如何在Python中获得布尔值的相反（否定）？

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如何在Python中获得布尔值的相反（否定）？

2023-06-02 17:55| 来源: 网络整理| 查看: 265

The not operator (logical negation)

Probably the best way is using the operator not:

>>> value = True >>> not value False >>> value = False >>> not value True

So instead of your code:

if bool == True: return False else: return True

You could use:

return not bool The logical negation as function

There are also two functions in the operator module operator.not_ and it's alias operator.__not__ in case you need it as function instead of as operator:

>>> import operator >>> operator.not_(False) True >>> operator.not_(True) False

These can be useful if you want to use a function that requires a predicate-function or a callback.

For example map or filter:

>>> lst = [True, False, True, False] >>> list(map(operator.not_, lst)) [False, True, False, True] >>> lst = [True, False, True, False] >>> list(filter(operator.not_, lst)) [False, False]

Of course the same could also be achieved with an equivalent lambda function:

>>> my_not_function = lambda item: not item >>> list(map(my_not_function, lst)) [False, True, False, True] Do not use the bitwise invert operator ~ on booleans

One might be tempted to use the bitwise invert operator ~ or the equivalent operator function operator.inv (or one of the other 3 aliases there). But because bool is a subclass of int the result could be unexpected because it doesn't return the "inverse boolean", it returns the "inverse integer":

>>> ~True -2 >>> ~False -1

That's because True is equivalent to 1 and False to 0 and bitwise inversion operates on the bitwise representation of the integers 1 and 0.

So these cannot be used to "negate" a bool.

Negation with NumPy arrays (and subclasses)

If you're dealing with NumPy arrays (or subclasses like pandas.Series or pandas.DataFrame) containing booleans you can actually use the bitwise inverse operator (~) to negate all booleans in an array:

>>> import numpy as np >>> arr = np.array([True, False, True, False]) >>> ~arr array([False, True, False, True])

Or the equivalent NumPy function:

>>> np.bitwise_not(arr) array([False, True, False, True])

You cannot use the not operator or the operator.not function on NumPy arrays because these require that these return a single bool (not an array of booleans), however NumPy also contains a logical not function that works element-wise:

>>> np.logical_not(arr) array([False, True, False, True])

That can also be applied to non-boolean arrays:

>>> arr = np.array([0, 1, 2, 0]) >>> np.logical_not(arr) array([ True, False, False, True]) Customizing your own classes

not works by calling bool on the value and negate the result. In the simplest case the truth value will just call __bool__ on the object.

So by implementing (or in Python 2) you can customize the truth value and thus the result of not:

class Test(object): def __init__(self, value): self._value = value def __bool__(self): print('__bool__ called on {!r}'.format(self)) return bool(self._value) __nonzero__ = __bool__ # Python 2 compatibility def __repr__(self): return '{self.__class__.__name__}({self._value!r})'.format(self=self)

I added a print statement so you can verify that it really calls the method:

>>> a = Test(10) >>> not a __bool__ called on Test(10) False

Likewise you could implement the method to implement the behavior when ~ is applied:

class Test(object): def __init__(self, value): self._value = value def __invert__(self): print('__invert__ called on {!r}'.format(self)) return not self._value def __repr__(self): return '{self.__class__.__name__}({self._value!r})'.format(self=self)

Again with a print call to see that it is actually called:

>>> a = Test(True) >>> ~a __invert__ called on Test(True) False >>> a = Test(False) >>> ~a __invert__ called on Test(False) True

However implementing __invert__ like that could be confusing because it's behavior is different from "normal" Python behavior. If you ever do that clearly document it and make sure that it has a pretty good (and common) use-case.

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如何在Python中获得布尔值的相反（否定）？

如何在Python中获得布尔值的相反（否定）？

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