Du kan bruge attributten `__name__` på ethvert funktionsobjekt i Python for at få dets navn som en streng. Når du skriver en dekoratør, kan du få adgang til den dekorerede funktions navn ved at bruge `func.__name__` inde i wrapperen. Dette er nyttigt til logning eller fejlfinding.


Bemærk


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

class TestTask(unittest.TestCase):
    def test_add_function_name_printed(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.add(10, 5)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "calling function: add" in output,
            "Function name 'add' is printed before execution",
            f"Expected function name 'add' in output, got: {output}",
        )

    def test_greet_function_name_printed(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.greet("Charlie")
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "calling function: greet" in output,
            "Function name 'greet' is printed before execution",
            f"Expected function name 'greet' in output, got: {output}",
        )

    def test_add_prints_args(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.add(1, 2)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "args=(1, 2)" in output,
            "Positional arguments are printed as tuple",
            f"Expected positional arguments '(1, 2)' in output, got: {output}",
        )

    def test_greet_prints_kwargs(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.greet("Bob", greeting="Hi")
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "kwargs={'greeting': 'hi'}" in output or 'kwargs={"greeting": "hi"}' in output,
            "Keyword arguments are printed as dictionary",
            f"Expected keyword arguments in output, got: {output}",
        )


    def test_decorator_return_value_unchanged(self):
        import user_code
        importlib.reload(user_code)
        res1 = user_code.add(7, 8)
        res2 = user_code.greet("Zoe", greeting="Hiya")
        _dynamic_test(
            self,
            res1 == 15 and res2 == "Hiya, Zoe!",
            "Decorator does not interfere with the function's return value",
            f"Expected 15 and 'Hiya, Zoe!', got {res1} and {res2}",
        )

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

Bliv ekspert i pakning/udpakning, fleksible funktionsargumenter, højere-ordens funktioner, lambdaer, variabelt omfang, closures, iteratorer og dekoratorer. Udviklet til kursister, der har gennemført et introduktionskursus i Python og ønsker at skrive mere effektiv, udtryksfuld og kraftfuld kode.

Udforsk kunsten at pakke og udpakke lister, tupler og ordbøger for at skrive mere udtryksfuld og effektiv Python-kode.

Dyk ned i verdenen af højereordensfunktioner, overførsel af funktioner som argumenter og skrivning af korte anonyme funktioner med lambda.

Opdag hemmelighederne bag variabelscope, og lær hvordan indlejrede funktioner og closures muliggør effektiv indkapsling.

Dyk ned i Pythons iterationsprotokol, brugerdefinerede iteratorer og generatorfunktioner for effektiv databehandling.

Challenge: Logging Decorator

Løsning