
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

Apprendere le tecniche di packing/unpacking, argomenti flessibili per le funzioni, funzioni di ordine superiore, lambda, ambito delle variabili, closure, iteratori e decorator. Progettato per chi ha completato un corso introduttivo di Python e desidera scrivere codice più efficiente, espressivo e potente.

Esplora l'arte del packing e unpacking di liste, tuple e dizionari per scrivere codice Python più espressivo ed efficiente.

Esplora il mondo delle funzioni di ordine superiore, il passaggio di funzioni come argomenti e la scrittura di funzioni anonime concise con lambda.

Svela i misteri dell'ambito delle variabili e scopri come le funzioni annidate e le closure consentano un'incapsulamento potente.

Approfondimento sul protocollo di iterazione di Python, iteratori personalizzati e funzioni generatrici per un'elaborazione efficiente dei dati.

Sfida: Decoratore Condizionale

Soluzione