## Puntos clave a recordar

- **Aislamiento de pruebas**: cada prueba debe ejecutarse de forma independiente, para que los cambios en una prueba no afecten a las demás;
- **Fixtures en pytest**: los fixtures proporcionan instancias nuevas o configuraciones para cada prueba, garantizando el aislamiento de las pruebas;
- **Diseño de clases**: definición de clases con atributos y métodos para organizar el comportamiento y el estado;
- **Aserciones en pruebas**: uso de sentencias `assert` para comprobar si el código se comporta como se espera, como verificar la longitud de una lista, el contenido de un elemento o los valores de retorno de métodos.


import unittest
import user_code
import ast
import re   
import importlib
import csv
import importlib
import sys
import types
import builtins

class TestTask(unittest.TestCase):
    def setUp(self):
        # Dynamically create user_code module from task code
        import os
        self.module_name = "user_code"
        self.test_filename = "user_code.py"
        with open(self.test_filename, "r") as f:
            self.code = f.read()
        # Remove module if already loaded
        if self.module_name in sys.modules:
            del sys.modules[self.module_name]

    def test_add_item(self):
        # Setup
        ns = {}
        exec(self.code, ns)
        ShoppingCart = ns.get('ShoppingCart', None)
        _dynamic_test(
            self,
            ShoppingCart is not None,
            "ShoppingCart class is defined",
            "ShoppingCart class is not defined"
        )
        cart = ShoppingCart()
        cart.add_item('Laptop', 1200.0)
        items = getattr(cart, 'items', None)
        _dynamic_test(
            self,
            isinstance(items, list),
            "ShoppingCart.items is a list",
            f"ShoppingCart.items is not a list: {items}"
        )
        _dynamic_test(
            self,
            len(items) == 1,
            "Cart has 1 item after adding",
            f"Cart should have 1 item, has {len(items)}"
        )
        _dynamic_test(
            self,
            isinstance(items[0], dict) and items[0].get("name") == 'Laptop',
            "Cart item name is 'Laptop'",
            f"Expected item name 'Laptop', got: {items[0].get('name') if isinstance(items[0], dict) else items[0]}"
        )

    def test_total_price(self):
        ns = {}
        exec(self.code, ns)
        ShoppingCart = ns.get('ShoppingCart', None)
        cart = ShoppingCart()
        cart.add_item('Book', 20.0)
        cart.add_item('Coffee', 5.0)
        get_total = getattr(cart, 'get_total', None)
        _dynamic_test(
            self,
            callable(get_total),
            "get_total method is callable",
            "get_total method is not callable"
        )
        total = cart.get_total()
        _dynamic_test(
            self,
            total == 25.0,
            "Cart total is correct after adding two items (20.0 + 5.0)",
            f"Expected total 25.0, got {total}"
        )

    def test_empty_cart_total(self):
        ns = {}
        exec(self.code, ns)
        ShoppingCart = ns.get('ShoppingCart', None)
        cart = ShoppingCart()
        get_total = getattr(cart, 'get_total', None)
        _dynamic_test(
            self,
            callable(get_total),
            "get_total method is callable",
            "get_total method is not callable"
        )
        total = cart.get_total()
        _dynamic_test(
            self,
            total == 0,
            "Cart total is 0 for empty cart",
            f"Expected total 0, got {total}"
        )

    def test_cart_fixture_isolation(self):
        # Test that a new ShoppingCart instance is returned each time from the fixture
        ns = {}
        exec(self.code, ns)
        ShoppingCart = ns.get('ShoppingCart', None)
        cart_fixture = ns.get('cart', None)
        _dynamic_test(
            self,
            callable(cart_fixture),
            "cart fixture is defined and callable",
            "cart fixture is not defined/callable"
        )
        cart1 = cart_fixture()
        cart2 = cart_fixture()
        cart1.add_item('A', 1)
        _dynamic_test(
            self,
            len(cart2.items) == 0,
            "Each cart fixture call returns a fresh cart (test isolation)",
            f"cart2.items should be empty, got: {cart2.items}"
        )

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

Un análisis profundo de conceptos avanzados de programación estructural en Python, enfocado en el manejo robusto de archivos, gestión de errores, concurrencia, programación asíncrona y pruebas.

Domina el sistema de excepciones de Python para un manejo de errores y depuración robustos.

Explora técnicas avanzadas para operaciones de archivos y gestión de recursos utilizando gestores de contexto.

Comparación y aplicación de los módulos de multithreading y multiprocessing de Python para la programación concurrente.

Domina la programación asíncrona en Python utilizando la biblioteca asyncio para aplicaciones escalables dependientes de E/S.

Explora cómo escribir, organizar y ejecutar pruebas utilizando los frameworks unittest y pytest de Python.

Desafío: Aseguramiento de la Calidad del Carrito

Puntos clave a recordar

Solución