
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import sys
import io

class TestTask(unittest.TestCase):
    def test_greet_returns_result_when_true(self):
        import user_code
        importlib.reload(user_code)
        result = getattr(user_code, 'greet', None)
        _dynamic_test(
            self,
            result is not None and callable(result),
            "greet is defined and callable",
            "greet function is missing or not callable",
        )
        output = user_code.greet("Alice")
        _dynamic_test(
            self,
            output == "Hello, Alice!",
            "greet returns correct result when decorator is True",
            f"Expected 'Hello, Alice!', got {output}",
        )

    def test_farewell_returns_none_when_false(self):
        import user_code
        importlib.reload(user_code)
        result = getattr(user_code, 'farewell', None)
        _dynamic_test(
            self,
            result is not None and callable(result),
            "farewell is defined and callable",
            "farewell function is missing or not callable",
        )
        output = user_code.farewell("Bob")
        _dynamic_test(
            self,
            output is None,
            "farewell returns None when decorator is False",
            f"Expected None, got {output}",
        )

    def test_decorator_not_calling_function_when_false(self):
        # Check that the decorated function is NOT called when should_run is False
        called = {'flag': False}
        def test_func(a, b):
            called['flag'] = True
            return a + b
        import user_code
        dec = getattr(user_code, 'conditional_run', None)
        _dynamic_test(
            self,
            dec is not None and callable(dec),
            "conditional_run is defined and callable",
            "conditional_run is missing or not callable",
        )
        decorated = dec(False)(test_func)
        result = decorated(1, 2)
        _dynamic_test(
            self,
            result is None,
            "Decorator returns None when should_run is False",
            f"Expected None when should_run is False, got {result}",
        )
        _dynamic_test(
            self,
            not called['flag'],
            "Original function is not called when should_run is False",
            "Original function was called when should_run is False",
        )

    def test_decorator_with_various_arguments(self):
        import user_code
        dec = getattr(user_code, 'conditional_run', None)
        _dynamic_test(
            self,
            dec is not None and callable(dec),
            "conditional_run is defined and callable",
            "conditional_run is missing or not callable",
        )
        @dec(True)
        def many_args(a, b, c=10, d=20):
            return a + b + c + d
        result = many_args(1, 2, d=3)
        _dynamic_test(
            self,
            result == 1 + 2 + 10 + 3,
            "Decorator supports functions with arbitrary arguments",
            f"Expected 16, got {result}",
        )

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)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    changed = False
    # Collect all assignment nodes to modify
    assign_nodes = [
        (i, node)
        for i, node in enumerate(tree.body)
        if isinstance(node, ast.Assign)
        and any(isinstance(target, ast.Name) and target.id == var_name for target in node.targets)
    ]

    # If nothing to change, return unmodified code
    if not assign_nodes:
        return code

    # Perform replacements for all matching assignments (from last to first to not break line offsets)
    for i, node in reversed(assign_nodes):
        start_line = node.lineno - 1
        line = lines[start_line]
        indent = ' ' * (len(line) - len(line.lstrip()))
        lines[start_line] = f"{indent}{var_name} = {value}"
        next_line = len(lines)
        for next_node in tree.body[i+1:]:
            if hasattr(next_node, 'lineno'):
                next_line = next_node.lineno - 1
                break
        if next_line > start_line + 1:
            lines[start_line+1:next_line] = []
        changed = True

    return '\\n'.join(lines) if changed else code

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


test_main.py

Maîtrise de l'emballage/déballage, des arguments de fonction flexibles, des fonctions d'ordre supérieur, des lambdas, de la portée des variables, des closures, des itérateurs et des décorateurs. Conçu pour les apprenants ayant suivi un cours d'introduction à Python et souhaitant écrire un code plus efficace, expressif et puissant.

Explorez l'art du packing et unpacking des listes, tuples et dictionnaires pour écrire un code Python plus expressif et efficace.

Plongez dans le monde des fonctions d'ordre supérieur, du passage de fonctions en tant qu'arguments, et de l'écriture de fonctions anonymes concises avec lambda.

Démystifier la portée des variables et découvrir comment les fonctions imbriquées et les closures permettent une encapsulation puissante.

Plongez dans le protocole d'itération de Python, les itérateurs personnalisés et les fonctions génératrices pour un traitement efficace des données.

Défi : Décorateur Conditionnel

Solution