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

import inspect

def whoami():
    return inspect.stack()[1][3]

def whosdaddy():
    return inspect.stack()[2][3]

def foo():
    print "hello, I'm %s, daddy is %s" % (whoami(), whosdaddy())
    bar()

def bar():
    print "hello, I'm %s, daddy is %s" % (whoami(), whosdaddy())

foo()
bar()

在IDE中,代码输出

你好,我是foo,爸爸是 你好,我是bar,爸爸是foo 你好,我是bar,爸爸是

其他回答

import inspect

def foo():
   print(inspect.stack()[0][3])
   print(inspect.stack()[1][3])  # will give the caller of foos name, if something called foo

foo()

输出:

喷火 < module_caller_of_foo >

我把这个实用工具放在附近:

import inspect
myself = lambda: inspect.stack()[1][3]

用法:

myself()

.f_back.f_code Sincesys._getframe()。Co_name在python 3.9中根本不起作用,下面可以从现在开始使用:

from inspect import currentframe


def testNameFunction() -> str:
    return currentframe().f_back.f_code.co_name


print(f'function name is {testNameFunction()}(...)')

结果:

function name is testNameFunction(...)

@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。

Python没有在函数本身中访问函数或其名称的特性。它已经被提出,但被否决了。如果你不想自己玩堆栈,你应该使用“bar”或bar。__name__取决于上下文。

给定的拒绝通知为:

此PEP被拒绝。它不清楚应该如何实现,也不清楚在边缘情况下应该有什么精确的语义,而且没有给出足够重要的用例。人们的反应充其量也只是不温不火。