L'incatenamento delle eccezioni e il rilancio delle stesse sono competenze fondamentali per costruire programmi Python affidabili. Quando si intercetta un'eccezione e si deve segnalarne una nuova, può essere utile preservare il contesto dell'errore originale. L'incatenamento delle eccezioni consente di farlo, fornendo un traceback completo che facilita il debug. Il rilancio delle eccezioni garantisce che gli errori non vengano ignorati silenziosamente, rendendo il codice più robusto e facile da mantenere. Applicazione di questi concetti per gestire gli errori in modo chiaro e trasparente nelle applicazioni.


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

Acquisizione di competenze pratiche nella gestione dei moduli e delle importazioni in Python per una gestione efficiente del codice. Padronanza delle tecniche avanzate di gestione degli errori per applicazioni più affidabili, automazione delle operazioni sui file con la gestione dei file e apprendimento di strategie di testing robuste con Pytest e Unittest per garantire l'integrità del codice.

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.

Sfida: Gestione degli Errori Concatenata

Soluzione