Summary  
Demonstrates how to use the len() function to measure the number of elements in a list (treating any nested list as a single element) and print that length.

General domain of usage  
Data processing

When working with large or complex lists, knowing how many elements they contain is often useful. Python provides the `len()` function, which returns the total number of items in a list.

> Note
>
> A nested list is considered a single item. The `len()` function doesn't count the individual items inside a nested list as separate items of the main list.

cities_list = ["Tokyo", "New York", "Sydney", "Berlin", ["Paris", "France"]]

list_length = len(cities_list)

print(list_length)

import unittest
import re
import importlib
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_list_length_is_declared(self):
        _dynamic_test(
            self,
            hasattr(user_code, 'list_length'),
            "The variable `list_length` is declared.",
            "Expected `list_length` to be declared."
        )

    def test_list_length_is_defined_correctly(self):
        expected = len(user_code.travel_wishlist)
        actual = user_code.list_length
        _dynamic_test(
            self,
            actual == expected,
            f"The `list_length` value equals the length of `travel_wishlist` ({expected}).",
            f"Expected `list_length` to equal {expected}, but got {actual}."
        )

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

        _dynamic_test(
            self,
            re.search(r'len\s*\(', user_code_source),
            "The `len()` function is used.",
            "Expected the `len()` function to be used."
        )

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.

Python List Length: Measuring and Managing List Size

Solution

Awesome!

Python List Length: Measuring and Managing List Size

Solution

Awesome!