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

class TestTask(unittest.TestCase):
    def test_scaling_positive_factor(self):
        import user_code
        importlib.reload(user_code)
        polygon = [(1, 2), (3, 4), (5, 6)]
        scale = 2
        expected = [(2, 4), (6, 8), (10, 12)]
        result = user_code.scale_polygon(polygon, scale)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Correct scaling for positive factor.",
            f"Expected {expected}, got {result} for scaling by {scale}",
        )

    def test_scaling_negative_factor(self):
        import user_code
        importlib.reload(user_code)
        polygon = [(1, -2), (-3, 4), (0, 0)]
        scale = -1
        expected = [(-1, 2), (3, -4), (0, 0)]
        result = user_code.scale_polygon(polygon, scale)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            f"Correct scaling for negative factor.",
            f"Expected {expected}, got {result} for scaling by {scale}",
        )

    def test_scaling_zero_points(self):
        import user_code
        importlib.reload(user_code)
        polygon = []
        scale = 5
        expected = []
        result = user_code.scale_polygon(polygon, scale)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Handles empty polygon correctly.",
            f"Expected empty list, got {result}",
        )

    def test_scaling_float_factor(self):
        import user_code
        importlib.reload(user_code)
        polygon = [(1, 2), (3, 4)]
        scale = 0.5
        expected = [(0.5, 1.0), (1.5, 2.0)]
        result = user_code.scale_polygon(polygon, scale)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Handles float scaling factor correctly.",
            f"Expected {expected}, got {result} for scaling by {scale}",
        )

    def test_original_not_modified(self):
        import user_code
        importlib.reload(user_code)
        polygon = [(2, 3), (4, 5)]
        polygon_copy = list(polygon)
        scale = 3
        _ = user_code.scale_polygon(polygon, scale)
        _dynamic_test(
            self,
            polygon == polygon_copy,
            "Original polygon is not modified.",
            f"Original polygon was modified: {polygon} != {polygon_copy}",
        )

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: Escalado

Solución