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

class TestTask(unittest.TestCase):
    def test_basic_case(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'format_scores', None)
        names = ["Alice", "Bob", "Charlie"]
        scores = [85, 92, 78]
        expected = [
            "1. Alice scored 85",
            "2. Bob scored 92",
            "3. Charlie scored 78"
        ]
        result = func(names, scores) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Correctly formats parallel lists with three items.",
            f"Expected {expected}, got {result}",
        )

    def test_empty_lists(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'format_scores', None)
        result = func([], []) if func else None
        _dynamic_test(
            self,
            result == [],
            "Returns empty list for empty input lists.",
            f"Expected empty list, got {result}",
        )

    def test_different_names(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'format_scores', None)
        names = ["Dana", "Eli"]
        scores = [100, 99]
        expected = [
            "1. Dana scored 100",
            "2. Eli scored 99"
        ]
        result = func(names, scores) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Correctly formats two pairs.",
            f"Expected {expected}, got {result}",
        )

    def test_single_element(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'format_scores', None)
        names = ["Sam"]
        scores = [70]
        expected = ["1. Sam scored 70"]
        result = func(names, scores) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Works for single element lists.",
            f"Expected {expected}, got {result}",
        )

    def test_non_string_names(self):
        import user_code
        importlib.reload(user_code)
        func = getattr(user_code, 'format_scores', None)
        names = ["Anna", 123, "Mark"]
        scores = [88, 77, 66]
        expected = [
            "1. Anna scored 88",
            "2. 123 scored 77",
            "3. Mark scored 66"
        ]
        result = func(names, scores) if func else None
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Handles non-string names by stringifying them.",
            f"Expected {expected}, 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

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: Built-In Iterators in Use

Solução