Kjeding av unntak og gjenoppretting av unntak er viktige ferdigheter for å bygge pålitelige Python-programmer. Når du fanger et unntak og må signalisere et nytt, kan det være ønskelig å bevare den opprinnelige feilkonteksten. Kjeding av unntak gjør dette mulig, og gir en fullstendig sporingsinformasjon som hjelper ved feilsøking. Gjenoppretting av unntak sikrer at feil ikke blir oversett, noe som gjør koden din mer robust og lettere å vedlikeholde. Øv på disse konseptene for å håndtere feil på en ryddig og gjennomsiktig måte i dine applikasjoner.


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

class TestTask(unittest.TestCase):
    def test_division_success(self):
        import user_code
        importlib.reload(user_code)
        result = user_code.safe_int_divide(10, 2)
        _dynamic_test(
            self,
            result == 5,
            "Returns correct integer division for (10, 2)",
            f"Expected 5, got {result}",
        )

    def test_zero_division_error_chained(self):
        import user_code
        importlib.reload(user_code)
        try:
            user_code.safe_int_divide(5, 0)
        except ValueError as ve:
            msg = str(ve)
            chained = ve.__cause__
            _dynamic_test(
                self,
                msg == "Cannot divide by zero" and isinstance(chained, ZeroDivisionError),
                "Raises ValueError with correct message and chains ZeroDivisionError",
                f"Expected ValueError('Cannot divide by zero') chained from ZeroDivisionError, got ValueError('{msg}') chained from {type(chained)}",
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "Should not raise other exception",
                f"Raised unexpected exception: {type(e)} {e}",
            )
        else:
            _dynamic_test(
                self,
                False,
                "Should raise ValueError for division by zero",
                "Did not raise ValueError for division by zero",
            )

    def test_other_exceptions_reraised(self):
        import user_code
        importlib.reload(user_code)
        class Dummy:
            def __floordiv__(self, other):
                raise RuntimeError("Custom error")
        d = Dummy()
        try:
            user_code.safe_int_divide(d, 2)
        except RuntimeError as e:
            _dynamic_test(
                self,
                str(e) == "Custom error",
                "Re-raises non-ZeroDivisionError exceptions unchanged",
                f"Expected RuntimeError('Custom error'), got {type(e)}('{e}')",
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "Should re-raise the original exception type",
                f"Raised unexpected exception: {type(e)} {e}",
            )
        else:
            _dynamic_test(
                self,
                False,
                "Should raise RuntimeError for Dummy object",
                "Did not raise any exception for Dummy object",
            )

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

Du vil tilegne deg praktiske ferdigheter i bruk av Python-moduler og import for effektiv kodehåndtering. Behersk avanserte teknikker for feilhåndtering for mer pålitelige applikasjoner, automatiser filoperasjoner med filhåndtering, og lær robuste teststrategier med Pytest og Unittest for å sikre kodeintegritet.

Master Python's exception system for robust error handling and debugging.

Explore advanced techniques for file operations and resource management using context managers.

Compare and apply Python's multithreading and multiprocessing modules for concurrent programming.

Master asynchronous programming in Python using the asyncio library for scalable I/O-bound applications.

Explore how to write, organize, and run tests using Python's unittest and pytest frameworks.

Utfordring: Kjedet Feilhåndtering

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