
import unittest
import user_code
import ast
import re   
import unittest
import importlib
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def test_add(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("add", 7, 5)
        _dynamic_test(
            self,
            result == 12,
            "Addition returns correct sum",
            f"Expected 12, got {result}",
        )

    def test_subtract(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("subtract", 10, 3)
        _dynamic_test(
            self,
            result == 7,
            "Subtraction returns correct difference",
            f"Expected 7, got {result}",
        )

    def test_multiply(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("multiply", 4, 6)
        _dynamic_test(
            self,
            result == 24,
            "Multiplication returns correct product",
            f"Expected 24, got {result}",
        )

    def test_divide(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("divide", 20, 5)
        _dynamic_test(
            self,
            result == 4,
            "Division returns correct quotient",
            f"Expected 4, got {result}",
        )

    def test_divide_by_zero(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("divide", 20, 0)
        _dynamic_test(
            self,
            result is None,
            "Division by zero returns None",
            f"Expected None for division by zero, got {result}",
        )

    def test_unsupported_operation(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_calculator("power", 2, 3)
        _dynamic_test(
            self,
            result is None,
            "Unsupported operation returns None",
            f"Expected None for unsupported operation, got {result}",
        )

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 how to write secure Python code by understanding common vulnerabilities, safe coding techniques, and practical security measures. This course covers essential security concepts, real-world scenarios, and hands-on tasks to help you protect your Python applications.

Explore the most common security pitfalls in Python, how vulnerabilities arise, and the foundational principles for writing secure code.

Master secure coding techniques to prevent vulnerabilities and ensure robust Python applications.

Learn how to handle, store, and process sensitive data securely in Python applications.

Challenge: Preventing Code Injection

Solution

Challenge: Preventing Code Injection

Solution