stouputils.decorators module#

This module provides decorators for various purposes:

silent(): Make a function silent (disable stdout, and stderr if specified) (alternative to stouputils.ctx.Muffle)
measure_time(): Measure the execution time of a function and print it with the given print function
handle_error(): Handle an error with different log levels
simple_cache(): Easy cache function with parameter caching method
deprecated(): Mark a function as deprecated

silent(func: Callable[[...], Any] | None = None, *, mute_stderr: bool = False) → Callable[[...], Any][source]#

Decorator that makes a function silent (disable stdout, and stderr if specified).

Alternative to stouputils.ctx.Muffle.

Parameters:

func (Callable[..., Any] | None) – Function to make silent
mute_stderr (bool) – Whether to mute stderr or not

Examples

>>> @silent
... def test():
...     print("Hello, world!")
>>> test()

>>> @silent(mute_stderr=True)
... def test2():
...     print("Hello, world!")
>>> test2()

>>> silent(print)("Hello, world!")

measure_time(print_func: ~typing.Callable[[...], None] = <function debug>, message: str = '', perf_counter: bool = True) → Callable[[...], Any][source]#

Decorator that will measure the execution time of a function and print it with the given print function

Parameters:

print_func (Callable) – Function to use to print the execution time (e.g. debug, info, warning, error, etc.)
message (str) – Message to display with the execution time (e.g. “Execution time of Something”), defaults to “Execution time of {func.__name__}”
perf_counter (bool) – Whether to use time.perf_counter_ns or time.time_ns

Returns:

Decorator to measure the time of the function.

Return type:

Callable

Examples

> @measure_time(info)
> def test():
>     pass
> test()  # [INFO HH:MM:SS] Execution time of test: 0.000ms (400ns)

class LogLevels(value)[source]#

Bases: Enum

Log level for the errors in the decorator handle_error()

NONE = 0#: Do nothing

WARNING = 1#: Show as warning

WARNING_TRACEBACK = 2#: Show as warning with traceback

ERROR_TRACEBACK = 3#: Show as error with traceback

RAISE_EXCEPTION = 4#: Raise exception

force_raise_exception: bool = False#: If true, the error_log parameter will be set to RAISE_EXCEPTION for every next handle_error calls, useful for doctests

handle_error(func: ~typing.Callable[[...], ~typing.Any] | None = None, *, exceptions: tuple[type[BaseException], ...] | type[BaseException] = (<class 'Exception'>,), message: str = '', error_log: ~stouputils.decorators.LogLevels = LogLevels.WARNING_TRACEBACK) → Callable[[...], Any][source]#

Decorator that handle an error with different log levels.

Parameters:

func (Callable[..., Any] | None) – Function to decorate
exceptions (tuple[type[BaseException]], ...) – Exceptions to handle
message (str) – Message to display with the error. (e.g. “Error during something”)
error_log (LogLevels) – Log level for the errors LogLevels.NONE: None LogLevels.WARNING: Show as warning LogLevels.WARNING_TRACEBACK: Show as warning with traceback LogLevels.ERROR_TRACEBACK: Show as error with traceback LogLevels.RAISE_EXCEPTION: Raise exception

Examples

>>> @handle_error
... def might_fail():
...     raise ValueError("Let's fail")

>>> @handle_error(error_log=LogLevels.WARNING)
... def test():
...     raise ValueError("Let's fail")
>>> # test()    # [WARNING HH:MM:SS] Error during test: (ValueError) Let's fail

simple_cache(func: Callable[[...], Any] | None = None, *, method: Literal['str', 'pickle'] = 'str') → Callable[[...], Any][source]#

Decorator that caches the result of a function based on its arguments.

The str method is often faster than the pickle method (by a little).

Parameters:

func (Callable[..., Any] | None) – Function to cache
method (Literal["str", "pickle"]) – The method to use for caching.

Returns:

A decorator that caches the result of a function.

Return type:

Callable[…, Any]

Examples

>>> @simple_cache
... def test1(a: int, b: int) -> int:
...     return a + b

>>> @simple_cache(method="str")
... def test2(a: int, b: int) -> int:
...     return a + b
>>> test2(1, 2)
3
>>> test2(1, 2)
3
>>> test2(3, 4)
7

deprecated(func: Callable[[...], Any] | None = None, *, message: str = '', error_log: LogLevels = LogLevels.WARNING) → Callable[[...], Any][source]#

Decorator that marks a function as deprecated.

Parameters:

func (Callable[..., Any] | None) – Function to mark as deprecated
message (str) – Additional message to display with the deprecation warning
error_log (LogLevels) – Log level for the deprecation warning LogLevels.NONE: None LogLevels.WARNING: Show as warning LogLevels.WARNING_TRACEBACK: Show as warning with traceback LogLevels.ERROR_TRACEBACK: Show as error with traceback LogLevels.RAISE_EXCEPTION: Raise exception

Returns:

Decorator that marks a function as deprecated

Return type:

Callable[…, Any]

Examples

>>> @deprecated
... def old_function():
...     pass

>>> @deprecated(message="Use 'new_function()' instead", error_log=LogLevels.WARNING)
... def another_old_function():
...     pass

abstract(func: Callable[[...], Any] | None = None, *, error_log: LogLevels = LogLevels.RAISE_EXCEPTION) → Callable[[...], Any][source]#

Decorator that marks a function as abstract.

Contrary to the abstractmethod decorator from the abc module that raises a TypeError when you try to instantiate a class that has abstract methods, this decorator raises a NotImplementedError ONLY when the decorated function is called, indicating that the function must be implemented by a subclass.

Parameters:

func (Callable[..., Any] | None) – The function to mark as abstract
error_log (LogLevels) – Log level for the error handling LogLevels.NONE: None LogLevels.WARNING: Show as warning LogLevels.WARNING_TRACEBACK: Show as warning with traceback LogLevels.ERROR_TRACEBACK: Show as error with traceback LogLevels.RAISE_EXCEPTION: Raise exception

Returns:

Decorator that raises NotImplementedError when called

Return type:

Callable[…, Any]

Examples

>>> class Base:
...     @abstract
...     def method(self):
...         pass
>>> Base().method()
Traceback (most recent call last):
        ...
NotImplementedError: Function 'method' is abstract and must be implemented by a subclass

stouputils.decorators module#

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