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decorative_secrets.utilities

get_logger 

get_logger(
    name: str | None = None,
    level: int | None = None,
    formatter: (
        logging.Formatter
        | type[logging.Formatter]
        | str
        | None
    ) = None,
    stream: (
        typing.TextIO | pathlib.Path | str | None
    ) = None,
    *,
    propagate: bool | None = None
) -> logging.Logger

Get a non-blocking logger.

Parameters:

  • name (str | None, default: None ) –

    Logger name, typically the __name__ of the calling module.

  • level (int | None, default: None ) –

    Optional log level to set on the logger and handlers. If not specified, defaults to logging.INFO if creating a new logger, otherwise uses the existing logger's level.

  • formatter (logging.Formatter | type[logging.Formatter] | str | None, default: None ) –

    Optional formatter to use for the logger. Can be an instance of logging.Formatter, a subclass of logging.Formatter, or a format string.

  • propagate (bool | None, default: None ) –

    Whether the logger should propagate messages to the root logger. If None (the default), propagation is left unchanged for an existing logger and defaults to True for a new one.

  • stream (typing.TextIO | pathlib.Path | str | None, default: None ) –

    A file-like object or path to write the log to.

Example 
import logging
import sys
from decorative_secrets.utilities import get_logger

log: logging.Logger = get_logger(
    __name__,
    formatter="%(asctime)s [%(levelname)s] %(message)s",
    stream=sys.stdout,
)
Source code in src/decorative_secrets/utilities.py 
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def get_logger(
    name: str | None = None,
    level: int | None = None,
    formatter: logging.Formatter | type[logging.Formatter] | str | None = None,
    stream: TextIO | Path | str | None = None,
    *,
    propagate: bool | None = None,
) -> logging.Logger:
    """
    Get a non-blocking logger.

    Parameters:
        name: Logger name, typically the `__name__` of the calling module.
        level: Optional log level to set on the logger and handlers. If not
            specified, defaults to `logging.INFO` if creating a new
            logger, otherwise uses the existing logger's level.
        formatter: Optional formatter to use for the logger. Can be an instance
            of `logging.Formatter`, a subclass of `logging.Formatter`, or a
            format string.
        propagate: Whether the logger should propagate messages to the root
            logger. If `None` (the default), propagation is left unchanged
            for an existing logger and defaults to `True` for a new one.
        stream: A file-like object or path to write the log to.

    Example:
        ```python
        import logging
        import sys
        from decorative_secrets.utilities import get_logger

        log: logging.Logger = get_logger(
            __name__,
            formatter="%(asctime)s [%(levelname)s] %(message)s",
            stream=sys.stdout,
        )
        ```
    """
    logger: logging.Logger = logging.getLogger(name)
    if logger.handlers:
        if propagate is not None:
            logger.propagate = propagate
        if level is not None:
            logger.setLevel(level)
            for handler in logger.handlers:
                handler.setLevel(level)
                # Also update the downstream handlers owned by the
                # `QueueListener`. The listener is created with
                # `respect_handler_level=True`, so a level set only on the
                # logger and its `QueueHandler` would still be enforced at
                # the original (higher) level here, dropping records the
                # logger now permits.
                listener: QueueListener | None = getattr(
                    handler, "listener", None
                )
                if listener is not None:
                    for downstream_handler in listener.handlers:
                        downstream_handler.setLevel(level)
    else:
        level = level if (level is not None) else logging.INFO
        logger.setLevel(level)
        logger.propagate = True if propagate is None else propagate
        log_queue: queue.Queue = queue.Queue(-1)
        log_queue_listener: QueueListener
        stream_handler: logging.StreamHandler
        if stream is not None:
            if isinstance(stream, str | Path):
                stream = open(stream, "w")  # noqa: SIM115
                atexit.register(stream.close)
            stream_handler = logging.StreamHandler(stream)
        else:
            stream_handler = logging.StreamHandler()
        stream_handler.setLevel(level)
        log_queue_listener = QueueListener(
            log_queue, stream_handler, respect_handler_level=True
        )
        queue_handler: QueueHandler = QueueHandler(log_queue)
        # Store the listener on the handler so a later `get_logger` call can
        # reach (and re-level) the listener's downstream handlers. The
        # stdlib `QueueHandler` has no `listener` attribute, so this is set
        # unconditionally rather than guarded behind `hasattr`.
        queue_handler.listener = log_queue_listener  # type: ignore[attr-defined]
        queue_handler.setLevel(level)
        if formatter is not None:
            stream_handler.setFormatter(
                logging.Formatter(formatter)
                if isinstance(formatter, str)
                else formatter()
                if isinstance(formatter, type)
                else formatter
            )
        logger.addHandler(queue_handler)
        log_queue_listener.start()
        atexit.register(log_queue_listener.stop)
    return logger

iscoroutinefunction 

iscoroutinefunction(function: typing.Any) -> bool

An adaptation of asyncio.iscoroutinefunction

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def iscoroutinefunction(function: Any) -> bool:
    """
    An adaptation of `asyncio.iscoroutinefunction`
    """
    if isinstance(function, partial):
        return iscoroutinefunction(function.func)
    return (
        inspect.iscoroutinefunction(function)
        or type(getattr(function, "_is_coroutine", None)) is object
    )

as_tuple 

as_tuple(
    function: collections.abc.Callable[
        ...,
        collections.abc.Iterable[typing.Any]
        | collections.abc.Awaitable[
            collections.abc.Iterable[typing.Any]
        ],
    ],
) -> collections.abc.Callable[..., typing.Any]

This is a decorator which will return an iterable as a tuple.

Examples:

from decorative_secrets.utilities import as_tuple


@as_tuple
def get_numbers() -> Iterable[int]:
    yield 1
    yield 2
    yield 3


assert get_numbers() == (1, 2, 3)
Source code in src/decorative_secrets/utilities.py 
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def as_tuple(
    function: Callable[..., Iterable[Any] | Awaitable[Iterable[Any]]],
) -> Callable[..., Any]:
    """
    This is a decorator which will return an iterable as a tuple.

    Examples:
        ```python
        from decorative_secrets.utilities import as_tuple


        @as_tuple
        def get_numbers() -> Iterable[int]:
            yield 1
            yield 2
            yield 3


        assert get_numbers() == (1, 2, 3)
        ```
    """
    if iscoroutinefunction(function):

        @wraps(function)
        async def wrapper(*args: Any, **kwargs: Any) -> tuple[Any, ...]:
            return tuple(  # --
                await function(*args, **kwargs) or ()  # type: ignore[misc]
            )

    else:

        @wraps(function)
        def wrapper(*args: Any, **kwargs: Any) -> tuple[Any, ...]:
            return tuple(
                function(*args, **kwargs) or ()  # type: ignore[arg-type]
            )

    return wrapper

as_str 

as_str(
    function: None = None, separator: str = ""
) -> collections.abc.Callable[
    ..., collections.abc.Callable[..., str]
]

as_str(
    function: collections.abc.Callable[
        ..., collections.abc.Iterable[str]
    ] = ...,
    separator: str = "",
) -> collections.abc.Callable[..., str]

as_str(
    function: (
        collections.abc.Callable[
            ..., collections.abc.Iterable[str]
        ]
        | collections.abc.Awaitable[
            collections.abc.Iterable[typing.Any]
        ]
        | None
    ) = None,
    separator: str = "",
) -> (
    collections.abc.Callable[
        ..., collections.abc.Callable[..., str]
    ]
    | collections.abc.Callable[..., str]
)

This decorator causes a function yielding an iterable of strings to
return a single string with the elements joined by the specified
`separator`.

Parameters:
    function: The function to decorate. If `None`, a decorating
        function is returned.
    separator: The string used to join the iterable elements.

Returns:
    A decorator which joins the iterable elements into a single string.

Examples:
    ```python
    from decorative_secrets.utilities import as_str


    @as_str(separator=", ")
    def get_fruits() -> Iterable[str]:
        yield "apple"
        yield "banana"
        yield "cherry"


    assert get_fruits() == "apple, banana, cherry"
    ```

    ```python
    from decorative_secrets.utilities import as_str


    @as_str
    def get_fruits() -> Iterable[str]:
        yield "apple

" yield "banana " yield "cherry"

    assert get_fruits() == "apple

banana cherry" ```

Source code in src/decorative_secrets/utilities.py 
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def as_str(
    function: Callable[..., Iterable[str]]
    | Awaitable[Iterable[Any]]
    | None = None,
    separator: str = "",
) -> Callable[..., Callable[..., str]] | Callable[..., str]:
    """
    This decorator causes a function yielding an iterable of strings to
    return a single string with the elements joined by the specified
    `separator`.

    Parameters:
        function: The function to decorate. If `None`, a decorating
            function is returned.
        separator: The string used to join the iterable elements.

    Returns:
        A decorator which joins the iterable elements into a single string.

    Examples:
        ```python
        from decorative_secrets.utilities import as_str


        @as_str(separator=", ")
        def get_fruits() -> Iterable[str]:
            yield "apple"
            yield "banana"
            yield "cherry"


        assert get_fruits() == "apple, banana, cherry"
        ```

        ```python
        from decorative_secrets.utilities import as_str


        @as_str
        def get_fruits() -> Iterable[str]:
            yield "apple\n"
            yield "banana\n"
            yield "cherry"


        assert get_fruits() == "apple\nbanana\ncherry"
        ```
    """

    def decorating_function(
        user_function: Callable[..., Iterable[str]],
    ) -> Callable[..., Any]:
        if iscoroutinefunction(user_function):

            @wraps(user_function)
            async def wrapper(*args: Any, **kwargs: Any) -> str:
                return separator.join(
                    await user_function(  # type: ignore[misc]
                        *args, **kwargs
                    )
                    or ()
                )

        else:

            @wraps(user_function)
            def wrapper(*args: Any, **kwargs: Any) -> str:
                return separator.join(user_function(*args, **kwargs) or ())

        return wrapper

    if function is None:
        return decorating_function
    return decorating_function(function)  # type: ignore[arg-type]

as_dict 

as_dict(
    function: collections.abc.Callable[
        ...,
        collections.abc.Iterable[
            tuple[typing.Any, typing.Any]
        ]
        | collections.abc.Awaitable[
            collections.abc.Iterable[
                tuple[typing.Any, typing.Any]
            ]
        ],
    ],
) -> collections.abc.Callable[..., typing.Any]

This is a decorator which will return an iterable of key/value pairs as a dictionary.

Examples:

from decorative_secrets.utilities import as_dict


@as_dict
def get_settings() -> Iterable[tuple[str, Any]]:
    yield ("host", "localhost")
    yield ("port", 8080)
    yield ("debug", True)


assert get_settings() == (
    {"host": "localhost", "port": 8080, "debug": True}
)
Source code in src/decorative_secrets/utilities.py 
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def as_dict(
    function: Callable[
        ..., Iterable[tuple[Any, Any]] | Awaitable[Iterable[tuple[Any, Any]]]
    ],
) -> Callable[..., Any]:
    """
    This is a decorator which will return an iterable of key/value pairs
    as a dictionary.

    Examples:
        ```python
        from decorative_secrets.utilities import as_dict


        @as_dict
        def get_settings() -> Iterable[tuple[str, Any]]:
            yield ("host", "localhost")
            yield ("port", 8080)
            yield ("debug", True)


        assert get_settings() == (
            {"host": "localhost", "port": 8080, "debug": True}
        )
        ```
    """

    if iscoroutinefunction(function):

        @wraps(function)
        async def wrapper(*args: Any, **kwargs: Any) -> dict[Any, Any]:
            return dict(
                await function(*args, **kwargs) or ()  # type: ignore[misc]
            )

    else:

        @wraps(function)
        def wrapper(*args: Any, **kwargs: Any) -> dict[Any, Any]:
            return dict(
                function(*args, **kwargs) or ()  # type: ignore[arg-type]
            )

    return wrapper

as_iter 

as_iter(
    function: collections.abc.Callable[
        ..., collections.abc.Iterable[typing.Any]
    ],
) -> collections.abc.Callable[..., typing.Any]

This is a decorator which will return an iterator for a function yielding an iterable.

Examples:

from decorative_secrets.utilities import as_iter
from collections.abc import Iterator


@as_iter
def get_settings() -> Iterable[tuple[str, Any]]:
    yield ("host", "localhost")
    yield ("port", 8080)
    yield ("debug", True)


assert issubclass(get_settings(), Iterator)
Source code in src/decorative_secrets/utilities.py 
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def as_iter(
    function: Callable[..., Iterable[Any]],
) -> Callable[..., Any]:
    """
    This is a decorator which will return an iterator for a function
    yielding an iterable.

    Examples:
        ```python
        from decorative_secrets.utilities import as_iter
        from collections.abc import Iterator


        @as_iter
        def get_settings() -> Iterable[tuple[str, Any]]:
            yield ("host", "localhost")
            yield ("port", 8080)
            yield ("debug", True)


        assert issubclass(get_settings(), Iterator)
        ```
    """

    if iscoroutinefunction(function):

        @wraps(function)
        async def wrapper(*args: Any, **kwargs: Any) -> Iterator[Any]:
            return iter(
                await function(*args, **kwargs) or ()  # type: ignore[misc]
            )

    else:

        @wraps(function)
        def wrapper(*args: Any, **kwargs: Any) -> Iterator[Any]:
            return iter(function(*args, **kwargs) or ())

    return wrapper

warn_retry_hook 

warn_retry_hook(
    error: Exception,
    attempt_number: int,
    *args: typing.Any,
    **kwargs: typing.Any
) -> bool

This is a retry hook which will issue a warning and retry number whenever an error occurs.

Source code in src/decorative_secrets/utilities.py 
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def warn_retry_hook(
    error: Exception,
    attempt_number: int,
    *args: Any,  # noqa: ARG001
    **kwargs: Any,  # noqa: ARG001
) -> bool:
    """
    This is a retry hook which will issue a warning and retry number
    whenever an error occurs.
    """
    message: str = f"Attempt # {attempt_number} failed with error: {error}"
    warn(
        message,
        stacklevel=2,
    )
    return True

create_log_warning_retry_hook 

create_log_warning_retry_hook(
    logger: (
        logging.Logger
        | collections.abc.Callable[[], logging.Logger]
    ),
) -> decorative_secrets.utilities.RetryHook

This factory creates a retry hook which logs warning using the provided logger.

Parameters:

  • logger (logging.Logger | collections.abc.Callable[[], logging.Logger]) –

    The logger to use for logging warnings, or a callable which

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def create_log_warning_retry_hook(
    logger: logging.Logger | Callable[[], logging.Logger],
) -> RetryHook:
    """
    This factory creates a retry hook which logs warning using the provided
    logger.

    Parameters:
        logger: The logger to use for logging warnings, or a callable which
        returns a logger.
    """
    if not isinstance(logger, logging.Logger) and callable(logger):
        logger = logger()
    if not isinstance(logger, logging.Logger):
        raise TypeError(logger)

    def retry_hook(
        error: Exception,
        attempt_number: int,
        *args: Any,  # noqa: ARG001
        **kwargs: Any,  # noqa: ARG001
    ) -> bool:
        logger.warning(
            "Attempt # %d failed with error: %s",
            attempt_number,
            str(error),
            stacklevel=2,
        )
        return True

    return retry_hook

create_async_log_warning_retry_hook 

create_async_log_warning_retry_hook(
    logger: logging.Logger,
) -> decorative_secrets.utilities.AsyncRetryHook

This factory creates an async retry hook which logs warning using the provided logger.

!!! Note Please make sure to use a non-blocking logger .

Parameters:

  • logger (logging.Logger) –

    The logger to use for logging warnings.

Source code in src/decorative_secrets/utilities.py 
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def create_async_log_warning_retry_hook(
    logger: logging.Logger,
) -> AsyncRetryHook:
    """
    This factory creates an async retry hook which logs warning using the
    provided logger.

    !!! Note
        Please make sure to use a [non-blocking logger
        ](https://docs.python.org/3/howto/logging-cookbook.html#dealing-with-handlers-that-block).

    Parameters:
        logger: The logger to use for logging warnings.
    """

    async def retry_hook(
        error: Exception,
        attempt_number: int,
        *args: Any,  # noqa: ARG001
        **kwargs: Any,  # noqa: ARG001
    ) -> bool:
        logger.warning(
            "Attempt # %d failed with error: %s",
            attempt_number,
            str(error),
            stacklevel=2,
        )
        return True

    return retry_hook

retry 

retry(
    errors: tuple[type[Exception], ...],
    retry_hook: (
        decorative_secrets.utilities.RetryHook
        | decorative_secrets.utilities.AsyncRetryHook
    ) = decorative_secrets.utilities._default_retry_hook,
    number_of_attempts: int = 2,
) -> collections.abc.Callable

This is a decorator which will retry a function a specified number of times, with exponential backoff, if it raises one of the specified errors types.

Parameters:

  • errors (tuple[type[Exception], ...]) –

    A tuple of exception types which should trigger a retry.

  • retry_hook (decorative_secrets.utilities.RetryHook | decorative_secrets.utilities.AsyncRetryHook, default: decorative_secrets.utilities._default_retry_hook ) –

    A function which is called with the exception instance (optionally) and an attempt number when an error occurs. If this function returns False, the exception is re-raised and no further retries are attempted.

  • number_of_attempts (int, default: 2 ) –

    The total number of attempts to make, including the initial attempt.

Source code in src/decorative_secrets/utilities.py 
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def retry(  # noqa: C901
    errors: tuple[type[Exception], ...],
    retry_hook: RetryHook | AsyncRetryHook = _default_retry_hook,
    number_of_attempts: int = 2,
) -> Callable:
    """
    This is a decorator which will retry a function a specified
    number of times, with exponential backoff, if it raises one of the
    specified errors types.

    Parameters:
        errors: A tuple of exception types which should trigger a retry.
        retry_hook: A function which is called with the exception instance
            (optionally) and an attempt number when an error occurs. If this
            function returns `False`, the exception is re-raised and no further
            retries are attempted.
        number_of_attempts: The total number of attempts to make, including
            the initial attempt.
    """

    def decorating_function(function: Callable) -> Callable:
        if iscoroutinefunction(function):

            @wraps(function)
            async def wrapper(*args: Any, **kwargs: Any) -> Any:
                __attempt_number: int = kwargs.pop("__attempt_number", 1)
                if (number_of_attempts - __attempt_number) > 0:
                    # If `number_of_attempts` is greater than `attempt_number`,
                    # we have remaining attempts to try, so catch errors.
                    try:
                        return await function(*args, **kwargs)
                    except errors as error:
                        if not (
                            (
                                await retry_hook(  # type: ignore[misc]
                                    error, __attempt_number
                                )
                                if len(
                                    inspect.signature(retry_hook).parameters
                                )
                                > 1
                                else await retry_hook(  # type: ignore[misc]
                                    error
                                )
                            )
                            if iscoroutinefunction(retry_hook)
                            else (
                                retry_hook(error, __attempt_number)
                                if len(
                                    inspect.signature(retry_hook).parameters
                                )
                                > 1
                                else retry_hook(error)
                            )
                        ):
                            raise
                        await asyncio.sleep(2**__attempt_number)
                        __attempt_number += 1
                        return await wrapper(
                            *args, __attempt_number=__attempt_number, **kwargs
                        )
                # This is our last attempt, so just call the function.
                return await function(*args, **kwargs)

        else:

            @wraps(function)
            def wrapper(*args: Any, **kwargs: Any) -> Any:
                __attempt_number: int = kwargs.pop("__attempt_number", 1)
                if (number_of_attempts - __attempt_number) > 0:
                    try:
                        return function(*args, **kwargs)
                    except errors as error:
                        if not (
                            retry_hook(error, __attempt_number)
                            if len(inspect.signature(retry_hook).parameters)
                            > 1
                            else retry_hook(error)
                        ):
                            raise
                        sleep(2**__attempt_number)
                        __attempt_number += 1
                        return wrapper(
                            *args, __attempt_number=__attempt_number, **kwargs
                        )
                return function(*args, **kwargs)

        return wrapper

    return decorating_function

timeout 

timeout(
    seconds: float, *, use_signals: bool | None = None
) -> collections.abc.Callable[
    [collections.abc.Callable], collections.abc.Callable
]

This is a decorator which enforces a maximum execution time on the decorated function. If the function does not return within seconds, a TimeoutError is raised.

This works for both synchronous and asynchronous functions:

  • Asynchronous functions are bounded using asyncio.wait, which cancels the coroutine on timeout. asyncio.wait is used in preference to asyncio.wait_for so the timeout does not rely on current_task(), which is unavailable once a running loop has been patched by nest_asyncio.
  • Synchronous functions are bounded using signal.SIGALRM when it is available, the call originates from the main thread, and no other timeout is already active, which interrupts the function in place.
  • Otherwise (for example on Windows, when called from a non-main thread, or when nested inside another timeout), synchronous functions are run in a daemon thread. The daemon thread cannot be killed, so it continues running to completion after the TimeoutError is raised; if it subsequently raises, that exception is logged rather than silently discarded. A daemon thread is used so that such a call cannot block interpreter shutdown.

Parameters:

  • seconds (float) –

    The maximum number of seconds to allow. Must be greater than zero.

  • use_signals (bool | None, default: None ) –

    If False, the SIGALRM strategy is passed over in favor of the daemon-thread strategy even when SIGALRM is available. If True or None, the SIGALRM strategy is used when available, and the daemon-thread strategy is used otherwise.

Examples:

from time import sleep

from decorative_secrets.utilities import timeout


@timeout(0.1)
def slow() -> str:
    sleep(1)
    return "done"


try:
    slow()
except TimeoutError:
    print("timed out")
Source code in src/decorative_secrets/utilities.py 
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def timeout(
    seconds: float,
    *,
    use_signals: bool | None = None,
) -> Callable[[Callable], Callable]:
    """
    This is a decorator which enforces a maximum execution time on the
    decorated function. If the function does not return within `seconds`,
    a `TimeoutError` is raised.

    This works for both synchronous and asynchronous functions:

    -   Asynchronous functions are bounded using `asyncio.wait`, which
        cancels the coroutine on timeout. `asyncio.wait` is used in
        preference to `asyncio.wait_for` so the timeout does not rely on
        `current_task()`, which is unavailable once a running loop has been
        patched by `nest_asyncio`.
    -   Synchronous functions are bounded using `signal.SIGALRM` when it is
        available, the call originates from the main thread, and no other
        `timeout` is already active, which interrupts the function in
        place.
    -   Otherwise (for example on Windows, when called from a non-main
        thread, or when nested inside another `timeout`), synchronous
        functions are run in a daemon thread. The daemon thread cannot be
        killed, so it continues running to completion after the
        `TimeoutError` is raised; if it subsequently raises, that exception
        is logged rather than silently discarded. A daemon thread is used
        so that such a call cannot block interpreter shutdown.

    Parameters:
        seconds: The maximum number of seconds to allow. Must be greater
            than zero.
        use_signals: If `False`, the `SIGALRM` strategy is passed over
            in favor of the daemon-thread strategy even when `SIGALRM` is
            available. If `True` or `None`, the `SIGALRM` strategy is used when
            available, and the daemon-thread strategy is used otherwise.

    Examples:
        ```python
        from time import sleep

        from decorative_secrets.utilities import timeout


        @timeout(0.1)
        def slow() -> str:
            sleep(1)
            return "done"


        try:
            slow()
        except TimeoutError:
            print("timed out")
        ```
    """
    if seconds <= 0:
        raise ValueError(seconds)

    def decorating_function(function: Callable) -> Callable:
        message: str = (
            f"{function.__qualname__} timed out after {seconds} seconds"
        )
        if iscoroutinefunction(function):

            @wraps(function)
            async def wrapper(*args: Any, **kwargs: Any) -> Any:
                # `asyncio.wait` (rather than `asyncio.wait_for`) is used so
                # the timeout does not depend on `current_task()`: on Python
                # 3.12+, `wait_for` delegates to `asyncio.timeouts.timeout`,
                # which raises `RuntimeError("Timeout should be used inside a
                # task")` when no current task is set -- as happens once
                # `nest_asyncio` has patched the running loop (see
                # `decorative_secrets._utilities.asyncio_run`).
                task: asyncio.Future = asyncio.ensure_future(
                    function(*args, **kwargs)
                )

                async def _cancel_and_drain() -> None:
                    # Cancel the inner task and await it so the cancellation
                    # propagates into the coroutine rather than leaving it
                    # running in the background (and so any exception it
                    # raises is retrieved rather than reported as "Task
                    # exception was never retrieved").
                    task.cancel()
                    with contextlib.suppress(
                        asyncio.CancelledError, Exception
                    ):
                        await task

                try:
                    await asyncio.wait({task}, timeout=seconds)
                except asyncio.CancelledError:
                    # The caller cancelled this wrapper; drain the inner
                    # task before propagating the cancellation.
                    await _cancel_and_drain()
                    raise
                if task.done():
                    # Completed within the limit: return its value, or
                    # re-raise the exception it raised.
                    return task.result()
                # The call exceeded the limit; the documented contract is
                # that a timed-out call always raises `TimeoutError`.
                await _cancel_and_drain()
                raise TimeoutError(message) from None

        else:

            @wraps(function)
            def wrapper(*args: Any, **kwargs: Any) -> Any:
                if (use_signals is not False) and _can_use_sigalrm():
                    return _run_with_sigalrm_timeout(
                        function, seconds, message, args, kwargs
                    )
                return _run_with_thread_timeout(
                    function, seconds, message, args, kwargs
                )

        return wrapper

    return decorating_function

get_exception_text 

get_exception_text() -> str

When called within an exception, this function returns a text representation of the error matching what is found in traceback.print_exception, but is returned as a string value rather than printing.

Source code in src/decorative_secrets/utilities.py 
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def get_exception_text() -> str:
    """
    When called within an exception, this function returns a text
    representation of the error matching what is found in
    `traceback.print_exception`, but is returned as a string value rather than
    printing.
    """
    return "".join(format_exception(*sys.exc_info()))