Understanding Python's call-by-object style of

Question

I am not sure I understand the concept of Python's call by object style of passing function arguments (explained here http://effbot.org/zone/call-by-object.htm). There don't seem to be enough examples to clarify this concept well (or my google-fu is probably weak! :D)

I wrote this little contrived Python program to try to understand this concept

def foo( itnumber, ittuple,  itlist, itdict   ):
    itnumber +=1 
    print id(itnumber) , itnumber 

    print id(ittuple)  , ittuple

    itlist.append(3.4)
    print id(itlist)   , itlist

    itdict['mary']  = 2.3
    print id(itdict),    itdict



# Initialize a number, a tuple, a list and a dictionary
tnumber = 1
print id( tnumber ), tnumber 

ttuple  = (1, 2, 3)
print id( ttuple ) , ttuple

tlist   = [1, 2, 3]
print id( tlist ) , tlist

tdict = tel = {'jack': 4098, 'sape': 4139}
print '-------'
# Invoke a function and test it
foo(tnumber, ttuple, tlist , tdict)

print '-------'
#Test behaviour after the function call is over
print id(tnumber) , tnumber 
print id(ttuple)  , ttuple
print id(tlist)   , tlist
print id(tdict),  tdict

The output of the program is

146739376 1
3075201660 (1, 2, 3)
3075103916 [1, 2, 3]
3075193004 {'sape': 4139, 'jack': 4098}

---------

146739364 2
3075201660 (1, 2, 3)
3075103916 [1, 2, 3, 3.4]
3075193004 {'sape': 4139, 'jack': 4098, 'mary': 2.3}

---------

146739376 1
3075201660 (1, 2, 3)
3075103916 [1, 2, 3, 3.4]
3075193004 {'sape': 4139, 'jack': 4098, 'mary': 2.3}

As you can see , except for the integer that was passed, the object id's (which as I understand refers to memeory location) remain unchanged.

So in the case of the integer, it was (effectively) passed by value and the other data structure were (effectively) passed by reference. I tried changing the list , the number and the dictionary to just test if the data-structures were changed in place. The number was not bu the list and the dictionary were.

I use the word effectively above, since the 'call-by-object' style of argument passing seems to behave both ways depending on the data-structure passed in the above code

For more complicated data structures, (say numpy arrays etc), is there any quick rule of thumb to recognize which arguments will be passed by reference and which ones passed by value?

Answer 1

Others have already posted good answers. One more thing that I think will help:

 x = expr

evaluates expr and binds x to the result. On the other hand:

 x.operate()

does something to x and hence can change it (resulting in the same underlying object having a different value).

The funny cases come in with things like:

 x += expr

which translate into either x = x + expr (rebinding) or x.__iadd__(expr) (modifying), sometimes in very peculiar ways:

>>> x = 1
>>> x += 2
>>> x
3

(so x was rebound, since integers are immutable)

>>> x = ([1], 2)
>>> x
([1], 2)
>>> x[0] += [3]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'tuple' object does not support item assignment
>>> x
([1, 3], 2)

Here x[0], which is itself mutable, was mutated in-place; but then Python also attempted to mutate x itself (as with x.__iadd__), which errored-out because tuples are immutable. But by then x[0] was already mutated!

Answer 2

Numbers, strings, and tuples in Python are immutable; using augmented assignment will rebind the name.

Your other types are merely mutated, and remain the same object.

Answer 3

The key difference is that in C-style language, a variable is a box in memory in which you put stuff. In Python, a variable is a name.

Python is neither call-by-reference nor call-by-value. It's something much more sensible! (In fact, I learned Python before I learned the more common languages, so call-by-value and call-by-reference seem very strange to me.)

In Python, there are things and there are names. Lists, integers, strings, and custom objects are all things. x, y, and z are names. Writing

x = []

means "construct a new thing [] and give it the name x". Writing

x = []
foo = lambda x: x.append(None)
foo(x)

means "construct a new thing [] with name x, construct a new function (which is another thing) with name foo, and call foo on the thing with name x". Now foo just appends None to whatever it received, so this reduces to "append None to the the empty list". Writing

x = 0
def foo(x):
    x += 1
foo(x)

means "construct a new thing 0 with name x, construct a new function foo, and call foo on x". Inside foo, the assignment just says "rename x to 1 plus what it used to be", but that doesn't change the thing 0.