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The warning module provides the @deprecated decorator for marking functions as deprecated and the OptionalNumpyWarning class used to signal that NumPy is unavailable.

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deprecated

Decorator that marks a function as deprecated. Issues a configurable warning on every call. 
from alexber.utils.warning import deprecated

@deprecated(version='1.0', reason="Use `new_function` instead.", for_removal=True)
def old_function(x, y):
    """Returns the sum of two numbers."""
    return x + y

result = old_function(3, 4)
# DeprecationWarning: old_function is deprecated since version 1.0: Use `new_function` instead. and is marked for removal.
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version
str | None
default:"None"
The version since which the function is considered deprecated. Included in the warning message if provided.
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reason
str | None
default:"None"
Human-readable explanation for the deprecation (e.g. "Use new_func() instead."). Appended to the warning message.
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for_removal
bool
default:"False"
If True, the warning message ends with "and is marked for removal.". If False, it ends with "and will be removed in a future version.".
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warning_class
type[Warning]
default:"DeprecationWarning"
The warning class to issue. Override with PendingDeprecationWarning, FutureWarning, or a custom subclass as appropriate.
Returns: A decorator that wraps the target function, preserving its __name__, __doc__, and other attributes via functools.wraps.

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Warning message format

The constructed message follows this template: 
{func.__name__} is deprecated [since version {version}][: {reason}] and [is marked for removal | will be removed in a future version].

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OptionalNumpyWarning

A custom Warning subclass issued by alexber.utils.randoms when NumPy is not installed and the module falls back to the standard random library. 
import warnings
from alexber.utils.warning import OptionalNumpyWarning

# Suppress the warning if you intentionally run without NumPy:
warnings.filterwarnings('ignore', category=OptionalNumpyWarning)

from alexber.utils.randoms import Sampler
OptionalNumpyWarning is issued at import time of alexber.utils.randoms, not at sampling time. Suppress it before importing randoms if you deliberately work without NumPy.

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