
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import math
import numpy as np

class TestTask(unittest.TestCase):
    def test_returns_correct_length(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.approximate_curve_with_polygon(np.sin, (0, np.pi), 5)
        _dynamic_test(
            self,
            isinstance(result, list) and len(result) == 5,
            "Returned list has correct number of vertices (5)",
            f"Expected 5 vertices, got {len(result) if isinstance(result, list) else 'not a list'}",
        )

    def test_returns_tuples_of_xy(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.approximate_curve_with_polygon(np.sin, (0, np.pi), 4)
        all_tuples = all(isinstance(pt, tuple) and len(pt) == 2 for pt in result)
        _dynamic_test(
            self,
            all_tuples,
            "All elements are tuples of length 2 (x, y)",
            f"Not all elements are tuples of length 2: {result}",
        )
        all_nums = all(isinstance(pt[0], (int, float, np.floating)) and isinstance(pt[1], (int, float, np.floating)) for pt in result)
        _dynamic_test(
            self,
            all_nums,
            "All tuple elements are numbers (x, y)",
            f"Not all tuple elements are numbers: {result}",
        )

    def test_x_values_evenly_spaced(self):
        import user_code
        importlib.reload(user_code)
        interval = (0, 10)
        num = 6
        result = user_code.approximate_curve_with_polygon(np.cos, interval, num)
        x_vals = [pt[0] for pt in result]
        expected_x = np.linspace(interval[0], interval[1], num)
        close = np.allclose(x_vals, expected_x)
        _dynamic_test(
            self,
            close,
            "x-values are evenly spaced in the interval",
            f"x-values are not evenly spaced: {x_vals} vs expected {expected_x}",
        )

    def test_y_values_correct(self):
        import user_code
        importlib.reload(user_code)
        interval = (0, np.pi)
        num = 4
        result = user_code.approximate_curve_with_polygon(np.sin, interval, num)
        x_vals = np.linspace(interval[0], interval[1], num)
        y_expected = np.sin(x_vals)
        y_vals = [pt[1] for pt in result]
        close = np.allclose(y_vals, y_expected)
        _dynamic_test(
            self,
            close,
            "y-values are correct for the given curve_func",
            f"y-values do not match function output: {y_vals} vs expected {list(y_expected)}",
        )

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

Apprenez les fondamentaux de la modélisation géométrique avec Python. Découvrez comment représenter, manipuler et approximer des figures géométriques de manière programmatique. Ce cours couvre les formes de base, les transformations et les techniques d'approximation pratiques, rendant les concepts géométriques accessibles et interactifs.

Commencez avec les concepts fondamentaux de la modélisation géométrique et découvrez comment Python peut être utilisé pour représenter et manipuler des formes de base.

Explorez les transformations géométriques telles que la translation, la rotation et la mise à l'échelle, et observez leur impact sur les formes en Python.

Apprenez à approximer des courbes et des formes complexes en utilisant des polygones et d'autres techniques en Python.

Défi : Approximation de Courbe

Solution