Python – Does the `is` Operator Use a __magic__ Method?

From the documentation:

Every object has an identity, a type and a value. An object’s identity never changes once it has been created; you may think of it as the object’s address in memory. The ‘is‘ operator compares the identity of two objects; the id() function returns an integer representing its identity (currently implemented as its address).

This would seem to indicate that it compares the memory addresses of the arguments, though the fact that it says "you may think of it as the object's address in memory" might indicate that the particular implementation is not guranteed; only the semantics are.

Your question is a bit generic. There is a comprehensive list of "special methods", even though it misses some stdlib specific methods(e.g. __setstate__ and __getstate__ used by pickle etc. But it's a protocol of the module pickle not a language protocol).

If you want to know exactly what the interpreter does you can use the dis module to disassemble the bytecode:

>>> import dis
>>> def my_func(a):
...     return a + 2
... 
>>> dis.dis(my_func)
  2           0 LOAD_FAST                0 (a)
              3 LOAD_CONST               1 (2)
              6 BINARY_ADD          
              7 RETURN_VALUE   

You can see that the intereper executes a BINARY_ADD byte code when doing addition. If you want to see exactly the operations that BINARY_ADD does you can download Python's source code and check the ceval.c file:

    case BINARY_ADD:
        w = POP();
        v = TOP();
        if (PyInt_CheckExact(v) && PyInt_CheckExact(w)) {
            /* INLINE: int + int */
            register long a, b, i;
            a = PyInt_AS_LONG(v);
            b = PyInt_AS_LONG(w);
            /* cast to avoid undefined behaviour
               on overflow */
            i = (long)((unsigned long)a + b);
            if ((i^a) < 0 && (i^b) < 0)
                goto slow_add;
            x = PyInt_FromLong(i);
        }
        else if (PyString_CheckExact(v) &&
                 PyString_CheckExact(w)) {
            x = string_concatenate(v, w, f, next_instr);
            /* string_concatenate consumed the ref to v */
            goto skip_decref_vx;
        }
        else {
          slow_add:
            x = PyNumber_Add(v, w);
        }
        Py_DECREF(v);
      skip_decref_vx:
        Py_DECREF(w);
        SET_TOP(x);
        if (x != NULL) continue;
        break;

So here we can see that python special cases int and string additions, and eventually falls back to PyNumber_Add, which checks if the first operand implements __add__ and calls it, eventually it tries __radd__ of the right hand side and if nothing works raises a TypeError.

Note that the byte codes are version-specific, so dis will show different results on different versions:

# python2.7
>>> def my_func():
...     return map((lambda x: x+1), range(5))
... 
>>> dis.dis(my_func)
  2           0 LOAD_GLOBAL              0 (map)
              3 LOAD_CONST               1 (<code object <lambda> at 0x16f8c30, file "<stdin>", line 2>)
              6 MAKE_FUNCTION            0
              9 LOAD_GLOBAL              1 (range)
             12 LOAD_CONST               2 (5)
             15 CALL_FUNCTION            1
             18 CALL_FUNCTION            2
             21 RETURN_VALUE        
# python3
>>> dis.dis(my_func)
  2           0 LOAD_GLOBAL              0 (map) 
              3 LOAD_CONST               1 (<code object <lambda> at 0x7f1161a76930, file "<stdin>", line 2>) 
              6 LOAD_CONST               2 ('my_func.<locals>.<lambda>') 
              9 MAKE_FUNCTION            0 
             12 LOAD_GLOBAL              1 (range) 
             15 LOAD_CONST               3 (5) 
             18 CALL_FUNCTION            1 (1 positional, 0 keyword pair) 
             21 CALL_FUNCTION            2 (2 positional, 0 keyword pair) 
             24 RETURN_VALUE  

Also the same byte code may be optimized in future versions, so even if the byte code is the same different versions of python will actually perform different instructions.

If you're interested in learning how python works behind the scenes I'd advise you to write some C extensions, following the tutorials and documentation that you can find on the official python's website.