Je kunt het attribuut `__name__` van elk functieobject in Python gebruiken om de naam van de functie als een string op te halen. Bij het schrijven van een decorator kun je de naam van de gedecoreerde functie benaderen met `func.__name__` binnen de wrapper. Dit is handig voor logging of foutopsporing.


Opmerking


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

Beheers het inpakken/uitpakken, flexibele functieargumenten, hogere-orde functies, lambda's, variabele scope, closures, iterators en decorators. Ontworpen voor cursisten die een inleidende Python-cursus hebben afgerond en efficiëntere, expressievere en krachtigere code willen schrijven.

Ontdek de kunst van het inpakken en uitpakken van lijsten, tuples en dictionaries om expressievere en efficiëntere Python-code te schrijven.

Verdiep je in de wereld van hogere-orde functies, het doorgeven van functies als argumenten en het schrijven van beknopte anonieme functies met lambda.

Ontrafel de mysteries van variabele scope en ontdek hoe geneste functies en closures krachtige encapsulatie mogelijk maken.

Verdiep u in het iteratieprotocol van Python, aangepaste iterators en generatorfuncties voor efficiënte gegevensverwerking.

Challenge: Logging Decorator

Oplossing