Summary  
This chapter covers Python’s string slicing syntax, showing how to extract substrings by specifying start, end, and step indices and how to use open-ended slicing patterns. It explains both fixed-range slicing and omitting components for flexible extraction.

General domain of usage  
Text processing

import unittest

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):
    # Expected values based on the given starter data
    EXP_NAME_CLEAN = "Ada Lovelace"
    EXP_HAS_QUICK = True
    EXP_INSIDE_PARENS = "quick"
    EXP_O_COUNT = 4
    EXP_DOMAIN = "example.com"
    EXP_SEP = " | "
    EXP_REPORT = f"{EXP_NAME_CLEAN}{EXP_SEP}{EXP_DOMAIN}{EXP_SEP}{EXP_O_COUNT}"

    def test_name_clean_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "name_clean"),
            "The `name_clean` variable is declared.",
            "Expected `name_clean` to be declared."
        )

    def test_name_clean_value(self):
        import user_code
        try:
            actual = user_code.name_clean
            condition = actual == self.EXP_NAME_CLEAN
            failure = f"Expected `name_clean` to be `{self.EXP_NAME_CLEAN}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `name_clean` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `name_clean` value is `{self.EXP_NAME_CLEAN}`.",
            failure
        )

    def test_has_quick_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "has_quick"),
            "The `has_quick` variable is declared.",
            "Expected `has_quick` to be declared."
        )

    def test_has_quick_value(self):
        import user_code
        try:
            actual = user_code.has_quick
            condition = actual == self.EXP_HAS_QUICK
            failure = f"Expected `has_quick` to be `{self.EXP_HAS_QUICK}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `has_quick` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `has_quick` value is `{self.EXP_HAS_QUICK}`.",
            failure
        )

    def test_inside_parens_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "inside_parens"),
            "The `inside_parens` variable is declared.",
            "Expected `inside_parens` to be declared."
        )

    def test_inside_parens_value(self):
        import user_code
        try:
            actual = user_code.inside_parens
            condition = actual == self.EXP_INSIDE_PARENS
            failure = f"Expected `inside_parens` to be `{self.EXP_INSIDE_PARENS}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `inside_parens` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `inside_parens` value is `{self.EXP_INSIDE_PARENS}`.",
            failure
        )

    def test_o_count_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "o_count"),
            "The `o_count` variable is declared.",
            "Expected `o_count` to be declared."
        )

    def test_o_count_value(self):
        import user_code
        try:
            actual = user_code.o_count
            condition = actual == self.EXP_O_COUNT
            failure = f"Expected `o_count` to be `{self.EXP_O_COUNT}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `o_count` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `o_count` value is `{self.EXP_O_COUNT}`.",
            failure
        )

    def test_domain_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "domain"),
            "The `domain` variable is declared.",
            "Expected `domain` to be declared."
        )

    def test_domain_value(self):
        import user_code
        try:
            actual = user_code.domain
            condition = actual == self.EXP_DOMAIN
            failure = f"Expected `domain` to be `{self.EXP_DOMAIN}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `domain` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `domain` value is `{self.EXP_DOMAIN}`.",
            failure
        )

    def test_report_is_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, "report"),
            "The `report` variable is declared.",
            "Expected `report` to be declared."
        )

    def test_report_value(self):
        import user_code
        try:
            actual = user_code.report
            condition = actual == self.EXP_REPORT
            failure = f"Expected `report` to be `{self.EXP_REPORT}`, but got `{actual}`."
        except AttributeError:
            condition = False
            failure = "Expected `report` to be declared."
        _dynamic_test(
            self,
            condition,
            f"The `report` value is `{self.EXP_REPORT}`.",
            failure
        )


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


test_main.py

Gain a solid understanding of Python's core data types and learn how to work with them effectively. Explore numbers, booleans, and strings through hands-on exercises and practical examples. Build confidence in performing basic operations and develop the foundational skills needed to write clean and efficient Python code.

Discover the essentials of numerical data types in Python and learn how to work with integers and floating-point numbers. Master basic arithmetic operations, explore the concept of immutability, and get hands-on experience using Python's built-in functions and tools to handle numbers efficiently in real-world scenarios.

Gain a clear understanding of the Boolean data type, a specialized subtype of numeric data that represents truth values. Although it may seem challenging at first, mastering Booleans is essential for writing logical and efficient programs. This section will help you confidently apply Boolean logic to real-world programming scenarios.

Strings allow you to work with text in Python, from displaying messages to processing user input. You'll explore how to create, modify, and manipulate strings effectively. Understanding strings is essential for writing interactive programs and communicating information clearly through your code.

Learn how to handle data types effectively to ensure accuracy and consistency in your programs. Convert values to the appropriate type, clean text before comparison, and separate numeric operations from text formatting. You'll also discover how to manage missing data deliberately and handle human-readable text differently from raw input, achieving reliable, consistent, and easy-to-read results.

Challenge: Slicing and Search Drills

Solution

Challenge: Slicing and Search Drills

Solution