Summary  
This chapter explains how to take advantage of Python list mutability to update list contents in place using indexing and slice assignments.

General domain of usage  
Travel itinerary management.

In Python, lists are **mutable**, which means that after a list is created, its contents can be modified, added, or removed. Because of this mutability, lists have much flexibility for working with lists and are, therefore, a very powerful tool for managing dynamic data.

### What Does Mutable Mean?

Mutable means that the data structure can be updated without creating a new object. For example, you could change the value of an existing item, replace several elements, or even remove and insert new ones directly into the same list.

Imagine you have a list of cities you plan to visit, but plans change. You can update or replace items in the list easily:

cities = ["Paris", "Tokyo", "New York", "Berlin", "Sydney"]

# Replacing the fourth city
cities[2] = "Rome"
print(cities)  # Output: ['Paris', 'Tokyo', 'Rome', 'Berlin', 'Sydney']

# Replacing the last two cities with new ones
cities[-2:] = ["Dubai", "Cape Town"]
print(cities)  # Output: ['Paris', 'Tokyo', 'Rome', 'Dubai', 'Cape Town']

In this example, the city `"New York"` was replaced at index 2 with `"Rome"`, and using negative indexing, the last two cities (`"Berlin"` and `"Sydney"`) were replaced with `"Dubai"` and `"Cape Town"`. Multiple changes can also be made in one step.

cities = ["Paris", "Tokyo", "New York", "Berlin", "Sydney"]

# Replacing multiple cities in the middle
cities[1:3] = ["Seoul", "Bangkok", "Mumbai"]

print(cities)  # Output: ['Paris', 'Seoul', 'Bangkok', 'Mumbai', 'Berlin', 'Sydney']

Here, we replaced "Tokyo" and "New York" with three cities: "Seoul", "Bangkok", and "Mumbai". This demonstrates how flexible list mutability can be for managing your data.

import unittest
import importlib
from contextlib import redirect_stdout
import io
import user_code

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 test_travel_wishlist_is_declared(self):
        _dynamic_test(
            self,
            hasattr(user_code, 'travel_wishlist'),
            "The `travel_wishlist` list is declared.",
            "Expected `travel_wishlist` to be declared."
        )

    def test_discount_applied_correctly(self):
        expected_costs = [
            2000 * 0.8,
            3000 * 0.8,
            2500 * 0.8
        ]
        actual_costs = [city[2] for city in user_code.travel_wishlist]
        _dynamic_test(
            self,
            actual_costs == expected_costs,
            f"The travel costs are correctly discounted: {actual_costs}.",
            f"Expected travel costs after discount to be {expected_costs}, but got {actual_costs}."
        )

    def test_discount_using_indexing(self):
        with open('user_code.py', 'r') as file:
            user_code_source = file.read()

        _dynamic_test(
            self,
            '[2]' in user_code_source,
            "The discount is applied using indexing.",
            "Expected the discount to be applied using indexing."
        )

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.

Updating and Changing Lists in Python

What Does Mutable Mean?

解答