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

class TestTask(unittest.TestCase):
    def test_chained_odds_squared_basic(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.chained_odds_squared(range(10))
        expected = [1, 9, 25, 49, 81]
        _dynamic_test(
            self,
            hasattr(user_code, 'chained_odds_squared') and callable(user_code.chained_odds_squared),
            "Function 'chained_odds_squared' is defined and callable.",
            "Function 'chained_odds_squared' is not defined or not callable."
        )
        _dynamic_test(
            self,
            hasattr(user_code, 'filter_odds') and callable(user_code.filter_odds),
            "Function 'filter_odds' is defined and callable.",
            "Function 'filter_odds' is not defined or not callable."
        )
        _dynamic_test(
            self,
            hasattr(user_code, 'square_numbers') and callable(user_code.square_numbers),
            "Function 'square_numbers' is defined and callable.",
            "Function 'square_numbers' is not defined or not callable."
        )
        _dynamic_test(
            self,
            result is not None and list(result) == expected,
            f"Correct output list for range(10): {expected}",
            f"Expected {expected}, got {list(user_code.chained_odds_squared(range(10)))}"
        )
    def test_chained_odds_squared_empty(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.chained_odds_squared([])
        expected = []
        _dynamic_test(
            self,
            result is not None and list(result) == expected,
            "Returns empty list for empty input.",
            f"Expected empty list, got {list(user_code.chained_odds_squared([]))}"
        )
    def test_chained_odds_squared_all_even(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.chained_odds_squared([2, 4, 6, 8])
        expected = []
        _dynamic_test(
            self,
            result is not None and list(result) == expected,
            "Returns empty list for all even input.",
            f"Expected empty list, got {list(user_code.chained_odds_squared([2,4,6,8]))}"
        )
    def test_chained_odds_squared_negative_numbers(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.chained_odds_squared([-5, -4, -3, -2, -1, 0, 1])
        expected = [25, 9, 1, 1]
        _dynamic_test(
            self,
            result is not None and list(result) == expected,
            "Correctly handles negative and zero values.",
            f"Expected {expected}, got {list(user_code.chained_odds_squared([-5, -4, -3, -2, -1, 0, 1]))}"
        )
    def test_chained_odds_squared_non_list_iterable(self):
        import user_code
        importlib.reload(user_code)
        def gen():
            for i in range(3, 8):
                yield i
        result = user_code.chained_odds_squared(gen())
        expected = [9, 25, 49]
        _dynamic_test(
            self,
            result is not None and list(result) == expected,
            "Works with any iterable, not just lists.",
            f"Expected {expected}, got {list(user_code.chained_odds_squared(range(3,8)))}"
        )

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

Domine técnicas de empacotamento e desempacotamento, argumentos flexíveis em funções, funções de ordem superior, lambdas, escopo de variáveis, closures, iteradores e decoradores. Desenvolvido para alunos que já concluíram um curso introdutório de Python e desejam escrever códigos mais eficientes, expressivos e poderosos.

Explore a arte de empacotar e desempacotar listas, tuplas e dicionários para escrever códigos Python mais expressivos e eficientes.

Aprofunde-se no mundo das funções de ordem superior, passando funções como argumentos e escrevendo funções anônimas concisas com lambda.

Desvende os mistérios do escopo de variáveis e compreenda como funções aninhadas e closures possibilitam um encapsulamento poderoso.

Aprofundamento no protocolo de iteração do Python, iteradores personalizados e funções geradoras para processamento eficiente de dados.

Challenge: Chaining and Composing Iterators

Solução