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
@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。
其他回答
我喜欢使用装饰器的想法，但我更喜欢避免触及函数参数。因此，我提供了另一种选择:
import functools
def withname(f):
@functools.wraps(f)
def wrapper(*args, **kwargs):
global __name
__saved_name = globals().get("__name")
__name = f.__name__
ret = f(*args, **kwargs)
__name = __saved_name
return ret
return wrapper
@withname
def f():
print(f"in f: __name=={__name}")
g()
print(f"back in f: __name=={__name}")
@withname
def g():
print(f"in g: __name=={__name}")
由于__name是一个全局变量，所以在调用函数时需要保存和恢复__name。调用上面的f()会产生:
in f: __name==f
in g: __name==g
back in f: __name==f
不幸的是，如果我们不改变函数参数，就没有全局变量的替代品。引用一个不是在函数上下文中创建的变量，将生成寻找全局变量的代码:
>>> def f(): print(__function__)
>>> from dis import dis
>>> dis(f)
1 0 LOAD_GLOBAL 0 (print)
2 LOAD_GLOBAL 1 (__function__)
4 CALL_FUNCTION 1
6 POP_TOP
8 LOAD_CONST 0 (None)
10 RETURN_VALUE
@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。
实现您自己的装饰器
# mydecorators.py
def resolve_function(func):
#in case annotated func is an staticmethod
if isinstance(func,staticmethod):
return func.__func__
return func
def print_my_name(func):
def function_caller(*args,**kwargs):
_func = resolve_function(func)
print("my name is: %s" %_func.__name__)
return _func(*args,**kwargs)
return function_caller
然后使用它
# foo.py
from mydecorators import *
@print_my_name
def bar():
#do something else
#in terminal: my name is: bar
我建议不要依赖于堆栈元素。如果有人在不同的上下文中使用你的代码(例如python解释器)，你的堆栈将改变并破坏你的索引([0][3])。
我建议你这样做:
class MyClass:
def __init__(self):
self.function_name = None
def _Handler(self, **kwargs):
print('Calling function {} with parameters {}'.format(self.function_name, kwargs))
self.function_name = None
def __getattr__(self, attr):
self.function_name = attr
return self._Handler
mc = MyClass()
mc.test(FirstParam='my', SecondParam='test')
mc.foobar(OtherParam='foobar')
这是一个经得起考验的方法。
将@CamHart和@Yuval的建议与@RoshOxymoron接受的答案结合起来，可以避免:
_hidden和潜在弃用的方法 在堆栈中建立索引(可以在未来的python中重新排序)
所以我认为这对未来的python版本(在2.7.3和3.3.2测试)很有帮助:
from __future__ import print_function
import inspect
def bar():
print("my name is '{}'".format(inspect.currentframe().f_code.co_name))
更新:在3.7.10,3.8.10和3.9.5测试
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