
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

Leer de basisprincipes van geometrisch modelleren met Python. Ontdek hoe je geometrische figuren programmeermatig kunt representeren, manipuleren en benaderen. Deze cursus behandelt basisvormen, transformaties en praktische benaderingstechnieken, waardoor geometrische concepten toegankelijk en interactief worden.

Maak kennis met de kernconcepten van geometrisch modelleren en hoe Python kan worden gebruikt om basisvormen te representeren en te manipuleren.

Verdiep u in geometrische transformaties zoals translatie, rotatie en schaling, en zie hoe deze vormen beïnvloeden in Python.

Leer hoe je krommen en complexe vormen kunt benaderen met behulp van polygonen en andere technieken in Python.

Challenge: Ellipsbenadering

Oplossing