Python3 multiple assignment and memory address [duplicate]

让人想犯罪 __ 提交于 2019-11-28 11:10:29

This is due to a constant folding optimization in the bytecode compiler. When the bytecode compiler compiles a batch of statements, it uses a dict to keep track of the constants it's seen. This dict automatically merges any equivalent constants.

Here's the routine responsible for recording and numbering constants (as well as a few related responsibilities):

static int
compiler_add_o(struct compiler *c, PyObject *dict, PyObject *o)
{
    PyObject *t, *v;
    Py_ssize_t arg;

    t = _PyCode_ConstantKey(o);
    if (t == NULL)
        return -1;

    v = PyDict_GetItem(dict, t);
    if (!v) {
        arg = PyDict_Size(dict);
        v = PyInt_FromLong(arg);
        if (!v) {
            Py_DECREF(t);
            return -1;
        }
        if (PyDict_SetItem(dict, t, v) < 0) {
            Py_DECREF(t);
            Py_DECREF(v);
            return -1;
        }
        Py_DECREF(v);
    }
    else
        arg = PyInt_AsLong(v);
    Py_DECREF(t);
    return arg;
}

You can see that it only adds a new entry and assigns a new number if it doesn't find an equivalent constant already present. (The _PyCode_ConstantKey bit makes sure things like 0.0, -0.0, and 0 are considered inequivalent.)

In interactive mode, a batch ends every time the interpreter has to actually run your command, so constant folding mostly doesn't happen across commands:

>>> a = 1000
>>> b = 1000
>>> a is b
False
>>> a = 1000; b = 1000 # 1 batch
>>> a is b
True

In a script, all top-level statements are one batch, so more constant folding happens:

a = 257
b = 257
print a is b

In a script, this prints True.

A function's code gets its constants tracked separately from code outside the function, which limits constant folding:

a = 257

def f():
    b = 257
    print a is b

f()

Even in a script, this prints False.

That's because of pythons interpreter optimization at UNPACK_SEQUENCE time, during loading the constant values. When python encounters an iterable during the unpacking, it doesn't load the duplicate objects multiple times, instead it just keeps the first object and assigns all your duplicate variable names to one pointer (In CPython implementation). Therefore, all your variables will become same references to one object. At python level you can think of this behavior as using a dictionary as the namespace which doesn't keep duplicate keys.

In other words, your unpacking would be equivalent to following command:

a = b = 257

And about the negative numbers, in python 2.X it doesn't make any difference but in python 3.X it seems that for numbers smaller than -5 python will create new object during unpacking:

>>> a, b = -6, -6
>>> a is b
False
>>> a, b = -5, -5
>>> 
>>> a is b
True

Any such rule is implementation-specific. CPython, for example, pre-allocates int objects for small integers (-5 through 256) as a performance optimization.

The only general rule is to assume any use of a literal will generate a new object.

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