output[3]}`."
        )

    def test_subtotal_price_correct(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        expected_subtotal = (162 * 1.2) + (25 - 3)
        pattern = rf"^\s*Subtotal:\s*\$\s*{expected_subtotal}\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[5]),
            f"The subtotal price is calculated correctly as ${expected_subtotal}.",
            f"Expected subtotal price to be ${expected_subtotal}, but got `{output[5]}`."
        )

    def test_tax_price_correct(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        expected_tax = ((162 * 1.2) + (25 - 3)) * 0.1
        pattern = rf"^\s*Tax\s*$\s*8\s*%\s*$:\s*\$\s*{expected_tax}\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[6]),
            f"The tax is calculated correctly as ${expected_tax}.",
            f"Expected tax price to be ${expected_tax}, but got `{output[6]}`."
        )

    def test_receipt_footer_correct(self):
        import user_code
        captured_output = io.StringIO()
        sys.stdout = captured_output
        importlib.reload(user_code)
        sys.stdout = sys.__stdout__

        output = captured_output.getvalue().strip().split("\\n")
        
        pattern = r"^\s*Thank you for shopping!\s*$"

        _dynamic_test(
            self,
            re.match(pattern, output[8]),
            "The receipt footer is printed correctly.",
            "Expected receipt footer to be printed correctly."
        )

if __name__ == '__main__':
    unittest.main()


test_main.py

Python is an interpreted high-level general-purpose programming language. Unlike HTML, CSS, and JavaScript, which are primarily used for web development, Python is versatile and can be used in various fields, including software development, data science, and back-end development. In this course, you'll explore the core aspects of Python, and by the end, you'll be crafting your own functions!

Dive into the basics of Python, explore your workspace, and perform simple math operations. Learn how to write readable code using comments and handle both basic and advanced mathematical expressions while displaying your results.

Learn how to store and manage data in Python by working with numbers, text, and variables. Understand how to assign values, follow naming conventions, and explore different data types. Gain hands-on experience with string operations, indexing, slicing, and memory recall techniques to efficiently manipulate text in Python.

Learn how to use comparison and logical operators, work with conditional expressions, and apply membership and type comparisons. Build a strong foundation in writing programs that respond dynamically to different conditions using if/else and if/elif/else structures.

Expand your understanding of data types by learning how to group multiple attributes within a single variable. Explore lists, tuples, and dictionaries to efficiently store and manage structured data, along with essential methods for manipulation and retrieval.

Master the art of writing loops in Python—essential constructs for iterating over lists, tuples, dictionaries, and other data structures. Learn to use while and for loops effectively, explore the range function, and work with nested loops to handle complex iteration patterns.

Explore essential built-in functions in Python and take the next step by creating your own. Learn how to define functions, use conditional logic, modify existing functions, and work with lambda expressions to write efficient, reusable code.

Bringing Python Fundamentals Together

Oplossing

Bringing Python Fundamentals Together

Oplossing