L'enchaînement et la relance des exceptions sont des compétences essentielles pour développer des programmes Python fiables. Lorsque vous interceptez une exception et devez en signaler une nouvelle, il peut être utile de conserver le contexte de l'erreur d'origine. L'enchaînement des exceptions permet cela, en fournissant une trace complète qui facilite le débogage. La relance des exceptions garantit que les erreurs ne sont pas ignorées silencieusement, rendant votre code plus robuste et plus facile à maintenir. Exercez-vous à appliquer ces concepts pour gérer les erreurs de manière élégante et transparente dans vos applications.


import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib

class TestTask(unittest.TestCase):
    def test_division_success(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_int_divide(10, 2)
        _dynamic_test(
            self,
            result == 5,
            "Returns correct integer division for (10, 2)",
            f"Expected 5, got {result}",
        )

    def test_zero_division_error_chained(self):
        import user_code
        importlib.reload(user_code)
        try:
            user_code.safe_int_divide(5, 0)
        except ValueError as ve:
            msg = str(ve)
            chained = ve.__cause__
            _dynamic_test(
                self,
                msg == "Cannot divide by zero" and isinstance(chained, ZeroDivisionError),
                "Raises ValueError with correct message and chains ZeroDivisionError",
                f"Expected ValueError('Cannot divide by zero') chained from ZeroDivisionError, got ValueError('{msg}') chained from {type(chained)}",
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "Should not raise other exception",
                f"Raised unexpected exception: {type(e)} {e}",
            )
        else:
            _dynamic_test(
                self,
                False,
                "Should raise ValueError for division by zero",
                "Did not raise ValueError for division by zero",
            )

    def test_other_exceptions_reraised(self):
        import user_code
        importlib.reload(user_code)
        class Dummy:
            def __floordiv__(self, other):
                raise RuntimeError("Custom error")
        d = Dummy()
        try:
            user_code.safe_int_divide(d, 2)
        except RuntimeError as e:
            _dynamic_test(
                self,
                str(e) == "Custom error",
                "Re-raises non-ZeroDivisionError exceptions unchanged",
                f"Expected RuntimeError('Custom error'), got {type(e)}('{e}')",
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "Should re-raise the original exception type",
                f"Raised unexpected exception: {type(e)} {e}",
            )
        else:
            _dynamic_test(
                self,
                False,
                "Should raise RuntimeError for Dummy object",
                "Did not raise any exception for Dummy object",
            )

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

Vous acquerrez des compétences pratiques dans les modules et les imports de Python pour une gestion efficace du code. Maîtrisez des techniques avancées de gestion des erreurs pour des applications plus fiables, automatisez les opérations de fichiers avec la gestion des fichiers, et apprenez des stratégies de test robustes avec Pytest et Unittest pour assurer l'intégrité de votre code.

Master Python's exception system for robust error handling and debugging.

Explore advanced techniques for file operations and resource management using context managers.

Compare and apply Python's multithreading and multiprocessing modules for concurrent programming.

Master asynchronous programming in Python using the asyncio library for scalable I/O-bound applications.

Explore how to write, organize, and run tests using Python's unittest and pytest frameworks.

Challenge: Gestion d’erreurs Chaînée

Solution