import unittest
import importlib
import io
from contextlib import redirect_stdout
import re

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 TestPeopleInformationFunction(unittest.TestCase):

    def test_people_information_function_declared(self):
        import user_code
        _dynamic_test(
            self,
            hasattr(user_code, 'people_information') and callable(user_code.people_information),
            "The `people_information` function is declared.",
            "Expected `people_information` function to be declared."
        )

    def test_people_information_correct_output_for_alex(self):
        import user_code
        people_d = {'Alex': (23, 178), 'Noah': (34, 189), 'Peter': (29, 175), 'John': (41, 185), 'Michelle': (35, 165)}

        f = io.StringIO()
        with redirect_stdout(f):
            user_code.people_information(people_d, "Alex")
        output = f.getvalue().strip()

        expected_output = "Name: Alex\\nAge: 23 y.o.\\nHeight: 178 cm"
        _dynamic_test(
            self,
            re.sub(r'\s+', ' ', output) == re.sub(r'\s+', ' ', expected_output),
            "The `people_information` function correctly prints information for `Alex`.",
            f"Expected output for `Alex`: `{expected_output}`, but got `{output}`."
        )

    def test_people_information_correct_output_for_michelle(self):
        import user_code
        people_d = {'Alex': (23, 178), 'Noah': (34, 189), 'Peter': (29, 175), 'John': (41, 185), 'Michelle': (35, 165)}

        f = io.StringIO()
        with redirect_stdout(f):
            user_code.people_information(people_d, "Michelle")
        output = f.getvalue().strip()

        expected_output = "Name: Michelle\\nAge: 35 y.o.\\nHeight: 165 cm"
        _dynamic_test(
            self,
            re.sub(r'\s+', ' ', output) == re.sub(r'\s+', ' ', expected_output),
            "The `people_information` function correctly prints information for `Michelle`.",
            f"Expected output for `Michelle`: `{expected_output}`, but got `{output}`."
        )

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


test_main.py

Python is an interpreted high-level general-purpose programming language. Unlike HTML, CSS, and JavaScript, which are primarily used for web development, Python is versatile and can be used in various fields, including software development, data science, and back-end development. In this course, you'll explore the core aspects of Python, and by the end, you'll be crafting your own functions!

Dive into the basics of Python, explore your workspace, and perform simple math operations. Learn how to write readable code using comments and handle both basic and advanced mathematical expressions while displaying your results.

Learn how to store and manage data in Python by working with numbers, text, and variables. Understand how to assign values, follow naming conventions, and explore different data types. Gain hands-on experience with string operations, indexing, slicing, and memory recall techniques to efficiently manipulate text in Python.

Learn how to use comparison and logical operators, work with conditional expressions, and apply membership and type comparisons. Build a strong foundation in writing programs that respond dynamically to different conditions using if/else and if/elif/else structures.

Expand your understanding of data types by learning how to group multiple attributes within a single variable. Explore lists, tuples, and dictionaries to efficiently store and manage structured data, along with essential methods for manipulation and retrieval.

Master the art of writing loops in Python—essential constructs for iterating over lists, tuples, dictionaries, and other data structures. Learn to use while and for loops effectively, explore the range function, and work with nested loops to handle complex iteration patterns.

Explore essential built-in functions in Python and take the next step by creating your own. Learn how to define functions, use conditional logic, modify existing functions, and work with lambda expressions to write efficient, reusable code.

Challenge: Creating Logging Function

Oplossing

Challenge: Creating Logging Function

Oplossing