Pass by Assignment

00:00 In your last lesson, you compared pass by value with pass by reference in C++. In this lesson, you’ll look at Python’s argument passing mechanism.

00:12 Python doesn’t use either pass by value or pass by reference. It uses something called pass by assignment. Other names for this include pass by object, pass by object reference, and pass by sharing.

00:25 But I’ll be using the phrase “pass by assignment.” It’s based on the following: First, everything in Python is an object. When you assign a variable to the value 5, an object representing the value 5 is created and then associated with that variable name.

00:43 The same is true for any assignment statement. Specifically, we call this “binding an object to a name.” Parameter names are also bound to objects when a function is called.

00:56 The object passed as an argument is bound to the parameter variable as well. If you reassign the parameter variable to a new object, that new object is created and bound to the parameter name.

01:11 That name is no longer bound to the object it previously had. However, note that the variable used as the argument to the function is still bound to that original object.

01:22 So, reassigning a parameter value has no effect on the argument variable. As I said, I’ll go into more detail on assignments and bindings in an upcoming lesson, but for now, let’s take a look at the effects of reassigning a parameter variable in a Python function.

01:40 Here’s a Python version of the same program from the last lesson that you saw on C++. Because Python’s assignment statements are much more closely tied to objects, in addition to the variable’s value, you’ll see the result of calling the id() function on each variable’s name.

01:59 Recall that every distinct object in Python has a unique ID number, which is returned by this function. But otherwise, it’s the same program. It defines a function f() that takes a single parameter fx.

02:15 It then displays the parameter’s value,

02:19 reassigns the parameter variable, then displays this new value. In the main script, it creates a variable x and assigns it a value, displays the value, uses the variable as the argument to the function f(), and then prints the value of that object once again.

02:44 I’ll go ahead and run this in the same terminal shell as the last lesson.

03:00 So, notice that fx’s first value and ID number match up with x’s. Because when the function is called, they’re both bound to the same object.

03:12 But then after fx is reassigned, it has a new value and a new ID number. This tells us a new object was created, and that object has a numeric value of 10. However, x is still the same object

03:32 with the same value that it was before.

03:37 Reassigning fx to a new object had no effect on the object bound to x. If you’re following along, you might get different ID numbers than you saw here.

03:50 Each time a Python program is run, it’ll generate new ID numbers for all of its objects. See, even if I run this a second time, I get a different set of numbers, but we still see the same effect.

04:06 The first, second, and last lines are all showing references to the same object. It’s only the third line where the new object was created and bound to the parameter variable fx is the ID number different than in the other lines.

04:28 I’ll have in a future lesson more to say about Python’s object binding, but first you should look at how Python’s mechanism does—or at least can be made to—provide some of the benefits pass by reference has.