Summary  
This chapter covers how to define integer literals correctly and use underscores as digit separators to improve readability.

General domain of usage  
Numeric computations

You might be accustomed to specifying numbers in ways such as:  
- `1,000,000` (with commas);  
- `1 000 000` (with spaces).
  
However, Python will not understand this. 

These formats are understandable for a person but not for a computer, so the right way is `1000000` without commas or spaces.

```python
var = 1000000
```

If you want to use separators for better readability, Python allows the following syntax:
```python
var = 1_000_000
```

import unittest
import importlib

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 setUp(self):
        # Import the user's code as a module
        self.module = importlib.import_module('user_code')

    def test_q1_budget_is_declared(self):
        _dynamic_test(
            self,
            hasattr(self.module, 'q1_budget'),
            "The `q1_budget` variable is declared.",
            "Expected `q1_budget` variable to be declared."
        )

    def test_q2_budget_is_declared(self):
        _dynamic_test(
            self,
            hasattr(self.module, 'q2_budget'),
            "The `q2_budget` variable is declared.",
            "Expected `q2_budget` variable to be declared."
        )

    def test_q1_budget_is_of_type_integer(self):
        _dynamic_test(
            self,
            isinstance(self.module.q1_budget, int),
            "The `q1_budget` is of type `int`.",
            "Expected `q1_budget` to be of type `int`."
        )

    def test_q2_budget_is_of_type_integer(self):
        _dynamic_test(
            self,
            isinstance(self.module.q2_budget, int),
            "The `q2_budget` is of type `int`.",
            "Expected `q2_budget` to be of type `int`."
        )

    def test_q1_budget_has_correct_value(self):
        expected_value = 750000
        _dynamic_test(
            self,
            self.module.q1_budget == expected_value,
            f"The `q1_budget` is `{expected_value}`.",
            f"Expected `q1_budget` to be `{expected_value}`, but got `{self.module.q1_budget}`."
        )

    def test_q2_budget_has_correct_value(self):
        expected_value = 1_200_500
        _dynamic_test(
            self,
            self.module.q2_budget == expected_value,
            f"The `q2_budget` is `{expected_value}`.",
            f"Expected `q2_budget` to be `{expected_value}`, but got `{self.module.q2_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.

Mastering Integer Numbers in Python

Solution

Awesome!

Mastering Integer Numbers in Python

Solution

Awesome!