
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import math

class TestTask(unittest.TestCase):
    def test_returns_correct_length(self):
        import user_code
        importlib.reload(user_code)
        points = user_code.approximate_ellipse(7, 2, 50)
        _dynamic_test(
            self,
            isinstance(points, list) and len(points) == 50,
            "Returned list has correct length for num_points=50",
            f"Returned list length is {len(points) if isinstance(points, list) else 'not a list'} instead of 50",
        )

    def test_points_are_tuples_of_floats(self):
        import user_code
        importlib.reload(user_code)
        points = user_code.approximate_ellipse(4, 1, 10)
        all_tuples = all(isinstance(pt, tuple) and len(pt) == 2 for pt in points)
        all_floats = all(isinstance(pt[0], float) and isinstance(pt[1], float) for pt in points)
        _dynamic_test(
            self,
            all_tuples and all_floats,
            "All points are tuples of two floats",
            "Not all points are tuples of two floats",
        )

    def test_first_and_last_points_not_identical(self):
        import user_code
        importlib.reload(user_code)
        points = user_code.approximate_ellipse(3, 2, 30)
        not_identical = points[0] != points[-1]
        _dynamic_test(
            self,
            not_identical,
            "First and last points are not identical",
            "First and last points should not be identical",
        )

    def test_points_on_ellipse(self):
        import user_code
        importlib.reload(user_code)
        a = 6
        b = 4
        num_points = 36
        points = user_code.approximate_ellipse(a, b, num_points)
        # Check a few random points for ellipse equation
        for i in [0, num_points // 4, num_points // 2]:
            x, y = points[i]
            lhs = (x / a) ** 2 + (y / b) ** 2
            _dynamic_test(
                self,
                abs(lhs - 1.0) < 1e-10,
                f"Point ({x:.4f}, {y:.4f}) satisfies the ellipse equation",
                f"Point ({x:.4f}, {y:.4f}) does not satisfy the ellipse equation (got {lhs})",
            )

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

Aprende los fundamentos de la modelización geométrica utilizando Python. Explora cómo representar, manipular y aproximar figuras geométricas de forma programática. Este curso abarca formas básicas, transformaciones y técnicas prácticas de aproximación, haciendo que los conceptos geométricos sean accesibles e interactivos.

Comience con los conceptos fundamentales del modelado geométrico y cómo Python puede utilizarse para representar y manipular formas básicas.

Profundiza en las transformaciones geométricas como la traslación, la rotación y la escala, y observa cómo afectan a las figuras en Python.

Aprenda a aproximar curvas y formas complejas utilizando polígonos y otras técnicas en Python.

Desafío: Aproximación de Elipse

Solución