
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

Learn the fundamentals of geometric modelling using Python. Explore how to represent, manipulate, and approximate geometric figures programmatically. This course covers basic shapes, transformations, and practical approximation techniques, making geometric concepts accessible and interactive.

Get started with the core concepts of geometric modelling and how Python can be used to represent and manipulate basic shapes.

Delve into geometric transformations such as translation, rotation, and scaling, and see how they affect shapes in Python.

Learn how to approximate curves and complex shapes using polygons and other techniques in Python.

Challenge: Scaling

Ratkaisu