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

In this course, you'll get to know the fundamental data structures of the Python programming language. We'll explore utilizing Python's native data structures like lists, dictionaries, tuples, and sets to tackle different 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

Awesome!

Deleting Elements in Python Lists: Removing Items Safely

Solution

Awesome!