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

class TestTask(unittest.TestCase):
    def test_only_long_strings_returned(self):
        import user_code
        importlib.reload(user_code)
        data = ["cat", "house", "sun", "elephant"]
        expected = ["house", "elephant"]
        result = user_code.filter_long_strings(data)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns only strings longer than 3 characters.",
            f"Expected {expected}, got {result}",
        )

    def test_returns_empty_list_when_none_long(self):
        import user_code
        importlib.reload(user_code)
        data = ["a", "be", "see"]
        expected = []
        result = user_code.filter_long_strings(data)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns empty list when no strings are longer than 3 characters.",
            f"Expected {expected}, got {result}",
        )

    def test_mixed_lengths_preserves_order(self):
        import user_code
        importlib.reload(user_code)
        data = ["dog", "tree", "sky", "river"]
        expected = ["tree", "river"]
        result = user_code.filter_long_strings(data)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Handles mix of short and long strings, preserves order.",
            f"Expected {expected}, got {result}",
        )

    def test_all_long_strings(self):
        import user_code
        importlib.reload(user_code)
        data = ["house", "river", "apple"]
        expected = ["house", "river", "apple"]
        result = user_code.filter_long_strings(data)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns all strings if all are longer than 3 characters.",
            f"Expected {expected}, got {result}",
        )

    def test_empty_input(self):
        import user_code
        importlib.reload(user_code)
        data = []
        expected = []
        result = user_code.filter_long_strings(data)
        _dynamic_test(
            self,
            isinstance(result, list) and result == expected,
            "Returns empty list for empty input.",
            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

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: Lambda con Filter

Soluzione