
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import types
import sys

class TestTask(unittest.TestCase):
    def test_function_returns_correct_values(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'process_numbers', None)
        _dynamic_test(
            self,
            callable(func),
            "Function 'process_numbers' is defined",
            "Function 'process_numbers' is not defined or not callable",
        )
        result = func([1, 2, 3]) if func else None
        expected = [6, 9, 14]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returned list is correct for input [1, 2, 3]",
            f"Expected {expected}, got {result}",
        )

    def test_function_returns_same_length(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'process_numbers', None)
        in_list = [5, 10, -2, 0]
        result = func(in_list) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and len(result) == len(in_list),
            "Returned list has the same length as input",
            f"Expected length {len(in_list)}, got {len(result) if isinstance(result, list) else result}",
        )

    def test_function_works_for_empty_list(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'process_numbers', None)
        result = func([]) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and result == [],
            "Function returns empty list for empty input",
            f"Expected [], got {result}",
        )

    def test_function_works_for_negative_numbers(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'process_numbers', None)
        result = func([-1, -3]) if func else None
        expected = [6, 14]
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Function works correctly for negative numbers",
            f"Expected {expected}, got {result}",
        )

    def test_helper_function_defined_inside(self):
        import user_code
        import ast
        import inspect
        importlib.reload(user_code)
        source = inspect.getsource(user_code.process_numbers)
        tree = ast.parse(source)
        class HelperFinder(ast.NodeVisitor):
            def __init__(self):
                self.found = False
            def visit_FunctionDef(self, node):
                if node.name == 'process_numbers':
                    for child in node.body:
                        if isinstance(child, ast.FunctionDef) and child.name == 'square_and_add_five':
                            self.found = True
        finder = HelperFinder()
        finder.visit(tree)
        _dynamic_test(
            self,
            finder.found,
            "Helper function 'square_and_add_five' is defined inside 'process_numbers'",
            "Helper function 'square_and_add_five' is not defined inside 'process_numbers'",
        )

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

Apprendere le tecniche di packing/unpacking, argomenti flessibili per le funzioni, funzioni di ordine superiore, lambda, ambito delle variabili, closure, iteratori e decorator. Progettato per chi ha completato un corso introduttivo di Python e desidera scrivere codice più efficiente, espressivo e potente.

Esplora l'arte del packing e unpacking di liste, tuple e dizionari per scrivere codice Python più espressivo ed efficiente.

Esplora il mondo delle funzioni di ordine superiore, il passaggio di funzioni come argomenti e la scrittura di funzioni anonime concise con lambda.

Svela i misteri dell'ambito delle variabili e scopri come le funzioni annidate e le closure consentano un'incapsulamento potente.

Approfondimento sul protocollo di iterazione di Python, iteratori personalizzati e funzioni generatrici per un'elaborazione efficiente dei dati.

Sfida: Funzione di supporto all'interno di una funzione

Soluzione