为什么 Python 不允许将全局变量分配给具有相同名称的本地变量？

Question

I understand the logic behind requiring global if a global variable is assigned to within a function, but I don't understand why this can't be done:

y = 0
def x():
    y = y
    # Now modify the local version, but not the global one

Calling x results in an UnboundLocalError , even though there's no ambiguity here: The right-hand side of the assignment should be evaluated to the global variable since y is undefined in a local scope when it is executed.

This question is similar to this one (which doesn't have any detailed answers), but is more about the reasoning behind the language design.

I wouldn't write code like that because it is confusing, but I don't see why the language would forbid it. It seems inconsistent with how globals (or for that matter nonlocal s) usually behave in python.

Answer 1

When a variable name is used on the left-hand side of an assignment statement Python creates a local variable. When a local variable has the same name as a global variable we say that the local shadows the global . A shadow means that the global variable cannot be accessed by Python because the local variable will be found first.

you're using an assignment statement on y inside the function.

The Python interpreter sees this at module load time and decides that the global scope's y should not be used inside the local scope, which leads to a problem when you try to reference the variable before it is locally assigned.

that is the reason you would need to add

y=0
def x():
    global y
    y=y
x()

This will tell Python that you don't intend to define ay variable inside the function's local scope. The Python interpreter sees this at module load time and decides to look up any references to the aforementioned variables in the global scope.

Though it is one of several good reasons for not using global variables. As you can see, it makes your code confusing and difficult to understand, one should refrain from doing this in code. I suggested adding a global keyword just to cement the understanding of how python is working here.