
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

Beherrschung von Packing/Unpacking, flexiblen Funktionsargumenten, Higher-Order-Funktionen, Lambdas, Variablenbereich, Closures, Iteratoren und Dekoratoren. Konzipiert für Lernende, die einen Einführungskurs in Python abgeschlossen haben und effizienteren, ausdrucksstärkeren und leistungsfähigeren Code schreiben möchten.

Erkunden Sie die Kunst des Packens und Entpackens von Listen, Tupeln und Dictionaries, um ausdrucksstärkeren und effizienteren Python-Code zu schreiben.

Tauchen Sie ein in die Welt der höherwertigen Funktionen, das Übergeben von Funktionen als Argumente und das Schreiben prägnanter anonymer Funktionen mit Lambda.

Entschlüsseln der Geheimnisse des Variablenbereichs und Erlernen, wie verschachtelte Funktionen und Closures eine leistungsstarke Kapselung ermöglichen.

Vertiefung in das Iterationsprotokoll von Python, benutzerdefinierte Iteratoren und Generatorfunktionen für effiziente Datenverarbeitung.

Herausforderung: Bedingter Dekorator

Lösung