Understanding the difference between **mutable** and **immutable** data types is crucial. Mutable data types can be changed after their creation, while immutable data types cannot be modified once created.

**Immutable** data types cannot be changed once they're created. In contrast, **mutable** data types can be altered after their creation.

To conclude, `int` and `float` are examples of immutable data types in Python. Reassigning a variable of these types does not alter their immutability.

# Define a variable `var1` with an initial value
var1 = 40
print(var1)  # output: 40

# Change the value of `var1`
var1 = 50
print(var1)  # output: 50

import unittest
import re
from io import StringIO
from unittest.mock import patch
import importlib

# Helper function to dynamically generate test names and assertions
def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message  # Rename the test for better readability
        test_case.assertTrue(True, success_message)  # Pass the test with a success message
    else:
        test_case._testMethodName = failure_message  # Rename the test with a failure description
        test_case.fail(failure_message)  # Fail the test with a failure message

class TestUserCode(unittest.TestCase):

    def setUp(self):
        # Reload the module to make sure we are testing the latest code
        self.module = importlib.import_module('user_code')
        importlib.reload(self.module)

    # Test if `project_budget` is declared
    def test_project_budget_is_declared(self):
        _dynamic_test(
            self,
            hasattr(self.module, 'project_budget'),
            "The `project_budget` variable is declared.",
            "Expected `project_budget` to be declared."
        )

    # Test if `project_budget` is equal to 150
    def test_project_budget_value_is_150(self):
        _dynamic_test(
            self,
            hasattr(self.module, 'project_budget') and self.module.project_budget == 150,
            "The `project_budget` is equal to 150.",
            f"Expected `project_budget` to be 150, but got `{getattr(self.module, 'project_budget', 'undefined')}`."
        )

    # Test if `print()` is used to output `project_budget` correctly
    def test_print_is_used_for_project_budget(self):
        with open('user_code.py', 'r') as file:
            user_code_source = file.read()
        _dynamic_test(
            self,
            re.search(r'print\s*\(\s*project_budget\s*\)', user_code_source),
            "The `print()` function is used to output `project_budget`.",
            "Expected `print()` to be used for `project_budget`."
        )

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

test_main.py

This course is going to help you dive deeper into data types and try to work with them. Here you will learn basic operations and all ins and outs of numbers, boolean data type, and strings. This course consists of a lot of practical tasks after which you will become a skillful programmer.

Numeric data types are crucial in Python, so it is important to start with them. Here you will work with simple math operations and find out the purposes of learning different types of numerical data.

Mastering boolean data types and logical operations in Python. You'll learn how to work with True and False, apply logical operators like and, or, and not, and understand how operator precedence works in complex expressions.

Strings are an essential part of Python programming, allowing you to work with text data. In this section, you'll learn how to manipulate strings, extract characters, slice words, and search for specific phrases.

This chapter consists of practical tasks that combine all the examined topics together with a bit of theory.

Mutable or Immutable?

Lösung

Mutable or Immutable?

Lösung