Summary  
This chapter explains how to perform floor division (//), modulus (%) for remainders, and exponentiation (**) in Python, alongside the distinction between these operators and default division.

General domain of usage  
Financial calculations

Python provides several additional math operations.

# Default division
print(18 / 4)

# Floor division
print(18 // 4)

# Remainder of the division
print(18 % 4)

# Raising to the power of 4
print(18 ** 4)

### Why Are These Operations Helpful?  

Imagine you have **$50** and want to buy as many cookie packs as possible, with each pack costing **$6**. To determine how many packs you can buy and how much money will remain, you can use these operations:  

- `50 // 6` gives `8`, meaning you can buy **8 packs**.  
- `50 % 6` results in `2`, meaning you’ll have **$2 left** after the purchase.  

import unittest
import importlib
import io
import re
import sys

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_floor_division_present(self):
        with open('user_code.py', 'r') as file:
            user_code_source = file.read()

        floor_div_check = re.search(r'234\s*//\s*32', user_code_source)

        _dynamic_test(
            self,
            floor_div_check is not None,
            "The floor division operation `234 // 32` is present.",
            "Expected the floor division operation `234 // 32` to be present."
        )

    def test_modulus_operation_present(self):
        with open('user_code.py', 'r') as file:
            user_code_source = file.read()

        modulus_check = re.search(r'356\s*%\s*17', user_code_source)

        _dynamic_test(
            self,
            modulus_check is not None,
            "The modulus operation `356 % 17` is present.",
            "Expected the modulus operation `356 % 17` to be present."
        )

    def test_floor_division_output_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")

        _dynamic_test(
            self,
            output[0] == "7",
            "The correct result `7` is printed for floor division.",
            f"Expected `7` to be printed, but got `{output[0]}`."
        )

    def test_modulus_output_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")

        _dynamic_test(
            self,
            output[1] == "16",
            "The correct result `16` is printed for modulus.",
            f"Expected `16` to be printed, but got `{output[1]}`."
        )

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.

Handle More Challenging Math in Python

Why Are These Operations Helpful?

解答