Puedes usar el atributo `__name__` de cualquier objeto función en Python para obtener su nombre como una cadena. Al escribir un decorador, accede al nombre de la función decorada usando `func.__name__` dentro del wrapper. Esto es útil para el registro de eventos o la depuración.


Nota


import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def test_add_function_name_printed(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.add(10, 5)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "calling function: add" in output,
            "Function name 'add' is printed before execution",
            f"Expected function name 'add' in output, got: {output}",
        )

    def test_greet_function_name_printed(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.greet("Charlie")
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "calling function: greet" in output,
            "Function name 'greet' is printed before execution",
            f"Expected function name 'greet' in output, got: {output}",
        )

    def test_add_prints_args(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.add(1, 2)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "args=(1, 2)" in output,
            "Positional arguments are printed as tuple",
            f"Expected positional arguments '(1, 2)' in output, got: {output}",
        )

    def test_greet_prints_kwargs(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.greet("Bob", greeting="Hi")
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "kwargs={'greeting': 'hi'}" in output or 'kwargs={"greeting": "hi"}' in output,
            "Keyword arguments are printed as dictionary",
            f"Expected keyword arguments in output, got: {output}",
        )


    def test_decorator_return_value_unchanged(self):
        import user_code
        importlib.reload(user_code)
        res1 = user_code.add(7, 8)
        res2 = user_code.greet("Zoe", greeting="Hiya")
        _dynamic_test(
            self,
            res1 == 15 and res2 == "Hiya, Zoe!",
            "Decorator does not interfere with the function's return value",
            f"Expected 15 and 'Hiya, Zoe!', got {res1} and {res2}",
        )

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

Domina el empaquetado/desempaquetado, argumentos flexibles en funciones, funciones de orden superior, lambdas, alcance de variables, closures, iteradores y decoradores. Diseñado para estudiantes que han completado un curso introductorio de Python y desean escribir código más eficiente, expresivo y potente.

Explora el arte de empaquetar y desempaquetar listas, tuplas y diccionarios para escribir código Python más expresivo y eficiente.

Adentrarse en el mundo de las funciones de orden superior, el paso de funciones como argumentos y la escritura de funciones anónimas concisas con lambda.

Descubre los misterios del alcance de las variables y aprende cómo las funciones anidadas y los closures permiten una encapsulación poderosa.

Profundización en el protocolo de iteración de Python, iteradores personalizados y funciones generadoras para el procesamiento eficiente de datos.

Desafío: Decorador de Registro

Solución