我有一个变量x,我想知道它是否指向一个函数。

我希望我能做一些像这样的事情:

>>> isinstance(x, function)

但这给了我:

Traceback (most recent call last):
  File "<stdin>", line 1, in ?
NameError: name 'function' is not defined

我选这个是因为

>>> type(x)
<type 'function'>

当前回答

在内置命名空间中没有构造函数的内置类型(例如函数、生成器、方法)在types模块中。你可以使用类型。isinstance调用中的函数类型:

>>> import types
>>> types.FunctionType
<class 'function'>

>>> def f(): pass

>>> isinstance(f, types.FunctionType)
True
>>> isinstance(lambda x : None, types.FunctionType)
True

注意,这里使用了一个非常具体的“函数”概念,这通常不是您所需要的。例如,它拒绝zip(严格来说是一个类):

>>> type(zip), isinstance(zip, types.FunctionType)
(<class 'type'>, False)

Open(内置函数有不同类型):

>>> type(open), isinstance(open, types.FunctionType)
(<class 'builtin_function_or_method'>, False)

和随机的。Shuffle(技术上是一种隐藏随机的方法。随机实例):

>>> type(random.shuffle), isinstance(random.shuffle, types.FunctionType)
(<class 'method'>, False)

如果你在做一些特定类型的事情。FunctionType实例,如反编译字节码或检查闭包变量,使用类型。FunctionType,但如果你只是需要一个对象像函数一样可调用,请使用callable。

其他回答

由于类也有__call__方法,我推荐另一种解决方案:

class A(object):
    def __init__(self):
        pass
    def __call__(self):
        print 'I am a Class'

MyClass = A()

def foo():
    pass

print hasattr(foo.__class__, 'func_name') # Returns True
print hasattr(A.__class__, 'func_name')   # Returns False as expected

print hasattr(foo, '__call__') # Returns True
print hasattr(A, '__call__')   # (!) Returns True while it is not a function

结果

callable(x) hasattr(x, '__call__') inspect.isfunction(x) inspect.ismethod(x) inspect.isgeneratorfunction(x) inspect.iscoroutinefunction(x) inspect.isasyncgenfunction(x) isinstance(x, typing.Callable) isinstance(x, types.BuiltinFunctionType) isinstance(x, types.BuiltinMethodType) isinstance(x, types.FunctionType) isinstance(x, types.MethodType) isinstance(x, types.LambdaType) isinstance(x, functools.partial)
print × × × × × × × × ×
func × × × × × × × ×
functools.partial × × × × × × × × × ×
<lambda> × × × × × × × ×
generator × × × × × × ×
async_func × × × × × × ×
async_generator × × × × × × ×
A × × × × × × × × × × ×
meth × × × × × × × ×
classmeth × × × × × × × × ×
staticmeth × × × × × × × ×
import types
import inspect
import functools
import typing


def judge(x):
    name = x.__name__ if hasattr(x, '__name__') else 'functools.partial'
    print(name)
    print('\ttype({})={}'.format(name, type(x)))
    print('\tcallable({})={}'.format(name, callable(x)))
    print('\thasattr({}, \'__call__\')={}'.format(name, hasattr(x, '__call__')))
    print()
    print('\tinspect.isfunction({})={}'.format(name, inspect.isfunction(x)))
    print('\tinspect.ismethod({})={}'.format(name, inspect.ismethod(x)))
    print('\tinspect.isgeneratorfunction({})={}'.format(name, inspect.isgeneratorfunction(x)))
    print('\tinspect.iscoroutinefunction({})={}'.format(name, inspect.iscoroutinefunction(x)))
    print('\tinspect.isasyncgenfunction({})={}'.format(name, inspect.isasyncgenfunction(x)))
    print()
    print('\tisinstance({}, typing.Callable)={}'.format(name, isinstance(x, typing.Callable)))
    print('\tisinstance({}, types.BuiltinFunctionType)={}'.format(name, isinstance(x, types.BuiltinFunctionType)))
    print('\tisinstance({}, types.BuiltinMethodType)={}'.format(name, isinstance(x, types.BuiltinMethodType)))
    print('\tisinstance({}, types.FunctionType)={}'.format(name, isinstance(x, types.FunctionType)))
    print('\tisinstance({}, types.MethodType)={}'.format(name, isinstance(x, types.MethodType)))
    print('\tisinstance({}, types.LambdaType)={}'.format(name, isinstance(x, types.LambdaType)))
    print('\tisinstance({}, functools.partial)={}'.format(name, isinstance(x, functools.partial)))


def func(a, b):
    pass


partial = functools.partial(func, a=1)

_lambda = lambda _: _


def generator():
    yield 1
    yield 2


async def async_func():
    pass


async def async_generator():
    yield 1


class A:
    def __call__(self, a, b):
        pass

    def meth(self, a, b):
        pass

    @classmethod
    def classmeth(cls, a, b):
        pass

    @staticmethod
    def staticmeth(a, b):
        pass


for func in [print,
             func,
             partial,
             _lambda,
             generator,
             async_func,
             async_generator,
             A,
             A.meth,
             A.classmeth,
             A.staticmeth]:
    judge(func)

Time

选择三种最常见的方法:

可调用的(x) hasattr (x, __call__) isinstance (x, typing.Callable)

time/s
callable(x) 0.86
hasattr(x, '__call__') 1.36
isinstance(x, typing.Callable) 12.19
import typing
from timeit import timeit


def x():
    pass


def f1():
    return callable(x)


def f2():
    return hasattr(x, '__call__')


def f3():
    return isinstance(x, typing.Callable)


print(timeit(f1, number=10000000))
print(timeit(f2, number=10000000))
print(timeit(f3, number=10000000))
# 0.8643081
# 1.3563508
# 12.193492500000001

被接受的答案在当时被认为是正确的。因为它 结果是,没有callable()的替代品,这又回到了Python中 3.2:具体来说,callable()检查对象的tp_call字段 测试。在普通的Python中没有对等的。大多数建议的测试都是 大多数时候是正确的:

>>> class Spam(object):
...     def __call__(self):
...         return 'OK'
>>> can_o_spam = Spam()


>>> can_o_spam()
'OK'
>>> callable(can_o_spam)
True
>>> hasattr(can_o_spam, '__call__')
True
>>> import collections
>>> isinstance(can_o_spam, collections.Callable)
True

方法中删除__call__来解决这个问题 类。为了让事情更有趣,在实例中添加一个假__call__ !

>>> del Spam.__call__
>>> can_o_spam.__call__ = lambda *args: 'OK?'

注意这个真的是不可调用的:

>>> can_o_spam()
Traceback (most recent call last):
  ...
TypeError: 'Spam' object is not callable

Callable()返回正确的结果:

>>> callable(can_o_spam)
False

但是hasattr错了:

>>> hasattr(can_o_spam, '__call__')
True

Can_o_spam确实有这个属性;它只是在调用时不使用 实例。

更微妙的是,isinstance()也会出错:

>>> isinstance(can_o_spam, collections.Callable)
True

因为我们之前使用了这个检查,后来删除了方法abc。ABCMeta 缓存结果。可以说这是abc.ABCMeta中的一个bug。也就是说, 没有比这更准确的结果了 结果比使用callable()本身,因为typeobject->tp_call 槽方法不能以任何其他方式访问。

只需使用callable()

作为公认的答案,John Feminella说:

检查鸭子类型对象属性的正确方法是询问它们是否嘎嘎叫,而不是查看它们是否适合鸭子大小的容器。“直接比较”的方法会对许多函数给出错误的答案,比如内置函数。

尽管有两个库来严格区分函数,但我画了一个详尽的可比表:

8.9. 内置类型的动态类型创建和名称。Python 3.7.0文档

30.13. inspect -检查活动对象- Python 3.7.0文档

#import inspect             #import types
['isabstract',
 'isasyncgen',              'AsyncGeneratorType',
 'isasyncgenfunction', 
 'isawaitable',
 'isbuiltin',               'BuiltinFunctionType',
                            'BuiltinMethodType',
 'isclass',
 'iscode',                  'CodeType',
 'iscoroutine',             'CoroutineType',
 'iscoroutinefunction',
 'isdatadescriptor',
 'isframe',                 'FrameType',
 'isfunction',              'FunctionType',
                            'LambdaType',
                            'MethodType',
 'isgenerator',             'GeneratorType',
 'isgeneratorfunction',
 'ismethod',
 'ismethoddescriptor',
 'ismodule',                'ModuleType',        
 'isroutine',            
 'istraceback',             'TracebackType'
                            'MappingProxyType',
]

“duck typing”是一般用途的首选解决方案:

def detect_function(obj):
    return hasattr(obj,"__call__")

In [26]: detect_function(detect_function)
Out[26]: True
In [27]: callable(detect_function)
Out[27]: True

至于内置函数

In [43]: callable(hasattr)
Out[43]: True

当进一步检查是内置函数还是用户定义函数

#check inspect.isfunction and type.FunctionType
In [46]: inspect.isfunction(detect_function)
Out[46]: True
In [47]: inspect.isfunction(hasattr)
Out[47]: False
In [48]: isinstance(detect_function, types.FunctionType)
Out[48]: True
In [49]: isinstance(getattr, types.FunctionType)
Out[49]: False
#so they both just applied to judge the user-definded

确定是否内置函数

In [50]: isinstance(getattr, types.BuiltinFunctionType)
Out[50]: True
In [51]: isinstance(detect_function, types.BuiltinFunctionType)
Out[51]: False

总结

采用可调用鸭类型检查函数, 使用类型。如果您有进一步指定的需求,请使用BuiltinFunctionType。

根据之前的回复,我想出了这个:

from pprint import pprint

def print_callables_of(obj):
    li = []
    for name in dir(obj):
        attr = getattr(obj, name)
        if hasattr(attr, '__call__'):
            li.append(name)
    pprint(li)