ai-content-maker/.venv/Lib/site-packages/sklearn/utils/_available_if.py

94 lines
2.8 KiB
Python

from functools import update_wrapper, wraps
from types import MethodType
class _AvailableIfDescriptor:
"""Implements a conditional property using the descriptor protocol.
Using this class to create a decorator will raise an ``AttributeError``
if check(self) returns a falsey value. Note that if check raises an error
this will also result in hasattr returning false.
See https://docs.python.org/3/howto/descriptor.html for an explanation of
descriptors.
"""
def __init__(self, fn, check, attribute_name):
self.fn = fn
self.check = check
self.attribute_name = attribute_name
# update the docstring of the descriptor
update_wrapper(self, fn)
def _check(self, obj, owner):
attr_err_msg = (
f"This {repr(owner.__name__)} has no attribute {repr(self.attribute_name)}"
)
try:
check_result = self.check(obj)
except Exception as e:
raise AttributeError(attr_err_msg) from e
if not check_result:
raise AttributeError(attr_err_msg)
def __get__(self, obj, owner=None):
if obj is not None:
# delegate only on instances, not the classes.
# this is to allow access to the docstrings.
self._check(obj, owner=owner)
out = MethodType(self.fn, obj)
else:
# This makes it possible to use the decorated method as an unbound method,
# for instance when monkeypatching.
@wraps(self.fn)
def out(*args, **kwargs):
self._check(args[0], owner=owner)
return self.fn(*args, **kwargs)
return out
def available_if(check):
"""An attribute that is available only if check returns a truthy value.
Parameters
----------
check : callable
When passed the object with the decorated method, this should return
a truthy value if the attribute is available, and either return False
or raise an AttributeError if not available.
Returns
-------
callable
Callable makes the decorated method available if `check` returns
a truthy value, otherwise the decorated method is unavailable.
Examples
--------
>>> from sklearn.utils.metaestimators import available_if
>>> class HelloIfEven:
... def __init__(self, x):
... self.x = x
...
... def _x_is_even(self):
... return self.x % 2 == 0
...
... @available_if(_x_is_even)
... def say_hello(self):
... print("Hello")
...
>>> obj = HelloIfEven(1)
>>> hasattr(obj, "say_hello")
False
>>> obj.x = 2
>>> hasattr(obj, "say_hello")
True
>>> obj.say_hello()
Hello
"""
return lambda fn: _AvailableIfDescriptor(fn, check, attribute_name=fn.__name__)