Summary  
This chapter demonstrates how to remove elements from a list by their index using the `del` keyword, including use of negative indexing to target items from the end.  

General domain of usage  
travel planning

The `del` keyword allows you to delete an element at a **specific index** in the list. This is useful when you know the exact position of the item you want to remove.

The syntax of `del` keyword is:
``` python
del list[index]
```
- The statement starts with the keyword `del`;
- Next, you typically identify the list item with its index, like `list[index]`.

Let's say you have a list of cities in your travel itinerary:
``` python
travel_wishlist = ["Paris", "Oslo", "Kyoto", "Sydney"]
```
You've decided to remove the city "Sydney", which is the last destination on your list. Using `del` and negative indexing:

travel_wishlist = ["Paris", "Oslo", "Kyoto", "Sydney"]

# Remove the last city
del travel_wishlist[-1]
print(travel_wishlist) # Output: ['Paris', 'Oslo', 'Kyoto']

You can remove any item from the list by using its index number.

import unittest
from contextlib import redirect_stdout
import io
import importlib

def _dynamic_test(test_case, condition, success_message, failure_message):
    """
    A reusable function for handling assertions dynamically.
    """
    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_travel_wishlist_is_declared(self):
        """
        Test to ensure `travel_wishlist` is declared.
        """
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, 'travel_wishlist'),
            "The `travel_wishlist` list is declared.",
            "Expected `travel_wishlist` to be declared."
        )

    def test_cities_removed_correctly(self):
        """
        Test to ensure the correct cities are removed from the list.
        """
        import user_code
        expected_list = ["Oslo", "Sydney", "Rome"]  # Paris and Kyoto should be removed
        _dynamic_test(
            self,
            user_code.travel_wishlist == expected_list,
            f"The cities were removed correctly: {user_code.travel_wishlist}.",
            f"Expected travel_wishlist to be {expected_list}, but got {user_code.travel_wishlist}."
        )

    def test_del_keyword_used_twice(self):
        """
        Test to ensure the `del` keyword is used twice.
        """
        with open('user_code.py', 'r') as file:
            user_code_source = file.read()

        del_occurrences = user_code_source.count("del ")

        _dynamic_test(
            self,
            del_occurrences >= 2,
            "The `del` keyword is used twice to remove elements.",
            "Expected the `del` keyword to be used twice to remove elements."
        )

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


test_main.py

Explore the fundamental data structures of the Python programming language, including lists, dictionaries, tuples, and sets, and learn how to apply them effectively to solve real-world programming challenges.

What is a list? A list is an ordered collection that can be modified. It also allows for duplicate elements.

What is a dictionary? A dictionary is an ordered collection that can be changed, but it doesn't allow duplicate entries. It consists of key:value pairs, which are used to optimize its structure.

What is a tuple? A tuple is an ordered collection that cannot be altered. It can have duplicate elements. While it's similar to a list, the values in a tuple can be of any type and are indexed by integers. Although not mandatory, it's common to enclose the values of a tuple in parentheses, making them easier to understand in Python.

What is a set? In Python, a set is an unordered collection that is both iterable and mutable, with no repeated elements. While the order of items in a set isn't fixed, it can include a variety of elements. A key benefit of using sets over lists is their highly efficient method for determining if an element exists within the set.

Deleting Elements in Python Lists: Removing Items Safely

Solution

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Deleting Elements in Python Lists: Removing Items Safely

Solution