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

class TestTask(unittest.TestCase):
    def test_lambda_cubes_argument(self):
        import user_code
        importlib.reload(user_code)
        cube = getattr(user_code, 'cube', None)
        _dynamic_test(
            self,
            callable(cube),
            "cube is defined and callable",
            "cube is not defined as a callable lambda function",
        )
        for val in [0, 1, 2, 5, -3]:
            expected = val ** 3
            actual = cube(val) if cube is not None else None
            _dynamic_test(
                self,
                actual == expected,
                f"cube({val}) returns {expected}",
                f"cube({val}) should return {expected}, got {actual}",
            )

    def test_cubed_numbers_list(self):
        import user_code
        importlib.reload(user_code)
        numbers = [1, 2, 3, 4, 5]
        cubed_numbers = getattr(user_code, 'cubed_numbers', None)
        _dynamic_test(
            self,
            isinstance(cubed_numbers, list),
            "cubed_numbers is a list",
            f"cubed_numbers should be a list, got {type(cubed_numbers)}",
        )
        expected = [n ** 3 for n in numbers]
        _dynamic_test(
            self,
            cubed_numbers == expected,
            f"cubed_numbers contains cubes: {expected}",
            f"cubed_numbers should be {expected}, got {cubed_numbers}",
        )

    def test_lambda_used_with_map(self):
        code = ""
        with open("user_code.py", "r") as f:
            code = f.read()
        found_lambda = "lambda" in code
        found_map = "map(" in code
        _dynamic_test(
            self,
            found_lambda and found_map,
            "Used lambda function with map as required",
            "Solution must use a lambda function with map",
        )

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

Beheers het inpakken/uitpakken, flexibele functieargumenten, hogere-orde functies, lambda's, variabele scope, closures, iterators en decorators. Ontworpen voor cursisten die een inleidende Python-cursus hebben afgerond en efficiëntere, expressievere en krachtigere code willen schrijven.

Ontdek de kunst van het inpakken en uitpakken van lijsten, tuples en dictionaries om expressievere en efficiëntere Python-code te schrijven.

Verdiep je in de wereld van hogere-orde functies, het doorgeven van functies als argumenten en het schrijven van beknopte anonieme functies met lambda.

Ontrafel de mysteries van variabele scope en ontdek hoe geneste functies en closures krachtige encapsulatie mogelijk maken.

Verdiep u in het iteratieprotocol van Python, aangepaste iterators en generatorfuncties voor efficiënte gegevensverwerking.

Uitdaging: Lambda met Map

Oplossing