在Python中，如果不使用traceback模块，是否有一种方法可以从函数内部确定函数的名称?
假设我有一个模块foo和一个功能栏。当执行foo.bar()时，是否有一种方法让bar知道bar的名字?或者更好的是，foo。酒吧的名字吗?
#foo.py
def bar():
print "my name is", __myname__ # <== how do I calculate this at runtime?
当前回答
我用自己的方法在多重继承场景中安全地调用super(我把所有代码都放在这里)
def safe_super(_class, _inst):
"""safe super call"""
try:
return getattr(super(_class, _inst), _inst.__fname__)
except:
return (lambda *x,**kx: None)
def with_name(function):
def wrap(self, *args, **kwargs):
self.__fname__ = function.__name__
return function(self, *args, **kwargs)
return wrap
示例用法:
class A(object):
def __init__():
super(A, self).__init__()
@with_name
def test(self):
print 'called from A\n'
safe_super(A, self)()
class B(object):
def __init__():
super(B, self).__init__()
@with_name
def test(self):
print 'called from B\n'
safe_super(B, self)()
class C(A, B):
def __init__():
super(C, self).__init__()
@with_name
def test(self):
print 'called from C\n'
safe_super(C, self)()
测试:
a = C()
a.test()
输出:
called from C
called from A
called from B
在每个@with_name修饰的方法中，您可以访问self。__fname__作为当前函数名。
其他回答
有几种方法可以达到相同的效果:
import sys
import inspect
def what_is_my_name():
print(inspect.stack()[0][0].f_code.co_name)
print(inspect.stack()[0][3])
print(inspect.currentframe().f_code.co_name)
print(sys._getframe().f_code.co_name)
注意inspect。堆栈调用比替代方法慢数千倍:
$ python -m timeit -s 'import inspect, sys' 'inspect.stack()[0][0].f_code.co_name'
1000 loops, best of 3: 499 usec per loop
$ python -m timeit -s 'import inspect, sys' 'inspect.stack()[0][3]'
1000 loops, best of 3: 497 usec per loop
$ python -m timeit -s 'import inspect, sys' 'inspect.currentframe().f_code.co_name'
10000000 loops, best of 3: 0.1 usec per loop
$ python -m timeit -s 'import inspect, sys' 'sys._getframe().f_code.co_name'
10000000 loops, best of 3: 0.135 usec per loop
2021年8月更新(原文章为Python2.7编写)
Python 3.9.1 (default, Dec 11 2020, 14:32:07)
[GCC 7.3.0] :: Anaconda, Inc. on linux
python -m timeit -s 'import inspect, sys' 'inspect.stack()[0][0].f_code.co_name'
500 loops, best of 5: 390 usec per loop
python -m timeit -s 'import inspect, sys' 'inspect.stack()[0][3]'
500 loops, best of 5: 398 usec per loop
python -m timeit -s 'import inspect, sys' 'inspect.currentframe().f_code.co_name'
2000000 loops, best of 5: 176 nsec per loop
python -m timeit -s 'import inspect, sys' 'sys._getframe().f_code.co_name'
5000000 loops, best of 5: 62.8 nsec per loop
print(inspect.stack()[0].function)似乎也可以工作(Python 3.5)。
这实际上是由这个问题的其他答案推导出来的。
以下是我的看法:
import sys
# for current func name, specify 0 or no argument.
# for name of caller of current func, specify 1.
# for name of caller of caller of current func, specify 2. etc.
currentFuncName = lambda n=0: sys._getframe(n + 1).f_code.co_name
def testFunction():
print "You are in function:", currentFuncName()
print "This function's caller was:", currentFuncName(1)
def invokeTest():
testFunction()
invokeTest()
# end of file
与使用inspect.stack()相比，这个版本可能的优势是它应该快数千倍[参见Alex Melihoff关于使用sys._getframe()与使用inspect.stack()的文章和计时]。
@jeff-laughlin的回答很漂亮。我对它进行了轻微的修改，以达到我认为的目的:跟踪函数的执行，并捕获参数列表以及关键字参数。谢谢你@jeff-laughlin!
from functools import wraps
import time
def named(func):
@wraps(func)
def _(*args, **kwargs):
print(f"From wrapper function: Executing function named: {func.__name__}, with arguments: {args}, and keyword arguments: {kwargs}.")
print(f"From wrapper function: {func}")
start_time = time.time()
return_value = func(*args, **kwargs)
end_time = time.time()
elapsed_time = end_time - start_time
print(f"From wrapper function: Execution of {func.__name__} took {elapsed_time} seconds.")
return return_value
return _
@named
def thanks(message, concepts, username='@jeff-laughlin'):
print(f"From inner function: {message} {username} for teaching me about the {concepts} concepts of closures and decorators!")
thanks('Thank you', 'two', username='@jeff-laughlin')
print('-'*80)
thanks('Thank you', 'two', username='stackoverflow')
print(thanks)
From wrapper function: Executing function named: thanks, with arguments: ('Thank you', 'two'), and keyword arguments: {'username': '@jeff-laughlin'}. From wrapper function: <function thanks at 0x7f13e6ceaa60> From inner function: Thank you @jeff-laughlin for teaching me about the two concepts of closures and decorators! From wrapper function: Execution of thanks took 2.193450927734375e-05 seconds. -------------------------------------------------------------------------------- From wrapper function: Executing function named: thanks, with arguments: ('Thank you', 'two'), and keyword arguments: {'username': 'stackoverflow'}. From wrapper function: <function thanks at 0x7f13e6ceaa60> From inner function: Thank you stackoverflow for teaching me about the two concepts of closures and decorators! From wrapper function: Execution of thanks took 7.152557373046875e-06 seconds. <function thanks at 0x7f13e6ceaca0>
最让我惊讶的是，有一种方法可以在运行时拦截函数，检查它们，并基于此采取一些操作。另一件令人惊讶的事情是内部函数的内存地址两次都是相同的。有人知道这是为什么吗?在我能够理解这个装饰器/闭包魔法之前，我还有一段路要走。
我找到了一个包装器，它将写入函数名
from functools import wraps
def tmp_wrap(func):
@wraps(func)
def tmp(*args, **kwargs):
print func.__name__
return func(*args, **kwargs)
return tmp
@tmp_wrap
def my_funky_name():
print "STUB"
my_funky_name()
这将打印
my_funky_name 存根
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